|
5hydroxysaxagliptin
rat (Wang 2024)
|
Preclinical (rat). Two-compartment intravenous PK model for the active
saxagliptin metabolite 5-hydroxy saxagliptin (5-OH SAX), directly linked
to a sigmoidal Emax model WITH a baseline term E0 for plasma dipeptidyl
peptidase-4 (DPP-4) inhibition, in streptozotocin plus high-fat-diet
induced type 2 diabetic male Sprague-Dawley rats. Wang 2024 Eq 4-6 write
the disposition as dA1/dt = (CL2/V2)A2 - (CL2/V)A1 -
(CL/V)A1 and dA2/dt = (CL2/V)A1 - (CL2/V2)A2, i.e. CL2 is a
conventional inter-compartmental clearance (k12 = CL2/V, k21 = CL2/V2)
and is encoded here as lq. The PD model is Wang 2024 Eq 7, E = E0 + Emax
C^Gam / (EC50^Gam + C^Gam), applied directly to the plasma 5-OH
SAX concentration with no effect compartment; the paper states
explicitly that 5-OH SAX binds DPP-4 immediately and that no hysteresis
was observed. This model is the metabolite half of Wang 2024 and is the
model the authors used to attribute part of the total DPP-4 inhibition
seen after oral saxagliptin to the metabolite; the parent-drug half is
modellib(‘Wang_2024_saxagliptin_rat’). The fitted potencies satisfy
EC50_5OHSAX = 0.46 * EC50_SAX, the paper’s central finding. All volumes
and clearances are body-weight normalised (mL/kg, mL/h/kg), so ODE state
amounts are in ng per kg body weight and the 0.5 mg/kg intravenous dose
is supplied as amt = 5e5 into central. Parameters are the arithmetic
means of three individually fitted rats (WinNonlin 8.1, naive individual
fitting); no population model and therefore no OMEGA was estimated, so
the model carries no eta terms and is intended for typical-value
simulation. The PK residual error was described as additive but its
magnitude was never reported, so addSd is FIXED at 0; the PD residual SD
(stdev0) IS reported and is used. E0 is kept on the linear scale because
the individual estimates in Supplementary Table S19-b include a negative
value (-3.85%).
|
|
8C2
(Abuqayyas 2012)
|
Preclinical (mouse). Two-compartment IV bolus population PK model of
8C2, a murine IgG1 anti-topotecan monoclonal antibody, in C57BL/6
wild-type, Fc-gamma-RI/RIII knockout, and Fc-gamma-RIIb knockout mice
(Abuqayyas 2012). Data were pooled across all three strains and three IV
bolus dose levels (0.04, 0.1, 0.4 mg/kg); strain was screened and found
not statistically significant on any structural parameter, so no
covariate effects are retained. Structural PK parameters were reported
per kg body weight (L/kg and L/day/kg), which corresponds to linear
body-weight scaling with a fixed exponent of 1.
|
|
Abacavir
(Archary 2019)
|
Two-compartment population PK model for abacavir in severely
malnourished HIV-infected children (Archary 2019); CL/F steps up between
day 1 and day 14 of antiretroviral treatment and bioavailability is 31%
higher in the early-ART arm
|
|
Abacavir
(Chandasana 2024b)
|
Two-compartment oral population PK model with first-order absorption and
elimination for abacavir in children with HIV-1 weighing 6 to 40 kg,
applied without re-estimation to the ABC/DTG/3TC fixed-dose combination
(dispersible tablet and tablet) in IMPAACT 2019 (Chandasana 2024)
|
|
Abacavir
(Jullien 2005)
|
Two-compartment population PK model for abacavir in HIV-infected adults
(Jullien 2005); apparent clearance scales with body weight via an
estimated power exponent, Q/F is fixed when BW is added to the model
|
|
Abacavir
(Tikiso 2021)
|
Two-compartment population PK model for oral abacavir in HIV-infected
African children (Tikiso 2021), with a Savic 2007-style analytical
transit-compartment chain feeding a first-order absorption depot,
allometric body-weight scaling on disposition (0.75 on CL/Q, 1 on Vc/Vp
at 70 kg), sigmoidal Hill-type maturation of CL on postmenstrual age,
and multiplicative covariate effects of efavirenz co-medication on CL,
rifampicin + super-boosted lopinavir/ritonavir co-medication on F,
fixed-dose-combination tablet formulation on MTT, and a time-decaying
malnutrition effect on F and CL.
|
|
Abacavir
(Zhao 2012)
|
Two-compartment population PK model for oral abacavir in HIV-infected
infants and toddlers (Zhao 2012) developed on the PENTA 15 crossover
trial of 8 mg/kg twice-daily vs 16 mg/kg once-daily dosing; CL/F scales
with body weight via an estimated power exponent (1.14) referenced to
the population median weight of 12 kg, and inter-occasion variability on
CL/F is multiplexed by the binary OCC indicator across the BID (occasion
1) and QD (occasion 2) study phases.
|
|
Abacavir
(Zhao 2013)
|
Two-compartment population PK model for oral abacavir in HIV-infected
infants, toddlers, and children (Zhao 2013); body weight is the only
retained covariate (allometric on CL/F and V1/F with estimated exponents
and reference weight 17.6 kg).
|
|
Abatacept
(Gandhi 2021)
|
Two-compartment population PK model for abatacept (CTLA4-Ig Fc-fusion)
pooled across adults with rheumatoid arthritis and patients aged 2-17
years with polyarticular juvenile idiopathic arthritis (Gandhi 2021),
with first-order SC absorption, zero-order IV infusion support,
first-order linear elimination, logit-scale SC bioavailability with
disease/age/weight covariates, and a KA parameterisation that enforces
KA > k_el.
|
|
Abatacept
(Li 2019)
|
Two-compartment population PK model for abatacept (CTLA4-Ig Fc-fusion)
in adults with rheumatoid arthritis (Li 2019), with first-order SC
absorption, zero-order IV infusion support, first-order linear
elimination, logit-scale SC bioavailability, full-block IIV on
CL/VC/Q/VP, and a KA parameterisation that enforces KA > k_el.
|
|
Abatacept
(Lon 2013)
|
Two-compartment population PK model with linear elimination and
short-term zero-order SC absorption for abatacept (CTLA-4Ig Fc-fusion)
in male Lewis rats with collagen-induced arthritis (Lon 2013).
|
|
Abatacept
(Takahashi 2023)
|
Two-compartment IV population PK model for abatacept (CTLA4-Ig
Fc-fusion) pooled across 685 adult/pediatric patients with rheumatoid
arthritis or polyarticular juvenile idiopathic arthritis and
adult/pediatric patients receiving allogeneic hematopoietic cell
transplantation in the ABA2 trial (Takahashi 2023). Linear elimination,
allometric weight scaling on CL/Vc/Vp/Q with estimated exponents, and a
three-level cohort categorical (RA/JIA reference, ABA2 HLA 7/8, ABA2 HLA
8/8) on CL and Vc.
|
|
Abatacept
(Zhong 2026)
|
Two-compartment population PK model for abatacept (CTLA4-Ig Fc-fusion)
pooled across 9 phase 2/3 studies (Zhong 2026): adults with rheumatoid
arthritis, patients aged 2-17 years with polyarticular juvenile
idiopathic arthritis, and patients aged 6+ years with hematologic
malignancies receiving HLA-matched unrelated-donor HSCT (the ABA2
trial). Final model has zero-order IV infusion, first-order SC
absorption, first-order linear elimination, additive plus proportional
residual error, allometric weight on CL/VC/VP, hepatic (AST) and renal
(cGFR) markers on CL, sex on CL and VC, two HSCT cohort indicators
(7-of-8 and 8-of-8 HLA-matched URD) on CL/VC, and a logit-scale SC
bioavailability sub-model with weight, age, and pJIA-disease covariates
fixed to a previously developed internal JIA PPK model (values match
Gandhi 2021).
|
|
ABT
102 (Othman 2013)
|
Population PK/PD model of body-temperature effects of ABT-102, a TRPV1
antagonist, in 108 healthy adult volunteers across three phase 1 trials
(Othman 2013). PK is a one-compartment model with one transit absorption
compartment, first-order elimination, and formulation-dependent
absorption lag (0.3 h solution, 0.6 h solid dispersion) and relative
bioavailability (40% solution vs solid-dispersion reference); PK
parameter values are taken from the upstream popPK analysis (Othman
2012, J Clin Pharmacol). The PD layer models body temperature as the
additive sum of (a) a measurement-type-dependent baseline (oral
thermometer vs core ingestible capsule), (b) a 24-h circadian rhythm
(cosine in time with measurement-type-dependent amplitude and a shared
7.6-h phase shift), and (c) an Emax drug effect on plasma concentration
with time-driven exponential tolerance (Emax decays with half-life T50 =
28 h). Two parallel outputs (BT_oral, BT_core) are produced with
measurement-type-dependent additive residual error; for a given subject
only one output is realised (oral thermometer subjects use BT_oral; core
ingestible-capsule subjects use BT_core).
|
|
Acetaminophen
(vanRongen 2016)
|
Parent-and-metabolites population PK model for intravenous acetaminophen
(paracetamol) and its glucuronide, sulphate, and CYP2E1-oxidation
(cysteine + mercapturate) metabolites in morbidly obese and non-obese
adults (van Rongen 2016). One-compartment plasma disposition for parent
acetaminophen with four parallel elimination pathways from the central
compartment (glucuronidation, sulphation, CYP2E1 oxidation, and
unchanged renal); one-compartment plasma disposition for glucuronide and
cysteine + mercapturate metabolites each fed via a
single-transit-compartment delay; two-compartment plasma disposition for
sulphate (central + peripheral, fixed equal volumes 5.66 L each). Lean
body weight (LBW; Janmahasatian et al. 2005 equation) enters as a
power-law covariate on parent V, all three formation clearances, the
CYP2E1 transit rate constant, and glucuronide elimination CL. Total body
weight enters on the glucuronide volume of distribution.
|
|
Acetaminophen
rat pbpk (Westerhout 2012)
|
PBPK (semi-mechanistic, regional brain) population PK model for
acetaminophen (paracetamol) in 24 male Wistar WU rats (225-275 g),
developed to investigate regional brain distribution kinetics with
simultaneous microdialysis sampling in striatum (brain extracellular
fluid), lateral ventricle (CSF_LV), and cisterna magna (CSF_CM) after a
10-min intravenous infusion of 15 mg/kg acetaminophen (Westerhout et
al. 2012, AAPS J). Seven physiological compartments: plasma plus
peripheral tissue plus brain extracellular fluid (with the brain
intracellular space volume added per paper text page 5) plus four
anatomically distinct CSF subcompartments (lateral ventricle, third and
fourth ventricle combined, cisterna magna, subarachnoid space). Brain
compartment volumes (V_pl, V_ICS, V_ECF, V_LV, V_TFV, V_CM, V_SAS) and
bulk fluid flows (Q_ECF, Q_CSF) are fixed to literature physiological
values for a 250-g rat; plasma-to-region and region- to-plasma
clearances are estimated. The plasma-to-third-fourth- ventricle
clearances CL15 / CL51 are structurally assumed equal to the
plasma-to-lateral-ventricle clearances CL14 / CL41 (paper Results). An
enterohepatic-recirculation continuous input F_abs * DOSE adds drug back
to plasma to capture the apparent plateau after t = 120 min. The model
is fitted to unbound plasma concentrations (plasma concentrations
corrected to free fraction fu_p = 0.805); fu_p is documented in
population metadata but does not enter the structural ODEs (see vignette
Assumptions and deviations).
|
|
Acyclovir
(Zeng 2009)
|
One-compartment population PK model with first-order absorption for
acyclovir in 43 children and young people (age 0.8-19.9 years; weight
7.3-70.2 kg) with malignancy, after intravenous acyclovir (5 mg/kg q8h,
1 h infusion) or oral valacyclovir prodrug (10 mg/kg q12h), developed in
NONMEM v5.1.1 (FOCE-I) from 1216 plasma observations. Structural model:
first-order absorption (ka) from a depot with bioavailability F (oral
valacyclovir delivered as systemic acyclovir), one-compartment
disposition with first-order elimination. Allometric body-weight scaling
on CL (fixed exponent 0.75) and V (fixed exponent 1) referenced to the
cohort median 19.6 kg; CL additionally varies with creatinine clearance
via a power function (CRCL/106.7 mL/min/1.73 m2)FAC.
Inter-individual variability is diagonal on CL, V, ka, and F. Residual
error is a combined exponential (proportional after linearization) +
additive model. Inter-occasion variability on CL (19.2% CV) and V (30.4%
CV) reported by Zeng 2009 Table 3 is NOT encoded structurally here (per
the Andrews 2017 / Brooks 2021 tacrolimus precedent) – the source paper
does not define an operational occasion column for the model-library use
case.
|
|
Adalimumab
(Drweesh 2026)
|
One-compartment population PK model with first-order subcutaneous
absorption and linear elimination for adalimumab originator (Humira) and
biosimilars (Amgevita, Hyrimoz) in adults with inflammatory bowel
disease and other autoimmune disorders, fit to multicenter
therapeutic-drug-monitoring trough data from Saudi Arabia and Qatar
(Drweesh 2026). Structural backbone (V/F, IIV variances, residual error)
inherited from Marquez-Megias 2023 because Drweesh 2026 reports only ka
(fixed) and the typical clearance value.
|
|
Adalimumab
(Marcantonio 2022)
|
QSP. One-compartment monospecific anti-ligand mechanistic PKPD model of
adalimumab-TNF-alpha binding in adults with rheumatoid arthritis
(Marcantonio 2022 Early Feasibility Assessment, Case Study 1). Drug
administered SC (first-order absorption) or IV, binds soluble TNF-alpha
(monovalent, effective valency = 1 per Tran 2017 / Lim 2018), and blocks
the reversible TNF:TNFR interaction. All species are eliminated by
first-order processes; the drug-target-ligand complex eliminates at the
same rate as the free drug; the ligand-receptor complex eliminates at
the same rate as the free receptor (paper Model Assumptions). All
parameters are FIXED from paper Table 2 (no fitting, no IIV, no residual
error reported). Initial conditions for L1 (free TNF), R1 (free TNFR),
L1R1 (TNF-TNFR complex) and S1 (soluble shed receptor) are derived
analytically from the reported steady-state concentrations and the
quasi-equilibrium ligand-receptor binding balance. Simulation output
activity (paper active_1_central) is the L1R1 complex amount; target
inhibition is computed as 1 - L1R1(t)/L1R1(0). Run in the Applied
BioMath Assess Monospecific Anti-Ligand model; the ODE system encoded
here reproduces the Assess reaction network verbatim (see Supplementary
Material Data Sheet 2, one_compartment_anti_ligand.pdf).
|
|
Adalimumab
(Marquez-Megias 2023)
|
One-compartment population PK model with first-order subcutaneous
absorption and linear elimination for adalimumab in adults with
inflammatory bowel disease, with albumin and anti-drug-antibody
covariates on apparent clearance (Marquez-Megias 2023)
|
|
Adalimumab
(Nader 2017)
|
One-compartment population PK model with first-order subcutaneous
absorption and linear elimination for adalimumab in adults with
moderate-to-severe hidradenitis suppurativa, with baseline body weight
and baseline C-reactive protein power effects on apparent clearance, a
time-delayed anti-adalimumab-antibody effect on apparent clearance, and
baseline body weight on apparent volume of distribution (Nader 2017).
|
|
Adalimumab
(Zheng 2012)
|
Preclinical (Gottingen minipig). Two-compartment population PK model for
adalimumab with first-order SC absorption and linear central clearance
in Gottingen minipigs, per Zheng 2012 minipig IV+SC study (Table 1
population mean parameter estimates).
|
|
ADC
human qsp (Scheuher 2023)
|
QSP. Human platform model for HER2-targeting antibody-drug conjugates in
HER2+ metastatic breast cancer (T-DM1 default; T-DXd variant via
parameter overrides). Extends the mouse model with: (i) HER2 receptor
sinks on normal cells in the central and peripheral compartments (with
binding, endocytosis, recycling, degradation); (ii) soluble HER2 (sHER2)
shed from cell-surface HER2 into central + peripheral + tumor
compartments, with reversible binding to ADC and Ab and its own
turnover; and (iii) larger physiologic volumes (3 L central, 13 L
peripheral for a 70 kg adult). Mouse-derived TGI parameters (kkill_max,
kc50, tau, n_Hill) are carried over from N87 xenograft fits. Amounts in
nmol; concentrations amount/volume.
|
|
ADC
invitro qsp (Scheuher 2023)
|
QSP. In vitro cellular ADC processing model for HER2-targeting
antibody-drug conjugates (T-DM1 default; T-DXd variant supported via
parameter overrides). 13 ODE states describing extracellular ADC / Ab /
free payload, cell-surface HER2 with reversible ADC and antibody
binding, endosomal HER2 species, endosomal / cytosolic payload, and
cytosolic intracellular target (tubulin for DM1, TOPO-1 for DXd).
Amounts in nmol per paper Modeling Convention; concentrations are
amount/volume. Parameter set defaults to SK-BR-3 cell line with T-DM1
(Erickson 2012 in vitro incubation).
|
|
ADC
mouse qsp (Scheuher 2023)
|
QSP. Mouse in vivo platform model for HER2-targeting antibody-drug
conjugates (T-DM1 default, N87 tumor xenograft; T-DXd variant supported
via parameter overrides). Combines: (i) mouse plasma PK for ADC / naked
antibody / free payload in central + peripheral compartments; (ii)
mechanistic tumor uptake via a Krogh cylinder + surface exchange model;
(iii) intracellular ADC processing (HER2 binding, endocytosis,
recycling, degradation, endosomal payload release, cytosol transport,
tubulin binding); and (iv) tumor growth inhibition via a Simeoni-style
4-stage transit-chain cascade with Hill-type kill on the proliferating
stage. Amounts in nmol; concentrations amount/volume.
|
|
Adecatumumab
(Cao 2013)
|
Second-generation minimal physiologically-based PK (mPBPK) model for
adecatumumab in adults (Cao 2013 Model A; clearance from plasma)
|
|
Aditoprim
pbpk (Mi 2024)
|
Veterinary (pig). PBPK (whole-body, seven-compartment, Berkeley Madonna
8.3.23.0) for the diaminopyrimidine aditoprim (ADP) after intramuscular
injection in swine, developed to optimise the dosage regimen against
Streptococcus suis and to predict the withdrawal interval for edible
tissues (Mi et al. 2024, Front Pharmacol 15:1378034). A single
well-mixed blood pool, liver, kidney, muscle, fat and a lumped
rest-of-body compartment are perfusion-limited and well stirred; liver,
kidney, muscle and fat are carried as separate states because they are
the edible tissues against which the maximum residue limits are set.
Intramuscular absorption is a two-step process: Frac = 92% of the
injected dose is immediately available at the injection site and is
absorbed into the venous mixing pool at first-order rate Kim, while the
remaining 8% is released from a slow depot at first-order rate Kdiss
into that same injection-site pool. Elimination is renal (from kidney)
plus hepatic metabolism (from liver). Plasma protein binding rescales
the free plasma concentration only – it does not gate tissue perfusion,
which is driven by TOTAL arterial concentration in the published code.
The seven parameters that Mi 2024 Table 3 carried through the
1000-animal Monte Carlo pop-PBPK analysis carry between-animal
variability here; every other parameter is a fixed physiological or
fitted chemical-specific constant. The model was hand-calibrated in
Berkeley Madonna against digitised literature data, so no standard
errors and no residual-error model are reported – the propSd term is a
placeholder. Several Table 2 / supplement-code discrepancies are
reproduced as coded; see the vignette Errata.
|
|
Aditoprim
pbpkpd (Mi 2024)
|
Veterinary (pig) + in vitro (Streptococcus suis ATCC 49619). Integrated
PBPK/PD model for the diaminopyrimidine aditoprim (ADP) after
intramuscular injection in swine (Mi et al. 2024, Front Pharmacol
15:1378034). The disposition layer is the seven-compartment whole-body
PBPK model of modellib(‘Mi_2024_aditoprim_pbpk’); the effect layer is a
two-subpopulation semi-mechanistic pharmacodynamic model fitted in
Monolix 2018R1 to in vitro time-killing curves against S. suis ATCC
49619 (MIC 0.5 ug/mL). Susceptible (S) and resistant (R) subpopulations
share one logistic growth term capped at the stationary-phase count Bmax
and are killed by a common sigmoid Emax function that differs only in
potency (EC50_R = 1.63 mg/L is 2.4-fold EC50_S = 0.685 mg/L), so
resistant organisms are selected under sub-optimal exposure. The
starting inoculum is split by the fixed mutation frequency MF = 1e-3.
The two layers are coupled one-way: the UNBOUND plasma concentration
predicted by the PBPK model replaces the static broth concentration
Cstastic of the time-kill experiment, and the bacteria do not feed back
on the drug. The unbound (not total) concentration is the driver – that
is what the published code computes as CAfree and is the only reading
that reproduces all four dose levels of Mi 2024 Figure 6; see the
vignette. Used to show that 20 mg/kg every 12 h for 3 days eradicates
both subpopulations while 5 mg/kg selects for resistance. Neither layer
reports between-animal or between-replicate random effects on the PD
parameters, so the PD block is typical-value only and propSd is a
placeholder.
|
|
Aflibercept
(Thai 2011)
|
Mechanism-based population PK model for free and bound aflibercept
(anti-VEGF Fc-fusion ‘trap’ protein; VEGF-Trap) in healthy adult male
subjects (Thai 2011 BJCP). Two-compartment disposition of free
aflibercept with linear elimination from the central compartment plus
Michaelis-Menten binding of free aflibercept to VEGF occurring in the
peripheral (tissue) compartment, producing a one-compartment
bound-aflibercept species that is eliminated by first-order
internalisation (kint). This is the second Michaelis-Menten
approximation of the TMDD model of Gibiansky et al. (irreversible
binding), with the bound complex carried as an explicit state. The
bound-aflibercept volume of distribution Vb is fixed equal to the
central volume Vc for identifiability. Pooled data from two phase 1
single-dose IV-infusion studies in healthy males (1, 2, 4 mg/kg over 1
h). No covariates were tested or retained in the final model.
|
|
Agomelatine
(Xie 2019)
|
A semiphysiological population pharmacokinetic model of agomelatine and
its metabolites in Chinese healthy volunteers
|
|
Albendazole
(PillayFuentesLorente 2024)
|
Joint population PK model for the two main albendazole metabolites after
a single oral 400 mg albendazole dose (with or without co-administered
ivermectin) in adolescents infected with Trichuris trichiura in Tanzania
and Cote d’Ivoire: Savic transit-compartment absorption feeding a
two-compartment albendazole sulfoxide disposition that converts
quantitatively to a one-compartment albendazole sulfone, with a
study-population (country) effect on both apparent clearances
|
|
AlbuminNanoparticles
mouse pbpk (Kutumova 2024)
|
Preclinical (mouse, BALB/c, male, 6-8 weeks, 0.024 kg). PBPK
(whole-body, BioUML) model for the biodistribution of intravenous
albumin nanoparticles (ANP, ~120 nm, zeta ~ -30 mV) during induction of
and recovery from lipopolysaccharide-induced acute lung injury. Seven
compartments: venous and arterial plasma plus four mononuclear phagocyte
system organs (lungs, spleen, liver, kidneys) and a rest-of-body
compartment. Each organ carries a membrane-limited triple of capillary
blood, tissue interstitium, and an internalised (phagocytosed) pool,
with time-dependent Hill-function endocytic uptake and first-order
exocytic release; the liver additionally phagocytoses directly from
capillary blood (Kupffer cells) and excretes into bile, and the kidneys
excrete into urine. The permeability (PAC) and distribution (P)
coefficients are cohort-specific: STUDY_LPS30M / STUDY_LPS6H /
STUDY_LPS24H select the ANP-after-LPS arm, with all three zero giving
the LPS-naive control. The observed quantity is organ total radiant
efficiency per luminous area (TRE), obtained from the simulated tissue
concentration through a single fitted scale factor k. Physiologic blood
flows, organ volumes, and capillary blood fractions are inherited from
the Cheng 2020 nanoparticle PBPK framework, which the authors cite as
their source for these values.
|
|
Alemtuzumab
(Mould 2007)
|
Two-compartment population PK model with Michaelis-Menten elimination
for alemtuzumab in B-cell chronic lymphocytic leukaemia (Mould 2007)
|
|
Alemtuzumab
wbc (Mould 2007)
|
Coupled population PK-PD model for alemtuzumab in B-cell chronic
lymphocytic leukaemia (Mould 2007): the two-compartment Michaelis-Menten
PK from Mould 2007 Table 2 driven by the simulated WBC state via Vmax =
TVVmax * (WBC/10)^0.194, joined to an indirect-response model on WBC
(stimulation of Kout by alemtuzumab; Mould 2007 Table 3). WBC is a state
variable initialised per subject at Kin/Kout.
|
|
Alirocumab
(Djebli 2017)
|
(Djebli 2017 writes the drug’s linear catabolic clearance as CLL; it is
stored here under the canonical name lcl.)
Quasi-steady-state target-mediated drug disposition (TMDD-QSS)
population PK model for alirocumab and total PCSK9 in healthy adults and
adults with hypercholesterolemia (Djebli 2017, final model on expanded
data set n=2870). Two-compartment disposition with first-order SC
absorption (lag time and bioavailability), linear catabolic clearance
from central, and PCSK9 binding / complex internalization described by
QSS algebra; allometric weight scaling on CLL, Q, and Vc plus a
statin-coadministration effect on CLL.
|
|
Alirocumab
(Martinez 2019)
|
Two-compartment population PK model for alirocumab in healthy volunteers
and adults with hypercholesterolemia (Martinez 2019, Part I), with
first-order SC absorption (with lag time), linear plus Michaelis-Menten
(target-mediated) elimination from the central compartment, and
logit-transformed bioavailability.
|
|
Allopurinol
(Wright 2013)
|
Sequential parent-metabolite population pharmacokinetic model for oral
and intravenous allopurinol and its principal long-lived active
metabolite oxypurinol in patients with chronic gout and healthy
volunteers, pooled from three Christchurch (New Zealand) clinical
studies (dose-escalation, furosemide-interaction, vitamin-C interaction)
and two digitally-extracted historic intravenous-allopurinol studies.
Structural model: 2-compartment first-order absorption disposition for
allopurinol (parent) with 80 percent molar conversion to a 1-compartment
oxypurinol (metabolite). Fat-free-mass (FFM) allometric scaling on all
clearance parameters (exponent 0.75) and volume parameters (exponent
1.0) referenced at FFM = 70 kg. Oxypurinol clearance is decomposed into
non-renal (0.178 L/h/70 kg FFM) plus renal (0.777 L/h/70 kg FFM per
creatinine clearance of 6 L/h) components, with a 39 percent reduction
of the renal component in patients on concomitant diuretic therapy. All
allopurinol structural parameters, allometric exponents, oral
bioavailability, and the molar conversion fraction were held FIXED
during the sequential fit; oxypurinol structural parameters, IIV, and
residual error were estimated. Wright 2013 Table 2 reports residual
epsilon components under a ‘(CV%)’ column label whose numeric values are
interpreted here as SD on fraction scale (see the model’s validation
vignette Assumptions and deviations section for the rationale).
|
|
Allopurinol
(Wright 2016)
|
One-compartment population PK-PD model for allopurinol (via the active
metabolite oxypurinol) and plasma urate in adults with gout (Wright 2016
BJCP). Oxypurinol disposition is a one-compartment first-order
absorption / first-order elimination model with Ka fixed at 1.09 1/h;
apparent oxypurinol clearance (CL/F_oxy) is allometrically scaled on
fat-free mass (Janmahasatian formula, exponent fixed at 0.75) and
power-scaled on Cockcroft-Gault creatinine clearance standardised to 70
kg, with a multiplicative reduction when a thiazide or loop diuretic is
coadministered; apparent volume (V/F_oxy) is allometrically scaled on
total body weight (exponent fixed at 1.0) and shares its IIV with
CL/F_oxy via a fixed fractional scaler (Bonate 2006 fractional-effect
parameterisation). Plasma urate is described by a direct-effect
sigmoidal Emax inhibition of urate production on top of a baseline urate
U0 that is power-scaled on renal function and multiplicatively higher
with concomitant diuretic. The dose entered into the model is
allopurinol oral mg; the implicit 1:1 molar conversion to oxypurinol is
absorbed into the apparent CL/F_oxy and V/F_oxy. Cc is oxypurinol
concentration (umol/L) and Eurate is plasma urate (mmol/L).
|
|
Alvespimycin
(Aregbe 2012)
|
Three-compartment population PK model for the heat shock protein 90
inhibitor 17-DMAG (alvespimycin, NSC 707545) given as a 1 h IV infusion
to adult patients with advanced solid tumors (Aregbe 2012), with
first-order elimination, log-normal IIV on CL/Q3/V1/V2/V3, and
between-occasion variability on Q2 and V1 multiplexed by an OCC
indicator across up to five daily dosing occasions.
|
|
Amatuximab
(Gupta 2016)
|
Two-compartment population PK model with parallel linear and
Michaelis-Menten elimination for amatuximab in patients with advanced
cancers / malignant pleural mesothelioma (Gupta 2016)
|
|
Amg221
(Gibbs 2011)
|
Semi-mechanistic population PK/PD model of subcutaneous adipose
11-beta-hydroxysteroid dehydrogenase type 1 (11-beta-HSD1) activity
after single oral doses of AMG 221, a selective 11-beta-HSD1 inhibitor,
in healthy obese adults (Gibbs 2011). Two-compartment PK with
first-order absorption and lag time; dose-dependent bioavailability
reduced at 3 mg vs 30/100 mg; adipose-tissue effect compartment linked
to plasma by a first-order equilibration rate constant (keo) and to the
tissue-concentration observation by an adipose-plasma density correction
factor (kpp); direct-effect Imax inhibitory model on 11-beta-HSD1
activity driven by the effect-site plasma-equivalent AMG 221
concentration.
|
|
Amifampridine
(Thakkar 2017)
|
Joint parent-metabolite population PK + fractional-Emax PD model for
3,4-diaminopyridine (3,4-DAP, amifampridine) free base and its N-acetyl
metabolite 3-Ac DAP in 49 adults with Lambert-Eaton myasthenia (Thakkar
2017). Two-compartment parent + one-compartment metabolite with Fm fixed
to 1 (all parent clearance forms metabolite). Body weight is
allometrically scaled on CL/F and CLm/F3ACDAP (exponent 0.75 fixed) and
linearly on Vp/F (exponent 1 fixed), all with reference weight 82 kg.
Serum creatinine acts on CLm/F3ACDAP through (0.8/SCR)^0.7 with median
SCR 0.8 mg/dL. The PD submodel describes the Triple Timed Up and Go
(3TUG) score in seconds via a fractional-inhibitory Emax equation Effect
= E0 * (1 - Emax * Cp / (EC50 + Cp)) where Cp is the parent 3,4-DAP
plasma concentration in ng/mL.
|
|
Amikacin
(Delattre 2010)
|
Two-compartment IV population PK model for amikacin in critically ill
adult patients with severe sepsis or septic shock during the first 24
hours of antibiotic treatment (Delattre 2010)
|
|
Amikacin
(Tod 1998)
|
Two-compartment intravenous population PK model for amikacin in febrile,
severely neutropenic adults with hematological malignancies (Tod 1998);
clearance modeled as the sum of a non-renal intercept and a
Cockcroft-Gault-like renal component with sex-stratified slope
coefficient (males theta_1, females theta_2), age-correction factor
(theta_3 - AGE/100), and Cockcroft-Gault-like renal-function ratio (WT /
CREAT). Power-variance residual-error model.
|
|
Aminocaproic
acid (Stricker 2015)
|
Two-compartment IV population PK model for epsilon-aminocaproic acid
(EACA) in infants undergoing craniofacial reconstruction and adolescents
undergoing posterior spinal fusion surgery (Stricker 2015)
|
|
AminocaproicAcid
(Stricker 2013)
|
Two-compartment IV population PK model for epsilon-aminocaproic acid
(EACA) in infants (2-24 months) undergoing craniofacial reconstruction
surgery. Allometric scaling on body weight (reference 8.82 kg; fixed
exponents 0.75 on CL and Q, 1.0 on V1 and V2), an asymptotically
increasing post-natal age maturation effect on clearance (age50 = 7.36
weeks), and binary intra-operative-period multipliers on CL (0.89) and
V1 (0.80) capturing the composite effect of anaesthesia, blood loss, and
surgical fluid management. Parameter values from Stricker 2013 Table 4.
|
|
Amivantamab
(Marcantonio 2022)
|
QSP. Two-compartment bispecific anti-receptor x anti-receptor
mechanistic PKPD model of amivantamab-(EGFR, c-Met) binding in adults
with EGFR-exon-20-mutant non-small-cell lung cancer (Marcantonio 2022
Early Feasibility Assessment, Case Study 2). Amivantamab has one arm for
EGFR (Kd 1.4 nM) and one arm for c-Met (Kd 0.04 nM) with valency 1 per
target (per Jarantow 2015). Model tracks membrane EGFR (R1), membrane
c-Met (R2), and soluble c-Met (S2) at 5.9 nM in both central and
peripheral compartments. Soluble EGFR is NOT modelled (shed_css_1 = 0 in
JSON). Drug states: free drug (Ab_00) plus five populated bound forms
Ab_R1, Ab_R2, Ab_S2, Ab_R1R2, Ab_R1S2 per compartment. Since each arm is
monovalent, the states with double- target arm binding (Ab_R1R1,
Ab_R2R2, Ab_S2S2) do not populate and are omitted. Parameters FIXED from
paper Tables 3 (target-side EGFR/c-Met) and 4 (drug-side) plus the
Assess run file JSON; disease and toxicity compartments omitted per
paper Case Study 2 text.
|
|
Amlitelimab
(Tiraboschi 2025)
|
Two-compartment population PK model for amlitelimab (anti-OX40L mAb) in
adults, with parallel first-order and Michaelis-Menten (TMDD)
elimination, SC absorption with lag time, allometric body-weight
scaling, and SCORE_EASI / albumin covariate effects (Tiraboschi 2025)
|
|
Amlodipine
valsartan (Heo 2016)
|
Joint two-drug population PK/PD model for the antihypertensive
interaction of amlodipine (calcium-channel blocker, unsuffixed parent)
and valsartan (angiotensin-II receptor blocker, sibling-drug suffix
_val) on systolic (SBP) and diastolic (DBP) blood pressure in healthy
adult Korean volunteers receiving a single-dose fixed-dose- combination
tablet of amlodipine 10 mg + valsartan 160 mg. Each drug has a
two-compartment popPK model with zero-order absorption (duration D1) and
theory-based allometric weight scaling on CL, Q (exponent 0.75) and V1,
V2 (exponent 1) at a reference weight of 70 kg. PD uses an
effect-compartment Imax model on BP: amlodipine drives two separate
effect compartments (SBP-side and DBP-side, different Keqs); valsartan
drives one shared effect compartment (single Keq). Imax is fixed at
0.164 (the valsartan monotherapy estimate) and applies to all four
drug/endpoint arms. Combined therapy uses a proportional interaction
term (Heo 2016 Eq 8): BP = BSL * (1 - PD_amlo - PD_val - alpha * PD_amlo
* PD_val) with PD_x = Imax * Ce_x / (IC50_x + Ce_x). alpha < 0 =
infra-additive, alpha = 0 = additive, alpha > 0 = synergistic.
Estimated alpha = -0.171 for SBP and -0.0312 for DBP (both
infra-additive). Combined- therapy baselines (BSL_SBP = 117 mmHg,
BSL_DBP = 72.8 mmHg) and alpha are estimated on the 48-subject FDC
dataset; monotherapy IC50s and Keqs are fixed at their monotherapy point
estimates (Tables 1 and 2).
|
|
Amodiaquine
(Ali 2018)
|
Joint parent-metabolite population PK model for oral amodiaquine and its
CYP2C8-derived active metabolite desethylamodiaquine in adults and
children with uncomplicated Plasmodium malaria, pooled across five WWARN
cohorts (Burkina Faso, Ghana, Kenya, Uganda, Thailand). Two-transit
absorption (NN = 2) into a 2-compartment amodiaquine disposition model
with complete in-vivo conversion (with MW correction) to a 3-compartment
desethylamodiaquine disposition model. Allometric body-weight scaling on
CL/Q (exponent 0.75) and Vc/Vp (exponent 1.0) referenced at WT = 50 kg;
sigmoidal postmenstrual-age maturation on both amodiaquine and
desethylamodiaquine clearance; 22.4% lower bioavailability on the first
daily dose relative to subsequent doses.
|
|
Amoxicillin
(Fournier 2018)
|
Two-compartment IV population PK model for amoxicillin in adult ICU burn
patients hospitalized at a Swiss tertiary-care centre, with
Cockcroft-Gault creatinine clearance as a linear covariate on CL
(centered at 110 mL/min) and body weight as a linear (allometric
exponent 1) covariate on the central volume V1 (centered at 70 kg)
(Fournier 2018).
|
|
Amoxicillin
(Keij 2023)
|
One-compartment population PK model with first-order absorption for oral
and intravenous amoxicillin in preterm and term neonates treated for
possible serious bacterial infection, pooled from three studies (RAIN,
Maastricht/Pullen, and SATT). Clearance carries fixed allometric weight
scaling (exponent 0.75, reference 70 kg) plus two estimated maturation
power terms on postnatal age (reference 6.8 days) and gestational age
(reference 35.8 weeks); central volume carries fixed linear weight
scaling (exponent 1.00, reference 70 kg). Oral bioavailability is 87.3%
and absorption is slow (Ka 0.085 1/h), so oral profiles are
absorption-rate-limited. Interindividual variability is on clearance
only; residual error is combined additive plus proportional (Keij 2023).
|
|
Amoxicillin
(Muller 2008)
|
Three-compartment population PK model for intravenous amoxicillin in
pregnant women before, during and immediately after labour, with
labour-state binary indicators reducing the peripheral volume V2 during
active labour (-13.7%) and the immediate postpartum period (-29.5%)
relative to before labour (Muller 2008).
|
|
Amoxicillin
(Tang 2019)
|
Two-compartment population PK model with first-order elimination for
intravenous amoxicillin in Chinese neonates and young infants (Tang
2019). Current weight enters as a fixed allometric power on both volumes
(exponent 1) and on CL and Q (exponent 0.75); CL is further modulated by
a maturation factor F_age that is the product of two power functions of
gestational age and postnatal age. Interindividual variability is
estimated on the peripheral volume V2 and on CL only; residual
variability follows an exponential model (proportional in linear space).
|
|
Amphenmulin
chicken (Wang 2024)
|
Preclinical (broiler chicken). One-compartment intravenous PK model for
amphenmulin, a novel pleuromutilin derivative, in healthy
yellow-feathered broiler chickens given a single 20 mg/kg body-weight
dose. Wang 2024 analysed the plasma concentration-time data
non-compartmentally in Phoenix 8.1 and reported no structural
compartmental model, but the paper states that a one-compartment open
model with first-order elimination was the structure used to drive the
companion in-vitro dynamic system, and the intravenous NCA parameters in
Table 1 determine such a model completely and self-consistently: CL =
1.17 L/h/kg and Vss = 3.64 L/kg give kel = 0.321 1/h (Table 1 T1/2Ke =
2.13 h implies 0.325 1/h) and MRT = Vss/CL = 3.11 h (Table 1 MRT = 3.13
h). ONLY the intravenous route is packaged. The oral and intramuscular
routes reported in Table 1 are deliberately excluded because they cannot
be represented by any one-compartment model built on these intravenous
parameters: the published oral Cmax of 0.73 ug/mL is 2.26 times
F*Dose/Vss = 0.323 ug/mL, which is the absolute upper bound on the
concentration a one-compartment model can reach after an oral dose of 20
mg/kg at F = 5.88%, and the published oral Cmax/AUC ratio of 0.658 1/h
exceeds kel = 0.321 1/h, which a one-compartment model also cannot
produce. The intramuscular route is feasible in magnitude but Wang 2024
reports no intramuscular absorption rate constant, and its Tmax of 0.38
h is incompatible with its own terminal rate constant of 0.13 1/h
(flip-flop absorption at 0.13 1/h would place Tmax at 4.7 h). See the
vignette Assumptions and deviations section. Wang 2024 reports mean and
SD of the individual NCA estimates but no population model, so no
between-subject variability is encoded and the residual error is held at
zero for typical-value simulation.
|
|
Amphenmulin
killrate (Wang 2024)
|
In vitro (Mycoplasma gallisepticum strain S6). Concentration-dependent
kill-rate PK/PD model for amphenmulin, a novel pleuromutilin derivative,
coupling the one-compartment first-order-elimination PK of Wang 2024’s
in-vitro dynamic system to the sigmoid Emax kill-rate relationship
fitted to the static time-kill curves. Wang 2024 Materials and Methods
(Static time-kill curves) parameterises the kill rate as E = E0 + Emax *
Ce^N / (EC50^N + Ce^N), where E is the kill rate in log10(CFU/mL) per
hour (POSITIVE = killing), E0 is the corresponding rate of change in the
untreated control (NEGATIVE, i.e. net growth), Ce is the amphenmulin
concentration and Emax is an INCREMENT above E0 rather than the
asymptote, so the saturating kill rate is E0 + Emax. Note that Wang
2024’s Results text calls Emax ‘the maximum kill rate’; the printed
equation, which matches the Phoenix Sigmoid Emax model the authors used,
is taken as authoritative. Parameters are Wang 2024 Table 2, row 0-24 h,
which the paper identifies as the optimal fit (R = 0.9936) and plots in
Figure 4b: Emax = 0.1261 1/h, EC50 = 0.0325 ug/mL, E0 = -0.0093 1/h,
Hill N = 0.9238. The bacterial density bact (linear CFU/mL) is
integrated as d/dt(bact) = -ln(10) * E * bact so that log10(bact) falls
at exactly E log10(CFU/mL) per hour, reproducing the paper’s fitted kill
rate exactly at any constant concentration. The PK is the paper’s
in-vitro dynamic model (Materials and Methods, In vitro dynamic model):
first-order elimination C = C0 * exp(-kt) with k set from the
chicken intravenous half-life T1/2Ke = 2.13 h, giving k = 0.3254 1/h,
realised in the apparatus as a 1.63 mL/min flow through the 300 mL
reaction chamber (1.6360/300 = 0.326 1/h). IMPORTANT PROVENANCE
NOTE: Wang 2024 fitted the kill-rate parameters to STATIC concentrations
and ran the dynamic apparatus as a separate experiment; the two were not
fitted jointly. This model composes them, which is the paper’s stated
PK/PD integration written as an ODE system. Setting the elimination rate
to zero recovers the static experiment and reproduces Table 2 exactly.
Wang 2024 reports no between-subject variability and no residual error
magnitude for either component, so no eta parameters are present and
both residual SDs are held at zero for typical-value simulation.
|
|
Amphenmulin
pkpd index (Wang 2024)
|
In vitro (Mycoplasma gallisepticum strain S6). Inhibitory sigmoid Emax
PK/PD-index model for the anti-mycoplasma effect of amphenmulin, a novel
pleuromutilin derivative, against M. gallisepticum strain S6 in Wang
2024’s in-vitro dynamic model. Wang 2024 Materials and Methods
(Integration and modeling of pharmacokinetics/pharmacodynamics)
parameterises the effect over a 24 h dosing interval as E = E0 - (E0 -
Emax) * Ce^N / (EC50^N + Ce^N), where E is the SIGNED change in M.
gallisepticum counts over 24 h of cultivation in log10(CFU/mL) (NEGATIVE
= bacterial reduction), E0 is the corresponding change in the untreated
control, Emax is the maximal (most negative) achievable change, and Ce
is a PK/PD index. The packaged model uses the paper’s best-correlating
index AUC24h/MIC (R = 0.9657, versus 0.8995 for Cmax/MIC), formed as the
per-interval covariate AUC_AMPH divided by the parameter mic. Parameters
from Wang 2024 Table 3, AUC24h/MIC column: Emax = -2.4214 log10(CFU/mL),
E0 = -0.3845 log10(CFU/mL), EC50 = 1199.4720 h, Hill N = 3.1997. Note
the sign convention differs from the companion
Wang_2024_amphenmulin_killrate model, whose Table 2 parameters are kill
RATES with positive meaning killing; here the effect is a signed change
with negative meaning killing. Substituting Table 3 into the equation at
the paper’s headline target of AUC24h/MIC = 904.05 h returns E = -0.97
log10(CFU/mL) against the stated 1 log10 reduction, confirming the sign
convention and the equation form to within the rounding of the
four-significant-figure parameters. The bacterial density bact (linear
CFU/mL) is integrated as d/dt(bact) = ln(10) * (E / 24) * bact so that
log10(bact) changes by exactly E across each 24 h interval, reproducing
the paper’s per-interval model exactly at every 24 h boundary. There is
no PK compartment: exposure enters as the externally supplied
per-interval AUC_AMPH, because Wang 2024 derived the AUC of the in-vitro
dynamic system non-compartmentally in Phoenix. Wang 2024 reports no
between-subject variability and no residual error magnitude, so no eta
parameters are present and addSd is held at zero for typical-value
simulation.
|
|
AmphotericinB
liposomal (Hong 2006)
|
Two-compartment population PK model for liposomal amphotericin B
(AmBisome) in 39 pediatric oncology patients receiving 1-h IV infusions
(Hong 2006). Clearance and central volume scale exponentially with body
weight centered at the cohort-median 21 kg; the paper additionally
reports substantial between-occasion variability on CL and V1 that is
encoded here as IIV on fixed-at-1 multiplicative anchors (Bellanti 2015
IOV-as-IIV pattern).
|
|
AmphotericinB
liposomal calbicans (Beredaki 2024)
|
In vitro (two Candida albicans isolates; one-compartment dilution PK/PD
model). Liposomal amphotericin B (L-AMB) in vitro PK/PD model for the
Candida albicans arm that Beredaki 2024 used to VALIDATE the in vitro
system against a published neutropenic-mouse model of disseminated
candidiasis. Beredaki 2024 simulated MOUSE L-AMB pharmacokinetics in the
internal compartment of a dilution model, re-spiking to a constant
target peak once daily with an average half-life of 8 h (range 7-11 h;
target 11 h). The 48 h change in log10 CFU/mL from the starting inoculum
was then related to the PK/PD index Cmax/MIC with the sigmoidal
variable-slope Emax model E = Emax * EI^n / (EI50^n + EI^n) (Methods,
‘PK/PD analysis’), where E is the REDUCTION in log10 CFU/mL relative to
the drug-free control and the MIC is the CLSI M27 amphotericin B
deoxycholate MIC. Beredaki 2024 printed the equation and its goodness of
fit (R^2 = 0.91) but no coefficients, so e0, lemax, lec50 and lhill were
recovered by digitising the fitted curve in Figure 2; the recovered
coefficients place the stasis exposure at 2.06 Cmax/MIC against the 2.1
(0.5-3.9) printed in Figure 2, which in turn brackets the 1.6-3.8
Cmax/MIC required for stasis in mouse kidneys. The fungal density bact
(linear CFU/mL) is integrated as d/dt(bact) = ln(10) * ((e0 - kill48) /
48) * bact so that log10(bact) changes by exactly (e0 - kill48) across
the paper’s 48 h observation window, reproducing the endpoint model
exactly at the time the paper actually fitted it. The Candida auris
models this arm validates are
Beredaki_2024_amphotericinB_liposomal_cauris48h and
Beredaki_2024_amphotericinB_liposomal_cauris24h.
|
|
AmphotericinB
liposomal cauris24h (Beredaki 2024)
|
In vitro (four Candida auris clinical isolates; one-compartment dilution
PK/PD model). Liposomal amphotericin B (L-AMB) in vitro PK/PD model for
the 24 h exposure-response relationship. Beredaki 2024 simulated human
L-AMB pharmacokinetics in the internal compartment of a dilution model,
re-spiking to a constant target peak once daily for 48 h with an average
half-life of 10 h (range 5-12 h; target 9 h). The 24 h change in log10
CFU/mL from the starting inoculum was then related to the PK/PD index
Cmax/MIC with the sigmoidal variable-slope Emax model E = Emax * EI^n /
(EI50^n + EI^n) (Methods, ‘PK/PD analysis’), where E is the REDUCTION in
log10 CFU/mL relative to the drug-free control and the MIC is the CLSI
M27 amphotericin B deoxycholate MIC. Beredaki 2024 printed the equation
and the fitted curves (Figure 5, R^2 = 0.86) but no coefficients, so e0,
lemax, lec50 and lhill were recovered by digitising the 24 h curve in
Figure 5; the recovered coefficients place the stasis exposure at 5.02
Cmax/MIC against the 5 (3-7) reported in the Figure 5 legend. The fungal
density bact (linear CFU/mL) is integrated as d/dt(bact) = ln(10) * ((e0
- kill24) / 24) * bact so that log10(bact) changes by exactly (e0 -
kill24) across the paper’s 24 h observation window, reproducing the
endpoint model exactly at the time the paper actually fitted it. The
companion 48 h parameterisation – the one the paper carries into its
Monte Carlo target-attainment analysis – is
Beredaki_2024_amphotericinB_liposomal_cauris48h, and the Candida
albicans validation arm is
Beredaki_2024_amphotericinB_liposomal_calbicans.
|
|
AmphotericinB
liposomal cauris48h (Beredaki 2024)
|
In vitro (four Candida auris clinical isolates; one-compartment dilution
PK/PD model). Liposomal amphotericin B (L-AMB) in vitro PK/PD model for
the 48 h exposure-response relationship. Beredaki 2024 simulated human
L-AMB pharmacokinetics in the internal compartment of a dilution model,
re-spiking to a constant target peak once daily for 48 h with an average
half-life of 10 h (range 5-12 h; target 9 h). The 48 h change in log10
CFU/mL from the starting inoculum was then related to the PK/PD index
Cmax/MIC with the sigmoidal variable-slope Emax model E = Emax * EI^n /
(EI50^n + EI^n) (Methods, ‘PK/PD analysis’), where E is the REDUCTION in
log10 CFU/mL relative to the drug-free control and the MIC is the CLSI
M27 amphotericin B deoxycholate MIC. Beredaki 2024 printed the equation
and its goodness of fit (R^2 = 0.86) but no coefficients, so e0, lemax,
lec50 and lhill were recovered by digitising the fitted 48 h curve in
Figure 5; the recovered coefficients place the stasis exposure at 9.03
Cmax/MIC against the 9 (6-14) reported in Figure 5. The fungal density
bact (linear CFU/mL) is integrated as d/dt(bact) = ln(10) * ((e0 -
kill48) / 48) * bact so that log10(bact) changes by exactly (e0 -
kill48) across the paper’s 48 h observation window, reproducing the
endpoint model exactly at the time the paper actually fitted it. The
companion 24 h parameterisation is
Beredaki_2024_amphotericinB_liposomal_cauris24h and the Candida albicans
validation arm is Beredaki_2024_amphotericinB_liposomal_calbicans.
|
|
Ampicillin
(Tremoulet 2014)
|
One-compartment IV population PK model for ampicillin in preterm and
term neonates (Tremoulet 2014; opportunistic POPS / PTN study).
Clearance is allometrically scaled linearly to body weight and modulated
by a serum-creatinine power factor (0.6/SCR)^0.428 and a
postmenstrual-age power factor (PMA/37)^1.34. Central volume scales
linearly with body weight (0.399 L/kg). Inter-individual variability is
supported on CL only; residual variability is proportional.
|
|
Ampicillin
sulbactam (Soto 2014)
|
Joint two-compartment population PK model for ampicillin and sulbactam
in 47 Japanese adults with moderate or severe community-acquired
pneumonia receiving 30-minute IV infusions of 3 g ampicillin/sulbactam
(2:1) every 6 hours (Soto 2014). Both drugs are fitted simultaneously
via the NONMEM L2 data item; a single common Cockcroft-Gault CLcr power
effect (0.701) is applied to CL of both drugs, and CL random effects are
correlated across drugs (rho = 0.858). Body weight is a fixed linear
allometric scalar on peripheral volume V2 for both drugs. Ampicillin
uses the unsuffixed canonical compartment / parameter set; sulbactam
carries the sibling-drug suffix _sbt throughout.
|
|
Amyloid
(vanMaanen 2025)
|
Population exposure-response model of brain amyloid plaque burden
(Centiloid, CL) in patients with mild cognitive impairment or mild
dementia due to Alzheimer’s disease. A single indirect-response
(turnover) ODE describes the natural plaque time course (zero-order
formation Kin, first-order elimination Kout). The BACE1 inhibitor
verubecestat inhibits plaque formation via a fixed-Imax AUC-driven
sigmoid on Kin (Inh_verub, AUC50 in uMh of verubecestat AUC over 24
h at steady state; Imax fixed to 1 per Table 1). Each of four
anti-A-beta monoclonal antibodies (aducanumab, donanemab, gantenerumab,
lecanemab) stimulates plaque elimination via a linear
AUC/molecular-weight term on Kout (Stim_mAb = slope_mAb (AUC_mAb /
MW_mAb), with distinct slopes per mAb). AUC of each drug is a
time-varying model input (covariate); the paper’s simulations set each
AUC to its steady-state value during dosing periods and to 0 during
washout. Baseline plaque burden is a per-subject covariate used as the
plaque initial condition. Fit by NONMEM FOCE-I to 370 individual
verubecestat amyloid PET measurements from 188 aMCI due to AD subjects
(phase 3 APECS, NCT01953601) pooled with 120 summary-level PET
measurements from four anti-A-beta mAb trial programmes; external
validation on 1506 amyloid-PET measurements from 521 amyloid-positive
ADNI subjects with up to 10 years of follow-up. No IIV is encoded
(paper: ‘no additional interindividual variability was included’;
summary-level mAb data constrained the model to central-tendency
predictions).
|
|
Anakinra
(Urien 2013)
|
One-compartment population pharmacokinetic model for subcutaneous
anakinra (recombinant nonglycosylated human IL-1 receptor antagonist) in
87 children and adolescents (8 months to 21 years, 4.3 to 83 kg) treated
for systemic-onset juvenile idiopathic arthritis (SJIA) and diverse
autoinflammatory syndromes (Urien 2013). First-order absorption (Ka)
into a single central compartment with first-order elimination; apparent
clearance CL/F and apparent volume V/F are allometrically scaled to body
weight with estimated power exponents (0.47 on CL/F and 0.76 on V/F,
reference 70 kg). Inter-individual variability is reported on CL/F and
between-occasion variability on V/F; no other covariate effect (age,
sex, co-administered anti-inflammatory drugs) was retained.
|
|
Angiotensin
(BuchwalderCsajka 1999)
|
Population pharmacodynamic dose-response model of the peak systolic
(SBP) and diastolic (DBP) blood pressure increase elicited by a single
intravenous bolus of exogenous angiotensin (used as a pharmacologic
probe / ‘challenge’) in 228 healthy male volunteers across 13 phase I
trials of antihypertensive drugs acting on the renin-angiotensin system.
The final structural form is the molecular-weight-corrected Emax model E
= Emax * D / (D + ED50) (Buchwalder-Csajka 1999 Table 1 last row), where
D = DOSE_AGT_UG is the angiotensin challenge dose in ug already
expressed as angiotensin II equivalents (multiply an angiotensin I dose
by Q = 0.78 in data preparation; the paper’s text reports Q = 0.78 as
the molar-weight ratio), and Emax / ED50 are estimated separately for
SBP and DBP. This is a purely algebraic snapshot model: no PK, no time
course, no ODEs. Each observation row in the event dataset carries one
DOSE_AGT_UG value (the dose given just before the peak was sampled) and
yields one peak BP increase. The model is suitable for simulating the
peak BP response to a single angiotensin bolus during dose-finding and
placebo-period segments of an angiotensin-challenge phase I protocol; it
is NOT a model of the antihypertensive drugs whose trials supplied the
data.
|
|
Anifrolumab
(Almquist 2022)
|
Two-compartment QSS-TMDD population PK model for anifrolumab
(anti-IFNAR1 IgG1-kappa) in healthy volunteers and adults with systemic
lupus erythematosus (Almquist 2022): linear plus quasi-steady-state
target-mediated elimination via a dynamic IFNAR1 receptor pool,
time-varying linear clearance (Emax-on-time), and IFNGS-high/low and
body-weight covariate effects.
|
|
Anrukinzumab
(Hua 2015)
|
Two-compartment population PK model for anrukinzumab (anti-IL-13 IgG1
monoclonal antibody) with first-order SC absorption and linear
elimination, pooling healthy volunteers, mild-to-moderate asthma,
moderate-to-severe asthma, and ulcerative colitis patients (Hua 2015)
|
|
Anthracycline
troponinT (deVriesSchultink 2018)
|
Kinetic-pharmacodynamic (K-PD) direct-effect model for serum
high-sensitive cardiac troponin T (hs-TnT) in early-breast-cancer
patients receiving an adjuvant anthracycline regimen (de Vries Schultink
2018). The dose enters a virtual K-PD body amount compartment with
first-order elimination at rate kel; the linear direct effect TRP = TRP0
* (1 + SLOPE * Aant) raises serum troponin T above a population baseline
TRP0 in proportion to the current K-PD amount. The proportional SLOPE is
anthracycline-type dependent: epirubicin produces a 0.524-fold smaller
effect than the doxorubicin reference, encoded jointly by the
CONMED_DOXORUBICIN and CONMED_EPIRUBICIN indicators. No other covariates
retained. Companion file
deVriesSchultink_2018_trastuzumab_LVEF.R consumes the
per-subject peak troponin T from this model as a covariate.
|
|
Anti
tryptase (Rymut 2023)
|
Mechanistic population PK/PD model for the anti-tryptase IgG4 monoclonal
antibody MTPS9579A in healthy adults and adults with moderate-to-severe
asthma (Rymut 2023). Two-compartment serum disposition with first-order
SC absorption and allometric weight scaling on linear CL and central
volume; quasi-equilibrium (QE) TMDD describes saturable binding of
MTPS9579A to total monomeric serum tryptase; a mechanistic airway
interstitial-fluid (ISF) compartment receives free mAb and mAb-monomer
complex from the systemic circulation through lymph flow with vascular
reflection coefficients; in the ISF, tryptase is secreted as the active
tetramer (target_isf), spontaneously dissociates into inactive monomers
(monomer_isf), and is rapidly disrupted by bound mAb (kbreak); free
MTPS9579A binds tetramer and monomer with the same KD. Estimated
systemic TMDD parameters come from a NONMEM 7.4.3 SAEM fit to 106
healthy Phase 1 subjects (Table 1); fixed mechanistic ISF parameters
come from in vitro / physiological literature and from a healthy-subject
visual fit of the upper-airway biodistribution coefficient at 3%
(Methods, Table S2, Figure S2).
|
|
Antithrombin
(DeJongh 2014)
|
Two-compartment population PK model with linear elimination from the
central compartment for recombinant human antithrombin (rhAT) in adults
with hereditary antithrombin deficiency (HD) undergoing perioperative or
peripartum treatment (DeJongh 2014). Delivery (pregnancy) status
approximately doubles CL and Vss versus non-pregnant surgery patients.
Baseline AT activity is modelled as a subject-level endogenous parameter
(Dansirikul-type baseline handling) that adds to the drug-derived AT
activity in the observation.
|
|
Antithrombin
(Moffett 2017)
|
One-compartment population PK model with exponential residual error for
intravenous human (plasma-derived) antithrombin (AT) concentrate in
paediatric patients (Moffett 2017). Structural clearance uses an
allometric weight arm with additive concurrent-UFH-dose potentiation;
volume of distribution uses allometric weight scaled by a power of the
per-subject baseline AT activity level. The observed AT activity level
is the sum of dose-derived AT concentration plus the endogenous baseline
(Dansirikul B3 handling of endogenous baseline).
|
|
Apitolisib
human (Moein 2024)
|
Integrated PK-PD-efficacy model for orally administered apitolisib
(GDC-0980), a dual PI3K/mTOR inhibitor, in patients with advanced solid
tumors or non-Hodgkin’s lymphoma (two phase 1 dose-escalation studies,
NCT00854152 and NCT00854126). Three sequentially-fitted layers in one
ODE system: (1) two-compartment first-order-absorption population PK
with an absorption lag (individual estimates carried in and held fixed);
(2) an indirect-response model in which apitolisib inhibits the
production rate of phosphorylated Akt (pAkt) measured in PLATELET-RICH
PLASMA as a surrogate for tumor target modulation, expressed as %pAkt
relative to a drug-free baseline of 100%; (3) exponential growth of the
RECIST sum of longest diameters at net rate kg opposed by a sigmoidal
shrinkage rate ks driven by the percent pAkt inhibition I = 100 - %pAkt.
Imax and the pAkt Hill exponent are fixed at 1, and kout is not
estimated but derived as kin/%pAkt(0) = kin/100, so the biomarker pool
equilibrates essentially instantaneously and %pAkt tracks the plasma
concentration directly. Only the five efficacy parameters (kg, kmax,
ki50, gamma2, proportional error) and the four tumor IIV terms were
estimated in this integrated fit. Companion preclinical model:
modellib(‘Moein_2024_apitolisib_mouse’).
|
|
Apitolisib
mouse (Moein 2024)
|
Preclinical (mouse; 786-O human renal cell adenocarcinoma xenograft).
Integrated PK-PD-efficacy model for orally administered apitolisib
(GDC-0980), a dual PI3K/mTOR inhibitor. Three sequentially-fitted layers
in one ODE system: (1) one-compartment first-order-absorption PK (CL/F,
V/F, ka carried in from the mouse PK model and held fixed); (2) an
indirect-response model in which apitolisib inhibits the production rate
of phosphorylated Akt (pAkt) measured in TUMOR TISSUE, expressed as
%pAkt relative to a drug-free control baseline of 100%; (3) exponential
tumor-volume growth at net rate kg opposed by a sigmoidal shrinkage rate
ks driven by the percent pAkt inhibition I = 100 - %pAkt. Imax and the
pAkt Hill exponent are fixed at 1, and kout is not estimated but derived
as kin/%pAkt(0) = kin/100, so the biomarker pool equilibrates
essentially instantaneously and %pAkt tracks the plasma concentration
directly. Only the five efficacy parameters (kg, kmax, ki50, gamma2,
proportional error) and the two tumor IIV terms were estimated in this
integrated fit.
|
|
Apixaban
(Ueshima 2018)
|
One-compartment population pharmacokinetic and pharmacogenomic model for
oral apixaban in Japanese adult patients with atrial fibrillation
(Ueshima 2018). Apparent oral clearance CL/F is the sum of an apparent
renal arm (power on creatinine clearance, CCR/70) and an apparent
non-renal arm carrying two recessive-/dominant-style pharmacogenomic
factors: CYP3A5 3 carrier (genotype 1/3 or 3/*3)
reduces non-renal CL/F by a factor of 0.312, and ABCG2 421A/A (rs2231142
homozygous variant) reduces non-renal CL/F by a factor of 0.341.
Apparent volume of distribution Vd/F = 24.7 L (no significant
covariates). Absorption rate constant ka was fixed at 0.42 1/h from a
prior publication (Frost 2013 Br J Clin Pharmacol, reference 13 in the
paper) because the sparse trough-and-2-point-postdose sampling design
lacked enough absorption-phase data to identify ka.
|
|
Apomine
(Bonate 2004)
|
Two-compartment population PK model for oral apomine (a synthetic
bisphosphonate-ester anti-cancer agent) in 38 subjects – 19 healthy
adult males and 19 male and female patients with advanced solid tumours
– pooled from four model-development studies (Bonate 2004 Studies 1, 2,
5, 6) with three validation studies (Studies 3, 4, 7). Apomine is
administered orally with or without food in single and multiple-dose
regimens over 30 to 2100 mg total daily dose. Disposition is a
two-compartment model with linear elimination and a first-order
absorption mixture: a dominant Group 1 subpopulation (97 %, paper P1
logit) with an estimable lag time and faster absorption rate, and a
minority Group 2 subpopulation (3 %) with no lag time and slower
absorption (Table 3). Apparent oral clearance is time-dependent via an
empirical sigmoid Emax auto-induction model in elapsed time (CL = CL0 +
CLmax * time^n / (cl_hill_t50^n + time^n); Table 3), reaching 50 % of
the maximal induction-driven increment in about two days. Relative
bioavailability F1 is dose-saturable (F1 = D50 / (Dose + D50)) with an
additional fractional food effect (1 + theta_food * FED), where the
F1max anchor is structurally fixed at 1 (Table 3). Cancer patients have
lower baseline CL/F and lower central volume than healthy males (encoded
via the DIS_CANCER indicator with log-additive effects e_cancer_cl and
e_cancer_vc back-derived from Table 3); intercompartmental clearance and
peripheral volume are common to both populations. Central volume scales
proportionally with body weight at a fixed allometric exponent of 1.0
(Table 3). A bimodal high-Vp subpopulation observed in the four
healthy-male multiple-dose subjects (Bonate 2004 Study 2) is encoded as
a binary indicator MIX_HIGH_VP multiplying the typical peripheral volume
by 23.5. Inter-occasion variability (18 % on CL and Vc, Table 3) is
omitted from this file because occasion definitions are
study-design-specific (per the standard nlmixr2lib practice; see
vignette Assumptions and deviations).
|
|
Apx3330
(Silva 2024)
|
Population pharmacokinetic model for APX3330 (E3330), a selective
APE1/Ref-1 redox inhibitor, measured as total quinone in plasma after
oral dosing. Two-compartment disposition with first-order absorption and
an absorption lag time, fitted to 1460 plasma concentrations pooled from
four Eisai studies in 49 healthy Japanese male volunteers (single
dose-escalation 10-600 mg, multiple-dose 120 mg once or twice daily, and
a fasted-vs-fed crossover) and one Apexian phase I study in 19 patients
with advanced solid tumors dosed 120-360 mg twice daily. All disposition
parameters are apparent (oral) values because absolute bioavailability
was never measured. Body weight is a power-model covariate on CL/F
(exponent 0.659) and V1/F (exponent 0.839) referenced to 70 kg; the
oncology cohort carries a log-additive shift on CL/F, and dosing in the
fed state carries a log-additive shift on the absorption lag time.
Inter-individual variability is estimated on CL/F, V1/F and ka with a
CL/F-V1/F correlation of 0.349, and residual error is proportional
(16%). The paper’s companion GastroPlus ACAT semi-mechanistic absorption
model is a commercial-platform model and is not reproduced here; see the
validation vignette.
|
|
Arginine
(Brussee 2016)
|
Two-compartment population PKPD model for intravenous L-arginine
adjunctive therapy in 73 adults with moderately severe falciparum
malaria. Exogenous L-arginine PK is two-compartment IV with allometric
scaling on CL and V1 and a multiplicative Papuan-ethnicity effect on CL.
Endogenous L-arginine concentration follows a second-order polynomial
recovery function indexed from approximately two days before
presentation (start of symptoms); lognormal between-subject variability
multiplies the typical polynomial. Pharmacodynamic output 1 (exhaled NO,
ppb) is linear in the exogenous arginine concentration with a
per-subject baseline. Pharmacodynamic output 2 (reactive-hyperemia
peripheral-arterial-tonometry index, RH-PAT) is linear in the predicted
NO minus its baseline, i.e., linear in the exogenous arginine
concentration.
|
|
Aripiprazole
(Kim 2008)
|
Joint one-compartment population PK model for oral aripiprazole and its
active metabolite dehydroaripiprazole in 80 Korean psychiatric patients
(Kim 2008). First-order absorption (Ka FIXED at 1.06 1/h per a prior
popPK analysis; the sparse-sampling design could not identify Ka) into a
single aripiprazole central compartment with first-order elimination,
and a metabolite central compartment that receives the entire parent
elimination flux (fm = 1 assumed for identifiability; metabolite CL and
V are apparent values scaled by the unknown fm and reported as CL(m)/fm
and V(m)/fm) with first-order elimination of dehydroaripiprazole.
Covariate analysis retained CYP2D6 genetic polymorphisms as the only
significant covariate on parent CL/F, with four genotype strata fit as
independent typical-value clearances (Group I 3.15 L/h, Group II 2.66,
Group III 2.27, Group IV 1.83); the paper rejected pooling Groups I+II
+III into a single CYP2D6 extensive-metabolizer stratum (uniting them
increased OFV by 15.8 points). Age, body weight, gender, and CYP3A5
genetic polymorphisms were screened and not retained. Inter-individual
variability is fit on CL/F (shared across strata), V/F, and CL(m)/fm
with an estimated covariance between CL/F and CL(m)/fm (value not
reported by the paper; see vignette Assumptions and deviations). A
proportional residual-error model is used separately for aripiprazole
and dehydroaripiprazole.
|
|
Aripiprazole
(Knights 2015)
|
Two-compartment population PK model for oral aripiprazole in adult
psychiatric patients (Knights 2015), with first-order absorption,
linear-deviation weight (gated by WT < 115 kg) and age effects on
apparent oral clearance, multiplicative CYP2D6 poor-metabolizer effect
on CL/F, linear weight (gated by WT < 115 kg) and age effects with
multiplicative female-sex effect on the peripheral volume, linear weight
(gated by WT < 115 kg) effect with multiplicative female-sex effect
on apparent inter-compartmental clearance, correlated inter-individual
variability across Vc/F, Q/F, and Vp/F, independent IIV on ka and CL/F,
and a proportional residual error.
|
|
Aripiprazole
(Koue 2007)
|
Two-compartment population PK model for oral aripiprazole in healthy
Japanese male volunteers (Koue 2007), with first-order absorption, an
absorption lag time, body-weight linear scaling on Vc/F, Vp/F, Q/F, and
CL/F, additive linear-deviation CYP2D6 intermediate- and
poor-metabolizer effects on CL/F (Group 1 = extensive metabolizer
reference), an additive linear-deviation itraconazole-coadministration
(CYP3A4 inhibitor) effect on CL/F, independent inter-individual
variability on every structural parameter, and a log-normal
(exponential) residual error.
|
|
Artemether
(Hietala 2010)
|
Joint parent-metabolite population PK model for oral artemether (ARM)
and its active metabolite dihydroartemisinin (DHA) in 50 Tanzanian
children (ages 1-10 years, weights 8-30 kg) with uncomplicated
Plasmodium falciparum malaria treated with the standard six-dose
weight-based Coartem (artemether 20 mg + lumefantrine 120 mg per tablet)
regimen at 0, 8, 24, 36, 48, and 60 hours (Hietala 2010). Absorption is
first-order with ka fixed at 1/h. Disposition is two-compartment for ARM
with complete in-vivo conversion to DHA (bioavailability of DHA fixed at
1 to render the metabolite model identifiable); DHA disposition is
one-compartment. The apparent oral clearance of ARM is time-dependent
with a linear increase per dose number occasion (CL/F_ARM = theta1 * (1
+ theta2 * (OCC - 1)), OCC = 1..6), reproducing a ~3.4-fold rise over
the six-dose regimen attributed to enzyme induction. All PK parameters
are reported per kilogram body weight (linear weight normalisation
applied inside model()).
|
|
Artemether
(Hoglund 2015)
|
Joint parent-metabolite population PK model for oral artemether and its
active metabolite dihydroartemisinin (DHA) in 89 HIV-infected Ugandan
adults receiving artemether-lumefantrine (Coartem) with or without
concomitant antiretroviral therapy (efavirenz, nevirapine, or
lopinavir/ritonavir) (Hoglund 2015). 3-transit-compartment absorption
with ka = ktr feeds a 1-compartment artemether disposition; complete
in-vivo conversion of artemether to a 1-compartment DHA disposition with
stoichiometric molar conversion. Enzymatic auto-induction of the
first-pass demethylation of artemether is modelled as a Hill function of
time-since-first-dose with fixed maximum maturation (100 % increase in
apparent CL) and fixed maturation half-time (62 h, literature value) and
an estimated Hill coefficient (0.445). Relative bioavailability F is
anchored at 1 (fixed) with log-normal IIV (58.6 % CV). Three
antiretroviral drug-drug interactions are encoded as linear-deviation
effects: lopinavir/ritonavir increases AM CL/F by 32.8 % and DHA CL/F by
143 %; efavirenz and nevirapine decrease relative bioavailability by
71.5 % and 66.3 % respectively; nevirapine additionally decreases DHA
CL/F by 44.5 %. IIV is retained on AM CL, DHA CL, the mean transit time,
and F. NONMEM additive residual error on log-transformed concentrations
is encoded as a proportional residual in linear concentration space for
both parent and metabolite.
|
|
Artemether
(Mosha 2014)
|
Joint parent-metabolite population PK model for oral artemether (AM) and
dihydroartemisinin (DHA) in 33 pregnant (2nd or 3rd trimester) and 22
non-pregnant women with uncomplicated Plasmodium falciparum malaria in
Rufiji, Tanzania after standard fixed-dose artemether-lumefantrine
(Mosha 2014). One-compartment AM disposition with first-order absorption
and linear metabolism to a one-compartment DHA disposition, including a
presystemic AM-to-DHA conversion fraction (1 - F1) with F1 =
expit(logit_F1) parameterised on the logit scale. Absorption ka fixed at
0.70 1/h and DHA volume fixed equal to AM Vc per the source paper. IIV
is present only on AM CL (99% CV); the remaining structural parameters
carry no IIV in the final model. None of the available covariates
(pregnancy, body weight, BMI, age, gestational age, diarrhoea) reached
statistical significance on AM or DHA PK in Mosha 2014 and so none are
encoded. AM residual error is combined (proportional plus additive); DHA
residual error is proportional.
|
|
Artemether
(Tarning 2012)
|
Joint parent-metabolite population PK model for oral artemether and its
active metabolite dihydroartemisinin (DHA) in 21 pregnant women (2nd or
3rd trimester) with uncomplicated Plasmodium falciparum malaria in
Uganda after the standard fixed-dose oral artemether-lumefantrine
regimen (Tarning 2012). Absorption is flexible: zero-order dissolution
into a depot of duration DUR feeds a 6-compartment transit chain at rate
ktr; the same ktr empties transit6 into central (ka set equal to ktr).
Disposition is 1-compartment for both artemether and DHA with complete
in-vivo conversion of artemether to DHA. Relative bioavailability F is
fixed at 1 with log-normal IIV; no statistically significant covariates
were retained in the final model (Methods / Results); a single combined
additive residual on log-transformed plasma concentrations is shared by
both species.
|
|
Artemether
parasitemia (Hietala 2010)
|
Joint artemether (ARM) + dihydroartemisinin (DHA) PK model coupled to a
semimechanistic Plasmodium falciparum parasite life-cycle PD model in
Tanzanian children (ages 1-10 years, weights 8-30 kg) with uncomplicated
falciparum malaria (Hietala 2010). The PK is the same Table 1
two-compartment ARM (with time-dependent CL/F_ARM via the OCC
dose-occasion covariate) and one-compartment DHA structure as
modellib(‘Hietala_2010_artemether’). The PD (Table 3) is a five-stage
parasite life-cycle model: parasites mature through tinyrings (PTR),
smallrings (PSR), largerings (PLR), and mature trophozoites / schizonts
(PMT), and parasites killed or injured by drug accumulate in a spleen
compartment (Pspleen) before clearance at a fixed elimination rate
k_spleen = 0.26 / h (Gordi et al. 2002, ref 9). Replication is encoded
as a multiplication factor REPL_p applied to the PMT -> PTR transit
(estimated to 4 in symptomatic patients; fixed to 1 in asymptomatic
children, not encoded in this file). Drug killing is modelled on all
visible developmental stages as k_ARM = S * log[ARM] and k_DHA = S *
log[DHA] with shared slope S_ARMDHA = 0.073 (Table 3). Visible
parasitemia is the sum of the ring-stage compartments plus the spleen
pool. Lumefantrine effect was tested but not retained in the source
paper and is intentionally absent from this model.
|
|
Artemisinin
(Asimus 2007)
|
Semiphysiological autoinduction popPK model for oral artemisinin, fit to
pooled plasma data from six clinical studies (33 healthy male Vietnamese
volunteers + 54 male falciparum-malaria patients). The structural model
is identical to the original Gordi 2005 saliva-based model except no
absorption lag-time is estimated. Three artemisinin compartments (gut
depot, liver V_H = 1 L fixed, sampling V_S = 26.1 L) are linked in a
circular well-stirred-hepatic-extraction loop with hepatic plasma flow
Q_H = 0.63 L/h/kg of body weight. Two enzyme states (precursor1 + enzyme
pool) drive autoinduction: hepatic artemisinin amount linearly
stimulates precursor formation (slope s_ind); the precursor transitions
to enzyme with rate constant kpout = 1/MIT = 1/(2.0 h); the enzyme
decays with first-order rate kdeg = ln(2)/94 h. Intrinsic clearance is
proportional to enzyme amount and saturates in hepatic concentration via
Michaelis-Menten kinetics (CL_int,t = vmax * enzyme / (km + C_H)),
giving a pre-induced hepatic extraction E_H = 0.74 increasing to 0.98
after autoinduction (a roughly 13-fold drop in oral bioavailability with
only a modest change in systemic clearance).
|
|
Artemisinin
(Birgersson 2016)
|
One-compartment population PK model for oral artemisinin in 15 healthy
male Vietnamese volunteers, with a seven-compartment transit-absorption
chain (number of transits fixed at 7). The published final model carries
inter-occasion variability on apparent clearance and mean transit-time
and inter-individual variability on relative bioavailability; for
forward simulation in nlmixr2lib the IOV terms are mapped onto etas
(etalcl, etalmtt) so a single-occasion simulation reproduces the
population variability. The published full covariate analysis found no
clinically significant effect (>20 %) of formulation, dose level (160
vs 500 mg), or concomitant piperaquine on the structural PK parameters,
so no covariates are carried in the model.
|
|
Artemisinin
(Sidhu 1998)
|
One-compartment population PK model with first-order absorption for oral
artemisinin in 23 paediatric (2-12 y) and 31 adult (16-45 y) Vietnamese
patients with uncomplicated falciparum malaria, fit to sparse capillary
plasma samples from a 5-day 10 mg/kg/day field-setting regimen. Separate
population estimates for CL/F and V/F are carried for adults
(per-subject) and children (per-kg body weight) via a CHILD age-group
covariate. Time-dependency in artemisinin disposition is modelled as a
6.9-fold systematic decrease in oral bioavailability between the Day 1
and Day 5 doses, with the published inter-occasion variability on
apparent CL/F and V/F retained per occasion. Inter-individual
variability on CL/F and V/F is collectively estimated for both age
groups; the published etaCL/etaVc correlation ‘near unity’ is encoded at
0.95 for numerical stability.
|
|
Artesunate
(Hendriksen 2013)
|
Joint parent-metabolite population PK model of intramuscular artesunate
(ARS) and its active metabolite dihydroartemisinin (DHA) in 70 African
children aged 7 months to 11 years admitted with severe Plasmodium
falciparum malaria (Hendriksen 2013). Each species has a one-compartment
apparent-volume disposition; ARS is delivered by a zero-order input over
a 1-min fixed duration (the IM absorption from the injection site, fixed
because too few samples were collected during the absorption phase to
identify the rate) and is converted mole-for-mole to DHA with no
separate parent elimination. Body weight is the dominant covariate
(allometric scaling with fixed exponents 0.75 on apparent clearance and
1.0 on apparent volume for both species; reference 10.9 kg), with
hemoglobin additionally lowering DHA clearance by 10.2% per g/dL above
the reference 7.1 g/dL.
|
|
Artesunate
(LohyDas 2018)
|
Joint parent-metabolite population PK model of oral artesunate (ARS) and
its active metabolite dihydroartemisinin (DHA) in 50 adult patients with
uncomplicated, artemisinin sensitive or resistant Plasmodium falciparum
malaria in southern Myanmar (Lohy Das 2018, Malaria Journal). ARS
absorption is described by a 3-transit-compartment chain (n = 3 fixed)
followed by a one-compartment ARS disposition; complete in-vivo
conversion of ARS to DHA is assumed (all ARS clearance is metabolic
conversion). DHA disposition is one-compartment. Allometric body-weight
scaling is applied to all CL (exponent 0.75) and V (exponent 1.0)
parameters, centered on the population-median 50 kg. F is fixed at 1.
The packaged model file omits the published time-varying
parasite-density covariates on MTT and on F (Eqs. 3 and 4) and the
entire PD layer (mixture-Emax parasite-killing model with effect
compartment); both depend on the upstream Lohy Das 2017 AAPS J paper
(ref [36]) which is not on disk. See the vignette’s Assumptions and
deviations section for the rationale.
|
|
Artesunate
(Morris 2011)
|
Joint parent-metabolite population PK model for single-dose oral
artesunate (AS) and its active metabolite dihydroartemisinin (DHA) in 26
pregnant and 25 non-pregnant women with asymptomatic Plasmodium
falciparum malaria in the Democratic Republic of Congo (Morris 2011).
Each species has a one-compartment apparent-volume disposition, with
mixed zero-order plus lagged first-order absorption of AS and complete
in-vivo conversion of AS to DHA (no separate AS elimination). Pregnancy
increases DHA apparent clearance by 42.3% relative to non-pregnant
controls (the only retained covariate); the postpartum sub-cohort could
not be characterised by a structural model and is not represented.
|
|
Artesunate
(Simpson 2013)
|
In vitro (P. falciparum). Sigmoid Emax inhibition model of artesunate
effect on hypoxanthine uptake by clinical Plasmodium falciparum isolates
from the Thai-Myanmar border (Shoklo Malaria Research Unit, 1993-2005),
with pfmdr1 genotype covariate effects on EC50. The ‘subject’ in the
NLME framework is a parasite isolate (n=474 isolates with artesunate
data). STIM_ARTESUNATE_NM is the per-well drug concentration in the in
vitro hypoxanthine-uptake-inhibition assay; the model has no PK and no
time evolution. E0 and Emax are fixed per Simpson 2013 Table 3 footnote.
|
|
Artesunate
(Tan 2009)
|
Joint parent-metabolite population PK model of oral artesunate (AS) and
its active metabolite dihydroartemisinin (DHA) in 91 healthy Korean
adult volunteers (Tan 2009). AS is described by a one-compartment
first-order absorption / first-order elimination disposition; DHA by a
two-compartment disposition (central + peripheral). AS is converted
mole-for-mole to DHA as the only elimination pathway. Body weight
linearly increases DHA apparent clearance (1.9 L/h per kg above the 61.5
kg reference) and a high-fat / high-caloric meal at dosing reduces AS
absorption rate Ka by 84%. Subjects pooled across four Phase I studies
(single-dose ascending, drug-interaction with pyronaridine, food-effect,
and three-day multiple-dose) at 2-5 mg/kg oral AS.
|
|
Artesunate
hamster pbpk (Kang 2023)
|
Preclinical (golden hamster). PBPK (minimal, joint parent + metabolite;
WinNonlin 8.3). Oral artesunate and its active metabolite
dihydroartemisinin, each described by a five-compartment minimal PBPK
model in which lung and trachea – the antiviral target tissues – are
explicit perfusion-rate-limited organs and all nontarget tissues are
lumped into a rest-of-body compartment (Kang et al. 2023, Pharmaceutics
15:838). Artesunate is treated as a prodrug that is completely
hydrolysed to dihydroartemisinin in the blood compartment, so the parent
apparent clearance CL/F is simultaneously the metabolite formation rate;
the two subsystems are therefore one jointly fitted model and are kept
in a single file. Plasma was the assay matrix and is recovered from
blood via the fixed blood-to-plasma ratio 0.75 for both compounds.
States carry molar amounts (nmol) so that the 1:1 artesunate to
dihydroartemisinin conversion is mass-balanced. Physiological volumes
and blood flows (Table 1) are fixed; the biochemical parameters (Table
2) were fitted to 60 artesunate and 127 dihydroartemisinin pooled
measurements by naive pooled-data analysis, so the model carries no
between-subject variability and is intended for typical-value
simulation. Two Table 2 / equation anomalies are reproduced verbatim –
see the vignette Errata.
|
|
Asc10a
(Lv 2025)
|
Population PK model of ASC10-A (also called NHC,
beta-D-N4-hydroxycytidine), the active nucleoside metabolite of the oral
double prodrug ASC10, in Chinese healthy adult volunteers (Lv 2025).
ASC10 is under clinical development for COVID-19 and shares an active
moiety with molnupiravir. Data pooled 57 subjects with 1,634 ASC10-A
plasma concentrations from a Phase I trial (NCT05523141) with a
multiple-ascending-dose part (50-800 mg BID x 5 days + one AM dose on
day 6) and a fasted/fed food-effect part. The final model is a
two-compartment disposition with first-order elimination and a
two-transit-compartment absorption chain (rate constant KTR). Body
weight enters as an estimated power on CL/F (exponent 0.903) and a fixed
power on Vc/F (exponent 1.0), normalised to the median 61.4 kg. Food
status enters KTR only: fed KTR is scaled by theta_KTR-food = 0.474,
i.e., ~52.6% reduction relative to fasted, with no effect on relative
bioavailability (F is fixed at 1). Residual error is combined additive
(2.3 ng/mL, fixed) + proportional (SD = 0.41).
|
|
Asenapine
(Dogterom 2018)
|
Two-compartment population PK model with first-order sublingual
absorption for asenapine in pediatric patients (aged 10-17 years) with
schizophrenia, bipolar I disorder, or other psychiatric disorders
(Dogterom 2018 Drug Design, Development and Therapy). Central /
peripheral volumes and absorption-rate constant were fixed from a Phase
I-only fit; no intrinsic covariate (age, BMI, race, sex) was retained in
the final model. Residual error switches per observation between
intensive Phase I PK sampling (27.8% CV) and sparse Phase III efficacy
sampling (56.0% CV), with an additional between-subject scaling of the
residual SD (19.2% CV).
|
|
ASP8232
(Snelder 2020)
|
Integrated multiple-target-mediated drug disposition (TMDD) population
PK-PD model for the small-molecule vascular adhesion protein-1 (VAP-1 /
AOC3) inhibitor ASP8232 in adults (Snelder 2020). First-order oral
absorption with lag time, three-compartment disposition (central + two
peripheral compartments; V3 fixed equal to V2). ASP8232 binds under a
quasi-steady-state assumption to soluble VAP-1 (sVAP-1) in the central
compartment and to membrane-bound VAP-1 (mVAP-1) in the central and both
peripheral compartments; sVAP-1 turnover and drug-target complex
elimination are assumed negligible so all VAP-1 pool sizes are held
constant per subject. A single dissociation constant KD applies to every
binding site. Three observed analytes: (1) total ASP8232 in the central
compartment (free + drug-sVAP-1 complex, matching the LC-MS assay), (2)
total sVAP-1 in the central compartment (matching the ELISA assay), and
(3) VAP-1 plasma activity (a power function of free sVAP-1). Pooled fit
across four studies – two phase 1 (first-in-human 8232-CL-0001 and
renal-impairment / T2DM-CKD 8232-CL-0002) and two phase 2 (VIDI in
diabetic macular oedema, ALBUM in diabetic kidney disease).
Between-population PK differences are explained by baseline eGFR
(CKD-EPI) effects on clearance (sigmoid Emax, Hill coefficient fixed at
10) and relative bioavailability (power). Female subjects have 12.5%
higher VAP-1 concentrations. Full omega block on CL, sVAP-1c, and the
activity slope SL. Log-additive residual errors with a multiplicative
factor of 1.88 on the phase-2 (VIDI + ALBUM) residuals for ASP8232 PK
and VAP-1 activity.
|
|
Astegolimab
(Kotani 2022)
|
Two-compartment population PK model for astegolimab (anti-ST2 IgG2) in
adults with severe asthma (Kotani 2022)
|
|
Asundexian
(Yassen 2025)
|
Two-compartment population PK model with two transit absorption
compartments for asundexian, an oral selective Factor XIa inhibitor, in
healthy volunteers and adult patients at risk for thromboembolic /
cardiovascular events (Yassen 2025)
|
|
AT9283
(Duong 2017)
|
Two-compartment IV population PK model for AT9283 (aurora kinase
inhibitor) in adults and children with leukaemia or solid tumours (Duong
2017): allometric body-weight scaling on all four disposition parameters
(CL, Vc, Q, Vp) with a power effect of estimated GFR on CL. Population
residual error switches between adults (combined additive +
proportional) and children (additive only) via the CHILD binary
indicator.
|
|
Atazanavir
(Colombo 2006)
|
One-compartment first-order-absorption population PK model with
absorption lag-time for orally administered atazanavir in HIV-1 infected
adults; binary low-dose ritonavir (RTV) coadministration reduces
apparent oral clearance by 46% (Colombo 2006).
|
|
Atazanavir
(Dickinson 2009)
|
One-compartment first-order-absorption population PK model with
absorption lag-time for oral ritonavir-boosted atazanavir in
HIV-infected adults and healthy volunteers; ritonavir AUC0-24 (median
7.52 mg*h/L) enters CL/F via a power function (Dickinson 2009).
|
|
Atazanavir
(Foissac 2011)
|
One-compartment first-order-absorption population PK model for orally
administered atazanavir in 51 HIV-1-infected children and adolescents
(3-18 years, 13-79 kg) on therapeutic drug monitoring. Body weight is
carried through a fixed-exponent allometric scaling on CL/F (0.75) and
V/F (1.0) referenced to 70 kg. Two binary co-medication indicators enter
linearly on apparent oral clearance: low-dose ritonavir as a PK booster
reduces CL/F (the typical CL/F = 7.1 L/h is the RTV-boosted reference,
and absence of ritonavir multiplies CL/F by 1.80) and concomitant 300 mg
tenofovir disoproxil fumarate increases CL/F by 25%. Between-subject
variability is retained only on CL/F; residual error is proportional
(Foissac 2011).
|
|
Atazanavir
(Hong 2011)
|
C0-delinked one-compartment first-order-absorption population PK model
with absorption lag-time for orally administered atazanavir (ATV) in
HIV-infected adults and pediatric patients (3 months to 21 years), with
covariate effects of age (ka), body weight (CL/F, V/F), sex, study-site
region (Africa), ritonavir comedication (CL/F and Frel), and
capsule-vs-powder formulation (Frel) (Hong 2011).
|
|
Atazanavir
(Rekic 2011)
|
Population PK / PD model for atazanavir (boosted with ritonavir 100 mg
QD) and its concentration-dependent effect on plasma bilirubin in adult
antiretroviral-naive HIV-positive patients from the NORTHIV trial (Rekic
2011). Atazanavir disposition is described by a one-compartment model
with first-order absorption and an absorption lag, fitted to
log-transformed plasma atazanavir concentrations; ka and the lag time
were fixed to the published values from the Colombo 2006 atazanavir
popPK report (ref 27) because sparse absorption-phase sampling did not
support their re-estimation, and CL/F and V/F were re-estimated under
fixed allometric scaling on body weight centred at 70 kg (exponents 0.75
on CL/F and 1 on V/F, both fixed a priori). The bilirubin response is
described by an indirect-response (turnover) model with
concentration-dependent inhibition of the fractional turnover rate kout:
dB/dt = kin - kout * (1 - Imax * Cc / (IC50 + Cc)) * B, with kin
re-parameterised at steady state as kin = kout * Baseline.
Inter-individual variability is supported only on V/F, CL/F (PK), and
bilirubin baseline (PD); the paper notes that the data did not support
IIV on the remaining PD parameters. PK residual variability is
proportional; bilirubin residual variability is combined additive +
proportional (the paper’s ‘slope-intercept’ model).
|
|
Atazanavir
ritonavir (Molto 2016)
|
Simultaneous one-compartment popPK model for oral atazanavir (ATV,
parent / substrate) and ritonavir (RTV, sibling-drug suffix _rtv) in 83
HIV-1-infected Caucasian adults receiving either ATV 400 mg or ATV 300
mg + RTV 100 mg once daily. Both drugs use a Savic transit- compartment
absorption chain (ATV: N = 7, MTT = 0.80 h, ka = 2.05 1/h; RTV: N = 11,
MTT = 0.522 h, ka = 1.21 1/h) feeding a depot, followed by first-order
elimination from a one-compartment central. ATV apparent clearance is
exponentially inhibited by RTV plasma concentration: CL/F_ATV(t) =
exp(lcl) * exp(-e_crtv_cl * C_RTV(t)) with the unboosted CL/F_ATV = 11.7
L/h and inhibition coefficient 0.296 L/mg. This functional form
reproduces the paper’s reported ~18% reduction in ATV CL at the
cohort-mean RTV concentration of 0.63 mg/L and explains 17.5% of
inter-individual variability in ATV CL. Demographic covariates (weight
allometric, gender, age, TDF, HCV, dose-timing, AAG, albumin) were
screened by GAM and tested in NONMEM but not retained; an Emax-form and
a linear-form inhibition were also tested and rejected (Emax:
unrealistic estimates; linear: biased fit). IIV on ka / CL/F / V/F is
reported for both drugs with unusually large IIV on absorption (~200%
CV) confirmed in the paper Results. ATV residual error is combined
(27.0% proportional + 0.07 mg/L additive); RTV residual error is
proportional only (28.0%; the additive component of the initial combined
error was deleted as negligible) (Molto 2016).
|
|
Atazanavir
ritonavir (Schipani 2013)
|
Simultaneous one-compartment first-order-absorption popPK model for oral
atazanavir (ATV) and ritonavir (RTV) in 30 HIV-infected adults receiving
ATV/RTV 300/100 mg once daily, with a direct sigmoidal-Emax inhibition
of ATV apparent clearance by RTV plasma concentration (Imax = 0.988,
IC50 = 0.221 mg/L). Both drugs share a one-compartment structure with
first-order absorption and an absorption lag time; ka values are fixed
to the separate-model final estimates (ATV ka = 1.81 1/h, RTV ka = 0.898
1/h) because joint estimation produced numerical instability.
Inter-individual variability is carried on V/F for both drugs and on
CL/F for RTV (correlated with V/F RTV, rho = 0.75); ATV CL/F is fitted
without IIV. Demographic covariates and tenofovir co-administration were
tested and none retained (Schipani 2013).
|
|
Atenolol
qsp (Fu 2022)
|
QSP (preclinical, beagle dog). Novel cardiovascular systems (CVS-CTR)
model integrating heart rate (HR), left-ventricular end- diastolic
volume (EDV), total peripheral resistance (TPR), and myocardial
contractility (CTR) via pressure-volume-loop theory (Fu 2022). Four
indirect-response (turnover) ODEs – one per hemodynamic state – are
coupled by mean arterial pressure (MAP) feedback and by algebraic
PV-loop relations that derive stroke volume (SV), end-systolic volume
(ESV), cardiac output (CO), and MAP from the four states plus a fixed
literature-derived isovolumic contraction time (TIC = 0.256 s, Templeton
1979). The paper uses atenolol (0.3-30 mg/kg PO) as proof-of-concept
beta1-blocker; Emax inhibition on HR-production and CTR-production is
driven by the central-compartment atenolol concentration with EC50 fixed
at the beta1 KD (58.3 ng/mL, Baker 2005). A positive TPR effect (beta2
mediated) was rejected during model development (Emax_TPR -> 0) and
is not included. Atenolol PK is fixed from a prior three-compartment
beagle-dog popPK model (Snelder 2013 / Venkatasubramanian 2018 as cited
in Fu 2022 references 16 and 18). Circadian rhythm modulates the
production rates of HR / TPR / CTR (24 h period on HR and CTR; 8 h
effective period on TPR); amplitudes are shared within a study but
differ between the two contributing studies (Servier – Study 1,
AstraZeneca – Study 2). Four outputs are observed with log-normal
residual error (HR, dP/dtmax); CO and MAP are derived algebraically. EDV
is included structurally (Fu 2022 Discussion: ‘baseline EDV was fixed to
a reported literature value’ 31.13 mL) to enable future extension to
compounds with a primary effect on EDV.
|
|
Atezolizumab
carboplatin nabpaclitaxel qsp (Wang 2024)
|
QSP. Quantitative systems pharmacology model of non-small-cell lung
cancer (NSCLC) describing the triple combination of the anti-PD-L1
checkpoint inhibitor atezolizumab with carboplatin and nab-paclitaxel,
extended from the published immuno-oncology QSP platform. Four
physiological compartments (central, peripheral, tumour, tumour-draining
lymph node) plus APC endosomal and surface compartments, two
immunological-synapse compartments and a separate three-compartment
Michaelis-Menten PK model for nab-paclitaxel. Covers naive and activated
CD4+/CD8+ T cell trafficking and proliferation, logistic tumour growth
against a dynamic vasculature-driven carrying capacity with a
drug-sensitive and a chemo-resistant cancer clone, self-antigen and
neo-antigen release, uptake, endosomal processing and MHC-I
presentation, TCR-mediated activation, PD-1/PD-L1/PD-L2 checkpoint
binding with atezolizumab blockade, CTLA-4/CD28/CD80/CD86 co-signalling,
MDSC recruitment with arginase-I and nitric-oxide suppression,
Th-to-Treg transdifferentiation, TGF-beta / IFN-gamma / IL-2 / CCL2
dynamics, and the cytotoxic plus anti-angiogenic effects of
nab-paclitaxel and carboplatin. 140 ODE states, 55 algebraic (repeated-
and initial-assignment) rules and 247 parameters, translated from the
SimBiology export in Supplementary Tables S2-S7. Deterministic mechanism
model: the authors generated virtual patients by Latin hypercube
sampling of the 26 parameter distributions in Supplementary Table S1
rather than by fitting IIV or residual error, so no etas and no error
model are encoded.
|
|
Atezolizumab
cibisatamab qsp (Anbari 2023)
|
QSP. Modular quantitative systems pharmacology platform for immuno-
oncology in metastatic colorectal cancer, describing combination therapy
with the anti-PD-L1 checkpoint inhibitor atezolizumab and the
CEA-directed bispecific T cell engager cibisatamab (CEA-TCB, RO6958688).
Four physiological compartments (central, peripheral, tumour,
tumour-draining lymph node) plus APC endosomal / surface compartments
and four immunological-synapse compartments. Covers naive and activated
CD4+/CD8+ T cell trafficking and proliferation, logistic tumour growth
with two cancer clones, antigen release, uptake, endosomal processing
and MHC-I presentation for a self-antigen and a neo-antigen,
TCR-mediated activation, PD-1/PD-L1/PD-L2 checkpoint binding with
atezolizumab blockade, CEA-cibisatamab-CD3 trimer formation in the
immunological synapse, MDSC recruitment with arginase-I and nitric oxide
suppression, Th-to-Treg transdifferentiation, and TGF-beta / IFN-gamma /
IL-2 / CCL2 dynamics. 90 ODE states, 38 algebraic (repeated- and
initial-assignment) rules and 192 parameters, translated from the
SimBiology export in Supplementary Tables S2-S6. Deterministic mechanism
model: the authors generated virtual patients by Latin hypercube
sampling of the parameter distributions in Supplementary Table S7 rather
than by fitting IIV or residual error, so no etas and no error model are
encoded.
|
|
Atorvastatin
(Kakara 2014)
|
PD-only indirect-response Imax model for LDL-cholesterol lowering by
atorvastatin (Kakara 2014). One LDL-C compartment with zero-order
synthesis Kin inhibited by Imax * DOSE / (ID50 + DOSE), where DOSE is
the current daily atorvastatin dose (mg/day) supplied as a time-varying
covariate column. An additive 0.109 contribution to the inhibition
fraction is applied when ezetimibe is coadministered (CONMED_EZE = 1).
The LDL-C synthesis-elimination loop is set up at steady state by
enforcing Kin = Baseline * Kout (Kout derived inside model() as Kin /
Baseline). Baseline LDL-C is age-scaled as 152 * (AGE/62)^(-0.240). Imax
(0.567), Kin (32.8 mg/dL/day), Baseline (152 mg/dL), the age power
exponent (-0.240), the ezetimibe INH contribution (0.109), and the IIV
magnitudes are shared with Kakara_2014_pitavastatin and
Kakara_2014_rosuvastatin (one joint NONMEM 7.2 FOCE-INTER fit across 378
patients). Atorvastatin ID50 = 2.22 mg per Kakara 2014 Table 2.
|
|
Avalglucosidase
alfa (Tuffal 2023)
|
Concatenated 3-compartment population PK model for avalglucosidase alfa
(enzyme replacement therapy) in adolescent and adult patients with
late-onset Pompe disease (Tuffal 2023). Pooled analysis of 2042 plasma
drug-activity determinations from 75 patients across three trials (phase
I/II NCT01898364, its follow-up NCT02032524, and phase III NCT02782741)
at 5, 10, and 20 mg/kg IV Q2W. Elimination from the central compartment
is the sum of a linear clearance (CL) and a parallel saturable
Michaelis-Menten clearance (Vmax, Km). The two peripheral compartments
are arranged in SERIES rather than in parallel: central exchanges
bidirectionally with peripheral1 (Q2), peripheral1 feeds peripheral2 one
way (Q3), and peripheral2 returns drug directly to central one way
(Qpc). That cycle is what produces the two chronological kinetic
sequences seen in the data - a first exposure-driving sequence
contributing about 99% of AUC, then a slow low-concentration rebound
peaking near 87 h and remaining above the LLOQ out to the next dose at
336 h. The authors explicitly tested and rejected a bidirectional Q3
(‘Markedly increased OFV’). Q2, V2, Q3, and V3 were fixed after
preliminary screening to avoid identifiability problems. No covariates
are retained: 12 demographic / laboratory covariates and 3
antidrug-antibody parameterisations were screened and none qualified, so
the screened set is documented in covariatesDataExcluded rather than
covariateData. Allometric scaling was tested and not retained, so the
model carries no body-weight term.
|
|
AvalglucosidaseAlfa
(Tiraboschi 2023)
|
Cyclic (concatenated) three-compartment population PK model for
intravenous avalglucosidase alfa in patients with late-onset and
infantile-onset Pompe disease (Tiraboschi 2023), with one-way
back-redistribution from the second peripheral compartment to central,
parallel linear and Michaelis-Menten elimination from the central
compartment, and time-varying body-weight allometric scaling on CL, Vc
and Vmax.
|
|
Avelumab
(Masters 2022)
|
Two-compartment population PK model for avelumab (anti-PD-L1 IgG1) with
time-dependent clearance in patients with advanced solid tumors (Masters
2022)
|
|
Avibactam
qsp (LopezArguello 2023)
|
QSP. In vitro (Pseudomonas aeruginosa PAO1). Whole-cell
penicillin-binding protein (PBP) covalent-binding model for avibactam
(diazabicyclooctane beta-lactamase inhibitor): seven coupled ODEs for
the rate of net influx of drug across the outer membrane into periplasm
and the competitive, mass-balanced acylation of six PBPs (1a, 1b, 2, 3,
4, 5/6) counted as molecules per bacterial cell. The intact parameter
switches between the intact whole-cell assay (penetration-limited; drug
enters periplasm at Rate_Influx/access) and the lysed isolated-membrane
assay (no outer membrane; a vast excess of drug molecules is present at
time 0).
|
|
Axatilimab
(Yang 2024)
|
Semimechanistic population PK/PD model for axatilimab (anti-CSF-1R IgG4
monoclonal antibody) in healthy adults, patients with advanced solid
tumors, and patients with chronic graft-versus-host disease (Yang 2024).
Two-compartment IV PK with parallel linear clearance and CSF-1R-mediated
saturable elimination via competitive Hill binding with circulating
CSF-1; CSF-1, NCMC, AST, and CPK pharmacodynamics integrated as turnover
indirect-response biomarkers.
|
|
Axitinib
(Garrett 2014)
|
Two-compartment population PK model for axitinib in healthy volunteers
(Garrett 2014). First-order absorption with fixed lag time, allometric
power-form effect of body weight on the central volume of distribution
(reference 75 kg), linear-proportional fasting effects on the
first-order absorption rate constant ka and on bioavailability F, and a
linear-proportional reduction in F for the marketed crystal polymorph
Form XLI relative to the earlier Form IV reference. Pooled data from 337
healthy subjects across ten Pfizer Phase I studies.
|
|
Axomadol
(MangasSanjuan 2016)
|
Semi-physiological population pharmacokinetic and joint pharmacodynamic
model of axomadol (a racemic analgesic with opioid agonistic and
monoamine-reuptake-inhibitor activity) and its O-demethyl (ODM)
metabolite in healthy adult volunteers. The PK structure carries two
parallel enantiomer chains (RR-suffix r and SS-suffix s), each
consisting of a first-order absorption depot, a liver compartment
mimicking first-pass conversion, a parent central compartment, and a
metabolite central compartment. Within each enantiomer the parent and
metabolite share a single apparent volume of distribution (VP = VM) and
share a single typical first-order elimination rate constant (kP0 =
kM0), although between-subject variability is estimated separately for
the two elimination pathways. The PD layer is shared across the
enantiomer chains and is driven by the SS parent in plasma (mydriatic
Emax) and by the RR metabolite at a hysteresis effect site (linearly
miotic). Pupil diameter is the sum of those two opposing effects;
cold-pressor analgesic AUC is a linear function of the parent and
metabolite contributions to pupil diameter. Parameter values are from
Mangas-Sanjuan et al. 2016 Tables 2, 4, and 5.
|
|
AZD6088
rat (Viberg 2012)
|
Preclinical (rat). Direct-effect population PK/PD model for the
muscarinic agonist AZD6088 (MW 406.57) in male Sprague-Dawley rats using
the spinal-nerve-ligation (SNL) heat-hyperalgesia model of neuropathic
pain. One-compartment oral PK (depot -> central) with the first-order
absorption rate constant ka fixed at 5 x kel (equivalent to 5 x cl/vc;
Viberg 2012 Results PK-model paragraph: ‘Lack of plasma concentration
data in the absorption phase made it impossible to estimate rate of
absorption and ka was therefore fixed to 5 time clearance’); the 40
umol/kg highest-dose cohort (DOSE_HIGH = 1) gates a distinct
typical-value apparent oral clearance of 3.92 L/h/kg vs 10.87 L/h/kg for
all other cohorts, per the paper’s OFV-supported categorical CL split
(delta OFV = -32). PD is a direct-effect Emax on paw withdrawal latency
(baseline 5.947 s, Emax 10.09 s, EC50 0.0433 umol/L; no time delay, no
sigmoidicity, no tolerance-development term - all three alternatives
increased OFV or degraded goodness-of-fit). Typical-value only: the
paper reports ‘exponential models were used to describe inter-individual
variability’ on CL and V but never publishes the omega^2 / CV%
magnitudes; see the vignette Assumptions and deviations section.
|
|
Azithromycin
(Merchan 2015)
|
Population PK model for intravenous azithromycin in preterm neonates at
risk for Ureaplasma respiratory tract colonization (Merchan 2015).
Pooled re-analysis of three studies (single 10 mg/kg, single 20 mg/kg,
and 3 daily doses of 20 mg/kg). Two-compartment linear model with all PK
parameters allometrically scaled on body weight: fixed exponent 0.75 on
CL and Q, fixed exponent 1.0 on V1 and V2, reference body weight 1 kg.
|
|
Azithromycin
(Sampson 2014)
|
Four-compartment mamillary population PK model for oral azithromycin
simultaneously describing concentrations in whole blood, peripheral
blood mononuclear cells (PBMCs), and polymorphonuclear cells (PMNs) in
healthy adults (Sampson 2014). First-order absorption with lag;
unidirectional flow from central to PBMC and to PMN compartments;
bidirectional flow between central and a peripheral tissue compartment;
elimination from central, PBMC, and PMN compartments. The observed
whole-blood concentration is a weighted sum of plasma, PBMC, and PMN
concentrations.
|
|
Azithromycin
(Zheng 2014)
|
Semi-mechanistic tissue distribution population PK model for oral
azithromycin in healthy adults (Zheng 2014). Three-compartment plasma PK
(depot with absorption lag time and first-order absorption, central, two
peripheral compartments) with concentration-dependent fraction unbound
in plasma (equation 1). Three tissue distribution compartments (muscle
interstitial space fluid, subcutaneous adipose tissue interstitial space
fluid, polymorphonuclear-leukocyte (PML) cytosol) each driven by free
unbound (or, for PML cytosol, free unionized) plasma drug via
first-order rate constants kin and kout, with tissue-specific
distribution factors df_muscle, df_adipose, df_pmn that scale the
steady-state tissue:plasma free-unbound ratio. Each tissue compartment
also exchanges with a deep nonspecific phospholipid-binding compartment
via shared kon and koff (Methods equations 1-13).
|
|
Azithromycin
(Zheng 2018)
|
Pediatric population PK model for intravenous azithromycin in children
with community-acquired pneumonia (Zheng 2018). Two-compartment model
with linear elimination, allometric scaling on clearance and
intercompartmental clearance (exponent 0.75 fixed) and on central and
peripheral volumes (exponent 1.0 fixed) with reference body weight 21.5
kg, and a binary alanine aminotransferase covariate that reduces CL by
24 percent when ALT > 40 IU/L.
|
|
Aztreonam
qsp (LopezArguello 2023)
|
QSP. In vitro (Pseudomonas aeruginosa PAO1). Whole-cell
penicillin-binding protein (PBP) covalent-binding model for aztreonam
(monobactam): seven coupled ODEs for the rate of net influx of drug
across the outer membrane into periplasm and the competitive,
mass-balanced acylation of six PBPs (1a, 1b, 2, 3, 4, 5/6) counted as
molecules per bacterial cell. The intact parameter switches between the
intact whole-cell assay (penetration-limited; drug enters periplasm at
Rate_Influx/access) and the lysed isolated-membrane assay (no outer
membrane; a vast excess of drug molecules is present at time 0).
|
|
Bapineuzumab
(Hu 2014)
|
Two-compartment population PK model for bapineuzumab in adults with
mild-to-moderate Alzheimer’s disease following IV administration (Hu
2014, reduced model)
|
|
Baricitinib
(Decker 2024)
|
Two-compartment population PK model with zero-order absorption, an
absorption lag, and fixed allometric scaling for oral baricitinib in 217
pediatric patients aged 2 to <18 years with polyarticular-course
juvenile idiopathic arthritis (JUVE-BASIS, NCT03773978). Apparent total
clearance is partitioned semi-mechanistically into an eGFR-dependent
apparent renal arm (CLr/F) and an eGFR-independent apparent non-renal
arm (CLnr/F). Baseline body weight enters through allometric exponents
fixed at 0.75 on all clearance terms (CLr/F, CLnr/F, Q) and at 1 on both
volumes (V1/F, V2/F), referenced to 74 kg. The structure was carried
unchanged from the adult rheumatoid-arthritis baricitinib population PK
model; no further covariate met the stepwise-covariate-modeling
inclusion criteria, so the base model is the final model.
|
|
BAY81
8973 (Garmann 2017)
|
Two-compartment population PK model for BAY 81-8973 (Kovaltry,
full-length unmodified recombinant human factor VIII) in patients with
severe haemophilia A aged 1-61 years pooled from the LEOPOLD I, II and
Kids trials (Garmann 2017). Final model uses NONMEM M3 likelihood for
samples below the chromogenic-assay limit of quantitation (1.5 IU/dL).
|
|
BAY94
9027 (Solms 2020)
|
One-compartment population PK model for BAY 94-9027 (damoctocog alfa
pegol, Jivi, an extended-half-life site-specifically PEGylated
B-domain-deleted recombinant factor VIII) in 198 male patients aged 2-62
years with severe haemophilia A pooled from the BAY 94-9027 phase I
(NCT01184820), PROTECT VIII (NCT01580293), and PROTECT VIII Kids
(NCT01775618) trials (Solms 2020). Final chromogenic-assay model has
lean body weight (LBW) as a power-form covariate on CL and Vc and von
Willebrand factor antigen (VWF) as a power-form covariate on CL;
between-subject variability is a BLOCK(2) on CL and Vc with correlation
0.449; residual error is combined additive plus proportional. NONMEM M3
likelihood was used for samples below the chromogenic-assay lower limit
of quantitation (1.5-3 IU/dL).
|
|
Bedaquiline
(Svensson 2013)
|
Three-compartment population PK model for bedaquiline (BDQ) with a
two-compartment N-desmethyl metabolite M2 and a two-compartment
N,N-bis-desmethyl metabolite M3 in healthy adult volunteers following
single 400 mg oral doses, with Savic 2007 analytical transit-compartment
absorption (non-integer NN feeding a first-order depot at rate ka) and
an instantaneous-switch concomitant-efavirenz induction factor of 2.07
on apparent CL_BDQ and CL_M2 and 1.12 on apparent CL_M3, applied from 1
week after the start of 600 mg once-nightly efavirenz co-administration.
|
|
Bedaquiline
(Svensson 2014)
|
Three-compartment population PK model for bedaquiline (BDQ) and a
two-compartment N-desmethyl metabolite M2 in healthy adult volunteers
following single 400 mg oral doses, with Savic 2007 analytical
transit-compartment absorption (non-integer NN feeding a first-order
depot at rate ka), fixed allometric scaling on disposition (0.75 on CL/Q
at 70 kg, 1 on Vc/Vp), and multiplicative rifampicin or rifapentine
drug-drug-interaction factors of 4.78 and 3.96 on bedaquiline and M2
apparent clearance, applied at full induction from day 3 of rifamycin
co-administration.
|
|
Bedaquiline
(Svensson 2017)
|
Pharmacodynamic exposure-response model for the mycobacterial load (MBL,
n bacteria per sample inoculum) in adult patients with drug-resistant
pulmonary tuberculosis treated with bedaquiline plus an optimized
background regimen. The latent MBL state declines mono-exponentially
with a half-life HL that is prolonged by 28.1% in patients with pre-XDR
or XDR tuberculosis and shortened by individual bedaquiline
weekly-average plasma concentration CAV via an Emax model with the
maximum fractional effect on HL fixed at -100% (EC50 1.42 mg/L). The
per-subject starting MBL_0 is informed by the baseline mean
Time-to-Positivity in MGIT liquid culture (TTP_MGIT_BASE) via a
power-form covariate (exponent -3.69 around the cohort median 6.8 days).
Inter-individual variability on log HL uses a Box-Cox-transformed eta
distribution (Petersson 2009 form, shape 0.66, variance 0.33);
inter-occasion variability in sputum sampling on log MBL (variance 3.71)
is folded into the residual log-scale error. The Svensson 2017 source’s
full 3-component model (longitudinal MBL plus per-sample probability of
bacterial presence plus MGIT-tube logistic-growth-driven time-to-event
for observed TTP) is reduced here to the MBL component, with the latent
MBL state treated directly as the observable; the
probability-of-presence and tube-growth-driven TTP machinery are
measurement-model artifacts of how MBL was inferred from TTP data and
are dropped (see vignette Assumptions and deviations). Bedaquiline CAV
is supplied as a time-varying covariate column from any popPK source;
the upstream popPK paper (Svensson 2016 CPT PSP, reference 21) is
shipped in nlmixr2lib as modellib(‘Svensson_2016_bedaquiline’).
|
|
Bedaquiline
(Svensson 2018)
|
Three-compartment population PK model for the antimycobacterial
bedaquiline (BDQ) and a two-compartment N-desmethyl metabolite M2 in
healthy adult volunteers following single 400 mg oral doses, with
four-transit-compartment first-order absorption (rate of absorption from
the last transit compartment fixed equal to the inter-transit transfer
rate, i.e. KA = KTR) and a multiplicative formulation effect adding 23%
to the typical mean absorption time when the four 100 mg tablets are
suspended in water before swallowing relative to swallowing the tablets
whole.
|
|
Bedaquiline
lpvr (Svensson 2014)
|
Three-compartment population PK model for bedaquiline (BDQ) and a
two-compartment N-desmethyl metabolite M2 in healthy adult volunteers
following single 400 mg oral doses, with Savic 2007 analytical
transit-compartment absorption (non-integer NN feeding a first-order
depot at rate ka), fixed allometric scaling on disposition (0.75 on CL/Q
at 70 kg, 1 on Vc/Vp), and multiplicative ritonavir-boosted lopinavir
(LPV/r) drug-drug-interaction factors of 0.347 on bedaquiline apparent
clearance and 0.578 on M2 apparent clearance during LPV/r
co-administration (study C110).
|
|
Bedaquiline
mpbpk (Mehta 2023)
|
mPBPK (minimal physiologically based, translational mouse-to-human).
Bedaquiline and its N-desmethyl metabolite M2 in pulmonary tuberculosis
patients, with explicit cavitary lung-lesion and uninvolved-lung
site-of-action compartments. Parallel first-order absorption from a fast
and a slow depot, a well-stirred liver compartment that converts
bedaquiline to M2 via a hepatic extraction ratio, a lumped peripheral
tissue pool for parent and for M2, and perfusion-limited lesion /
uninvolved-lung compartments driven by penetration ratios. Physiological
volumes and flows are computed from body weight (Brown 1997); clearance
terms are allometrically scaled from the mouse fit with an exponent of
0.75. The lesion and uninvolved-lung states hold concentrations (mg/L),
not amounts. Intended for typical-value and population simulation of
site-of-action target attainment; the paper did not fit this model to
individual human data.
|
|
Bedaquiline
nvp (Svensson 2014)
|
Three-compartment population PK model for bedaquiline (BDQ) and a
two-compartment N-desmethyl metabolite M2 in HIV-1-infected ART-naive
adult volunteers following single 400 mg oral doses, with Savic 2007
analytical transit-compartment absorption (non-integer NN feeding a
first-order depot at rate ka), fixed allometric scaling on disposition
(0.75 on CL/Q at 70 kg, 1 on Vc/Vp), and multiplicative nevirapine (NVP)
drug-drug-interaction factors of 0.915 on bedaquiline and 1.05 on M2
apparent clearances during steady-state NVP co-administration (study
C117). The factors are fixed-effects only because BSV on the NVP
interaction effects was not estimated.
|
|
Belantamab
(Papathanasiou 2025)
|
Two-compartment population PK model for the antibody-drug conjugate
(ADC) belantamab mafodotin in patients with relapsed/refractory multiple
myeloma, with sigmoidal time-varying clearance and covariate effects of
baseline body weight, BMI, albumin, soluble BCMA, serum IgG, race, and
combination therapy (Papathanasiou 2025; ADC moiety only – the
cys-mcMMAF payload sub-model is not included; see vignette for
rationale)
|
|
Belantamab
mprotein (Collins 2023)
|
Concentration-driven tumor growth inhibition (TGI) model for serum
M-protein in patients with relapsed/refractory multiple myeloma treated
with the antibody-drug conjugate belantamab mafodotin, with logistic
growth plus a modified weak Allee term, a saturating effect-compartment
driven kill term, an exponential resistance decay, and covariate effects
of baseline beta-2-microglobulin on the growth rate, baseline M-protein
on the kill rate, and extramedullary disease plus baseline soluble BCMA
on the effect-compartment rate constant (Collins 2023). The embedded
two-compartment time-varying-clearance PK layer is a typical-value ADC
driver taken from Collins 2023 Table S1; for the full covariate
population PK model of belantamab mafodotin see
modellib(‘Papathanasiou_2025_belantamab’). The paper’s ocular-safety
discrete time Markov model is not included (see vignette).
|
|
Belatacept
(Shen 2013)
|
PK/PD model for belatacept (CTLA-4/IgG1 fusion protein, selective T-cell
co-stimulation blocker) in adult kidney transplant recipients (Shen
2013). The PK side is a one-compartment IV-infusion model derived from
the paper’s noncompartmental analysis (Table 1, 10 mg/kg substudy, n =
10): typical clearance and volume for a 70 kg adult are set so the model
reproduces the reported geometric-mean CL, Vss, AUC over a 4-week dosing
interval, and ~8-9 day terminal half-life. The PD side is the inhibitory
Emax model of Eq. 2 (Section 3.2, n = 62 in the phase II
corticosteroid-avoidance substudy IM103034) describing free CD86
receptor expression on peripheral-blood monocytes (MESF) as E0 - Emax *
Cc / (EC50 + Cc); CD86 receptor occupancy is derived as 100 * (E0 -
freeCD86) / E0. Belatacept exhibited linear PK across 5-10 mg/kg with
relatively low between-subject variability; the full population PK with
body-weight covariates was published separately by Zhou et al. (2012)
and is not refit here.
|
|
Belimumab
(Marcantonio 2022)
|
QSP. One-compartment monospecific anti-ligand mechanistic PKPD model of
belimumab-BAFF binding in adults with systemic lupus erythematosus (SLE)
(Marcantonio 2022 Early Feasibility Assessment, Case Study 3). Belimumab
binds soluble BAFF (BLyS); model treats BAFF as the ligand and BAFF-R as
the cognate receptor (BAFF also binds BCMA and TACI in vivo but this
model uses only the BAFF-R affinity 15 nM per Day 2005 / Cachero 2006 /
Hymowitz 2005 as reported in Table S5). Belimumab valency = 1 (BAFF
trimer binds 3:3 per Shin 2018). Parameters FIXED from paper Table S5.
|
|
Belimumab
(Struemper 2017)
|
Linear two-compartment subcutaneous population PK model for belimumab in
healthy volunteers and adult patients with systemic lupus erythematosus,
with first-order absorption + lag time, allometric body-weight scaling
on CL/Vc/Q/Vp, and baseline BMI on Vc and baseline albumin and IgG on CL
(Struemper 2017)
|
|
Belimumab
(Zhou 2021)
|
Linear two-compartment IV population PK model for belimumab in Chinese
and non-Chinese adult and pediatric patients with systemic lupus
erythematosus (Zhou 2021)
|
|
Belzutifan
(Marathe 2023)
|
Two-compartment population PK model for oral belzutifan (Welireg, a
hypoxia-inducible factor 2 alpha inhibitor) in 239 pooled subjects
across four phase I studies and one pivotal phase II study: 83 healthy
participants, 74 patients with advanced renal cell carcinoma, 21 with
other advanced solid tumors, and 61 with von Hippel-Lindau
disease-associated RCC. First-order absorption with an absorption lag
and linear elimination from the central compartment. Body weight scales
clearances (shared exponent on CL/F and Q/F) and volumes (shared
exponent on V2/F and V3/F); age scales CL/F and V2/F; fed state and the
final market formulation each slow the absorption rate constant; and the
polymorphic UGT2B17 and CYP2C19 metabolizer phenotypes shift CL/F, with
UGT2B17 poor metabolizers additionally showing 11% higher relative
bioavailability. Residual variability is split into healthy-participant
and patient strata.
|
|
BempedoicAcid
(Jadhav 2023)
|
Population PK model for bempedoic acid (ATP-citrate lyase inhibitor) in
healthy subjects and patients with dyslipidemia, renal or hepatic
impairment, or type 2 diabetes mellitus (Jadhav 2023): two-compartment
disposition with a single transit absorption compartment and linear
elimination, pooled across 22 phase 1/2/3 studies. Covariate effects on
apparent clearance (sex, body weight, Black race, hyperlipidemia, type 2
diabetes, eGFR, ezetimibe), on apparent central volume (sex, age, body
weight, simvastatin), on the absorption rate constant (food), and on
relative oral bioavailability (atorvastatin).
|
|
BempedoicAcid
ldlc (Jadhav 2023)
|
Joint population PK + PK/PD model for bempedoic acid and serum
low-density lipoprotein cholesterol (LDL-C) in patients with
dyslipidemia (Jadhav 2023). The PK layer is the two-compartment /
single-transit-absorption popPK model from the companion
Jadhav_2023_bempedoicAcid.R file (Table 2). The PD layer (Table 3) is a
type 1 indirect-response model in which bempedoic acid inhibits LDL-C
production, with covariate effects on the maximum fractional inhibition
Imax (sex, body weight, Black race, concomitant statin intensity,
concomitant ezetimibe, prior statin therapy) and on baseline LDL-C
(concomitant statin intensity, HeFH, type 2 diabetes, prior ezetimibe
therapy, prior statin therapy). The authors fit the PD layer
sequentially, conditioned on individual post hoc PK parameters from the
popPK model.
|
|
Benazepril
pbpk (Luo 2024)
|
PBPK (semi-mechanistic, custom WinNonlin 8.1 implementation). Joint
benazepril + benazeprilat disposition in healthy adults and in liver
cirrhosis (Child-Pugh A/B/C). Benazepril is an inactive ester prodrug
hydrolysed by hepatic CES1 to the active diacid benazeprilat, which is
eliminated renally. Both analytes are highly bound to albumin (free
fractions 0.03 and 0.05), which Section 4 cites as a reason the
cirrhosis AUCR was poorly predicted. The semi-PBPK circuit is stomach,
three small-intestinal lumen segments (duodenum / jejunum / ileum), the
matching three gut-wall segments, portal vein, liver, kidney and a
two-compartment systemic compartment. Cirrhosis is applied by switching
the Child-Pugh-specific physiology of Table 1 (organ blood flows,
functional liver volume, GI transit rates, GFR, plasma-binding protein
concentrations, hepatic CES1 content) and rescaling CLint, CLint,K, Peff
and Vsys through Eq 1-6. Deterministic: the paper’s virtual populations
are uniform 80-120% draws on the drug parameters, not lognormal random
effects, so no IIV is encoded.
|
|
Benralizumab
(Wang 2017)
|
Two compartment PK model of benralizumab (anti-IL-5Ralpha) in healthy
volunteers and patients with asthma (Wang 2017)
|
|
Benzathine
benzylpenicillin g (Kado 2020)
|
One-compartment population PK model for penicillin released from
benzathine benzylpenicillin G (Bicillin L-A) with three parallel
absorption pathways (slow and fast via a transit compartment, plus an
immediate pathway that bypasses the transit compartment) and
route-specific structural parameters for intramuscular (IM) and
subcutaneous (SC) administration, developed from 311 dried-blood-spot
penicillin concentrations in a randomized crossover of 15 healthy adult
male volunteers each receiving 1.2 MIU IM and 1.2 MIU SC into the
dorsogluteal region (Kado 2020).
|
|
Benznidazole
(Soy 2015)
|
One-compartment population PK model with first-order absorption and
first-order elimination for oral benznidazole in adult patients with
chronic Chagas disease (Soy 2015; CINEBENZ trial, n = 39 index plus n =
10 external validation). Apparent clearance CL/F = 1.73 L/h, apparent
volume of distribution V/F = 89.6 L, and absorption rate constant Ka =
1.15 1/h fixed from the literature (Raaflaub & Ziegler 1979).
Inter-individual variability is on CL/F (33.4% CV) and V/F (68.8% CV);
inter-occasion variability is on CL/F (29.5% CV), folded into the CL/F
eta as BSV-equivalent for forward simulation. Residual error is combined
additive (0.57 mg/L) plus proportional (19.53% CV). No demographic or
biological covariates were retained in the final model.
|
|
Benzylpenicillin
(Nielsen 2011)
|
In vitro (Streptococcus pyogenes M12 NCTC P1800). Semimechanistic PKPD
model of benzylpenicillin time-kill kinetics; two-stage bacterial
life-cycle (proliferating drug-sensitive S and non-growing
drug-insensitive R) with sigmoidal Emax killing of S via an effect
compartment; first-order drug elimination (ke set per in vitro
kinetic-system flow rate) plus drug-specific degradation kdeg. Parameter
values are from the combined static and dynamic estimation in Table 3.
|
|
Benzylpenicillin
(Shah 2023)
|
Two-compartment intravenous population PK model for benzylpenicillin in
critically unwell adults, with a priori allometric body-weight scaling
on all disposition parameters and a serum-creatinine power effect on
clearance.
|
|
Benzylpenicillin
horse (Lallemand 2023)
|
Preclinical (horse). Three-compartment population pharmacokinetic model
for benzylpenicillin (BP) in horses, developed as an international
meta-analysis to derive PK/PD cutoff values supporting equine clinical
breakpoints (VetCAST approach). Seven parallel absorption depots
reproduce the five modalities the authors modelled simultaneously: (1)
IV sodium or potassium BP dosed directly into the central compartment;
(2) IM sodium BP with two SEQUENTIAL first-order rate constants, the
rapid Ka being replaced by the slower Ka2 once time-after-dose exceeds a
lag time; (3) IM procaine BP from four single-ingredient products
(France Depocilline, Sweden Penovet, USA1 Norocillin, Japan Procaine BP
G sol ‘KS’), sharing one Ka and one logit-scale bioavailability that are
each modified by a ‘source of dataset’ covariate; (4) the Duplocilline
fixed combination, whose total BP dose is split by SPC composition into
a procaine BP fraction and a benzathine BP fraction absorbed in
PARALLEL, each with its own Ka and bioavailability; and (5) IM
penethamate hydriodide given at three separate injection sites, each
site carrying its own sequential rapid-then-slow Ka pair and its own
switch delay. All seven depots and the IV route share one set of
disposition parameters (Vc, Vp, Vp2, CL, Q, Q2), which were FROZEN in
the full model at the values estimated from the 23 IV profiles alone;
plasma clearance carries a ‘source of dataset’ covariate with France as
reference. The PK/PD layer reproduces the paper’s Monte Carlo machinery:
a fixed unbound fraction of 0.4 converts total to free BP, and the free
AUC and the cumulative time above MIC are integrated as states so that
fAUC/MIC and fT>MIC can be read directly. Pooled meta-analysis of 40
horses providing 63 rich profiles and 1022 BP plasma concentrations from
France, Sweden, Japan and the USA (Lallemand 2023).
|
|
Betamethasone
(Schoenmakers 2025)
|
Two-compartment population PK model with first-order absorption (no lag
time) for intramuscular betamethasone in pregnant women admitted with
imminent preterm birth, including early-onset pre-eclampsia (eoPE;
diagnosed before 34 weeks gestation). Apparent clearance is multiplied
by 0.617 (a 38% reduction, or ~60% of the non-eoPE clearance) when eoPE
is present; this is the only retained covariate after backward
elimination at P < 0.01. Body weight, BMI, lean body weight, age,
gestational age, number of foetuses, white blood cell counts and CRP
were screened but did not retain after backward elimination.
|
|
Bevacizumab
(Han 2015)
|
Two-compartment population PK model for IV bevacizumab in paediatric
cancer patients (0.5-21 years) with fixed allometric body-weight scaling
on all four disposition parameters, plus additional covariate effects of
sex, baseline serum albumin, and primary-CNS-tumour-vs-sarcoma
indication on CL and V1 (Han 2015, Table 2 final model)
|
|
Bevacizumab
(Han 2016)
|
Two-compartment population PK model for IV bevacizumab in adult cancer
patients (Han 2016) with allometric body-weight scaling and covariate
effects of sex, baseline albumin, baseline alkaline phosphatase, and
concomitant interferon alpha on clearance.
|
|
Bevacizumab
(Panoilia 2015)
|
Quasi-steady-state target-mediated drug-disposition (TMDD QSS) model for
IV bevacizumab and free VEGF165 in adults with stage IV colorectal
cancer, with fixed allometric body-weight scaling on PK clearances and
volumes (Panoilia 2015, Table 3 TMDD model column)
|
|
Bevacizumab
pk (Papachristos 2020)
|
Two-compartment population PK model for IV bevacizumab in adults with
metastatic colorectal cancer, with allometric weight scaling and ICAM-1
/ VEGF-A genotype covariates (Papachristos 2020, Table 1)
|
|
Bevacizumab
pkpd (Papachristos 2020)
|
Two-compartment population PK plus immediate-response Imax PK/PD model
for IV bevacizumab and free VEGF-A in adults with metastatic colorectal
cancer, with allometric weight scaling and ICAM-1 / VEGF-A genotype
covariates (Papachristos 2020, Table 3)
|
|
Bevacizumab
qss (Papachristos 2020)
|
Quasi-steady-state target-mediated drug-disposition (TMDD QSS) model for
IV bevacizumab and free VEGF-A in adults with metastatic colorectal
cancer, with allometric weight scaling and ICAM-1 / VEGF-A genotype
covariates (Papachristos 2020, Table 2)
|
|
BIIB023
(Galluppi 2016)
|
Two-compartment population PK model for intravenous BIIB023, an
anti-TWEAK monoclonal antibody, in healthy Chinese, Japanese and
Caucasian volunteers and adults with rheumatoid arthritis (Galluppi
2016); parallel first-order linear and Michaelis-Menten elimination from
the central compartment with body weight on CL and V, and sex on V.
|
|
Biib107
(Toukam 2025)
|
Two-compartment population PK model with parallel linear and
Michaelis-Menten elimination, plus direct sigmoidal Emax PK/PD model of
alpha-4 integrin receptor saturation, for BIIB107 (humanized aglycosyl
anti-alpha-4 integrin IgG4 monoclonal antibody) in healthy adult
volunteers (Toukam 2025).
|
|
Bivalirudin
(Zhang 2012)
|
Population PK and PK-PD model for bivalirudin, a synthetic bivalent
direct thrombin inhibitor, in young healthy Chinese volunteers (Zhang
2012). PK: two-compartment intravenous disposition with
body-weight-normalised structural parameters (CL = 0.323 L/h/kg, V1 =
0.086 L/kg, Q = 0.0957 L/h/kg, V2 = 0.0554 L/kg); no covariates retained
after a 30-covariate screen; log-normal IIV on CL, V1, and V2 with IIV
on Q fixed to zero. PD: direct-response sigmoid Emax (Hill coefficient
fixed at 1) on activated clotting time (ACT) using the
central-compartment concentration as the effect site (E0 = 134 s, Emax =
318 s, EC50 = 2.44 mg/L); one covariate retained – red blood cell count
(RBC, 10^12 cells/L) on EC50 via the linear-deviation form EC50_i =
theta_EC50 * exp(eta_EC50) * (1 + 1.70 * (RBC - 4.40)) centred at the
cohort median 4.40.
|
|
Bosentan
pbpk (Aoki 2024)
|
PBPK-TMDD (semi-mechanistic, dispersion liver). Bosentan disposition
after single intravenous doses of 10-750 mg in healthy adults,
re-estimated by Aoki & Sugiyama (2024) with the Cluster Gauss-Newton
method (CGNM) on the model structure of Koyama et al. (2021). The liver
is resolved as a five-compartment tandem dispersion model: five hepatic
extracellular (sinusoidal) sub-compartments in series with the hepatic
blood flow, each exchanging with its own hepatocyte sub-compartment.
Sinusoid-to-hepatocyte transport is the sum of saturable OATP-mediated
uptake (Michaelis-Menten in unbound sinusoidal concentration) and
passive diffusion; efflux back to the sinusoid is passive diffusion
scaled by the influx/efflux ratio gamma_dif. Drug is eliminated by
hepatic metabolism from the hepatocytes and by renal clearance from
plasma. Muscle, skin and adipose are perfusion-limited well-stirred
tissues. Superimposed on the PBPK backbone is a target-mediated drug
disposition (TMDD) layer in plasma: unbound drug binds a finite
endothelin-receptor pool of total amount rtot with dissociation constant
kd and off-rate koff, which is the source of the low-dose nonlinearity
and which permits receptor occupancy to be simulated. The eight
parameters below without fixed() are the CGNM estimates of Aoki 2024
Table S2 (all eight identifiable when the 10 mg arm is included); every
other value is a fixed physiological or compound constant taken from the
published model code. CGNM is a fixed-effects nonlinear-least-squares
method, so this model has no between-subject variability and the paper
reports no residual-error model – the propSd term is a placeholder. See
the vignette Errata.
|
|
Brazikumab
(Zhang 2023)
|
Two-compartment population PK model with first-order lagged SC
absorption and linear clearance for brazikumab (anti-IL-23 p19 mAb) in
healthy adults and adults with Crohn’s disease (Zhang 2023)
|
|
Brazikumab
crp (Zhang 2023)
|
Indirect-response PK/PD model of Crohn’s Disease Activity Index (CDAI)
for brazikumab with a constant inhibitory placebo effect and a
baseline-C-reactive-protein-dependent sigmoid drug effect on the CDAI
input rate, in adults with moderately to severely active Crohn’s disease
(Zhang 2023)
|
|
Brazikumab
il22 (Zhang 2023)
|
Indirect-response PK/PD model of Crohn’s Disease Activity Index (CDAI)
for brazikumab with a constant inhibitory placebo effect and a
baseline-serum-IL-22-dependent sigmoid drug effect on the CDAI input
rate, in adults with moderately to severely active Crohn’s disease
(Zhang 2023)
|
|
Brentuximab
(Li 2017)
|
Semimechanistic coupled population PK model for brentuximab vedotin
antibody-drug conjugate (ADC) and its released small-molecule payload
monomethyl auristatin E (MMAE) in adults with CD30-expressing
hematologic malignancies (Li 2017). ADC is described by a linear
3-compartment model with first-order elimination; MMAE by a linear
2-compartment model with first-order elimination. MMAE formation is
driven by (1) proteolytic degradation of the ADC (scaled by a
time-decaying drug-antibody ratio DAR(t) and a cycle-dependent fraction
Fmc = Cycle^Fm) and (2) a first-order deconjugation flux proportional to
the per-ADC MMAE payload above the minimum-detectable DAR. Modeled in
molar units (amount nmol, volume L, concentration pmol/mL = nmol/L = nM)
following the paper’s convention.
|
|
Brentuximab
(Suri 2018)
|
Coupled population PK model for brentuximab vedotin antibody-drug
conjugate (ADC) and its released payload monomethyl auristatin E (MMAE)
in 380 patients with CD30-positive malignancies (Hodgkin lymphoma,
systemic anaplastic large-cell lymphoma, mycosis fungoides, primary
cutaneous ALCL) pooled from six clinical studies including the phase III
ALCANZA study (Suri 2018). ADC is described by a linear 3-compartment
model with zero-order input and first-order elimination; MMAE by a
2-compartment model with first-order elimination, fed from ADC by (a) a
saturable target-binding flux KdTargetADC (initial Target = 1,
irreversibly depleted) and (b) a proteolytic flux
FMexp(-ALFMtad)K10ADC whose conversion fraction
declines as a function of time after the most recent dose. Both fluxes
accumulate in an intermediate Lag compartment that empties to MMAE
central with rate Klag (FM is fixed to 1).
|
|
Brentuximab
(Zhou 2025)
|
Coupled population PK model for brentuximab vedotin antibody-drug
conjugate (ADC) and its released payload monomethyl auristatin E (MMAE)
in pediatric patients (5-18 years) with relapsed/refractory or newly
diagnosed Hodgkin lymphoma or systemic anaplastic large-cell lymphoma
(Zhou 2025). ADC is described by a linear 3-compartment model with
first-order elimination; MMAE by a 2-compartment model with first-order
elimination. ADC -> MMAE flux is the sum of (a) a one-time saturable
target-binding flux KdTargetADC (initial Target = 1 unitless,
irreversibly depleted) and (b) a proteolytic flux
FMexp(-ALFMtad)K10ADC where the conversion fraction
declines as a function of time after the most recent dose. Both fluxes
accumulate in an intermediate Lag compartment that empties to MMAE
central with rate Klag. Final-model parameter values come from Zhou 2025
supplementary Tables S1 (ADC) and S2 (MMAE); equations come from the
NONMEM control streams in Zhou 2025 Supplementary Methods.
|
|
Brepocitinib
(Maleki 2024)
|
Two-compartment population pharmacokinetic model with first-order
absorption for oral brepocitinib (PF-06700841, a dual TYK2/JAK1
inhibitor) in healthy participants and patients with alopecia areata,
hidradenitis suppurativa, psoriasis, psoriatic arthritis, ulcerative
colitis, or vitiligo. Apparent (oral) disposition parameters carry fixed
allometric body-weight scaling; clearance additionally depends on
baseline aspartate aminotransferase and Asian race, apparent central
volume on sex, and the absorption rate constant on ulcerative-colitis
status. An absorption lag time applies only to the tablet formulation,
and relative bioavailability is 30 percent higher above 100 mg/day.
Interindividual variability on CL/F and Vc/F is Box-Cox transformed
(Petersson 2009 form) and its magnitude, together with the combined
additive-plus-proportional residual error, differs between healthy
participants and patients.
|
|
Brigatinib
(Hanley 2024)
|
Two-compartment oral population pharmacokinetic reduction of the Simcyp
minimal-PBPK-with-single-adjusting-compartment (SAC) model for the ALK
inhibitor brigatinib in healthy adults (Hanley 2024). The source model
was built in the Simcyp Population-based Simulator (versions 15 and 17)
and its whole-body mass-balance equations are not published, so the
platform model itself cannot be encoded here. What IS fully reported is
the brigatinib compound layer, and it is sufficient to reconstruct the
disposition as an ordinary compartmental model: first-order absorption
into a depot, distribution between a systemic compartment and the SAC
(the paper’s k_in / k_out, encoded as the canonical k12 / k21), and
first-order elimination from the systemic compartment. Systemic
clearance is obtained from the reported unbound hepatic intrinsic
clearance through the well-stirred liver model plus the reported renal
clearance; bioavailability is the reported f_a times f_G times the f_H
implied by that same well-stirred calculation. No parameter is fitted
here and none is imported from a Simcyp population file: every value is
either a Table 1 / Appendix S1 input or an arithmetic consequence of
one. The reduction reproduces the paper’s own predicted Cmax, Tmax and
AUC after single 90 mg and 180 mg oral doses to within 6.4%, and Cmax at
both doses to within 1% (see the validation vignette). This is a
typical-value simulation model: the source reports no inter-individual
variance components and no residual-error model, so there are no etas
and propSd is fixed at zero. The drug-drug-interaction predictions that
are the paper’s main contribution (itraconazole, rifampin, diltiazem,
verapamil, efavirenz, and the transporter substrates) depend on
proprietary Simcyp perpetrator compound files and are NOT reproducible
from this model; see the vignette for the full list of deviations.
|
|
Brivaracetam
(Schoemaker 2017)
|
One-compartment population PK model for oral brivaracetam in paediatric
patients with epilepsy aged 1 month to 16 years (Schoemaker 2017).
First-order absorption, single-compartment distribution, and first-order
elimination, with allometric scaling of CL/F (exponent 0.750 fixed) and
V/F (exponent 1.00 fixed) on lean body weight normalised to a 50 kg
adult typical value. Co-administration of phenobarbital (PB; pooled with
primidone), carbamazepine (CBZ), or valproate (VPA) modify apparent oral
clearance via linear-additive multiplicative factors.
|
|
Brodalumab
(Timmermann 2019)
|
Two-compartment population PK model for brodalumab in adults with
moderate-to-severe plaque psoriasis (Timmermann 2019), with first-order
SC absorption, fixed bioavailability, and combined linear plus
Michaelis-Menten (target-mediated) elimination from the central
compartment.
|
|
Busulfan
(Choe 2012)
|
One-compartment IV PK model for intravenous busulfan in adult Korean
hematopoietic stem cell transplant recipients, with allometric scaling
on actual body weight (fixed exponent 0.5) on CL and Vd and a sex effect
on Vd (Choe 2012).
|
|
Busulfan
(Lawson 2022)
|
Two-compartment IV PK model for once-daily busulfan in pediatric
hematopoietic stem cell transplant recipients with allometric
normal-fat-mass (NFM) scaling, postmenstrual-age maturation on CL, and a
time-associated within-treatment-course CL decline (Lawson 2022).
|
|
Busulfan
(Long-Boyle 2015)
|
One-compartment IV PK model with Michaelis-Menten elimination for
busulfan in pediatric and young adult patients (0.1-24 yrs) undergoing
hematopoietic cell transplant. Allometric body-weight scaling on
intrinsic clearance (CLin, exponent fixed 0.75) and central volume (Vc,
exponent fixed 1) with reference weight 22 kg; hockey-stick age effect
on CLin (linear increase below the 12-yr breakpoint applied to AGE
directly, multiplicative linear decrease above). Correlated IIV on CLin
and Vc; combined proportional + additive residual error (Long-Boyle
2015).
|
|
Busulfan
(Schreib 2024)
|
One-compartment population pharmacokinetic model with intravenous
infusion and a time-varying elimination rate constant for busulfan in
124 pediatric patients undergoing hematopoietic stem cell
transplantation (HSCT) at the University Children’s Hospital Zurich,
October 2010 to February 2020, receiving twice-daily (q12h) 2-hour to
4-hour intravenous busulfan infusions as conditioning. Schreib 2024 fit
ln(V) and ln(k) directly rather than CL and V, because ‘building the
model on V and CL would result in two parameters with similar covariates
… potentially masking the covariates for k’. Two further parameters
describe an exponential decline of the elimination rate constant over
the course of therapy: kel(t) = kel(0) * (1 + kel_exp_famp * (1 -
exp(-kel_exp_kdes * t))), with kel_exp_famp = -0.167 (a 16.7% average
fall in k and CL at steady state) and a 13.4 h half-life for the change.
The fractional amplitude carries its own inter-individual variability
and is doubled to -0.312 (a 31% fall) in the hemophagocytic
lymphohistiocytosis / X-linked lymphoproliferative disease group. Volume
scales near-proportionally with calculated total body water; the
elimination rate constant depends on total body water, a
postmenstrual-age maturation function, serum albumin, an acute
lymphoblastic leukemia indicator, and the infusion duration. Total body
water and the maturation function are derived inside model() from
weight, height, age, and sex, so no separate columns are required.
IMPORTANT: simulate this model with rxSolve(…, useLinCmt = FALSE). It is
a one-compartment linear-elimination model, so rxSolve()’s default
ODE-to-linCmt() auto-conversion replaces the ODE with a closed-form
solution that holds the elimination rate constant at its t = 0 value and
therefore silently discards the time dependence that is the entire point
of this paper. The error is large and one-sided: exposure per dosing
interval is under-predicted by about 17% at steady state (45% in the
HLH/XLP group). See the validation vignette for the demonstration.
|
|
Butanediol
rat (Fung 2008)
|
Preclinical (rat). Population PK model for 1,4-butanediol (BD) and its
bioactivation pathway in adult male Sprague-Dawley rats after
intravenous and oral dosing, jointly with the unmeasured semialdehyde
intermediate (ALD), the gamma-hydroxybutyric acid metabolite (GHB), and
co-administered ethanol (ETOH). Each of the four substances follows
two-compartment disposition with Michaelis-Menten (mixed-order)
elimination; GHB additionally has a parallel first-order elimination.
The metabolic flux is BD -> ALD -> GHB; ETOH has no metabolic
connection to the BD/ALD/GHB chain. Mutual competitive inhibition is
encoded for BD elimination inhibited by GHB and by ETOH; ALD elimination
inhibited by BD; GHB elimination inhibited by BD; ETOH elimination
inhibited by BD. Oral BD absorption is first-order with a 7.5 min
lag-time; the absorbed fraction (F = 0.93, dose-independent) is split
between BD and ALD central compartments to represent pre-systemic
conversion of BD to ALD. The fraction entering as BD was dose-dependent
in the source paper (30 percent at 1.58 mmol/kg and 55 percent at 6.34
mmol/kg); the model defaults to the low-dose 1.58 mmol/kg fractions (30
percent as BD, 70 percent as ALD); see the vignette Assumptions and
deviations for the high-dose alternative. Volume of distribution of ALD
is mathematically non-identifiable and was constrained so that Vss of
ALD equals Vss of BD (source paper footnote c). Volume of the central
compartment for GHB was fixed at the average rat plasma volume of 0.010
L (source paper footnote b). Fit by NONMEM VI ADVAN9 with FOCE-I.
|
|
C3G
(Jeon 2012)
|
One-compartment first-order absorption population PK model with an
absorption lag time for cyanidin-3-glucoside (C3G) following 2-week
multiple oral dosing of 1 g black bean (Phaseolus vulgaris,
Cheongjakong-3-ho) seed coat extract once daily in 12 healthy adult
Korean volunteers (Jeon 2012), with log-normal IIV on CL/F and V/F (with
correlation rho = 0.883) and on Ka, and proportional residual error.
|
|
Cabamiquine
(Courlet 2023)
|
Semi-mechanistic joint blood- and liver-stage population PK/PD model for
the Plasmodium elongation factor 2 (eEF2) inhibitor cabamiquine
(formerly DDD107498 / M5717) in healthy adult men challenged with
Plasmodium falciparum (Courlet 2023, Table 1 and Fig. 2). The PK layer
is the three-compartment transit-absorption plus enterohepatic-
recycling model of modellib(‘Courlet_2023_cabamiquine_pk’), whose
individual parameters were carried forward. The PD layer is a parasite
turnover model at two life-cycle stages: a liver compartment seeded with
Finc * inoculum infected hepatocytes that grows at a fixed kgr,l =
ln(30000)/(624) = 0.072 /h and releases merozoites into blood
through a logistic transfer function Tr_lb(t) centred on T50 = 6 days,
and a blood compartment seeded at baseline parasitemia P0 that grows at
kgr,b. Cabamiquine concentration in the central compartment drives
parasite killing at both stages through a sigmoid Emax term with a
shared maximum kill rate kki and a shared inverse-exponential onset
delay (1 - exp(-kt t)) that lets the killing rate maximise over
the first ~48 h after dosing. Blood-stage potency differs between the
two challenge populations: EC50,b,SpzCh = EC50,b,IBSM * (1 - 0.83 *
STUDY_SPZCH). Liver-stage potency (EC50,l = 0.66 ng/mL) is higher than
blood-stage potency, reproducing the paper’s finding of superior
efficacy against the liver stage. Set STUDY_SPZCH = 0 to simulate the
induced blood stage malaria (IBSM) design (blood inoculation only) and
STUDY_SPZCH = 1 for the sporozoite challenge (SpzCh) design (liver
inoculation only).
|
|
Cabamiquine
pk (Courlet 2023)
|
Population PK model for the Plasmodium elongation factor 2 (eEF2)
inhibitor cabamiquine (formerly DDD107498 / M5717) in healthy adult men,
pooled from a first-in-human single-ascending-dose / induced blood stage
malaria (IBSM) trial and a sporozoite-challenge (SpzCh) chemoprophylaxis
trial (Courlet 2023 Supplementary Material 1). Three-compartment
apparent disposition with linear elimination; a Savic transit-absorption
chain feeds a depot that is absorbed into central at rate ka; and an
enterohepatic recycling loop moves drug from central into a recycling
(gallbladder / bile) compartment at rate k2g and releases it back into
the absorption depot at rate kg1 once the depot emptying time MTIME is
reached, reproducing the secondary concentration peak observed 24-30 h
post-dose. The observed lack of dose proportionality is captured
empirically by a power effect of the administered dose on the apparent
central volume V2/F (exponent -0.50); allometric body-weight scaling is
fixed at 0.75 on the apparent clearances and 1 on the apparent volumes.
This is the parsimonious PK model that was carried forward, with
individual parameters fixed, into the parasitemia PK/PD model; see
modellib(‘Courlet_2023_cabamiquine’).
|
|
Cabazitaxel
(Ferron 2013)
|
Three-compartment population PK model for intravenous cabazitaxel in
patients with advanced solid tumors (Ferron 2013)
|
|
Cabazitaxel
(Janssen 2017)
|
Two-compartment population PK model for intravenous cabazitaxel in 10
men with metastatic castration-resistant prostate cancer, with
individual midazolam clearance as a CYP3A metabolic-phenotype covariate
on cabazitaxel clearance (Janssen 2017 Table 2B ‘Metabolic phenotype
model’). The covariate enters via a linear deviation from the population
midazolam clearance reference of 26 L/h. The individual midazolam
clearance is sourced from the companion Janssen 2017 midazolam model
(see modellib(‘Janssen_2017_midazolam’)).
|
|
Cabozantinib
(Lacy 2018)
|
Two-compartment population PK model for oral cabozantinib (tyrosine
kinase inhibitor) in healthy volunteers and patients with renal cell
carcinoma, castration-resistant prostate cancer, medullary thyroid
carcinoma, glioblastoma multiforme, or other advanced malignancies (Lacy
2018, n=1534 across 9 clinical studies). Absorption is described by
parallel dual processes: a fraction F1 enters depot1 via first-order
absorption rate Ka with absorption lag time ALAG1, and the remaining
(1-F1) enters depot2 via zero-order infusion over duration D2. Capsule
(vs tablet, reference) formulation reduces both Ka and overall
bioavailability; Ka also scales with dose via a power function (DOSE/60
mg)^0.677. Two-compartment disposition (central + peripheral1) with
first-order elimination from central. Covariates on CL/F and Vc/F are
baseline age (power on median 64 y), body weight (power on median 81
kg), female sex, race (Black/Asian/Other vs White reference), and tumor
type (RCC/CRPC/MTC/GB/Other vs HV reference); MTC cancer type drives an
approximately 93% higher CL/F.
|
|
Cabozantinib
dose modification (Lacy 2018)
|
Repeated time-to-event (RTTE) hazard model for the ‘dose modification of
any kind’ (DMAK) endpoint in adults with advanced renal cell carcinoma
(RCC) treated with oral cabozantinib in the phase III METEOR study (Lacy
2018 exposure-response analysis, n=317 patients with 0-52 events per
patient). The instantaneous risk of a dose modification (interruption,
reduction, or escalation) depends on whether the patient is currently on
an active dose or on a dose interruption. When on active dose (DOSE >
0) the hazard increases log-linearly with the time-varying average
cabozantinib plasma concentration CAV. When on a dose interruption (DOSE
= 0) the hazard is governed by a separate, larger baseline log-hazard
with no cabozantinib effect (cabozantinib effect on hold-state hazard
was tested and dropped during base-model development). The drug input
Cavg is the individual predicted daily average plasma cabozantinib
concentration (ng/mL) derived from the upstream Lacy 2018 popPK model
Lacy_2018_cabozantinib. Forward simulation exposes
hazard (instantaneous DMAK rate per day) and
sur (survival = probability of no DMAK event since t = 0)
as derived outputs.
|
|
Cabozantinib
tumor (Lacy 2018)
|
Longitudinal sum-of-tumor-diameter (SOD) growth-inhibition PD model for
oral cabozantinib in adults with advanced renal cell carcinoma (RCC)
enrolled in the phase III METEOR study (Lacy 2018 exposure-response
analysis, n=319 patients with 1637 evaluable tumor-diameter
measurements). The tumor diameter Y follows first-order exponential
growth at rate k_grow, with a saturable cabozantinib drug-effect of the
form Cavg/(EC50 + Cavg) modulating a time-dependent decay rate decay(t)
= k_dmax + k_dmax_tot * exp(-k_tol * t). The k_dmax term is the
non-attenuating asymptotic decay rate, k_dmax_tot is the magnitude of
the resistance-driven loss of decay rate, and k_tol governs the
attenuation kinetics (paper-reported attenuation half-life 25.6 days).
The drug input Cavg is the individual predicted daily average plasma
cabozantinib concentration (ng/mL) carried as a time-varying CAV data
column; the upstream popPK model is Lacy_2018_cabozantinib
(Lacy 2018 popPK companion paper). Residual error is additive on Y (mm);
IIV is exponential on Y(0), k_grow, k_dmax, and k_dmax_tot, with IIV on
EC50 and k_tol fixed at a near-zero variance (paper Supplemental Table 3
footnote b).
|
|
Canakinumab
(AitOudhia 2012)
|
Integrated population PK/PD model of canakinumab (anti-IL-1beta IgG1/k
mAb) in adults with rheumatoid arthritis (Ait-Oudhia 2012).
Two-compartment popPK for total canakinumab is coupled to a
quasi-equilibrium target-binding model with endogenous IL-1beta
(zero-order production ksyn, linear clearance CLL). Predicted free
IL-1beta drives downstream PD: (1) a three-compartment CRP transduction
chain with a power-law stimulation (beta) on free-IL-1beta ratio and an
empirical amplification (gamma) on the input to the third compartment,
and (2) a single-compartment ACR latent variable (ACRL) regulated by a
sigmoid Emax on the drop in free IL-1beta below baseline plus a
first-order placebo build-up; the latent is mapped to ACR20/50/70
response probabilities via a logit transform with a between-subject
random effect. Only body weight was a significant covariate (allometric
on CL, CLL, CLDL, Vc, Vp with reference 70 kg).
|
|
Canakinumab
(Chakraborty 2012)
|
Population pharmacokinetic-binding model for canakinumab (anti-IL-1b
IgG1/k monoclonal antibody) and its endogenous target IL-1b in adult
cryopyrin-associated periodic syndromes (CAPS) patients (Chakraborty
2012). Two physical compartments (central and peripheral) each carry
three species: free canakinumab, free IL-1b, and the canakinumab-IL-1b
complex. Drug, ligand, and complex share the same volumes of
distribution; complex clearance is set equal to free-drug clearance (CLX
= CLD). Distribution between compartments uses two
permeability-surface-area coefficients: PSD for free drug and complex,
PSL for free ligand. Endogenous IL-1b production RLI enters the
peripheral compartment. Drug-ligand binding is solved algebraically
under a quasi-steady-state assumption with dissociation constant KD
(Hayashi 2007 form). Subcutaneous bioavailability F1 was estimated on
the logit scale; this file uses the Sp2/0 cell-line value (commercial
Ilaris). Body weight modifies CLD, VC, VP via centred power covariates;
serum albumin modifies CLD; age modifies SC ka. Two observed analytes:
total canakinumab (free + complex) in ug/mL and total IL-1b (free +
complex) in pg/mL.
|
|
Canrenone
(Suyagh 2012)
|
One-compartment population PK model for canrenone, the pharmacologically
active metabolite of intravenous potassium canrenoate (K-canrenoate), in
23 paediatric patients (2 days to 10 years; median weight 4 kg, range
2.16-28.0 kg) receiving K-canrenoate in the NICU / PICU for retained
fluids or congestive heart failure (Suyagh 2012). The K-canrenoate dose
compartment (modelled as ‘depot’ because only canrenone is measured) is
converted to canrenone by a first-order metabolic transformation rate kf
(paper symbol) = 5.25 1/h. Canrenone disposition is described by
apparent clearance CL/F and apparent central volume V/F (the ‘F’ factor
absorbs the unknown fraction of K-canrenoate that ultimately reaches the
canrenone compartment; the model assumes the total dose is converted to
canrenone). Bodyweight scales CL/F and V/F by fixed allometric exponents
(0.75 on CL, 1.0 on V) with a reference weight of 70 kg. No other
covariate (gestational age, postnatal age, postmenstrual age, serum
creatinine, serum albumin, haematocrit, sex) was retained in the final
model. Residual error is proportional only.
|
|
Capecitabine
(Blesch 2003)
|
Population PK model ‘CAP7440’ for oral capecitabine, evaluated by
simultaneously fitting plasma concentrations of three sequential
metabolites: 5’-DFUR (5’-deoxy-5-fluorouridine), 5-FU (5-fluorouracil),
and FBAL (alpha-fluoro-beta-alanine). Parent capecitabine and the first
metabolite 5’-DFCR are not modelled as compartments; the dose enters the
5’-DFUR pool directly through a first-order absorption rate constant KA
with absorption lag TLAG. Sequential first-order kinetics carry mass
through 5’-DFUR -> 5-FU -> FBAL using apparent oral clearances
CL/F and volumes V/F (CL1/V1 for 5’-DFUR, CL2/V2 for 5-FU, CL3/V3 for
FBAL). 5-FU volume V2 is fixed at 17.8 L from literature (Heggie 1987)
because it was not sensitive to the dataset. Three retained covariate
effects in the final population PK model: alkaline phosphatase on 5-FU
clearance (CL2), creatinine clearance on FBAL clearance (CL3) and volume
(V3), and body surface area on FBAL volume (V3) – all multiplicative
power forms. Fit to 481 patients with advanced or metastatic colorectal
cancer (Phase III studies) plus 24 patients with extensive sampling from
a Phase I bioequivalence study.
|
|
Capecitabine
(Urien 2005)
|
Population PK model for oral capecitabine and its three sequential
metabolites 5’-DFCR (5’-deoxy-5-fluorocytidine), 5’-DFUR
(5’-deoxy-5-fluorouridine), and 5-FU (5-fluorouracil) in 40 adult
patients with metastatic cancer (Urien 2005). Capecitabine PK is a
one-compartment apparent V1/F model with first-order absorption (Ka) and
a lag time; non-transformation elimination CL10/F runs in parallel with
the formation clearance CL12/F to 5’-DFCR. Each metabolite has its own
central compartment with apparent volume fixed to 1 L (only output rate
constants are identifiable in the source NONMEM ADVAN6 fit), so the
chain 5’-DFCR -> 5’-DFUR -> 5-FU -> output is described by
first-order rate constants K23, K34, K40 (paper’s notation). Total
bilirubin (canonical TBILI; source column BILT, umol/L) is the only
retained covariate: power exponent +0.32 on CL10/F and -0.36 on K34,
both centred on the median bilirubin 8.8 umol/L. Inter-individual
variability is reported on TLAG, V1, CL10, K23, K34, and K40; ISV on
CL12 was fixed to 0 and ISV on Ka was deleted in favour of a large
inter-occasion variability on Ka that is not represented in this static
model file (see vignette Errata).
|
|
Carbenicillin
qsp (LopezArguello 2023)
|
QSP. In vitro (Pseudomonas aeruginosa PAO1). Whole-cell
penicillin-binding protein (PBP) covalent-binding model for
carbenicillin (penicillin): seven coupled ODEs for the rate of net
influx of drug across the outer membrane into periplasm and the
competitive, mass-balanced acylation of six PBPs (1a, 1b, 2, 3, 4, 5/6)
counted as molecules per bacterial cell. The intact parameter switches
between the intact whole-cell assay (penetration-limited; drug enters
periplasm at Rate_Influx/access) and the lysed isolated-membrane assay
(no outer membrane; a vast excess of drug molecules is present at time
0).
|
|
Carboplatin
(Ekhart 2008)
|
Two-compartment population PK model for free (ultrafilterable)
carboplatin in adult cancer patients (Ekhart 2008)
|
|
Carboplatin
(Zandvliet 2008)
|
Two-compartment population PK model for free (ultrafilterable)
carboplatin in adult cancer patients receiving combination chemotherapy
with indisulam (Zandvliet 2008). Clearance is modelled as a renal +
non-renal split: a Cockcroft-Gault creatinine-clearance-proportional
renal component (theta1 = 0.76) plus a fixed non-renal component (theta2
= 1.5 L/h, fixed at the Calvert 1989 estimate).
|
|
Carfentanil
iv (Mann 2022)
|
Three-compartment IV carfentanil population PK with a first-order
biophase (effect-site) equilibrium compartment, used as the agonist
input layer of the Mann 2022 translational opioid-overdose model. Mann
2022 had no full carfentanil clinical PK study to fit – only a single
microdose case report (Minkowski 2012) reporting a roughly 45-minute
plasma half-life. They therefore took the fentanyl Algera 2021 PK
micro-constants and applied a fixed set of rate- constant modifications
(k_el and k13 divided by 10; k21 and k31 multiplied by 10; k1 increased
to 10/min) to reproduce the longer plasma persistence and faster
effect-site equilibration of carfentanil. The resulting macro-constants
encoded in ini() below yield exactly those micro-constants when combined
with (WT/70)^0.75 / (WT/70) allometric scaling. Inter-subject
variability is assumed equal to the fentanyl model (same omega^2 values,
no carfentanil-specific IIV estimated). Outputs plasma concentration Cc
in ng/mL and effect-site Ce in pM for downstream consumption by
Mann_2022_mu_receptor_binding.
|
|
Carvedilol
(Honda 2005)
|
One-compartment population PK model for orally administered racemic
carvedilol in 23 healthy Japanese volunteers, with R- and S-enantiomer
whole-blood concentrations measured by chiral HPLC at 2 h and 6 h after
a single 5- or 10-mg oral dose (Honda 2005). NONMEM ADVAN1/TRANS2 with
very rapid absorption: the racemic dose is split equally between two
parallel central compartments (central_r, central_s) with no separate
absorption depot. CL/F and V/F scale linearly with body weight; an S/R
ratio theta_3 (CL/F) and theta_4 (V/F) parameterise the stereoselective
difference. One subject-level eta on CL/F and one on V/F are shared
between enantiomers (correlated block IIV, rho ~ 0.90). Power-variance
residual error with fixed exponent 1/2 (Honda Eq. 3), shared between R-
and S-enantiomer observations. CYP2D610 genotype is not in the
structural model; Honda 2005 reports the 10-carrier effect only as
a post-hoc stratification of the individual Bayes estimates (Figs. 3-4).
|
|
Carvedilol
(Hwang 2023)
|
Sequential population PK-PD model for oral carvedilol in 21 healthy
Korean male volunteers genotyped for CYP2D6 (Hwang 2023). PK is a
two-compartment model (central + peripheral1) with zero-order absorption
of duration D1 into the central compartment preceded by an absorption
lag time Tlag, and first-order elimination; volumes and clearances are
apparent (CL/F, Vc/F, Vp/F, Q/F). The only retained covariate is the
CYP2D610/10 (intermediate-metabolizer-2) genotype, which
reduces CL/F by 32.8 percent relative to the pooled CYP2D61/1,
1/2, 1/10, 2/10 reference. PD is a
direct-effect competitive-antagonism Emax model for the heart-rate
response to an isoproterenol sensitivity test: HR = E0 + Emax * D /
(ED50 * (1 + C / IC50) + D), where D is the isoproterenol challenge dose
in ug (covariate DOSE_ISOPROTERENOL_UG), C is the carvedilol plasma
concentration in ng/mL, and the Hill exponent was fixed at 1. Carvedilol
competitively shifts the isoproterenol dose-response curve to the right
without changing Emax; no covariate, including CYP2D6 phenotype, was
retained on any PD parameter.
|
|
Carvedilol
(Othman 2007)
|
Two-compartment population PK model for S(-)-carvedilol in healthy
volunteers after oral administration of the immediate-release (IR) and
the new controlled-release (CR) dosage forms of carvedilol (Othman
2007). Three parallel depot compartments encode the dosage-form-specific
absorption: depot (CR, 3-stage time-varying KA), depot2 (IR morning,
2-stage), depot3 (IR evening, 2-stage). Diurnal variability in IR
absorption is captured by separate morning and evening KAs and a lower
IR-PM relative bioavailability.
|
|
Casirivimab
(Lin 2024)
|
Two-compartment population PK model for casirivimab in pediatric and
adult subjects (non-infected, ambulatory or hospitalized
SARS-CoV-2-infected, or household contacts) following IV or SC
administration (Lin 2024, casirivimab arm of the joint casirivimab +
imdevimab popPK model)
|
|
Caspofungin
(Wurthwein 2013)
|
Linear two-compartment population PK model with proportional residual
error for once-daily 2-hour intravenous caspofungin infusions (70, 100,
150, 200 mg QD) in adults with proven or probable invasive aspergillosis
(Wurthwein 2013). Clearance and central volume share a single linear
body-weight fractional change centred on the cohort median body weight
of 76 kg (CL_i = CL_typ * [1 + 0.0102 * (WT - 76)]; V1_i = V1_typ * [1 +
0.0102 * (WT - 76)]). Inter-individual variability is modelled
exponentially on CL, V1, and V2 with an estimated CL-V1 covariance
(correlation 0.802). Inter-occasion variability (16% CV) is included on
CL across five sampling occasions (days 1, 4, 7, 14, 28) via the OCC
covariate; downstream users who only need typical-value or IIV-only
simulations can pass OCC = 0 (or any value outside 1..5) so the IOV
terms zero out. Dose-level, gender, age, baseline serum bilirubin and
baseline creatinine clearance were screened but not retained.
|
|
CC292
(Li 2017)
|
Two-compartment population PK model for oral CC-292 (spebrutinib, a
potent Bruton tyrosine kinase inhibitor) in 145 pooled subjects: 32
healthy adults (AVL-292-004) and 113 patients with relapsed and/or
refractory B-cell malignancies including chronic lymphocytic leukemia
(AVL-292-003). First-order absorption with a single absorption lag,
linear elimination from the central compartment, with linear-deviation
female-sex effect on apparent clearance (females have 26% lower CL/F)
and a power age effect on apparent central volume (reference age 62
years). Residual variability is split into healthy-volunteer and patient
strata.
|
|
Cebranopadol
(Kleideiter 2017)
|
Two-compartment population PK model for oral cebranopadol with two
lagged transition compartments in healthy subjects and chronic-pain
patients (Kleideiter 2017; with 2018 correction)
|
|
Cebranopadol
(Kleideiter 2018)
|
Two-compartment population PK model for cebranopadol, a NOP / opioid
receptor agonist, in healthy adults and adult chronic-pain patients (low
back pain or osteoarthritis, diabetic polyneuropathy,
post-bunionectomy), with two transit absorption compartments before
central, first-order elimination, and covariate effects from sex, CYP2C9
phenotype, ALT, CrCl, age, body weight, formulation, and disease status
(Kleideiter 2018)
|
|
Cediranib
(Li 2017)
|
Two-compartment population PK model for oral cediranib (AZD2171) in
adult cancer patients (Li 2017), with sequential zero- and first-order
absorption (zero-order release into depot followed by first-order
absorption to central), bioavailability fixed to 1, allometric power
scaling on apparent clearance ((WT/73 kg)^0.517 and (Age/59 y)^-0.409)
and on apparent central volume ((WT/73 kg)^0.65), correlated
inter-individual variability between CL/F and Vc/F (correlation 0.839),
independent IIV on Ka, and proportional residual error (rich-sampling
estimate).
|
|
Cefadroxil
mouse pbpk (Saleh 2023)
|
PBPK (LeiCNS-PK3.0 CNS physiologically-based model, mouse version).
Preclinical (mouse, C57BL/6 Pept2+/+). Nine-compartment CNS PBPK model
predicting unbound cefadroxil concentrations in brain extracellular
fluid (brain ECF) after a single 36 mg/kg intravenous dose. The CNS
structure is the mouse re-parameterisation of LeiCNS-PK3.0: brain
microvasculature (brain_vascular), brain ECF, a phospholipid
brain-cell-membrane binding compartment (brain_cell_membrane), brain
intracellular fluid (brain_icf), lysosomes (brain_lysosome), and the
four CSF compartments (lateral ventricles, third + fourth ventricles,
cisterna magna, subarachnoid space) draining in series back to plasma.
Transport across the BBB and BCSFB is the sum of a paracellular
clearance (Qp, charged + neutral drug) and a transcellular clearance
(Qt, neutral drug only, scaled by pH-dependent neutral fractions PHF and
by asymmetry factors AF that encode active transport). Every CNS
parameter is fixed to mouse physiology (Table III) or derived from the
drug’s physicochemical properties (Table I); none was fitted here. The
BBB asymmetry factors are back-calculated from Kp,uu,BBB = 0.05
(estimated by the authors; Table V). The plasma PK model is the
empirical one-compartment model of Table IV (in-house Monolix fit) and
acts purely as a forcing function: brain uptake does not deplete plasma,
exactly as published.
|
|
Cefathiamidine
(Zhi 2018)
|
Two-compartment population PK model for intravenous cefathiamidine (a
first-generation cephalosporin) in 54 children (age 2.0-11.8 years;
weight 8.0-36.0 kg) with hematologic disease, developed in NONMEM v7.2
(FOCE-I) from 120 sparse plasma samples. Structural model: first-order
elimination from a central compartment, with allometric body-weight
scaling on CL, Q (exponent 0.75) and V1, V2 (exponent 1), reference
weight 17.75 kg (the cohort median current weight). Inter-individual
variability (exponential) is estimated for CL and V2 only; residual
variability is exponential (lognormal on the linear scale). Bodyweight
was the only retained covariate; age and creatinine clearance were not
significant in the limited cohort (CrCL range 130-462 mL/min).
|
|
Cefepime
(Capparelli 2005)
|
One-compartment population PK model for cefepime in preterm and term
neonates (Capparelli 2005); additive renal-plus-non-renal CL on serum
creatinine, additive Vc step for PCA < 30 weeks.
|
|
Cefepime
(Jonckheere 2019)
|
Two-compartment population PK model for IV cefepime in critically ill
ICU patients (Jonckheere 2019), updated by simultaneously fitting plasma
+ urine PK from the original Jonckheere 2017 pilot (STDY1) and the
Jonckheere 2019 target-controlled-infusion cohort (STDY2). Total
clearance is the sum of an estimated-creatinine-clearance-driven renal
arm (CL_renal = 2.29 * (eCrCL/60)^0.943 L/h per 70 kg) and a
covariate-free non-renal arm (CL_nonren = 0.795 L/h per 70 kg); all PK
parameters are scaled allometrically with body weight (reference 70 kg,
exponent 3/4 for clearances, 1 for volumes). The structural form encodes
the non-dialysis patient (paper Equations 1-4); a separate CL_dialysis =
4.48 L/h applied during intermittent hemodialysis sessions in the source
dataset is documented in the vignette but not enabled in this model
file.
|
|
Cefepime
(Shoji 2016)
|
Two-compartment IV population PK model for cefepime in 91 neonates,
infants, and children (Shoji 2016); body-weight allometric scaling
(fixed exponents 0.75 on CL and Q, 1.0 on Vss), nonlinear
postmenstrual-age maturation on CL, a power effect of serum creatinine
on CL, and a power effect of gestational age on Vss. Central volume of
distribution enters as a fixed fraction of steady-state volume (V/Vss =
0.460).
|
|
Cefepime
qsp (LopezArguello 2023)
|
QSP. In vitro (Pseudomonas aeruginosa PAO1). Whole-cell
penicillin-binding protein (PBP) covalent-binding model for cefepime
(cephalosporin): seven coupled ODEs for the rate of net influx of drug
across the outer membrane into periplasm and the competitive,
mass-balanced acylation of six PBPs (1a, 1b, 2, 3, 4, 5/6) counted as
molecules per bacterial cell. The intact parameter switches between the
intact whole-cell assay (penetration-limited; drug enters periplasm at
Rate_Influx/access) and the lysed isolated-membrane assay (no outer
membrane; a vast excess of drug molecules is present at time 0).
|
|
Cefotaxime
(Ahsman 2010)
|
One-compartment population PK model for cefotaxime (CTX) and its active
metabolite desacetylcefotaxime (DACT) in critically ill neonates and
infants on extracorporeal membrane oxygenation (ECMO). IV bolus parent
with first-order elimination; the metabolite is generated 1:1 from
parent elimination on a CTX-equivalent mass basis (the source paper
converted observed DACT concentrations to CTX equivalents by the
molecular weight ratio Mr_CTX / Mr_DACT = 455.5 / 413.4 before fitting,
and assumed a conversion fraction FDACT/CTX = 1). Parent CL is scaled by
body weight (WT) via a power model centred at 3.5 kg; both parent and
metabolite CL include a power covariate effect of time after ECMO
decannulation (T_POST_ECMO) centred at 100 h that is removed during ECMO
(T_POST_ECMO = 0). Metabolite CL additionally includes a power covariate
effect of continuous venovenous hemofiltration flow Q_CVVH centred at
193 mL/min that is removed when CVVH is not running (Q_CVVH = 0).
Volumes (Vc, Vc_dact) carry no covariate effects.
|
|
Cefotaxime
(Leroux 2016)
|
Two-compartment IV population PK model for cefotaxime in neonates and
young infants (Leroux 2016). Clearance, central volume, peripheral
volume, and inter-compartmental clearance are allometrically scaled to
current body weight (fixed exponents 0.75 on CL and Q, 1.0 on V1 and V2;
reference weight 1.665 kg). Clearance carries a power-form maturation
function on gestational age (reference 30 weeks) and postnatal age
(reference 12 days). Only CL has inter-individual variability; residual
error is proportional.
|
|
Cefoxitin
qsp (LopezArguello 2023)
|
QSP. In vitro (Pseudomonas aeruginosa PAO1). Whole-cell
penicillin-binding protein (PBP) covalent-binding model for cefoxitin
(cephalosporin): seven coupled ODEs for the rate of net influx of drug
across the outer membrane into periplasm and the competitive,
mass-balanced acylation of six PBPs (1a, 1b, 2, 3, 4, 5/6) counted as
molecules per bacterial cell. The intact parameter switches between the
intact whole-cell assay (penetration-limited; drug enters periplasm at
Rate_Influx/access) and the lysed isolated-membrane assay (no outer
membrane; a vast excess of drug molecules is present at time 0).
|
|
Cefpirome
(Bulitta 2011)
|
Three-compartment population PK model for IV cefpirome with simultaneous
fit of plasma concentrations and amounts excreted unchanged in urine.
Built from a pooled cohort of 24 Caucasian adults: 12 cystic fibrosis
(CF) patients and 12 healthy volunteers (HVs) each given a single 10-min
IV infusion of 2 g cefpirome. Body size is captured by allometric
scaling on lean body mass (LBM) with fixed exponents 0.75 on clearance
terms and 1.0 on volumes (reference LBM = 53 kg). Total clearance is
split into an estimated renal arm (CL_R, urinary recovery is tracked in
the canonical urine compartment) and a non-renal arm (CL_NR). A CF / HV
cohort indicator DIS_CF (1 = CF patient, 0 = HV reference) carries three
disease- specific scale factors estimated by the paper: FCYF_CLR = 1.07
applied to CL_R, FCYF_CLNR = 1.13 applied to CL_NR, and FCYF_VSS = 0.98
applied uniformly to V1 (central), V2 (shallow peripheral), and V3 (deep
peripheral). The inter-compartmental clearances Q12 (central <->
shallow) and Q23 (central <-> deep) are shared across cohorts.
Typical-value clearance and volume estimates are anchored to DIS_CF = 0
(HV reference) per the DIS_CF covariate convention registered in
inst/references/covariate-columns.md.
|
|
Cefpirome
(Kang 2020)
|
Two-compartment IV-bolus population PK model for cefpirome in critically
ill adults on venoarterial extracorporeal membrane oxygenation (VA-ECMO)
(Kang 2020). Final-model covariates: power-form serum creatinine on CL
(reference 1.6 mg/dL), and a binary ECMO-active treatment-status
indicator on CL (1.41-fold higher when ECMO-ON) and V1 (4.22-fold higher
when ECMO-ON).
|
|
Cefquinome
pbpk (Mi 2023)
|
Veterinary (pig). PBPK (whole-body, six-compartment, Berkeley Madonna
10.1.3) for the cephalosporin cefquinome after intramuscular injection
in swine, developed to optimise the dosage regimen against
respiratory-tract pathogens and to predict the withdrawal interval for
edible tissues (Mi et al. 2023, PLoS Comput Biol 19:e1011331). Plasma
(venous and arterial blood pools), liver, kidney, muscle and a lumped
rest-of-body compartment are perfusion-limited and well stirred; the
lung is permeability-limited and resolves into vascular blood,
interstitial fluid and tissue sub-compartments, because lung
interstitial fluid is the site of action for respiratory pathogens and
was measured directly by microdialysis in this study. Only unbound drug
crosses between the lung sub-compartments and only unbound arterial drug
perfuses the tissues. Intramuscular absorption is a two-step process:
90% of the injected dose is immediately available at the injection site
and is absorbed into venous blood at first-order rate Kim, while 10% is
released from a slow depot at first-order rate Kdiss into the same
injection-site pool. Elimination is renal (from kidney) plus
hepatobiliary (from liver). The 11 parameters that Mi 2023 Table 4
carried through the 1000-animal Monte Carlo pop-PBPK analysis carry
between-animal variability here; every other parameter is a fixed
physiological or fitted chemical-specific constant. The model was
hand-calibrated in Berkeley Madonna against digitised literature data,
so no standard errors and no residual-error model are reported – the
propSd term is a placeholder. Several Table 3 / supplement-code
discrepancies are reproduced as coded; see the vignette Errata.
|
|
Ceftaroline
(Minichmayr 2024)
|
Two-compartment population PK model with linear elimination for
ceftaroline (the active metabolite of the prodrug ceftaroline fosamil)
in 12 healthy male volunteers receiving either the standard dosing
regimen (ceftaroline fosamil 600 mg every 12 h as a 1 h intravenous
infusion) or the approved intensified regimen (600 mg every 8 h as a 2 h
intravenous infusion). Doses are entered as milligrams of the
administered prodrug ceftaroline fosamil; the model converts to
ceftaroline via the fixed ceftaroline-to-ceftaroline-fosamil molar-mass
ratio of 0.883 applied as the bioavailability of the central
compartment, reflecting the paper’s finding that prodrug-to-drug
conversion is complete and effectively instantaneous (a depot / k_trans
conversion compartment worsened the fit, and a sensitivity analysis
favoured k_trans > 1000/h). Exponential interindividual variability
on CL, Vc and Vp; combined additive and proportional residual error. No
covariates were retained: creatinine clearance was screened on CL as
linear and power functions and via a previously published CL-CLcr
relationship, but was not significant in this small, homogeneous cohort
with unimpaired renal function. The model underpins the paper’s
systematic comparison of the three components of dosing intensification
(dosing interval, infusion duration and total daily dose) on the PK/PD
index fT>MIC against Staphylococcus aureus.
|
|
Ceftaroline
(Riccobene 2016)
|
Joint two-compartment ceftaroline fosamil (prodrug) plus
three-compartment ceftaroline (active metabolite) population PK model
with an algebraic epithelial-lining-fluid (ELF) partition coefficient,
developed on plasma and bronchoalveolar-lavage ELF data from 50 healthy
adults given 600 mg ceftaroline fosamil as a 1-h IV infusion q12h or q8h
to steady state (Riccobene 2016). Ceftaroline fosamil is assumed to be
converted completely to ceftaroline, so the whole prodrug elimination
clearance CLcf enters the ceftaroline central compartment. ELF
concentrations are not a distribution compartment: the parallel decline
of plasma and ELF made an ELF compartment unidentifiable, so ELF is
modelled as the ceftaroline plasma concentration scaled by a partition
coefficient (0.193) carrying inter-individual variability. Body weight
enters allometrically on all clearances (0.75) and volumes (1);
BSA-normalised creatinine clearance below 80 mL/min/1.73 m2, age,
hemodialysis status and healthy-versus-patient status act on ceftaroline
clearance, and healthy-versus-patient status acts on ceftaroline central
volume. An intramuscular depot (first-order ka, bioavailability fixed to
1) is carried from the upstream adult model; the ELF study itself used
IV dosing only.
|
|
Ceftazidime
(Bulitta 2010)
|
Three-compartment population PK model for ceftazidime after 5-min IV
infusion in cystic fibrosis patients and healthy volunteers (Bulitta
2010), with allometric fat-free-mass scaling and a
cystic-fibrosis-vs-healthy disease-group factor on total clearance.
|
|
Ceftazidime
(Conil 2007)
|
Two-compartment IV population PK model for ceftazidime in adult burn-ICU
patients, with creatinine clearance on CL and sex / mechanical
ventilation / creatinine clearance on the peripheral volume V2 (Conil
2007)
|
|
Ceftazidime
(Georges 2009)
|
Two-compartment IV population PK model for ceftazidime in critically ill
adults (ICU). Total clearance is an additive linear function of
MDRD-estimated glomerular filtration rate; central volume V1 is selected
by mechanical-ventilation status; peripheral volume V2 is selected by
ICU admission etiology (polytrauma, postsurgical, or medical).
|
|
Ceftazidime
(Shi 2018)
|
One-compartment IV population PK model for ceftazidime in infants
0.1-2.0 years (Shi 2018) with allometric body-weight scaling and a
power-form creatinine-clearance effect on clearance.
|
|
Ceftazidime
(Zieck 2023)
|
One-compartment IV population PK model for ceftazidime in adult
general-ward patients spanning adequate to severely impaired renal
function (Zieck 2023); clearance is a power function of CKD-EPI
estimated glomerular filtration rate and is 1.56-fold higher with
concomitant use of another antibiotic.
|
|
Ceftazidime
avibactam control (Zazo 2024)
|
Semi-mechanistic PK/PD model of ceftazidime-avibactam against
Pseudomonas aeruginosa (strain 2154) in the NON-ICU control population.
One-compartment linear PK for each drug, with volume proportional to
body weight and clearance a linear function of creatinine clearance,
driving a two-state bacterial growth model (an actively growing
population carried on the log10 scale and a resting population carried
on the linear CFU/mL scale) under a shared logistic capacity limit.
Ceftazidime kill follows a sigmoidal Emax function whose EC50 is lowered
biexponentially by avibactam; exponential delay functions retard growth
and initial kill; ceftazidime is degraded by a
bacterial-density-dependent Hill function that avibactam inhibits.
Sibling model for the critically ill population:
Zazo_2024_ceftazidime_avibactam_icu.
|
|
Ceftazidime
avibactam fosfomycin hfim (Kroemer 2024)
|
In vitro (Escherichia coli, clinical MDR isolate; CTX-M-15 + TEM-4 ESBL
and OXA-244 carbapenemase). Semi-mechanistic PK/PD model of the dynamic
hollow fiber infection model for ceftazidime/avibactam and fosfomycin:
the static time-kill model (susceptible plus joint resistant
subpopulation, sigmoidal Emax or power-model kill, Bliss independence,
GPDI synergy) extended with two phenotypically less susceptible
subpopulations growing at 3x MIC, whose emergence is suppressed by
ceftazidime and fosfomycin through subpopulation synergy. Drug
concentrations are dosable one-compartment states declining with the
nominal hollow fiber half-life. Sibling model:
Kroemer_2024_ceftazidime_avibactam_fosfomycin_tkc.
|
|
Ceftazidime
avibactam fosfomycin tkc (Kroemer 2024)
|
In vitro (Escherichia coli, clinical MDR isolate; CTX-M-15 + TEM-4 ESBL
and OXA-244 carbapenemase). Semi-mechanistic PK/PD model of the static
time-kill experiments for ceftazidime, avibactam and fosfomycin: a
susceptible and a joint resistant bacterial subpopulation under a shared
capacity limit, with sigmoidal Emax or power-model mono-drug kill, Bliss
independence as the additivity criterion, and general pharmacodynamic
interaction (GPDI) terms describing the >99% reduction of the
ceftazidime EC50 by avibactam and of the fosfomycin EC50 by ceftazidime.
Drug concentrations are static covariates (no dosing events). Sibling
model: Kroemer_2024_ceftazidime_avibactam_fosfomycin_hfim.
|
|
Ceftazidime
avibactam icu (Zazo 2024)
|
Semi-mechanistic PK/PD model of ceftazidime-avibactam against
Pseudomonas aeruginosa (strain 2154) in the CRITICALLY ILL (intensive
care unit) population. One-compartment linear PK for each drug, with
volume proportional to body weight and clearance a linear function of
creatinine clearance, driving a two-state bacterial growth model (an
actively growing population carried on the log10 scale and a resting
population carried on the linear CFU/mL scale) under a shared logistic
capacity limit. Ceftazidime kill follows a sigmoidal Emax function whose
EC50 is lowered biexponentially by avibactam; exponential delay
functions retard growth and initial kill; ceftazidime is degraded by a
bacterial-density-dependent Hill function that avibactam inhibits.
Sibling model for the non-ICU control population:
Zazo_2024_ceftazidime_avibactam_control.
|
|
Ceftazidime
qsp (LopezArguello 2023)
|
QSP. In vitro (Pseudomonas aeruginosa PAO1). Whole-cell
penicillin-binding protein (PBP) covalent-binding model for ceftazidime
(cephalosporin): seven coupled ODEs for the rate of net influx of drug
across the outer membrane into periplasm and the competitive,
mass-balanced acylation of six PBPs (1a, 1b, 2, 3, 4, 5/6) counted as
molecules per bacterial cell. The intact parameter switches between the
intact whole-cell assay (penetration-limited; drug enters periplasm at
Rate_Influx/access) and the lysed isolated-membrane assay (no outer
membrane; a vast excess of drug molecules is present at time 0).
|
|
Ceftobiprole
(Cojutti 2023)
|
Three-compartment IV population PK model for ceftobiprole in adults with
severe Gram-positive infections (real-life multicentre therapeutic drug
monitoring cohort, Italy). Clearance rises exponentially with CKD-EPI
estimated glomerular filtration rate; central volume V1 is larger in
males. Supports probability-of-target-attainment analysis against
free-trough or free-steady-state fCtrough/MIC and fCss/MIC targets.
|
|
Ceftriaxone
(Garot 2011)
|
Two-compartment IV-infusion population PK model for ceftriaxone in
critically ill adult ICU patients with sepsis, severe sepsis, or septic
shock (Garot 2011)
|
|
Ceftriaxone
(Tsai 2023)
|
Two-compartment population PK model for intravenous ceftriaxone in
Indigenous Australian adults with end-stage renal disease on
three-times-weekly intermittent high-flux hemodialysis, receiving a
novel 2 g three-times-weekly post-dialysis regimen. PK is parameterised
on unbound drug: the central state carries unbound ceftriaxone and an
explicit second-order albumin-binding exchange (k1 on / k2 off) against
a capacity bmax derived from serum albumin carries the bound drug, so
total and unbound plasma concentrations are both model outputs.
Clearance is replaced (not augmented) by a > 10-fold higher dialytic
clearance while a session is running, gated by the time-varying
RRT_HEMODIAL_ACTIVE covariate; interdialytic clearance falls with serum
bilirubin through an inverse-power relationship. Estimated with the
Pmetrics non-parametric adaptive grid (NPAG). Tsai 2023, n = 16
subjects, 122 total-and-unbound plasma samples.
|
|
Cefuroxime
(Alqahtani 2018)
|
Two-compartment IV population PK model for cefuroxime in adults
undergoing coronary artery bypass graft (CABG) surgery with
cardiopulmonary bypass (Alqahtani 2018), with a power-form
creatinine-clearance (Cockcroft-Gault) effect on clearance.
|
|
Cefuroxime
(Nielsen 2011)
|
In vitro (Streptococcus pyogenes M12 NCTC P1800). Semimechanistic PKPD
model of cefuroxime time-kill kinetics; two-stage bacterial life-cycle
(proliferating drug-sensitive S and non-growing drug-insensitive R) with
sigmoidal Emax killing of S via an effect compartment; first-order drug
elimination (ke set per in vitro kinetic-system flow rate) plus
drug-specific degradation kdeg. Parameter values are from the combined
static and dynamic estimation in Table 3.
|
|
Cefuroxime
(Viberg 2006)
|
Two-compartment population PK model for intravenous cefuroxime in adult
patients with bacterial infections and a wide range of renal function
(Viberg 2006); reciprocal serum cystatin C (1/CYSC) and body weight
enter as centred-linear covariates on clearance, and body weight enters
as a centred-linear covariate on the central volume of distribution.
|
|
Cefuroxime
axetil (Bulitta 2009)
|
Semiphysiological population PK model for oral cefuroxime axetil
(acetoxyethyl-ester prodrug of cefuroxime) in healthy adult male
volunteers after a standardized high-fat breakfast. Three drug
compartments (stomach -> intestine -> central): a saturable,
time-dependent Michaelis-Menten release from the stomach to the
intestine followed by first-order absorption from the intestine to the
central compartment, with one-compartment linear disposition. The
maximum gastric-release rate Vmax is modulated over time-past- meal by a
sigmoidal (Hill) function whose maximum fractional change Emax is
logit-transformed to range over [-1, 9]. Vmax and Km are estimated as
fractions of dose (Bulitta 2009 Results, ‘estimated and are reported as
fractions of the cefuroxime dose’), so the absolute Vmax (mg/h) and Km
(mg) scale linearly with the stomach-compartment dose amount. Parameter
values reproduced here are from the S-ADAPT importance-sampling Monte
Carlo EM fit (Bulitta 2009 Table 2, ‘S-ADAPT Population mean’ column),
which the authors recommend as the best parametric fit; NONMEM and NPAG
estimates are reported alongside in the paper for comparison.
|
|
Cemiplimab
(Yang 2021)
|
Two-compartment population PK model for cemiplimab (anti-PD-1 IgG4) with
time-varying clearance (sigmoid Emax) in adults with advanced solid
tumors including cutaneous squamous cell carcinoma (Yang 2021)
|
|
Cephalexin
rat (Padoin 1998)
|
Preclinical (rat, male Wistar). Two-compartment population PK model for
cephalexin after intra-arterial (IA) or oral (gastric-tube)
administration in rats, with first-order absorption and a competitive
drug-drug interaction from coadministered oral quinapril that lowers
cephalexin Ka (paper Table 4: 0.249 to 0.177 1/h; ~29% lower) and CL
(paper Table 4: 0.810 to 0.640 L/h/kg; ~21% lower) when both drugs are
given by the oral route. The paper parameterizes the disposition as {CL,
Vc, CL_D, Vss = Vc + Vp}; this implementation uses the canonical {CL,
Vc, Q, Vp} parameterization with the typical-value Vp derived as Vss -
Vc = 1.23 - 0.416 = 0.814 L/kg. Intra-arterial quinapril or
intra-arterial cephalexin produced no detectable interaction on
cephalexin elimination, attributed by the authors to the much higher
cephalexin renal concentrations outcompeting quinapril at the renal
anionic transport carrier (and to Ka being irrelevant for IA dosing).
|
|
Cephalothin
(Kuroda 2023)
|
Veterinary (Thoroughbred horse). Three-compartment population PK model
for the first-generation cephalosporin cephalothin (CET) in Thoroughbred
horses, fitted jointly to single-dose intramuscular (11 mg/kg bwt, 8
horses, this study) and single-dose intravenous (22 mg/kg bwt, 12
horses, Kuroda 2021 Equine Vet J 53:1239-1249) plasma data by nonlinear
mixed-effects modelling in Phoenix WinNonlin 8.3. Absorption from the
intramuscular site is first order (Kabs) with a bioavailability factor
F; disposition is a central compartment (V1) connected to a rapidly
equilibrating peripheral compartment (V2, distribution clearance CL2)
and a slowly equilibrating peripheral compartment (V3, distribution
clearance CL3), with elimination clearance CL from V1. Every structural
parameter is reported per kilogram of body weight in Kuroda 2023 Table
1, so the model scales each of them linearly with WT (exponent 1 fixed);
doses are therefore given in mg and concentrations come out in ug/mL.
The unbound concentration Cu = fu * Cc (fu = 0.8, taken from Ambrose
2007 and used unchanged by Kuroda 2023) is the quantity that drives the
paper’s PK/PD target, fT > MIC for 40% of the dosing interval, and
its Monte Carlo probability of target attainment. Kuroda 2023 states
that between-subject variability was described by an exponential model
on the structural parameters but reports NO variance estimates anywhere
(the Table 1 CV% column is bootstrap precision of the typical value, not
BSV), so every eta is encoded as fixed(0) and the model simulates
typical-value profiles unless the user supplies variances. The residual
model is combined proportional plus additive; the additive component was
estimated separately per route and the packaged value is the
intramuscular one (see the addSd comment for the intravenous value).
|
|
Certolizumab
(Wade 2015)
|
One-compartment population PK model with first-order SC absorption and
an additive baseline concentration for certolizumab pegol in adults with
Crohn’s disease (Wade 2015)
|
|
Cetagliptin
(Zhou 2024)
|
Two-compartment population PK model with first-order absorption and
saturable Michaelis-Menten elimination for cetagliptin, coupled by a
direct-effect sigmoid Emax model to plasma DPP-4 inhibition, in Chinese
patients with type 2 diabetes mellitus. Total bilirubin is a power
covariate on the peripheral volume of distribution.
|
|
Cetuximab
(Dirks 2008)
|
Two-compartment population PK model for intravenous cetuximab (anti-EGFR
chimeric IgG1) in adults with recurrent and/or metastatic squamous cell
carcinoma of the head and neck (SCCHN), with Michaelis-Menten
(target-mediated) elimination from the central compartment. Ideal body
weight and white blood cell count are linear-deviation covariates on
Vmax; total body weight is a linear-deviation covariate on V1 (Dirks
2008 J Clin Pharmacol; Chapter 3 of the Dirks 2010 UTHSC PhD
dissertation).
|
|
ChlorogenicAcid
rat (Chen 2024)
|
Preclinical (rat). Two-compartment intravenous pharmacokinetic model for
chlorogenic acid (CGA), one of eight constituents of guhong injection
(GHI) quantified in plasma, in male Sprague-Dawley rats subjected to 30
min left-anterior-descending ligation followed by 1 h reperfusion
(myocardial ischemia/reperfusion, MI/R) (Chen 2024). GHI was given as a
single tail-vein injection of 2.5, 5 or 10 mL/kg; the chlorogenic acid
dose is the GHI volume dose times its content in GHI (12.9 ug/mL),
i.e. 32.25 ug/kg, 64.5 ug/kg, 129 ug/kg. Disposition was fitted
separately in each dose group with Drug and Statistics (DAS) v3.2.6, so
V1, V2, CL1 and Q are selected from the covariate DOSE_GHI_MLKG rather
than through a dose-covariate function the authors did not fit.
Direct-effect sigmoid-Emax models link the chlorogenic acid plasma
concentration to the GHI-minus-model-group difference in creatine
kinase-MB (CK-MB), ischemia-modified albumin (IMA), cardiac troponin I
(cTn I) and alpha-hydroxybutyrate dehydrogenase (alpha-HBDH) (E = Emax *
C^gamma / (ED50^gamma + C^gamma); Tables 12, 13, 14, 15). Chen 2024
fitted a PK/PD model only for the analyte/biomarker/dose combinations
whose PLSR coefficient was negative, so the effect of an unfitted
combination is returned as zero rather than extrapolated. No
between-subject variability or residual error was reported; every
parameter is fixed at the published mean and the residual SDs are fixed
at zero.
|
|
Chloroquine
(Simpson 2013)
|
In vitro (P. falciparum). Sigmoid Emax inhibition model of chloroquine
effect on hypoxanthine uptake by clinical Plasmodium falciparum isolates
from the Thai-Myanmar border (Shoklo Malaria Research Unit, 1993-2005),
with pfmdr1 genotype covariate effects on EC50. The ‘subject’ in the
NLME framework is a parasite isolate (n=421 isolates with chloroquine
data). STIM_CHLOROQUINE_NM is the per-well drug concentration in the in
vitro hypoxanthine-uptake-inhibition assay; the model has no PK and no
time evolution. E0 and Emax are fixed per Simpson 2013 Table 3 footnote.
|
|
Ciclosporin
(Fanta 2007)
|
Three-compartment population PK model with first-order absorption for
ciclosporin in paediatric renal transplant candidates (Fanta 2007)
|
|
Ciclosporin
(Frobel 2013)
|
Parametric time-to-event (TTE) model for the first acute rejection (AR)
event after paediatric kidney transplantation in patients receiving oral
ciclosporin A (Neoral microemulsion). The baseline hazard is a
five-interval step-function exponential with break-points at 5, 8, 25,
and 100 days after transplantation. The final model carries no
covariates: 15 candidate covariates (including ciclosporin AUC, baseline
AUC, demographics, donor characteristics, HLA mismatches, dialysis time,
basiliximab induction) were screened by univariate testing, stepwise
covariate modelling, cross-validated SCM, and bootstrap-SCM, and none
reached statistical significance or clinical relevance. The model output
sur is the probability of remaining acute-rejection-free at
time t; hazard and cumhaz are exposed as
derived outputs.
|
|
Ciclosporin
(Ni 2013)
|
One-compartment first-order-absorption population PK model for oral
ciclosporin in Chinese children with aplastic anemia (Ni 2013)
|
|
Ciclosporin
(Press 2010)
|
Two-compartment population pharmacokinetic model for oral ciclosporin A
(Neoral) in adult kidney transplant recipients (Press 2010). Delayed
absorption is described by one transit compartment with the first-order
transit rate constant set equal to the absorption rate constant ka
(chain: depot -> transit1 -> central at common rate ka; mean
absorption time = (n+1)/ka with n = 1 transit compartment). Oral
bioavailability is FIXED at 0.5 (Methods ‘Structural model’). Apparent
clearance CL and apparent central volume of distribution Vc are
allometrically scaled to body weight at a 76 kg median reference with
theory-based exponents 0.75 on CL and 1.0 on Vc; the peripheral volume
Vp and intercompartmental clearance Q are not weight-scaled. Concomitant
high-dose oral prednisolone (PRED_DOSE >= 20 mg/day) is associated
with a 55% reduction in the absorption rate constant and a 22% reduction
in bioavailability (binary threshold-form covariate). Inter-occasion
variability on bioavailability is encoded here as IIV on lfdepot because
the source does not specify a per-subject occasion count for downstream
simulation (see vignette Assumptions and deviations).
|
|
Ciclosporin
(Wilhelm 2012)
|
Two-compartment population PK model for ciclosporin (CsA) in adults
undergoing haematopoietic allogeneic stem cell transplantation, with
first-order oral absorption + lag time and a 3 h intravenous infusion
directly into the central compartment (Wilhelm 2012). Twenty subjects on
routine fluconazole antimycotic prophylaxis (a CYP3A4 inhibitor) were
included; ciclosporin was assayed in whole blood by FPIA (AxSYM,
Abbott). Body weight, body surface area, co-medication with CYP3A4
inducers and co-medication with CYP3A4 inhibitors were tested but none
reached statistical or clinical significance, so no covariates are
retained in the final model. Inter-individual variability was reported
on every PK parameter (CL, Vc, Q, Vp, ka, F, tlag); the paper estimated
a full omega variance-covariance matrix but did not publish the
off-diagonal elements, so the packaged model uses diagonal IIVs only
(see vignette Assumptions and deviations).
|
|
Ciclosporin
(Willemze 2008)
|
Two-compartment population PK model for ciclosporin in children (aged
1.8-16.1 years) after allogeneic haematopoietic stem cell
transplantation (Willemze 2008). First-order absorption with lag time
and partial bioavailability for oral Neoral microemulsion; intravenous
Sandimmune is given as a 2-hour infusion to the central compartment. The
‘alternative parameterization’ (CL, Q, Vp, plus Ka, Vc, Tlag, F)
reported in Table 2 is used directly because it is the more
physiologically interpretable set. IIV on Vc was fixed to zero; IIVs on
Ka, CL, Q, Vp, Tlag, and F are estimated. Residual error is
proportional. No covariate (body weight, length, age, or estimated GFR)
was retained in the final model; those covariates are documented in
covariatesDataExcluded.
|
|
Ciclosporin
(Woillard 2014)
|
Two-compartment population PK model with Erlang-distributed transit
absorption (5 sequential delay compartments) and first-order elimination
for oral ciclosporin (CsA) in adult haematopoietic stem cell transplant
(HSCT) recipients on graft-versus-host disease prophylaxis (Woillard
2014, NONMEM final model). The apparent peripheral volume of
distribution Vp/F is fixed at 500 L; no covariate effects were retained
in the final model. Combined additive plus proportional residual error.
|
|
Cilazapril
pbpk (Luo 2024)
|
PBPK (semi-mechanistic, custom WinNonlin 8.1 implementation). Joint
cilazapril + cilazaprilat disposition in healthy adults and in liver
cirrhosis (Child-Pugh A/B/C). Cilazapril is an inactive ester prodrug
hydrolysed by hepatic CES1 to the active diacid cilazaprilat, which is
eliminated renally. Absorption is described by a directly reported
first-order ka rather than by a permeability. The semi-PBPK circuit is
stomach, three small-intestinal lumen segments (duodenum / jejunum /
ileum), the matching three gut-wall segments, portal vein, liver, kidney
and a two-compartment systemic compartment. Cirrhosis is applied by
switching the Child-Pugh-specific physiology of Table 1 (organ blood
flows, functional liver volume, GI transit rates, GFR, plasma-binding
protein concentrations, hepatic CES1 content) and rescaling CLint,
CLint,K, Peff and Vsys through Eq 1-6. Deterministic: the paper’s
virtual populations are uniform 80-120% draws on the drug parameters,
not lognormal random effects, so no IIV is encoded.
|
|
Cilostazol
(Yoo 2009)
|
Two-compartment population PK model for oral cilostazol with first-order
absorption from the depot and an absorption lag time, estimated in 104
healthy Korean male volunteers receiving a single 50- or 100-mg dose
(Yoo 2009). Apparent oral clearance CL/F is modulated by two
pharmacogenetic covariates entered in linear-fractional form: a
three-level CYP3A5 genotype (CYP3A51/1 = reference,
1/3 = -22.3%, 3/3 = -40.7%) and a three-level CYP2C19
metabolizer phenotype (extensive metabolizer = reference, intermediate =
-14.7%, poor = -27.2%). The final NONMEM ADVAN4/TRANS4 model places
exponential IIV on CL/F, Vc/F, Q/F and Vp/F with a partial OMEGA BLOCK
retaining the (Vp/F, CL/F), (Q/F, Vc/F) and (Vp/F, Q/F) covariances; the
remaining off-diagonals are held at zero. Residual error is combined
additive plus proportional.
|
|
Cipaglucosidase
(Hajjar 2018)
|
Two-compartment population PK model for IV cipaglucosidase alfa (ATB200;
recombinant human acid alpha-glucosidase / rhGAA) in adult patients with
Pompe disease (Hajjar 2018 ACCP poster, phase 1/2 study ATB200-02 /
NCT02675465). Disposition has parallel linear clearance (CL 0.569 L/h
per 70 kg) and Michaelis-Menten saturable elimination (Vmax 98.6 mg/h
per 70 kg, Km 62.4 mg/L) from the central compartment. Clearance and
volume parameters are allometrically scaled by total body weight
(exponent 0.75 fixed on all clearances, exponent 1 fixed on all volumes;
reference 70 kg). Co-administration of the pharmacological chaperone
miglustat (AT2221) reduces ATB200 linear CL: 130 mg AT2221 multiplies CL
by 0.738 (26.2% reduction), 260 mg AT2221 multiplies CL by 0.595 (40.5%
reduction); both effects are estimated as separate categorical covariate
multipliers (paper Methods ‘A categorical covariate effect model was
implemented’). Residual error is proportional (variance 0.0317, SD 0.178
on the linear-scale concentration).
|
|
Cipargamin
(Hien 2017)
|
Population PK / PD model of the spiroindolone antimalarial cipargamin
(KAE609) in Vietnamese adults with acute uncomplicated Plasmodium
falciparum malaria (Hien 2017). PK is a flexible transit-absorption
chain (NN = 3 transit compartments fixed) into a one-compartment
disposition model with fixed allometric body-weight scaling on CL/F and
V/F. Bioavailability is anchored at F = 100% with between-subject
variability. PD is a two-population parasite-clearance model: the
asexual parasite pool at enrolment is split by a sensitive fraction Fsen
and its complement (refractory subpopulation); sensitive parasites grow
at a fixed Kgrow (= ln(10)/48 = 0.0479 /h corresponding to 10-fold
multiplication per 48-h intraerythrocytic cycle) and are killed via an
Emax / EC50 saturable-effect term driven by cipargamin plasma
concentration; refractory parasites become active (join the sensitive
pool) at first-order rate Kact and are then subject to the same drug
kill. The typical Emax is dose-dependent per Hien 2017 Table 3 equation
7: Emax_i = TVEmax * (dose/10)^COVdose_Emax. Structural PK estimates are
the Table 3 population values referenced to a 59 kg typical patient
receiving 10 mg cipargamin. Reproduces the individually predicted
parasite clearance profiles in Hien 2017 Fig 3.
|
|
Ciprofloxacin
(Schaefer 1996)
|
Two-compartment population PK model for intravenous and oral
ciprofloxacin in 10 pediatric cystic fibrosis patients aged 6-16 years
(Schaefer 1996). First-order absorption from a depot, two disposition
compartments, plus a cumulative urine compartment driven by an
independently estimated renal clearance. Total clearance is a
linear-with-intercept function of body weight (CL = 8.8 + 0.396 * WT,
L/h), and central / peripheral volumes are directly proportional to body
weight with slopes 0.698 and 1.3 L/kg respectively. Intercompartmental
clearance, absorption rate, renal clearance, and oral bioavailability
are weight-independent. IIV is retained on CL, Vc, and Vp only; residual
error is proportional. Calibrated to the study weight range (15-42 kg);
extrapolation beyond is not appropriate per the source authors.
|
|
Ciprofloxacin
(Thuo 2011)
|
One-compartment population PK model with first-order absorption and
absorption lag for oral ciprofloxacin in Kenyan children with severe
malnutrition (Thuo 2011). Apparent CL and apparent Vc are allometrically
scaled to body weight (exponents 0.75 and 1) and modified by linear
deviations from a serum sodium reference of 136 mmol/L; apparent CL is
further reduced by 28.3% in the paper-defined high-mortality-risk
stratum.
|
|
Ciprofloxacin
(Zhao 2014)
|
Two-compartment population PK model with first-order elimination for
intravenous ciprofloxacin in neonates and young infants less than three
months of age (Zhao 2014). Central and peripheral volumes (V1, V2) scale
allometrically with current body weight (fixed exponent 1, reference
1.955 kg); clearance (CL) and inter-compartmental clearance (Q) scale
with current body weight at a fixed exponent of 0.75. CL is further
multiplied by a renal-maturation factor in gestational age and postnatal
age (F_age), a renal-function factor in serum creatinine (RF =
exp((CREAT - 42 umol/L) * theta7)), and a fractional reduction (factor
0.708) when inotropic / vasoactive agents are coadministered. IIV is
reported on V1, V2, and CL as %CV on an exponential model. Residual
error is proportional. Inter-occasion variability on CL (16.4%CV)
reported by Zhao 2014 is not encoded structurally here – the source
paper does not define an operational occasion mapping for the
model-library use case; users who need IOV can add an OCC indicator and
per-occasion eta downstream.
|
|
Ciprofloxacin
colistin invitro (Zhao 2024)
|
In vitro (Escherichia coli; one clinical urinary isolate C47 plus MG1655
wild type LM347 and its isogenic gyrA1/marR mutants LM378 and LM421).
Semi-mechanistic PK/PD model of static-concentration time-kill for
ciprofloxacin and colistin alone and in combination. Five pre-existing
subpopulations (the 2x2 ciprofloxacin/colistin susceptible-resistant
grid plus a pre-existing resting subpopulation present only in C47),
each cycling between a growing S state, a density-driven resting R state
and a transient ciprofloxacin-induced non-colony-forming Nc state.
Killing is additive across drugs (subpopulation synergy) with
concentration-independent interaction factors shifting the ciprofloxacin
and colistin EC50 in combination. Colistin loss to labware is described
by an Emax free-fraction model at time zero plus saturable binding
kinetics during the experiment; ciprofloxacin is held at its nominal
concentration. Sibling models: Zhao_2024_ciprofloxacin_colistin_plasma,
Zhao_2024_ciprofloxacin_colistin_kidney.
|
|
Ciprofloxacin
colistin kidney (Zhao 2024)
|
Semi-mechanistic PK/PD (QSP) model predicting Escherichia coli killing
in the kidney interstitium (pyelonephritis) by intravenous ciprofloxacin
and colistimethate sodium, alone and in combination. The in vitro
time-kill PD model of Zhao 2024 (five pre-existing subpopulations on the
2x2 ciprofloxacin/colistin susceptible-resistant grid plus a
pre-existing resting subpopulation, additive killing with EC50-shifting
interaction factors) is driven by UNBOUND KIDNEY INTERSTITIAL
concentrations, predicted by appending a lumped kidney
tissue-plus-tubule compartment per species to two published
critically-ill population PK models: a two-compartment model for
ciprofloxacin (Khachman 2011) and the CMS1/CMS2 prodrug plus
formed-colistin model of Kristoffersson 2020. Kidney concentrations are
predicted about 10-fold (ciprofloxacin) and 150-fold (colistin) higher
than plasma, so effective killing is reached at much lower doses and
much higher MICs than for a bloodstream infection. Colistin EC50 is
rescaled to the simulated strain MIC. Sibling models:
Zhao_2024_ciprofloxacin_colistin_invitro (the underlying time-kill fit)
and Zhao_2024_ciprofloxacin_colistin_plasma (the same model driven by
unbound plasma concentrations).
|
|
Ciprofloxacin
colistin plasma (Zhao 2024)
|
Semi-mechanistic PK/PD (QSP) model predicting Escherichia coli killing
in human plasma (bloodstream infection) by intravenous ciprofloxacin and
colistimethate sodium, alone and in combination. The in vitro time-kill
PD model of Zhao 2024 (five pre-existing subpopulations on the 2x2
ciprofloxacin/colistin susceptible-resistant grid plus a pre-existing
resting subpopulation, additive killing with EC50-shifting interaction
factors) is driven by unbound plasma concentrations from two published
critically-ill population PK models: a two-compartment model for
ciprofloxacin (Khachman 2011) and the CMS1/CMS2 prodrug plus
formed-colistin model of Kristoffersson 2020. Colistin EC50 is rescaled
to the simulated strain MIC. Sibling models:
Zhao_2024_ciprofloxacin_colistin_invitro (the underlying time-kill fit)
and Zhao_2024_ciprofloxacin_colistin_kidney (the same model driven by
kidney interstitial concentrations).
|
|
Cisplatin
(Boer 2015)
|
Two-compartment population PK model for long-term circulating platinum
(Pt) decay after cisplatin-based chemotherapy in adult testicular cancer
survivors followed 1-13 years post-treatment (Boer 2015). Dose is the
cumulative cisplatin dose expressed as elemental Pt in mg (multiply
cumulative cisplatin in mg by 0.6502, the Pt/cisplatin mass ratio
195.08/300.05). An apparent bioavailability F1 (fdepot) accounts for the
fraction of the administered Pt remaining in the body after the rapid
pre-measurement urinary-excretion phase. Pt is assumed to be cleared
solely via urine.
|
|
Cisplatin
(Royer 2011)
|
Four-compartment population PK model for platinum after cisplatin
intraperitoneal perioperative chemotherapy (PIPC), with or without
intraperitoneal epinephrine, in adult women with recurrent epithelial
ovarian cancer (Royer 2011). Compartments are peritoneum (paper-
mechanistic IP dosing / sampling site), central (serum ultrafilterable
platinum), peripheral1, and bound (paper-mechanistic protein-bound
plasma platinum). Ultrafiltered platinum transfers peritoneum ->
central at rate IPCL * (peritoneum / IPV), distributes central <->
peripheral at rate constants k12 = 0.632 /h and k21 = 0.0425 /h (paper
notation k23 / k32), and is eliminated from central at rate CL * Cc.
Protein-bound platinum is formed from central via a Michaelis-Menten
binding term modulated by baseline serum total protein (Vmax * Cc / (KM
+ Cc) * TPRO, per Supplementary Data S1) and eliminated first-order at
rate kB. Epinephrine decreases IPCL by 53.1% and increases central
volume V by 80.5% (multiplicative fractional coefficients on the typical
values). Ultrafiltered and protein-bound platinum are fitted
simultaneously to 316 peritoneum + 577 unbound plasma + 577 bound plasma
observations from 55 patients (26 with epinephrine, 29 without).
|
|
Cisplatin
(Urien 2004)
|
Integrated two-compartment population PK model for ultrafilterable
(unbound) plasma platinum coupled to a metabolite compartment
representing irreversibly protein-bound plasma platinum (Urien 2004
BJCP). Fitted simultaneously to 396 unbound and 477 total plasma
platinum concentration-time observations from 43 adult cancer patients
receiving 30-min cisplatin infusions. Unbound clearance depends on body
surface area and Cockcroft-Gault creatinine clearance; the unbound
central volume depends on BSA. The bound formation parameter fm/Vm
depends on dose per m^2 and total serum protein; its BSA and
creatinine-clearance exponents are fixed at the negatives of the unbound
CL exponents so the formation flux (fm/Vm)CLCc is net BSA- and
CLCr-neutral. The apparent metabolite volume Vm is not separately
identifiable; the composite parameters fm/Vm (1/L) and CLm0/Vm (1/h)
absorb Vm and the bound state is carried in concentration units.
|
|
Cladribine
(Savic 2017)
|
Population PK model for cladribine (CdA) in patients with
relapsing-remitting multiple sclerosis (Savic 2017): three-compartment
disposition with first-order oral absorption, separate fasted vs fed (or
unknown food-state) absorption parameters, renal clearance proportional
to Cockcroft-Gault creatinine clearance, and a multiplicative
non-renal-clearance effect of concomitant subcutaneous interferon
beta-1a coadministration.
|
|
Clarithromycin
(Abduljalil 2009)
|
Semimechanistic population pharmacokinetic model for oral clarithromycin
and its 14-(R)-hydroxy metabolite during repeated b.i.d. administration
(Abduljalil 2009): a single-phase Weibull absorption (kw, lambda) into a
one-compartment parent disposition with linear distribution and a parent
clearance that is partly inhibited by the parent’s own concentration in
a hypothetical effect-style inhibition compartment (Imax form with FCLp
= fraction of CLp not subject to inhibition and IC50 =
inhibition-compartment concentration giving 50% of maximum inhibition);
all parent metabolic clearance feeds a parallel one-compartment
metabolite disposition (14-OH-clarithromycin). Body weight enters
allometrically with fixed exponents 0.75 on CL and 1.0 on V (parent and
metabolite), reference 70 kg.
|
|
Clazakizumab
(Muthukrishnan 2025)
|
Population PK and PK-PD model for the anti-interleukin-6 monoclonal
antibody clazakizumab given as a 3-minute IV bolus to adults with
end-stage kidney disease undergoing maintenance dialysis (POSIBIL 6 ESKD
phase 2b, NCT05485961; Muthukrishnan 2025). Two-compartment linear PK
with allometric weight scaling on CL and V1 and a baseline free IL-6
covariate on CL; sequential-fit indirect-response inhibition of hs-CRP
zero-order production (kin) with Imax fixed to 1, an estimated Hill
coefficient, and a Manly-transformed IIV on IC50. Baseline hs-CRP enters
kin as a power covariate so the pre-dose steady state E0 = kin/kout
tracks the observed baseline distribution.
|
|
Clesrovimab
(Hu 2026)
|
Two-compartment population PK model for clesrovimab in preterm and
full-term infants (Hu 2026)
|
|
Clindamycin
(Bouazza 2012)
|
One-compartment population PK model for clindamycin administered orally
(immediate-release tablet) or intravenously (20-min infusion) in 50
adult patients (ages 18-93 y, body weight 23-133 kg) treated for bone
and joint infections (Bouazza 2012). First-order absorption for oral
dosing with estimated absolute bioavailability F = 0.876; apparent
clearance CL/F = 15.2 L/h at 70 kg, with an estimated (non-allometric)
body-weight exponent of 0.497 on CL. Apparent volume V/F = 66.2 L and
absorption rate Ka = 0.967 1/h, neither carrying retained
interindividual variability. IIV is retained only on CL/F (omega =
0.39). Residual variability is proportional (sigma = 0.38). Rifampicin
co-administration was screened but not retained in the final model (see
covariatesDataExcluded).
|
|
Clindamycin
(Muller 2010)
|
Three-compartment intravenous popPK model for clindamycin in pregnant
women during the peripartum period (Muller 2010). Fit to 175 maternal
venous serum concentrations from 7 women receiving either 600 mg over 20
min every 6 h (endocarditis prophylaxis) or 900 mg over 30 min every 8 h
(group B streptococcal disease prophylaxis). No covariates were retained
in the final model; demographic and laboratory screens (maternal age,
gestational age, BMI, weight, edema, temperature, creatinine, ALP, AST,
ALT, mode of delivery) are documented in covariatesDataExcluded.
Proportional residual error with a per-subject log-normal scaling eta on
the residual error magnitude (NONMEM omega-sigma interaction with an
extra ETA on epsilon).
|
|
Clindamycin
(Smith 2017)
|
One-compartment population PK model for intravenous clindamycin in obese
and nonobese children, with allometric total body weight on CL and V,
sigmoidal Hill maturation on CL by postmenstrual age, and power effects
of serum albumin and alpha-1 acid glycoprotein on V (Smith 2017).
|
|
Clomethiazole
(Zingmark 2003)
|
Two-compartment intravenous population PK model for clomethiazole
(Zingmark 2003) in 774 adult acute-stroke patients dosed with a
three-phase IV infusion of clomethiazole edisilate over 24 h (6 mg/kg
over 0.25 h then 31 mg/kg over 0.25-8 h then 31 mg/kg over 8-24 h, total
68 mg/kg edisilate). The structural model is parameterized in CL/V1/Q/V2
with body weight as a linear covariate on V1 and V2 and a
piecewise-linear covariate on CL (linear up to WT50 = 100 kg, constant
above) plus a multiplicative effect of concomitant liver-enzyme-
inducing drugs (carbamazepine, phenytoin, rifampicin) on CL. IIV uses
parameter-specific etas combined with a shared eta common to all four PK
parameters (paper text: attributed to clomethiazole adsorption to the
infusion tubing) – the joint structure induces a single pairwise
correlation among the structural parameters. The paper also reports a
proportional-odds sedation-score PD model with a sensitive/non-sensitive
mixture component; that PD layer is not encoded here – it requires a
NONMEM MIXNUM-style mixture construct that is not naturally expressed in
nlmixr2 / rxode2 model files, and the NIH stroke-scale covariate is not
yet in the canonical covariate register. See the validation vignette’s
Assumptions and deviations section.
|
|
Clonazepam
pediatric (Yukawa 2002)
|
Steady-state population PK model for clonazepam relative clearance
(CL/F) in 137 Japanese pediatric and adult epileptic patients (Yukawa
2002 Table III row 4). CL/F is a body-weight power function with a
3-tier drug-interaction factor for concomitant antiepileptic drugs
(monotherapy, +1 AED (CBZ or VPA), +>=2 AEDs).
|
|
Clonidine
(Kleiber 2017)
|
One-compartment population PK model for intravenous clonidine in
critically ill neonates and children on venovenous or venoarterial
extracorporeal membrane oxygenation (ECMO) with concomitant continuous
venovenous hemofiltration (CVVH). Central compartment only with IV bolus
and IV infusion dosing (no absorption). Clearance carries the standard
allometric fixed exponent 0.75 on body weight (reference 70 kg), a
Hill-type maturation function of postnatal age (steep exponent 3.02 and
T50 = 1.13 weeks – ~70% of mature clearance by 10 days of PNA), and a
multiplicative diuretic-use effect (CL x 0.659 when any diuretic is
active). Volume of distribution carries the standard fixed allometric
exponent 1 on body weight and a sigmoidal Emax effect of time-on-ECMO
(Emax = +55%, T50 = 51.7 h, Hill exponent 18.5 – effectively a step
increase reached by 72 h on ECMO). Residual error is proportional only.
|
|
Clopidogrel
(Danielak 2017)
|
Joint parent-metabolite population PK model for oral clopidogrel and its
active thiol H4 metabolite (the antiplatelet-active diastereomer) in
adult Caucasian patients undergoing elective coronarography or
percutaneous coronary intervention on chronic clopidogrel 75 mg/day
(Danielak 2017). Clopidogrel is described by a one-compartment model
with first-order absorption (rate constant ka = source k12) and
first-order elimination (CL/F = source CL/F, V/F = source V2/F). The H4
metabolite is described by a one-compartment model with irreversible
first-order formation from clopidogrel central at the rate FM * CL/F *
(clopidogrel central / Vc) and first-order elimination (CL_h4/F = source
Q2/F, V_h4/F = source V3/F). FM was constrained to <= 20% in the
source fit because clopidogrel undergoes extensive first-pass metabolism
to the inactive carboxylic acid (the competing CES1 pathway accounts for
~85% of the absorbed dose); the final estimate is FM = 4.5%. H4 plasma
concentrations were assayed after bromo-3’-methoxyacetophenone
derivatisation of the labile thiol and were adjusted to the mass
equivalent of clopidogrel, so the parent <-> H4 flux carries 1:1
molar / mass-equivalent stoichiometry. Inter-individual variability is
reported on ka, V/F, CL/F, and FM with a covariance between ka and V/F.
The only retained covariate is CYP2C19*2 carriage on FM
(linear-deviation effect, e_cyp2c19_s2_fm = -0.45); carriers convert 45%
less of the absorbed dose to the active H4 metabolite. Bioavailability F
was assumed to be unity (typical value 1, not estimated because no IV
clopidogrel data exist). Residual error is proportional on the
linear-concentration scale for both observed analytes; M3-method
handling was used for samples below the quantitation limit (0.25 ng/mL
for both clopidogrel and H4).
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|
Clopidogrel
(Jung 2024)
|
Joint parent-plus-two-metabolite population PK model for oral
clopidogrel with a sequentially-fitted platelet-reactivity (PRU)
turnover PD submodel, in healthy Korean male adults stratified by
CYP2C19 metabolizer phenotype (Jung 2024). A hepatic first-pass
compartment (liver) sits between the depot and the central
compartment; all absorbed parent drug is assumed to be metabolized in
the liver, so the parent’s only elimination pathway is the hepatic
metabolic clearance CLc. Clopidogrel itself is described by a
two-compartment model (central + peripheral1)
exchanging with the liver at Qc and with the periphery at Qp; the
hepatic volume was set equal to the central volume (VH = Vc) because the
two were not separately identifiable. The hepatic metabolic flux CLc *
(liver / VH) is split three ways by two nested logit-scale fractions:
fm1 * fm2 to the active thiol metabolite clopidogrel H4 (one
compartment, central_h4), (1 - fm1) * fm2 to the inactive
clopidogrel carboxylic acid (two compartments,
central_cloca + peripheral1_cloca), and 1 -
fm2 to unmeasured other metabolites. Each metabolite formation flux
carries a molar-mass ratio scaling factor (1.106 for H4, 0.956 for the
carboxylic acid) so that a mass-unit parent flux produces the correct
mass-unit metabolite amount. CYP2C19 phenotype is the only retained
covariate and acts as an additive shift on the logit scale of both fm1
and fm2, reducing the active-metabolite fraction from 0.120 in extensive
metabolizers to 0.071 in intermediate and 0.034 in poor metabolizers.
The PD endpoint is the P2Y12 reaction unit (PRU) from the VerifyNow
P2Y12 assay, modeled as a turnover pool in which clopidogrel H4
stimulates the fractional turnover rate Kout through a sigmoid Emax
function; the drug-free baseline is Kin / Kout = 212.67 PRU.
Inter-individual variability is reported on Vc, CLc, Qc (with a
correlation between Vc and CLc), fm1, fm2, Vp2, CLm2, Kin, and Emax.
Residual error is proportional for all three analytes and additive for
PRU. PK and PD were fitted sequentially: all PK parameters were fixed to
their final PK-model estimates before the PD parameters were estimated.
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|
Clopidogrel
(Pejcic 2024)
|
Joint semi-physiological population PK model for oral clopidogrel (CLO)
and its inactive carboxylic acid metabolite (CLO-CA) in healthy
Caucasian adults, pooled from two 2-way crossover bioequivalence studies
of 150 mg (2 x 75 mg) single oral doses (Pejcic 2024). Absorption is an
Erlang-type transit chain (depot -> transit1 -> transit2 ->
liver) with a single transit rate constant Ktr = 3 / MTT. The first-pass
effect is represented by a hepatic compartment (Vh = 1.5 L/70 kg, liver
plasma flow Qh = 50 L/h, both fixed) that receives the whole absorbed
dose and also receives the parent returning from the systemic
circulation at CLP, so that all parent drug is ultimately metabolised
there. Hepatic outflow Qh/Vh is partitioned into three branches whose
fractions sum to one: FP to systemic clopidogrel, FiaM to CLO-CA, and
FaM to the active thiol CLO-TH (a sink; CLO-TH concentrations were not
measured). The fractions use the source’s softmax reparameterisation
FiaM = FR1 / (1 + FR1 + FR2), FaM = FR2 / (1 + FR1 + FR2), FP = 1 / (1 +
FR1 + FR2) with FaM fixed at 12%, giving FiaM = 87.27% (Study 1) and
86.87% (Study 2). A molecular-weight factor of 0.9565 (307.80 / 321.82)
scales the CLO-CA formation flux. Clopidogrel is one-compartment; CLO-CA
is two-compartment. Body weight is applied allometrically (exponent 0.75
on clearances, 1 on volumes) to a 70 kg reference. MTT, the
generic-product relative bioavailability, FR1, the IIV and IOV
magnitudes and the proportional residual error are all study- specific,
selected by the STUDY_CLO_BE2 indicator; inter-occasion variability on
bioavailability and MTT reflects the crossover design.
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|
Clozapine
(Li 2012)
|
One-compartment parent-plus-metabolite population PK model for oral
clozapine and its primary active metabolite norclozapine
(N-desmethylclozapine) in 162 Chinese adult inpatients (74 male, 88
female; 35.5 +/- 10.6 years) with refractory schizophrenia on
maintenance oral clozapine therapy (Li 2012). First-order absorption (Ka
fixed at 1.3 1/h from prior rich-data clozapine PK studies) into a
single central compartment with first-order elimination; a fixed
fraction (KF = 0.66) of the absorbed clozapine dose is converted in the
parent central compartment to norclozapine and feeds a separate
one-compartment metabolite compartment with its own apparent clearance
and apparent volume. Two binary covariates were retained in the final
forward-and-backward-selected model: current-smoker status increases
apparent clearance of both species (clozapine by 45%, norclozapine by
54.3%), and male sex increases apparent clearance of both species
(clozapine by 20.8%, norclozapine by 24.2%); the typical values reported
in Table 2 are for the female-nonsmoker reference stratum. A combined
additive-plus-proportional residual error model is reported separately
for clozapine and norclozapine. The model was internally validated using
normalized prediction distribution errors (NPDE).
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|
Colchicine
mouse pbpk (Saleh 2023)
|
PBPK (LeiCNS-PK3.0 CNS physiologically-based model, mouse version).
Preclinical (mouse, NMRI). Nine-compartment CNS PBPK model predicting
unbound colchicine concentrations in brain extracellular fluid (brain
ECF) after a single 1.5 mg/kg intravenous dose. The CNS structure is the
mouse re-parameterisation of LeiCNS-PK3.0: brain microvasculature
(brain_vascular), brain ECF, a phospholipid brain-cell-membrane binding
compartment (brain_cell_membrane), brain intracellular fluid
(brain_icf), lysosomes (brain_lysosome), and the four CSF compartments
(lateral ventricles, third + fourth ventricles, cisterna magna,
subarachnoid space) draining in series back to plasma. Transport across
the BBB and BCSFB is the sum of a paracellular clearance (Qp, charged +
neutral drug) and a transcellular clearance (Qt, neutral drug only,
scaled by pH-dependent neutral fractions PHF and by asymmetry factors AF
that encode active transport). Every CNS parameter is fixed to mouse
physiology (Table III) or derived from the drug’s physicochemical
properties (Table I); none was fitted here. The BBB asymmetry factors
are back-calculated from Kp,uu,BBB = 0.14 (taken from ref [20]; Table
V). The plasma PK model is the empirical two-compartment model of Table
IV (in-house NONMEM fit) and acts purely as a forcing function: brain
uptake does not deplete plasma, exactly as published.
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|
Colistin
(Jacobs 2016)
|
Two-state parent-metabolite population PK model for colistimethate
sodium (CMS, prodrug) and colistin (active polymyxin) in critically ill
ICU patients with acute renal failure requiring intermittent
hemodialysis (n=8). One compartment each for CMS and colistin. CMS renal
clearance is structurally fixed at 0 (anuric HD population); the
estimated CMS clearance is therefore nonrenal (CL_NRCMS). Colistin
disposition is parameterised in apparent units (V_col/f_m and
CL_col/f_m) because the fraction f_m of nonrenally cleared CMS that
becomes colistin is not separately identifiable from plasma data.
Hemodialysis clearances of CMS (90 mL/min) and colistin (137 mL/min) are
fixed experimental constants from Marchand 2010 (ref 7 of Jacobs 2016)
and are gated on/off by the time-varying RRT_HEMODIAL_ACTIVE covariate;
PK sampling in the source study was conducted between HD sessions, so
RRT_HEMODIAL_ACTIVE = 0 over the model-fit data.
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|
Colistin
(Karaiskos 2015)
|
Population PK model for colistimethate sodium (CMS, prodrug) and
colistin (active polymyxin formed by in vivo hydrolysis) in critically
ill adults after a 9 MU CMS loading dose. CMS distributes through four
compartments representing two states of the prodrug (CMS1 = more fully
sulfomethylated, CMS2 = partially sulfomethylated derivatives); each
state has central and peripheral compartments sharing volumes Vc and Vp
but distinct inter-compartmental clearances Q1 and Q2. The same nonrenal
clearance CL_NR drives the first-order hydrolysis CMS1 -> CMS2 (in
both central and peripheral, with the same rate constant) and CMS2 ->
colistin (central only); CMS1 and CMS2 central compartments are
additionally cleared by renal clearance proportional to creatinine
clearance. Colistin disposition follows a one-compartment model with
apparent clearance and volume (CL/fm, V/fm) scaled to the unknown
fraction of administered CMS converted to colistin. Measured
colistimethate concentration is the sum of CMS1 and CMS2 central
concentrations.
|
|
Colistin
(Lee 2013)
|
One-compartment population PK model of colistin in adult burn-ICU
patients receiving colistimethate sodium (CMS) as a 30-minute IV
infusion every 12 hours, with first-order CMS-to-colistin conversion
(Lee 2013). Apparent CL and Vc of colistin are scaled inversely by the
relative fraction of CMS converted to colistin (RFM = 1 - theta4 *
(CRCL/128)); the CMS-to-colistin turnover rate constant TR is reduced in
patients with clinically-evident peripheral edema (TR = theta3 - theta5
* DIS_EDEMA).
|
|
Colistin
(Mohamed 2012)
|
Two-compartment population PK model for colistin methanesulfonate (CMS,
prodrug) plus a one-compartment apparent model for colistin (formed
metabolite) in critically ill patients, with concentration-dependent
unbound fraction of colistin A and a semimechanistic Pseudomonas
aeruginosa bacterial-kill PKPD (susceptible / resting compartments from
Bulitta 2010)
|
|
Colistin
(Plachouras 2009)
|
Two-compartment population PK model for colistin methanesulfonate (CMS,
prodrug) and one-compartment model for the formed colistin (active
metabolite) in critically ill adults receiving 3 MU q8h IV CMS for
multidrug-resistant Gram-negative infections (Plachouras 2009). Colistin
metabolite parameters are apparent values scaled by the unknown fraction
(fm) of CMS that forms colistin (CL_col is CL/fm; Vc_col is V/fm).
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|
Colistin
(Rodjun 2023)
|
Population PK model for colistimethate sodium (CMS, the inactive
prodrug) and formed colistin (the active polymyxin) in critically ill
adults, as encoded by Rodjun 2023 for Monte Carlo
probability-of-target-attainment simulation against carbapenem-,
multidrug- and colistin-resistant Acinetobacter baumannii. CMS follows a
two-compartment model with an intravenous 30-min infusion; its total
clearance is the sum of a renal component proportional to creatinine
clearance and a non-renal component. The entire non-renal CMS clearance
is the formation pathway for colistin, which then follows a
one-compartment model whose total clearance is likewise the sum of a
CrCL-proportional renal component and a non-renal component. Unbound
colistin concentration is returned as Ccu_col using the reported unbound
fraction of 0.49, because the paper’s PK/PD target is the unbound AUC
ratio fAUC/MIC >= 7.4.
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|
Concizumab
(Yuan 2019)
|
QSP. Systems PK/PD model for concizumab (humanized anti-TFPI IgG4)
describing binding to both membrane-bound TFPI (mTFPI; non-linear
clearance via receptor-mediated endocytosis) and soluble TFPI (sTFPI;
linear clearance via FcRn-recycled pinocytosis) in a minimal
physiologically-based PK framework with two nested endothelial endosome
compartments. Parameter values for 70 kg adult humans (Yuan 2019 Tables
1-2); the paper also tabulates monkey and rabbit parameter sets.
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|
ConestatAlfa
(Farrell 2013)
|
One-compartment population PK model with Michaelis-Menten elimination
for intravenous recombinant human C1 inhibitor (rhC1INH; conestat alfa;
Ruconest) in healthy volunteers and adolescent / adult patients with
hereditary angioedema (Farrell 2013). Total functional plasma C1INH is
modelled as the sum of an estimated endogenous baseline (separate
baselines for healthy volunteers and HAE patients) plus exogenously
administered rhC1INH, with the endogenous production rate derived from
the Michaelis-Menten elimination at baseline so the no-dose steady state
is preserved. Allometric power scaling of central volume on body weight
(exponent 0.612).
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|
Corifollitropin
alfa (Zandvliet 2016)
|
One-compartment subcutaneous population pharmacokinetic model for
corifollitropin alfa (a long-acting recombinant gonadotrophin) in women
undergoing controlled ovarian stimulation (Zandvliet 2016). Pooled
analysis of 2557 evaluable women from five phase II and III trials
(single SC doses of 60-180 ug). Corifollitropin alfa is absorbed
first-order from a subcutaneous depot into a one- compartment central
pool with first-order elimination; body weight is the major covariate,
with allometric (WT/60)^exponent power effects on apparent clearance and
apparent volume. Apparent bioavailability is modulated by body-mass
index, race (Asian and Black indicators vs Caucasian reference), and
remains anchored at F = 1. The model jointly describes total FSH
immunoreactivity by adding an endogenous follicle stimulating hormone
(FSH) compartment whose pre-dose steady-state baseline is FSHbaseline
and whose synthesis is set to zero from corifollitropin administration
onwards (per the paper’s structural model). Total FSH immunoreactivity
(IU/L) equals SCALE * corifollitropin concentration (ng/mL) plus the
endogenous FSH compartment value, where SCALE is fixed at 6.11 IU/L per
ng/mL from an upstream analysis. Trial- specific multiplicative effects
on the FSH immunoreactivity prediction (1.26 for trial 06029 and 1.12
for trial 38825) are exposed via binary study indicators that default to
zero for general simulation use.
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|
Cotadutide
qsp (Bosch 2024)
|
QSP. 4GI quantitative systems pharmacology model (glucose, insulin,
GLP-1, glucagon, GIP) coupled to a one-compartment first-order-
absorption cotadutide PK model in adults with type 2 diabetes mellitus
(Bosch 2024). Cotadutide is a dual GLP-1/glucagon receptor agonist; in
vivo EC50s for cotadutide on each receptor are derived from the in vitro
EC50 ratio vs the endogenous ligand (Eq 1). The drug’s
free-fraction-corrected central concentration drives four saturable Emax
effects on the system: (1) stimulation of glucose- dependent insulin
secretion via GLP-1R, (2) inhibition of meal- glucose absorption via
GLP-1R, (3) inhibition of glucagon production via GLP-1R, and (4)
stimulation of glucose production via GCGR. A fifth Emax inhibits
endogenous active GLP-1 production (Eq 3). The placebo arm’s
lifestyle-change effect on fasting plasma glucose is modelled as an
inverse Bateman attenuation of endogenous glucose production (Eq 2).
Cotadutide PK structure and typical values are fixed from the upstream
popPK analysis of Guan et al. 2022 (KA=0.343 1/h, CL=1.04 L/h, V=18.7
L). All 4GI system- specific disposition and effect parameters are fixed
from the upstream 4GI model of Bosch et al. 2022; meal-effect, baseline,
lifestyle and EMAX_5/EC50_5S parameters were re-estimated against the
cotadutide MAD/Ph2a dataset (NCT02548585; n=51, T2DM). Five outputs:
plasma glucose (mmol/L), insulin (pmol/L), GLP-1 (pmol/L), glucagon
(pmol/L) and GIP (pmol/L), each with proportional residual error.
Individual fasting plasma glucose enters via the FPG covariate; meal
glucose enters as dosing events on the glucose-gut compartment. Defaults
are T2DM; healthy-volunteer parameter set from Bosch 2022 is given in
source-trace comments. No IIV is encoded (sequential model fit with
individual PK / glucose- baseline inputs from Guan 2022 and the observed
dataset).
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|
Crisantaspase
(Sassen 2017)
|
Two-compartment population PK model for intravenous Erwinia asparaginase
(crisantaspase; Erwinase) in pediatric acute lymphoblastic leukemia
patients, with allometric scaling on clearance and volumes and a higher
first-month clearance (Sassen 2017).
|
|
CrisprCas9
human (Desai 2024)
|
QSP. Translational quantitative systems pharmacology platform for in
vivo CRISPR-Cas9 gene editing delivered by lipid nanoparticle (LNP),
covering the whole-body disposition of all three components of the
therapy - the LNP delivery vehicle, the single guide RNA (sgRNA) and the
Cas9 messenger RNA (mRNA) - plus intracellular Cas9 translation and
ribonucleoprotein (RNP) assembly (Desai 2024). The PK layer is a
minimal-PBPK structure with plasma, lymph, a three-region liver
(vascular / endosomal / interstitial-cellular), kidney and a lumped
remainder tissue; the kidney compartment is present for LNP and sgRNA
but absent for mRNA, which is too large to be renally cleared. LNP
additionally undergoes opsonin bio-corona formation (kass / kdis),
phagocytosis into the mononuclear phagocyte system (kint) and
LDL-receptor-mediated endocytosis (kon,LNP / koff,LNP) with receptor
recycling. This is the clinical arm of the platform (step 4 of the
paper’s four-step workflow), scaled to human physiology and re-estimated
against NTLA-2001 LNP plasma PK and serum transthyretin from the
first-in-human study (0.1-1 mg/kg total RNA by 2 h IV infusion). The
pharmacodynamic layer is an indirect-response model in which the liver
ribonucleoprotein concentration inhibits TTR production; unlike the NHP
arm the human TTR model carries no Hill coefficient. Sibling
extractions: Desai_2024_crisprCas9_mouse and Desai_2024_crisprCas9_nhp.
|
|
CrisprCas9
mouse (Desai 2024)
|
Preclinical (mouse). QSP. Translational quantitative systems
pharmacology platform for in vivo CRISPR-Cas9 gene editing delivered by
lipid nanoparticle (LNP), covering the whole-body disposition of all
three components of the therapy - the LNP delivery vehicle, the single
guide RNA (sgRNA) and the Cas9 messenger RNA (mRNA) - plus intracellular
Cas9 translation and ribonucleoprotein (RNP) assembly (Desai 2024). The
PK layer is a minimal-PBPK structure with plasma, lymph, a three-region
liver (vascular / endosomal / interstitial-cellular), kidney and a
lumped remainder tissue; the kidney compartment is present for LNP and
sgRNA but absent for mRNA, which is too large to be renally cleared. LNP
additionally undergoes opsonin bio-corona formation (kass / kdis),
phagocytosis into the mononuclear phagocyte system (kint) and
LDL-receptor-mediated endocytosis (kon,LNP / koff,LNP) with receptor
recycling. This is the mouse arm of the platform (step 2 of the paper’s
four-step workflow): it was fitted to plasma sgRNA and mRNA
concentrations after a single 2 mg/kg total RNA IV bolus, and carries no
pharmacodynamic layer because no biomarker was measured in mice. The
rate of exocytosis and the mRNA degradation rate were estimated here;
the rate of endocytosis was fixed from the NHP estimate and scaled with
an allometric exponent of -0.25. Sibling extractions:
Desai_2024_crisprCas9_nhp and Desai_2024_crisprCas9_human.
|
|
CrisprCas9
nhp (Desai 2024)
|
Preclinical (cynomolgus monkey). QSP. Translational quantitative systems
pharmacology platform for in vivo CRISPR-Cas9 gene editing delivered by
lipid nanoparticle (LNP), covering the whole-body disposition of all
three components of the therapy - the LNP delivery vehicle, the single
guide RNA (sgRNA) and the Cas9 messenger RNA (mRNA) - plus intracellular
Cas9 translation and ribonucleoprotein (RNP) assembly (Desai 2024). The
PK layer is a minimal-PBPK structure with plasma, lymph, a three-region
liver (vascular / endosomal / interstitial-cellular), kidney and a
lumped remainder tissue; the kidney compartment is present for LNP and
sgRNA but absent for mRNA, which is too large to be renally cleared. LNP
additionally undergoes opsonin bio-corona formation (kass / kdis),
phagocytosis into the mononuclear phagocyte system (kint) and
LDL-receptor-mediated endocytosis (kon,LNP / koff,LNP) with receptor
recycling. Two pharmacodynamic case studies are attached to the liver
RNP concentration: NTLA-2001 (transthyretin amyloidosis) via a sigmoidal
indirect-response model inhibiting TTR production, and VERVE-101
(LDL-cholesterol lowering) via a Friberg-type transit / feedback model
on serum PCSK9 feeding a precursor-dependent LDL-cholesterol model.
Estimated against cynomolgus monkey LNP plasma PK (1-3 mg/kg total RNA),
serum TTR (1.5-6 mg/kg) and serum PCSK9 / LDL-cholesterol (0.75-1.5
mg/kg), all by 2 h IV infusion. Sibling extractions:
Desai_2024_crisprCas9_mouse and Desai_2024_crisprCas9_human.
|
|
Crizotinib
mouse (Yamazaki 2008)
|
Preclinical (athymic mouse; GTL16 gastric carcinoma or U87MG
glioblastoma xenograft). Integrated PK + cMet phosphorylation
(effect-compartment link model) + exponential tumor-growth-inhibition
(TGI) model for orally administered crizotinib (PF02341066), an
ATP-competitive cMet receptor tyrosine kinase inhibitor. PK is
one-compartment first-order absorption with a fixed 0.8 h lag, fitted by
naive-pooled analysis (dose-group-specific estimates due to nonlinear
kinetics; the encoded set is Study 2 at 50 mg/kg). The cMet
phosphorylation response is the Sheiner 1979 link model with E0, Emax,
and Hill coefficient all fixed at 1 (Imax 1/(1 + Ce/EC50) form). The
tumor-growth model is exponential, with the growth rate inhibited by the
plasma concentration via a sigmoidal Imax 1/(1 + Cc/EC50_tumor) function
(Emax fixed at 1; the saturable tumor-volume capacity term TG50 was
rejected by the authors as TG50 >> Tmax). Default TGI parameters
reproduce the GTL16 fit; the U87MG variant (kin_tumor=0.0134,
kout_tumor=0.00236, EC50_tumor=94.1 ng/mL) is documented in
population$notes and demonstrated in the validation vignette.
|
|
CyaaE7
(ParraGuillen 2013)
|
Preclinical (mouse, female C57BL/6 with subcutaneous TC1 tumor
expressing HPV E7). Semi-mechanistic K-PD tumor-growth-dynamics model of
single-dose CyaA-E7 cancer vaccine: a virtual vaccine compartment feeds
a two-compartment transit chain to a vaccine-elicited inhibitory signal
SVAC that reduces tumor size via a second-order k3 * SVAC * tumor_size
term, inhibited by a Hill-function regulator REG driven by tumor size; a
binary mixture covariate MIX_VAC_RELAPSE gates the SVAC degradation rate
(k2 = 0 for cure, k2 = k1 for relapse).
|
|
Cyclophosphamide
mouse (Campagne 2019)
|
Preclinical (mouse). Plasma and brain/tumor extracellular-fluid (ECF)
population PK model for cyclophosphamide (CTX) and its sequential
metabolites 4-hydroxy-cyclophosphamide (4OH-CTX) and
carboxyethylphosphoramide mustard (CEPM) in female CD-1 nude mice
(non-tumor-bearing and orthotopic Group 3 medulloblastoma G3MB),
following a single 130 mg/kg intraperitoneal dose of cyclophosphamide
(Campagne 2019). Three sequential two-compartment plasma sub-models are
linked by full (Fm = 1) conversion CTX -> 4OH-CTX -> CEPM (so
reported CL and V for the two metabolites are apparent CL/F and V/F);
each compound additionally has a one-compartment brain/tumor ECF
sub-model linked to its plasma central via influx (CLin) and efflux
(CLef) clearances driven by the unbound plasma concentration FU x Cp.
ECF volume fixed at 0.001 L/kg (Stewart 2010, ref 26 of source). No
covariate effects retained; pooled fit across non-tumor-bearing and G3MB
mice.
|
|
Cyclophosphamide
mouse pbpk (Saleh 2023)
|
PBPK (LeiCNS-PK3.0 CNS physiologically-based model, mouse version).
Preclinical (mouse, CD1 nude). Nine-compartment CNS PBPK model
predicting unbound cyclophosphamide concentrations in brain
extracellular fluid (brain ECF) after a single 130 mg/kg intraperitoneal
dose. The CNS structure is the mouse re-parameterisation of
LeiCNS-PK3.0: brain microvasculature (brain_vascular), brain ECF, a
phospholipid brain-cell-membrane binding compartment
(brain_cell_membrane), brain intracellular fluid (brain_icf), lysosomes
(brain_lysosome), and the four CSF compartments (lateral ventricles,
third + fourth ventricles, cisterna magna, subarachnoid space) draining
in series back to plasma. Transport across the BBB and BCSFB is the sum
of a paracellular clearance (Qp, charged + neutral drug) and a
transcellular clearance (Qt, neutral drug only, scaled by pH-dependent
neutral fractions PHF and by asymmetry factors AF that encode active
transport). Every CNS parameter is fixed to mouse physiology (Table III)
or derived from the drug’s physicochemical properties (Table I); none
was fitted here. The BBB asymmetry factors are back-calculated from
Kp,uu,BBB = 0.339 (estimated by the authors; Table V). The plasma PK
model is the empirical two-compartment model of Table IV (ref [7]) and
acts purely as a forcing function: brain uptake does not deplete plasma,
exactly as published.
|
|
Cyclosporin
(Debord 2001)
|
Two-compartment population PK model for oral cyclosporin microemulsion
(Neoral) in stable renal transplant recipients (Debord 2001), with a
gamma-distribution absorption (Savic 2007 analytical transit-compartment
form) feeding the central compartment directly, F fixed to 1, and
population typical values derived from the means of the 21
individually-fitted patients in Table I of the paper.
|
|
Cyclosporine
(Philippe 2015)
|
Pediatric PK-PD-time-to-event model for oral cyclosporine in children
with severe aplastic anemia (Philippe 2015). PK is a two-compartment
model with first-order absorption, lag time, and linear elimination;
absorption parameters (F, Tlag, ka) are fixed from the literature, and
V1, V2, Cl, Q are allometrically scaled to body weight (reference 34 kg;
fixed exponents 0.75 on clearance and 1 on volume). The pharmacodynamic
interface model (Eq. 5) describes an effective concentration Ce driven
by the predicted trough concentration Ctrough, with production active
only when Ctrough lies inside an effective range (lower bound gamma1 =
87 ng/mL, upper bound gamma2 = 120 ng/mL) and first-order elimination at
rate alpha. The instantaneous hazard of neutrophil response (Eq. 6) is
lambda(t) = lambda0 * (1 + slope * Ce); cumhaz and sur are exposed as
derived outputs. In this implementation the predicted Cc (multiplied by
1000 to convert mg/L to ng/mL) is used as the Ctrough input to the
interface model; see vignette Assumptions and deviations for the full
justification.
|
|
Cysteamine
(Belldina 2003)
|
Two-compartment population PK model with first-order oral absorption and
an absorption lag, sequentially linked to a one-compartment effect-site
PD model with fractional inhibitory Emax (Hill = 1) for white-blood-cell
cystine content reduction by cysteamine in 11 paediatric and young-adult
patients (age 3-15 y, weight 14.3-60.2 kg) with nephropathic cystinosis
at steady state on cysteamine bitartrate (Cystagon) approximately every
6 hours. PK and PD parameters in the source paper were estimated as
individual NONMEM fits per subject and summarised as arithmetic mean /
geometric mean / median / min / max across the 11 patients (Tables 2 and
3); this package encodes the arithmetic means as the typical values,
with linear allometric weight scaling fixed at exponent 1.0 to reflect
the paper’s per-kg parameterisation of all clearance and volume terms.
Dose is in mg cysteamine bitartrate salt (MW 227.24 g/mol); the model
converts internally to plasma cysteamine in micromolar (free-base
moiety, MW 77.15 g/mol, the measured analyte). PD output cystine is
white-blood-cell cystine content in nmol cystine per mg protein.
|
|
Dabigatran
(Liesenfeld 2013)
|
Two-compartment population PK model for oral dabigatran (after
dabigatran etexilate prodrug) in seven end-stage renal disease (ESRD)
subjects undergoing intermittent hemodialysis, with first-order
absorption, absorption lag, an apparent total body clearance (renal +
non-renal), and an apparent dialysis clearance described by the Michaels
equation as a function of blood and dialysate flow rates and a
hemodialyzer mass transfer-area coefficient (Liesenfeld 2013).
|
|
Dabigatran
aPTT (Liesenfeld 2006)
|
Pharmacodynamic model for the prolongation of activated partial
thromboplastin time (aPTT) by dabigatran in orthopaedic surgery patients
receiving oral dabigatran etexilate after total hip replacement
(Liesenfeld 2006 BISTRO I PK-PD analysis). The concentration-aPTT
relationship combines a linear and an Emax model; the baseline aPTT and
the maximum nonlinear effect Emax both decline with time since surgery
via a proportional inhibitory Emax form sharing a single ET50. Covariate
analysis retained no demographic, comedication, or laboratory variables.
The 2006 paper does not develop a PK model; the PK component embedded
here is the Liesenfeld 2013 two-compartment dabigatran disposition with
all PK thetas fixed so the model is self-contained for simulation. The
2013 PK was fit in end-stage renal-disease subjects and will
overestimate dabigatran exposure for the 2006 BISTRO I
orthopaedic-surgery population; users targeting BISTRO I-style scenarios
should override the PK thetas or supply observed concentrations to the
PD layer.
|
|
Dabigatran
ECT (Liesenfeld 2006)
|
Pharmacodynamic model for the prolongation of ecarin clotting time (ECT)
by dabigatran in orthopaedic surgery patients receiving oral dabigatran
etexilate after total hip replacement (Liesenfeld 2006 BISTRO I PK-PD
analysis). The concentration-ECT relationship is a single linear
function whose slope decays exponentially from an initial value SLO0 to
a final value SLO_F with rate constant KM; the baseline ECT also
declines with time-since-surgery via a proportional inhibitory Emax
form. Covariate analysis retained no demographic, comedication, or
laboratory variables. The 2006 paper does not develop a PK model; the PK
component embedded here is the Liesenfeld 2013 two-compartment
dabigatran disposition with all PK thetas fixed so the model is
self-contained for simulation. The 2013 PK was fit in end-stage
renal-disease subjects and will overestimate dabigatran exposure for the
2006 BISTRO I orthopaedic- surgery population; users targeting BISTRO
I-style scenarios should override the PK thetas or supply observed
concentrations to the PD layer.
|
|
Daclizumab
(Othman 2014)
|
Two-compartment population PK model with first-order subcutaneous
absorption and lag time for daclizumab high-yield process (HYP) in
healthy volunteers (Othman 2014)
|
|
Daclizumab
cd25 (Diao 2016)
|
Kinetic-binding PK/PD model of CD25 receptor occupancy on peripheral
CD4+ T cells following subcutaneous daclizumab high-yield process (HYP)
in adults with relapsing-remitting multiple sclerosis (Diao 2016). The
receptor-occupancy state occ_cd25 obeys dOcc/dt = konCc(1 -
Occ) - koffOcc; the PD output is the percentage of CD4+ T cells
staining positive for unoccupied CD25, computed as E0 (1 -
occ_cd25). This is a REPARAMETERISATION of the paper’s published
sigmoidal Emax (Equation 1) with its two-parameter-set (saturation-phase
/ desaturation-phase) Hill function – kon and koff are calibrated to
reproduce the paper’s phenomenology (rapid saturation within 7 h after
first 150 mg SC dose per Figure 1A; return of unoccupied CD25 to
baseline in ~24 weeks after last steady-state dose per Figure 1B) rather
than transcribed from a paper table. See the companion vignette
Assumptions and deviations for the calibration rationale. The PK
backbone is inherited verbatim from Othman 2014.
|
|
Daclizumab
cd56bright (Diao 2016)
|
Indirect-response PK/PD model of CD56 bright natural killer (NK) cell
expansion following subcutaneous daclizumab high-yield process (HYP) in
adults with relapsing-remitting multiple sclerosis (Diao 2016).
Daclizumab HYP serum concentration stimulates the zero-order production
rate (Kin) of CD56 bright NK cells (% of all lymphocytes) via a
saturable Smax function; first-order elimination rate Kout is fixed by
the median baseline. The PK backbone is the two-compartment, first-order
SC absorption + lag model from Othman 2014 (file
inst/modeldb/specificDrugs/Othman_2014_daclizumab.R), copied verbatim
with weight-based allometric scaling.
|
|
Daclizumab
treg (Diao 2016)
|
Sigmoidal Emax PK/PD model of regulatory T cell (Treg) reduction
following subcutaneous daclizumab high-yield process (HYP) in adults
with relapsing-remitting multiple sclerosis (Diao 2016). The PD output
is the percentage of Treg (CD4+ CD127low/- Foxp3+) among all CD4+ T
cells; daclizumab HYP serum concentration drives a maximum 60% reduction
via a sigmoidal Emax function. The PK backbone is the two-compartment,
first-order SC absorption + lag model from Othman 2014 (file
inst/modeldb/specificDrugs/Othman_2014_daclizumab.R), copied verbatim
with weight-based allometric scaling.
|
|
Dactinomycin
(Mondick 2006)
|
Three-compartment intravenous population PK model for actinomycin-D
(dactinomycin) in 33 pediatric and young-adult patients (1.58-20.3
years) with Wilms’ tumor or rhabdomyosarcoma. All disposition parameters
are allometrically scaled by total body weight, normalized to a
reference weight of 70 kg, with theory-based fixed exponents (0.75 on
clearances, 1.0 on volumes; not explicitly stated in the abstract).
Inter-individual variability was reported only for V1 (54.4% CV) and CL
(57.2% CV); residual error and the remaining IIV terms (V2, V3, Q2, Q3)
were not reported in the source conference abstract and are encoded as
fixed(0). Mondick 2006 (PAGE 15 Abstr 938).
|
|
Dalteparin
(Schoemaker 1996)
|
One-compartment population PK/PD model for the low molecular weight
heparin dalteparine (trade name Fragmin) in healthy volunteers, fitted
simultaneously to intravenous and subcutaneous administration data
(Schoemaker & Cohen 1996, Example 3 / Table 4). The kinetic
sub-model is a one-compartment IV bolus / first-order SC absorption
disposition with an estimated constant basal anti-Xa activity (extending
the Schoemaker 1996 Example 2 enoxaparine model with a depot compartment
and bioavailability). The pharmacodynamic sub-model links anti-Xa
activity (Cc) to activated partial thromboplastin time (APTT) through an
exponential concentration-effect relationship parameterised by I10 (the
anti-Xa activity increment required to produce a 10% increase in APTT).
Common kinetic parameters are shared between IV and SC routes within
each subject; only F (bioavailability) and ka (absorption rate) differ
between routes. Validation of this model and the companion enoxaparine
PK model share a single vignette.
|
|
Danoprevir
(Canini 2015)
|
Combined pharmacokinetic / viral-kinetic (PK/VK) model for the HCV
NS3/4A protease inhibitor danoprevir in adults with chronic hepatitis C
(Canini 2015). PK is a two-compartment disposition (central = plasma,
peripheral1 = tissue including liver) with zero-order absorption of
duration Tk0 into central after a post-dose lag Tlag, followed by
first-order elimination. The viral-kinetic layer follows the standard
Neumann 1998 model with target cells assumed to remain constant (only
the productively-infected cell pool infected and the
free-virion pool virus are carried as ODE states). Drug
effectiveness e(t) = C1 / (EC50 + C1) is a Hill-Emax function with Emax
fixed at 1 and Hill coefficient fixed at 1 (the Canini 2015
model-selection winner over h = 2 and h = 3 by AICc/BIC); e(t) blocks
virion production so d/dt(virus) = (1 - e) * p * infected - c * virus.
Because Canini 2015 does not estimate the virion production rate p or
the infection rate beta separately, the packaged model fixes p = 1 as a
mathematical scaling (the identifiability constraint p * beta_T = d * c
at the pre-treatment steady state fully determines beta_T = d * c and
I(0) = c * V0). All 10 estimated typical values from Canini 2015 Table 2
(Tlag, Tk0, V1, ke, k12, k21, V0, c, d, EC50) and all 10 IIVs are
carried; cohort-specific V0 offsets (Table 2 cohorts 2-5) and the
screened HCV genotype covariate are documented in vignette Errata but
not applied as covariates in the packaged model (see notes in population
and in the vignette Assumptions section). PK is in per-hour units to
match the paper’s Table 2 reporting; the viral-kinetic /day-scale rate
constants c and d are converted inline to /h so the integrated system
runs on a single hour-scale time axis.
|
|
Dapagliflozin
(vanderWalt 2013)
|
Semi-mechanistic joint parent-metabolite population PK model for
dapagliflozin and its inactive UGT1A9 glucuronide metabolite
dapagliflozin 3-O-glucuronide (D3OG, identified as M15 in
chromatography) in healthy adults, T2DM subjects with normal or impaired
renal function, and patients with hepatic impairment (van der Walt
2013). Parent: 2-compartment disposition with first-order absorption fed
by a Savic 2007 transit-compartment chain (continuous N estimated
alongside MTT) and a logit bioavailability anchor; three parallel parent
elimination pathways are estimated separately as renal excretion of
unchanged dapagliflozin (CLP_renal, proportional to baseline creatinine
clearance), metabolic formation of D3OG (CLP_M15), and metabolic
clearance to unmeasured metabolites (CLP_other, allometrically scaled
like CLP_M15). Metabolite: 1-compartment with renal elimination CLM
proportional to creatinine clearance. Plasma observations only are
emulated here – the source paper also fitted urine dapagliflozin and
D3OG concentrations simultaneously with a replicate residual-error
structure; see the validation vignette for the urine and
replicate-residual deviations. Covariates: creatinine clearance (CRCL;
IBW-corrected, mL/min) on CLP_M15, CLP_renal, and CLM; AGE on CLP_other;
Child-Pugh Class C (HEPIMP_SEV) on CLP_M15 and V2M; Child-Pugh Class B
or C (HEPIMP_MODSEV) on V3P and CLM; female sex (SEXF) on total CLP and
on CLM; allometric WT scaling on CLP_M15, CLP_other, V2P, V3P, V2M.
|
|
Dapsone
(Gatti 1996)
|
One-compartment population PK model with first-order oral absorption and
first-order elimination for dapsone 100 mg twice weekly oral
Pneumocystis carinii pneumonia prophylaxis in 53 HIV-infected adults
(Gatti 1996). Apparent clearance CL/F and apparent central volume V/F
are scaled multiplicatively by concomitant rifampin co-administration
(shared 69.6% increase on both parameters, reflecting a first-pass /
bioavailability effect). Apparent absorption rate constant Ka is scaled
multiplicatively by total serum bilirubin (per-mg/dL fractional
decrease). IIV on CL/F (35% CV) and Ka (85% CV); V/F inter-individual
variability was found non-significant after covariate inclusion and
dropped from the final model. Residual-error magnitudes were not
reported in the publication; propSd and addSd are FIXED at 0 in this
packaged model so users must supply their own residual error to run any
stochastic VPC – see the validation vignette’s Errata section.
|
|
Dapsone
(Hall 2017)
|
One-compartment population PK model with first-order oral absorption for
dapsone in healthy US adults across a wide weight range; covariate
effects on Ka, CL, and Vc are encoded via the published MARS
piecewise-linear basis functions of weight, age, and blood urea nitrogen
(Hall 2017).
|
|
Daptomycin
(Garonzik 2016)
|
In vitro (Staphylococcus aureus USA300, methicillin-resistant CA-MRSA
reference strain). Mechanism-based mathematical pharmacodynamic (MBM)
model of daptomycin time-kill activity in supplemented Mueller-Hinton
broth with 0%, 10%, 30%, 50%, or 70% v/v heat-inactivated human serum.
The bacterial population is split into three subpopulations of
decreasing daptomycin susceptibility (susceptible, intermediate,
resistant), each described by two states (state 1 vegetative, state 2
replicating; six bacterial compartments total). Replication of state 2
cells back into state 1 is gated by a successful-replication probability
(REP = 2 x Plateau, with Plateau saturating at a maximum CFU/mL CFUm),
and the vegetative-to-replicating transition k12 is modulated by an
exponential lag-phase term (Eq 3) and a saturable carrying-capacity term
(Eq 7) parameterised by Imax_k12 and IC50_k12. Daptomycin acts on each
subpopulation via two mechanisms: a Hill-type stimulation of the
probability of death (STI; reduces successful replication via IREP = 1 -
STI) and a Hill-type direct killing of bacteria (Kill); the relative
balance of the two is the dominant pharmacodynamic feature, with SC50
(0.05 mg/L) much lower than KC50 (4.8 mg/L). The intermediate and
resistant subpopulations share the same SC50 and KC50 but have reduced
Smax and Kmax (Smax_r and Kmax_r fixed to 0) and the resistant
subpopulation has a slower vegetative-to-replicating transition (FR_K12r
= 0.0442). Protein binding by human serum is encoded as an ‘active
fraction’ factive(HS) multiplying the total static daptomycin
concentration to give an effective drug concentration DAP_EF; the active
fraction takes five experimental levels (factive = 1 at 0% HS, then
0.346, 0.284, 0.239, 0.252 at 10%, 30%, 50%, 70% HS). The model is
in-vitro PD only – there is no human PK component; daptomycin is dosed
once at t = 0 into the dap compartment and is chemically stable in the
medium for the 24-h experiment. Random effects (eta) are NOT present:
the paper reports replicate-level experimental fits with additive plus
small-count Poisson residual error on log10 CFU/mL.
|
|
Daratumumab
(Xu 2020)
|
Two-compartment population PK model for intravenous daratumumab
(anti-CD38 IgG1k) in adults with multiple myeloma, with parallel linear
and Michaelis-Menten eliminations from the central compartment. The
maximum velocity of the saturable (target-mediated) elimination decays
mono-exponentially from its baseline value at first-order rate KDES,
mimicking depletion of the CD38 target over weekly 16 mg/kg therapy (Xu
2020 MMY1001 D-Kd / D-KRd cohorts).
|
|
Daratumumab
qsstmdd (Li 2021)
|
Two-compartment semi-mechanistic target-mediated drug-disposition (TMDD)
population PK model for IV daratumumab (anti-CD38 IgG1) in adults with
multiple myeloma, with parallel non-specific linear clearance and
CD38-mediated saturable clearance under the quasi-steady-state (QSS)
approximation of Gibiansky 2008. The TMDD/QSS form supersedes an earlier
empirical Michaelis-Menten parameterisation with time-dependent Vmax:
receptor (CD38) turnover and complex internalisation reproduce
mechanistically the observed Vmax time-dependency. PAGE 29 (2021)
abstract II-52 by Li, Perez Ruixo, Zhou, Perez Ruixo, and Dosne (Janssen
R and D, Beerse). Distinct from Xu 2020 daratumumab, which uses the
empirical 2-cmt parallel-linear / time-dependent Vmax form.
|
|
Darbepoetin
(Takama 2007)
|
Two-compartment intravenous population PK model for darbepoetin alfa in
Japanese adult haemodialysis (HD) and peritoneal dialysis (PD) patients
with an additive endogenous erythropoietin baseline concentration
(Takama 2007). Body weight enters as a linear-deviation effect (centred
on 54 kg) on clearance and central volume; peritoneal-dialysis modality
adds a +17% multiplicative increment to central volume relative to the
HD reference.
|
|
Darbepoetin
alfa (Agoram 2006)
|
Two-compartment population PK model with first-order subcutaneous
absorption for darbepoetin alfa in healthy adult subjects (Agoram 2006).
Both IV and SC routes are supported. SC bioavailability is a linear
function of the SC dose amount (in ug). Body weight modifies clearance
and central volume via a normalized power model (reference 70 kg);
subject age modifies the absorption rate constant via a normalized power
model (reference 47 years, the development-cohort mean). Total measured
serum concentration is the sum of the simulated darbepoetin alfa and an
individual-specific endogenous-erythropoietin (eEPO) constant that the
ELISA assay cross-detects. Exponential (log-normal) residual error.
|
|
Darunavir
(Brochot 2015)
|
Two-compartment population PK model for ritonavir-boosted darunavir with
alpha-1 acid glycoprotein (AAG)-dependent apparent clearance and
allometric weight scaling, in HIV-1-infected pediatric (>=3 to <18
years) and adult patients (Brochot 2015).
|
|
Dasabuvir
(Mensing 2017)
|
Two-compartment population PK model for oral dasabuvir in HCV genotype-1
infected adults receiving the 3D regimen (Mensing 2017). First-order
absorption, linear elimination, combined proportional + additive
residual error, IIV on CL/F only. The author’s final model retained
cirrhosis, gender, creatinine clearance, and body weight as significant
covariates on CL/F (and age, body weight on Vc/F and Vp/F), but the
paper does not publish point estimates for these covariate coefficients
(only graphical exposure-ratio forest plots in Figure 2); the
implemented model is the structural typical-value model with covariate
coefficients omitted (documented in covariatesDataExcluded).
|
|
Datopotamab
(Hong 2025)
|
Coupled population PK model for datopotamab deruxtecan (Dato-DXd,
anti-TROP2 antibody-drug conjugate) and its released payload DXd in
adults with advanced solid tumors (Hong 2025). Dato-DXd disposition is a
two-compartment model with parallel linear (CL_lin) and Michaelis-Menten
(Vmax / Km) elimination from the central compartment. DXd is a
one-compartment model whose formation rate equals the total Dato-DXd
elimination rate (linear + nonlinear) scaled by the molecular-weight
ratio (493.5 / 150000) and a time-and-cycle-dependent drug-to-antibody
ratio DAR(tad, CYCLE) = 4 * (0.25 + 0.75 * exp(-beta * tad)) * (1 if
CYCLE = 1 else Factor1). Body weight is included as a mechanistic
covariate with a fixed allometric exponent of 0.75 on Dato-DXd linear
clearance and estimated exponents on Dato-DXd volumes (paper Eq. 8-10)
and on DXd CL/Vc (Eq. 14-15).
|
|
Daunorubicin
(Bogason 2011)
|
Two-compartment population PK model for daunorubicin (DNR) in adults
with acute myeloid leukaemia, with baseline white blood cell count as a
covariate on central volume of distribution (Bogason 2011)
|
|
Daunorubicin
(Varatharajan 2016)
|
Population PK model for IV daunorubicin (Dnr) and its primary
carbonyl-reductase metabolite daunorubicinol (DOL) in adult de novo
acute myeloid leukaemia (AML) patients (Varatharajan 2016). Each
component (parent and metabolite) is described by an independent
two-compartment disposition parameterised on apparent clearance, central
volume, and the inter-compartmental rate constants K12 and K21.
Daunorubicin is converted to daunorubicinol via parent elimination (the
model assumes the fraction metabolised fm = 1, so the published DOL CL
and V are ‘apparent’ values that absorb fm). No covariates were retained
in the final structural model; demographic / pharmacogenetic
associations in the paper are reported on post hoc empirical-Bayes
estimates rather than as fixed-effects covariate parameters.
|
|
Daunorubicin
liposomal (Hempel 2003)
|
One-compartment IV-infusion population PK model for total daunorubicin
(free plus liposome-encapsulated) following liposomal daunorubicin
(Daunoxome) in paediatric and adolescent oncology patients (Hempel
2003). Clearance and volume of distribution scale linearly with total
body weight (CL = theta_CL * WT; V = theta_V * WT, i.e. the source
paper’s per-kg parameterisation with allometric exponent fixed to 1 and
no reference-weight normalisation). The final model (Table 2 model 15)
retains inter-individual variability on CL (51% CV) and V (27% CV),
inter-occasion variability on CL (16.7% CV) – documented but NOT encoded
structurally here, per the Andrews 2017 / Brooks 2021 nlmixr2lib
precedent for IOV without an operational occasion column – and a
proportional residual error (22%). Distinct from
Varatharajan_2016_daunorubicin (free daunorubicin + daunorubicinol
metabolite in adult AML).
|
|
Decitabine
(Han 2015)
|
Two-compartment IV population pharmacokinetic model coupled with two
parallel Friberg-style myelosuppression PD chains (absolute neutrophil
count, ANC, and platelet count, PC) for decitabine post-transplant
maintenance in adult Korean patients with higher-risk myelodysplastic
syndrome or secondary acute myeloid leukemia (Han 2015). The platelet
feedback baseline rises asymptotically over cycles per the paper’s IMP /
IMK extension (BASE_P_t = BASE_P + IMP * (1 - exp(-IMK * t))); the
neutrophil chain uses a time-invariant baseline. PK parameters are
body-surface-area-normalized (per m^2): doses must be supplied in mg/m^2
and central-compartment concentrations are returned in mg/L (= ug/mL =
1000 ng/mL). PD outputs ANC and PLT are in 10^9 cells/L.
|
|
Deferiprone
(Bellanti 2014)
|
One-compartment population PK model for the oral iron chelator
deferiprone in healthy adult subjects, with first-order absorption,
absorption lag time, and a binary sex effect on the apparent volume of
distribution (Bellanti 2014).
|
|
Deferiprone
(Bellanti 2017)
|
One-compartment population PK model for the oral iron chelator
deferiprone in paediatric patients aged <6 years with
transfusion-dependent haemoglobinopathies, with first-order absorption
and first-order elimination and fixed allometric scaling of clearance
and volume on body weight (Bellanti 2017).
|
|
Deferoxamine
(Bellanti 2015)
|
Indirect-response disease model for serum ferritin in chronic
transfusional iron overload (beta-thalassaemia major) with proportional
deferoxamine effect on ferritin degradation rate. Two-compartment 8-h
SC-infusion deferoxamine PK (literature-derived) enters as a
time-varying steady-state concentration covariate; the ferritin
compartment captures the baseline turnover (Kin, Kout), the
disease-status-modulated transfusion-driven production (CRT), and the
chelator effect (1 + DFO) on Kout.
|
|
Degarelix
(Tornoe 2006)
|
Population PK/PD model of the hypothalamic-pituitary-gonadal (HPG) axis
after repeated subcutaneous (s.c.) injections of the GnRH receptor
blocker degarelix in prostate-cancer patients. PK is a two-compartment
disposition model with two parallel first-order absorption routes from a
self-forming s.c. depot: a rapid release (fraction Fr via ka,fast) and a
prolonged slow release ((1 - Fr) via ka,slow). The packaged values
correspond to the 40 mg/mL dose-concentration arm of Tornoe 2007 Table 3
(Fr_40, F_40 and t_1/2,slow,40); the 20 and 60 mg/mL alternatives are
tabulated in the validation vignette. PD is a four-state HPG-axis
feedback model (feedback compartment F, LH pool P, LH, testosterone Te)
with sigmoidal Imax inhibition of LH pool release by degarelix and a
positive interaction (F) from the feedback compartment on LH synthesis
and release; testosterone secretion is stimulated by LH via a sigmoidal
Emax model. ke_LH, ke_F, lambda, LH_base and Te_base are the
degarelix-study-specific values from Table 4.
|
|
Desmopressin
(Agerso 2004)
|
Three-compartment population PK model for intravenous desmopressin with
simultaneous plasma and urinary-amount outputs. Systemic clearance is
split into renal and non-renal components, each modulated linearly by
creatinine clearance (CRCL), in healthy subjects and patients with
varying degrees of renal impairment (Agerso 2004).
|
|
Desmopressin
(Schutte 2018)
|
Two-compartment apparent population PK model describing the time profile
of endogenous factor VIII coagulant activity (FVIII:C) following a
desmopressin (DDAVP) administration in nonsevere haemophilia A patients
(Schutte 2018; final covariate model with FVIII-recent on baseline
FVIII, V1 and CL). Desmopressin is the administered intervention; the
apparent PK parameters describe the resulting endogenous FVIII:C release
as if it were a unit-dose drug input (the source paper fixed the dose to
unity because no FVIII concentrate was infused).
|
|
Dexamethasone
rat (Li 2012)
|
Preclinical (rat). Mechanism-based PK/PD model for CYP3A1/2 induction by
dexamethasone (DEX, single 100 mg/kg ip dose) in male Sprague-Dawley
rats. PK is a two-compartment mammillary model with zero-order ip
absorption of duration T0 directly into the central compartment (no
first-order rate constant; CL/F, Q/F, Vc/F, Vp/F all reported as
kg-normalised apparent values). PK BSV is exponential and is retained
only on Q/F (all other PK BSVs were not significant). The PD cascade
describes CYP3A1 and CYP3A2 induction at three molecular levels: (1)
mRNA dynamics use an indirect-response (Dayneka-style) model in which a
Hill-type fractional occupancy of CYP3A DNA-responsive elements by the
DEX-PXR complex (FO = Cp^gamma / (SC50^gamma + Cp^gamma)) drives a
stimulation signal Si,0 = Smax * FO that flows through a per-isoform
chain of transit compartments with mean transit time tau (one
compartment for CYP3A1, eight compartments for CYP3A2) before
stimulating mRNA synthesis as d/dt(mRNAi) = kin,i * (1 + Si,ni) - kout,i
* mRNAi. (2) Protein dynamics translate mRNA to CYP3A protein via
d/dt(CYP3Ai) = ksyn,i * mRNAi^mi - kdeg,i * CYP3Ai, where the
per-isoform amplification factor mi is a paper-mechanistic power
exponent on mRNA. (3) Enzyme activity (rate of 6beta-hydroxytestosterone
formation) is the algebraic linear combination EA = alpha * CYP3A1 +
beta * CYP3A2 with per-isoform turnover-number rates alpha and beta
(pmol 6beta-OHT / min / pmol CYP3A). The PK and PD layers were fit
sequentially in NONMEM 7.1.2 with FOCE+I, the PK model first then the PD
layers simultaneously with PK fixed. Three PD layers were fit by the
naive pool approach (each animal contributed one PD observation per time
point), so no PD IIVs are present. Numbers of transit compartments (n1 =
1, n2 = 8) are paper-mechanistic fixed structural integers.
|
|
Dexmedetomidine
(Perez-Guille 2018)
|
Two-compartment IV population PK with sigmoidal Imax PD on heart rate
(HR) and mean arterial pressure (MAP) fractional responses for
dexmedetomidine in Mexican Mestizo children (2-18 y) undergoing
ambulatory surgery, with a priori allometric scaling on CL and Q
(exponent 0.75) and V1 and V2 (exponent 1) at a 70 kg reference weight
(Perez-Guille et al. 2018, Tables 2 and 3, allometric model)
|
|
Dexmedetomidine
(Smuszkiewicz 2017)
|
Two-compartment population PK model for intravenous dexmedetomidine
continuous infusion in adult ICU patients undergoing analgosedation
(Smuszkiewicz 2017). 27 medical and surgical ICU patients (17 male, 10
female; median age 59.5 y, median weight 75 kg) received continuous
infusions of 0.1-1.5 ug/kg/h for 23.7-102 h. Age, sex, body weight,
infusion duration, pretreatment SOFA score, and inotrope use were
screened as covariates but none reached statistical significance, so the
final model contains no covariate effects. IIVs on Vc, CL, Vp, and Q are
diagonal (no clear correlations). Proportional residual error.
|
|
Dexmedetomidine
(Su 2016)
|
Two-compartment IV population PK model for dexmedetomidine in neonates
(1 day-1 month) and infants (1-24 months) after open heart surgery, with
a priori allometric weight scaling on CL, Q (exponent 0.75) and V1, V2
(exponent 1) at a 70 kg reference weight; an Emax-form postnatal-age
maturation on CL with TM50 = 0.032 months; a power-form effect of total
cardiopulmonary bypass duration on CL centred at 60 min; and a 1.24-fold
multiplicative increase in CL for patients with right-to-left
intracardiac shunt (Qp:Qs < 1) (Su 2016 Table 4, allometric
weight-normalized full covariate model)
|
|
Dexmedetomidine
(Talke 2018)
|
Three-compartment IV population PK plus effect-compartment sigmoid Emax
PD model for dexmedetomidine-induced peripheral vasoconstriction (ADC
units from finger photoplethysmography) in healthy adult volunteers,
with a priori allometric body-weight scaling on CL, Q2, Q3 (exponent
0.75) and V1, V2, V3 (exponent 1) at a 70 kg reference weight (Talke and
Anderson 2018, Tables 3 and 4)
|
|
Dexmedetomidine
piglet (Ezzati 2014)
|
Preclinical (newborn piglet). One-compartment IV population PK model of
dexmedetomidine in a piglet perinatal-asphyxia model with therapeutic
hypothermia (Ezzati 2014). Clearance scales allometrically with body
weight (Holford exponent 0.75) standardised to 70 kg, decreases with
body temperature centred at 37 C (Ftemp), and is multiplied by a
paper-specific factor FAED (= 0.558) in the post-hypoxic-ischemic state;
volume scales allometrically with weight (exponent 1).
|
|
Dextroamphetamine
(Castelli 2022)
|
One-compartment population PK model for dextroamphetamine transdermal
system (d-ATS) in adults and children with ADHD (Castelli 2022 APNA
poster), with sequential zero- and first-order absorption (zero-order
release over duration D1 into depot, then first-order Ka into central),
power-law body-weight scaling on CL/F (exponent 0.47), V/F (0.53), and
Ka (-0.29) at an assumed 70 kg reference, independent IIV on CL/F, V/F,
Ka, and D1, bioavailability anchored at F = 1, and residual error not
reported in the conference poster (encoded fixed at 0; see vignette
Errata).
|
|
Dextromethorphan
(TerHeine 2014)
|
Semi-physiological eight-compartment population PK model for
dextromethorphan and its three phase I metabolites (dextrorphan,
3-methoxymorphinan, 3-hydroxymorphinan) in adult breast-cancer patients
receiving chronic oral tamoxifen, used as a dual CYP2D6 / CYP3A
phenotypic probe (single 30 mg oral dose). Pre-systemic and systemic
metabolism are integrated via a hypothetical hepatic metabolism
compartment in rapid (quasi-steady-state) equilibrium with the
dextromethorphan central compartment; the algebraic hepatic
concentration drives parallel CYP2D6 (dextromethorphan ->
dextrorphan) and CYP3A (dextromethorphan -> 3-methoxymorphinan)
formation steps. Subsequent CYP3A-mediated conversion of dextrorphan and
CYP2D6-mediated conversion of 3-methoxymorphinan both feed the terminal
3-hydroxymorphinan pool, which is eliminated by a single clearance to
other species. All metabolite apparent volumes are fixed to 419 L
(Abduljalil 2009 literature value) for identifiability. Individual
post-hoc CYP2D6 (CL_CYP2D6,1) and CYP3A (CL_CYP3A,1) clearances serve as
the phenotypic probe covariates used downstream by the companion
tamoxifen / endoxifen model (TerHeine_2014_tamoxifen).
|
|
Dha
ring early (Cao 2017)
|
In vitro (P. falciparum 3D7 laboratory strain, early-ring-stage
parasites). Dynamic stress PD model from Cao 2017 capturing the delayed
dihydroartemisinin (DHA) killing effect observed in tightly
age-synchronized parasite cultures; one of four stage-specific NLME fits
in Table 1 (early-ring stage corresponds to 2 h post-infection per the
Klonis 2013 experimental design that supplied the viability data). The
killing rate k = kmax(S) * C^hill / (Kc(S)^hill + C^hill) is modulated
by a dynamic stress variable S(t) that accumulates while drug
concentration C exceeds C* = 0.1 nM (dS/dt = lambda(1 - S)) and
resets toward zero otherwise. Stress-dependent kmax(S) = alphaS and
Kc(S) = beta1*(1 - S) + beta2 (paper eq 7 and 8). DHA concentration
evolves in the central compartment with first-order decay (default kdrug
= log(2)/8 /h for in vitro experiments; override for in vivo
simulations). Parasite count N(t) is normalized to N(0) = 1, so the
deterministic parasites state IS the surviving viability
fraction (paper eq 17). See modellib(‘Cao_2017_dha_ring_mid’),
modellib(‘Cao_2017_dha_troph_early’),
modellib(‘Cao_2017_dha_troph_late’) for the other three stage-specific
fits combined in the in vivo PK-PD simulation of Fig 6.
|
|
Dha
ring mid (Cao 2017)
|
In vitro (P. falciparum 3D7 laboratory strain, mid-ring-stage
parasites). Dynamic stress PD model from Cao 2017 capturing the delayed
dihydroartemisinin (DHA) killing effect; one of four stage-specific NLME
fits in Table 1 (mid-ring stage corresponds to 7.5 h post-infection).
Mid-ring is the slowest-accumulating stage (half-life of the unstressed
state ~1.86 h) and exhibits the strongest delay in the drug
concentration-killing rate curve (Fig 3, Fig 4A). The killing rate k =
kmax(S) * C^hill / (Kc(S)^hill + C^hill) is modulated by a dynamic
stress variable S(t) that accumulates while drug concentration C exceeds
C* = 0.1 nM (dS/dt = lambda(1 - S)) and resets toward zero
otherwise. Stress-dependent kmax(S) = alphaS and Kc(S) = beta1*(1 -
S) + beta2 (paper eq 7 and 8). DHA concentration evolves in the central
compartment with first-order decay (default kdrug = log(2)/8 /h for in
vitro experiments; override for in vivo simulations). Parasite count
N(t) is normalized to N(0) = 1, so the deterministic
parasites state IS the surviving viability fraction (paper
eq 17). See modellib(‘Cao_2017_dha_ring_early’),
modellib(‘Cao_2017_dha_troph_early’),
modellib(‘Cao_2017_dha_troph_late’) for the other three stage-specific
fits combined in the in vivo PK-PD simulation of Fig 6.
|
|
Dha
troph early (Cao 2017)
|
In vitro (P. falciparum 3D7 laboratory strain, early-trophozoite-stage
parasites). Dynamic stress PD model from Cao 2017 capturing the delayed
dihydroartemisinin (DHA) killing effect; one of four stage-specific NLME
fits in Table 1 (early-trophozoite stage corresponds to 24 h
post-infection). The killing rate k = kmax(S) * C^hill / (Kc(S)^hill +
C^hill) is modulated by a dynamic stress variable S(t) that accumulates
while drug concentration C exceeds C* = 0.1 nM (dS/dt = lambda(1 -
S)) and resets toward zero otherwise. Stress-dependent kmax(S) =
alphaS and Kc(S) = beta1*(1 - S) + beta2 (paper eq 7 and 8).
Trophozoite stages have substantially higher maximum killing rate alpha
than ring stages (Fig 4B), reflecting greater drug susceptibility once
stress has accumulated. DHA concentration evolves in the central
compartment with first-order decay (default kdrug = log(2)/8 /h for in
vitro experiments; override for in vivo simulations). Parasite count
N(t) is normalized to N(0) = 1, so the deterministic
parasites state IS the surviving viability fraction (paper
eq 17). See modellib(‘Cao_2017_dha_ring_early’),
modellib(‘Cao_2017_dha_ring_mid’), modellib(‘Cao_2017_dha_troph_late’)
for the other three stage-specific fits combined in the in vivo PK-PD
simulation of Fig 6.
|
|
Dha
troph late (Cao 2017)
|
In vitro (P. falciparum 3D7 laboratory strain, late-trophozoite-stage
parasites). Dynamic stress PD model from Cao 2017 capturing the delayed
dihydroartemisinin (DHA) killing effect; one of four stage-specific NLME
fits in Table 1 (late-trophozoite stage corresponds to 34 h
post-infection). The killing rate k = kmax(S) * C^hill / (Kc(S)^hill +
C^hill) is modulated by a dynamic stress variable S(t) that accumulates
while drug concentration C exceeds C* = 0.1 nM (dS/dt = lambda(1 -
S)) and resets toward zero otherwise. Stress-dependent kmax(S) =
alphaS and Kc(S) = beta1*(1 - S) + beta2 (paper eq 7 and 8). DHA
concentration evolves in the central compartment with first-order decay
(default kdrug = log(2)/8 /h for in vitro experiments; override for in
vivo simulations). Parasite count N(t) is normalized to N(0) = 1, so the
deterministic parasites state IS the surviving viability
fraction (paper eq 17). See modellib(‘Cao_2017_dha_ring_early’),
modellib(‘Cao_2017_dha_ring_mid’), modellib(‘Cao_2017_dha_troph_early’)
for the other three stage-specific fits combined in the in vivo PK-PD
simulation of Fig 6.
|
|
Diazepam
(Ku 2018)
|
Two-compartment population PK model for intravenous diazepam in children
aged 3 months to 18 years treated for status epilepticus. Clearance,
central volume, inter-compartmental clearance, and peripheral volume
scale allometrically with total body weight referenced to a 70 kg adult
(fixed exponents 0.75 on CL and Q; 1 on V1 and V2). IIV is estimated on
CL and V1 only; IIV on Q and V2 was held fixed at 0 in the final model
to avoid >50% shrinkage. Proportional residual error.
|
|
Diazepam
pbpk kpu human (Yau 2023)
|
PBPK (14-compartment whole-body, four common Kpu clusters). Diazepam
disposition in healthy adults after IV administration. The second of two
whole-body PBPK simplification strategies investigated by Yau et
al. (2023): rather than lumping compartments, the full kinetic structure
and every individual tissue blood flow and volume are retained, and only
the number of unknown distribution parameters is reduced. Tissues are
grouped a priori by similarity of tissue composition using hierarchical
clustering (drug-independent), and each cluster is assigned one common
unbound tissue:plasma partition coefficient (Kpu). This reduces the
distribution parameters from 13 to 4 while leaving the kinetic structure
of the whole-body model intact, so individual tissue concentration-time
profiles remain available. The lung, arterial and venous blood are
treated as a single quasi-steady-state ‘central’ compartment (the only
kinetic assumption); the remaining 13 tissues are perfusion-limited
well-stirred compartments. Stomach, gut, spleen and pancreas drain into
the liver via the portal vein; hepatic elimination uses the well-stirred
model and renal elimination is placed on the central compartment. The
four clusters are (1) bone, brain, muscle, pancreas and rest of body,
(2) lung, gut, stomach, kidney, heart, spleen and liver, (3) skin and
(4) adipose. Together with the four-scalar variant this was one of the
two models the paper found best described the human diazepam data.
|
|
Diazepam
pbpk kpu rat (Yau 2023)
|
Preclinical (rat). PBPK (14-compartment whole-body, four common Kpu
clusters, k-means clustering). Diazepam disposition in rats after IV
administration - the rat counterpart of
Yau_2023_diazepam_pbpk_kpu_human. The full kinetic structure and every
individual tissue blood flow and volume are retained; only the number of
unknown distribution parameters is reduced, by grouping tissues a priori
on similarity of tissue composition and assigning one common unbound
tissue:plasma partition coefficient (Kpu) per group. The lung, arterial
and venous blood are treated as a single quasi-steady-state ‘central’
compartment; the remaining 13 tissues are perfusion-limited well-stirred
compartments, with stomach, gut, spleen and pancreas draining into the
liver via the portal vein. Clustering here is the k-means solution,
which the paper selected as one of its three primary rat candidates: the
four clusters are (1) bone, brain, muscle, pancreas and rest of body,
(2) kidney, spleen and liver, (3) skin, lung, gut, stomach and heart,
and (4) adipose. Note this differs from the hierarchical grouping used
for the human model, where lung and the splanchnic organs cluster with
kidney and liver. Rat physiology is scaled from body weight using the
authors’ own control-stream construction, which reproduces the 250-g
reference-rat values of Table S1 exactly. Because the rat hepatic
clearance implied by CLb exceeds hepatic blood flow, hepatic clearance
is capped at 0.99 * Q_liver as the authors’ control stream and the
Figure S4 footnote specify; the balance is carried as renal clearance.
|
|
Diazepam
pbpk lumped human (Yau 2023)
|
PBPK (kinetically lumped 3-compartment, physiologically parameterised).
Diazepam disposition in healthy adults after IV administration. One of
two whole-body PBPK simplification strategies investigated by Yau et
al. (2023): Nestorov kinetic lumping collapses the 16-state whole-body
PBPK model into three compartments on the basis of tissue time constants
(paper Table 1). The lung, arterial and venous blood are lumped into a
quasi-steady-state ‘central’ compartment; all remaining tissues except
adipose form the moderately equilibrating ‘peripheral1’ compartment;
adipose alone forms the slowly equilibrating ‘peripheral2’ compartment.
Micro-constants are not free parameters - they are computed from the
70-kg reference-man blood flows and volumes (Table S1) and the estimated
unbound tissue:plasma partition coefficients via supplement Eq S12-S16,
so the model retains physiological interpretability while having the
same number of free parameters as an empirical 3-compartment model. Only
total blood clearance and three lumped Kpu values are estimated. Kpu1 is
the lung Kpu (blood + lung central pool), Kpu2 the common Kpu of the
peripheral1 tissues and Kpu3 the adipose Kpu. Elimination is split into
hepatic and renal components using the well-stirred model and the
reported urinary excretion fraction fe = 0.0005; because only 0.05% of
the dose is excreted unchanged the renal term is negligible and
clearance is effectively all hepatic.
|
|
Diazepam
pbpk lumped rat (Yau 2023)
|
Preclinical (rat). PBPK (kinetically lumped 3-compartment,
physiologically parameterised). Diazepam disposition in rats after IV
administration - the rat counterpart of
Yau_2023_diazepam_pbpk_lumped_human. Nestorov kinetic lumping collapses
the 16-state whole-body PBPK model into three compartments on the basis
of tissue time constants (paper Table 1). The lung, arterial and venous
blood are lumped into a quasi-steady-state ‘central’ compartment; all
remaining tissues except skin form the moderately equilibrating
‘peripheral1’ compartment; skin alone forms the slowly equilibrating
‘peripheral2’ compartment. Note the lump differs from the human model:
skin is the slow compartment in rat (skin is a much larger fraction of
body weight in rat) whereas adipose is the slow compartment in human,
which is precisely the cross-species scaling limitation the paper
discusses. Micro-constants are computed from body-weight-scaled blood
flows and volumes via supplement Eq S12-S16, so only total blood
clearance and three lumped Kpu values are estimated. Rat physiology is
scaled from body weight using the authors’ own control-stream
construction (cardiac output = 0.235 * BW^0.75, fractional cardiac
outputs and fractional tissue weights), which reproduces the 250-g
reference-rat values of Table S1 exactly. Because the rat hepatic
clearance implied by CLb exceeds hepatic blood flow, hepatic clearance
is capped at 0.99 * Q_liver exactly as the authors’ control stream and
Figure S4 footnote specify; the balance is carried as renal clearance.
|
|
Diazepam
pbpk scalar human (Yau 2023)
|
PBPK (14-compartment whole-body, four common Kpu scalars). Diazepam
disposition in healthy adults after IV administration. Variant 2.2 of
the Yau et al. (2023) simplification strategies: the full kinetic
structure and every individual tissue blood flow and volume are
retained, tissue Kpu values are first predicted bottom-up with the
Rodgers and Rowland (R&R) equations from tissue composition and
diazepam physicochemistry, and then corrected by a small number of
estimated multiplicative scaling factors shared within composition-based
clusters (Eq 10: Kpu_i = Kpu_predRR,i * SF_i). The scalar therefore
quantifies the systematic bias of the bottom-up R&R prediction
rather than replacing it, which is why the paper judged this
parameterisation the most promising for interspecies translation - the
bias is assumed to be similar across species. The R&R weak-base
branch is used because diazepam’s basic pKa is 3.4 (< 7), so tissue
binding is driven by extracellular albumin rather than acidic
phospholipids. The lung, arterial and venous blood are treated as a
single quasi-steady-state ‘central’ compartment; the remaining 13
tissues are perfusion-limited well-stirred compartments, with stomach,
gut, spleen and pancreas draining into the liver via the portal vein.
The four clusters are (1) bone, brain, muscle, pancreas and rest of
body, (2) lung, gut, stomach, kidney, heart, spleen and liver, (3) skin
and (4) adipose. Together with the four-common-Kpu variant this was one
of the two models the paper found best described the human diazepam
data.
|
|
Diazepam
pbpk scalar rat (Yau 2023)
|
Preclinical (rat). PBPK (14-compartment whole-body, four common Kpu
scalars, hierarchical clustering). Diazepam disposition in rats after IV
administration - the rat counterpart of
Yau_2023_diazepam_pbpk_scalar_human. The full kinetic structure and
every individual tissue blood flow and volume are retained; tissue Kpu
values are first predicted bottom-up with the Rodgers and Rowland
(R&R) equations from rat tissue composition and diazepam
physicochemistry, and then corrected by a small number of estimated
multiplicative scaling factors shared within composition-based clusters
(Eq 10: Kpu_i = Kpu_predRR,i * SF_i). The scalar therefore quantifies
the systematic bias of the bottom-up R&R prediction rather than
replacing it, which is why the paper judged this parameterisation the
most promising for interspecies translation. The R&R weak-base
branch is used because diazepam’s basic pKa is 3.4 (< 7). The lung,
arterial and venous blood are treated as a single quasi-steady-state
‘central’ compartment; the remaining 13 tissues are perfusion-limited
well-stirred compartments, with stomach, gut, spleen and pancreas
draining into the liver via the portal vein. Clustering here is the
hierarchical solution, which the paper selected as one of its three
primary rat candidates: the four clusters are (1) bone, brain, muscle,
pancreas and rest of body, (2) lung, gut, stomach, kidney, heart, spleen
and liver, (3) skin and (4) adipose. Rat physiology is scaled from body
weight using the authors’ own control-stream construction, which
reproduces the 250-g reference-rat values of Table S1 exactly. Hepatic
clearance is capped at 0.99 * Q_liver as the control stream and the
Figure S4 footnote specify.
|
|
Diclazuril
chicken pbpk (Yang 2023)
|
PBPK (whole-body, flow-limited; broiler chicken). Nine-compartment
physiologically based pharmacokinetic model for the anticoccidial
diclazuril in broiler chickens after continuous oral exposure via
medicated feed or drinking water, comprising intestinal contents
(absorption site), liver, kidney, lumped skin + fat, muscle, a lumped
rest-of-body compartment, lung, arterial plasma and venous plasma; all
tissues are perfusion (flow) limited with tissue:plasma partition
coefficients, absorption from the gut lumen is first order (Ka) in
competition with first-order fecal loss of unabsorbed drug (Kgut), and
elimination is hepatic (Clhe) plus fecal excretion. Built to predict
edible-tissue residues and withdrawal periods against Chinese and
European maximum residue limits (Yang 2023).
|
|
Diclofenac
(Henin 2012)
|
Semi-mechanistic Gastro-Intestinal Transit Time (GITT) absorption model
applied to enteric-coated diclofenac (Henin 2012, The AAPS Journal
14:155-163). The intact tablet moves through the stomach (no drug
release due to enteric coating) into the proximal small intestine,
distal small intestine, and colon; drug release and absorption are
collapsed into a single first-order rate per GI region because the drug
release and absorption phenomena were indistinguishable in the observed
plasma-only dataset. The effective absorption rate from the intact
tablet is a step- function-weighted combination KA_PSI (proximal SI,
1.06 1/h), KA_DSI (distal SI, 8.64 1/h), and KA_Col (colon, 1 1/h FIXED)
gated by tablet-position STEP functions with per-subject inflection
points IP_APSI (gastric emptying), IP_PSI_DSI, and IP_DSI_C (population
distributions from Table II). Total absorbed fraction is limited by the
gut-wall bioavailability FA = 0.61 (Table III, IIV 8% CV). Disposition
is a three-compartment model with population parameters allometrically
scaled to a 70 kg reference (CL = 16.5 L/h/70kg^0.75, V1 = 3.68 L/70kg,
Q2 = 1.75 L/h/70kg^0.75, V2 = 7.48 L/70kg, Q3 = 7.21 L/h/70kg^0.75, V3 =
3.79 L/70kg). Combined additive (10 nmol/L) + proportional (12.6%)
residual error. This extraction encodes only the ‘no return to fundus’
subpopulation and treats the fundus + antrum transit as a single
stomach-to-PSI event, appropriate for an enteric-coated tablet whose
contents do not release in the stomach.
|
|
Diclofenac
(Standing 2008)
|
One-compartment population PK model for oral diclofenac suspension in
children and adult volunteers (Standing 2008): two parallel
transit-absorption arms (Savic 2007 analytical input form) feeding two
depot compartments that each absorb into a single central disposition
compartment with linear elimination. Allometric weight scaling on
clearance and volume to a 70 kg reference. Captures the double-peak
absorption profile common to immediate-release diclofenac. Separate
proportional residual error for paediatric and adult cohorts. Source
paper additionally fits between-occasion variability (BOV) on CL/F (20%)
and Vd/F (93%) – BOV is not implemented in this nlmixr2 model file
because it requires an OCC column in the user dataset; users who want
BOV can add an etalcl_bov / etalvc_bov occasion-level random effect
themselves.
|
|
Didanosine
(Hirt 2009)
|
One-compartment population PK model for didanosine (ddI) administered
once daily as buffered chewable Videx tablets in West African
HIV-1-infected children; first-order absorption with ka fixed at 4 1/h,
additive residual error, exponential IIV on CL/F and Vc/F with
off-diagonal covariance
|
|
Digoxin
(Jelliffe 2014)
|
Two-compartment population PK/PD model of digoxin in adults with
first-order oral absorption, creatinine-clearance-dependent renal
elimination, and a peripheral effect compartment normalized per body
weight (Jelliffe et al. 2014, Ther Drug Monit; structural parameters
carried from Reuning et al. 1973).
|
|
Digoxin
(Zhou 2010)
|
One-compartment first-order oral absorption population PK model of
digoxin in older Chinese patients (Zhou 2010, Acta Pharmacol Sin);
concomitant spironolactone, body weight, and serum creatinine modify
Cl/F via multiplicative linear-deviation terms.
|
|
Dihydroartemisinin
(Tarning 2012)
|
One-compartment population PK model for oral dihydroartemisinin (parent
drug, dosed as a fixed-dose tablet co-formulated with piperaquine) in 24
pregnant (second / third trimester) and 24 matched non-pregnant women
with uncomplicated malaria on the Thai-Myanmar border (Tarning 2012
AAC). Transit-compartment absorption with 7 fixed transit compartments
(ktr = (n+1)/MTT with n=7); drug-transit rate is set equal to the
absorption rate from the last transit to central (single estimated ktr).
Allometric scaling of CL/F (exponent 3/4) and V/F (exponent 1) on body
weight centered at the cohort median 48.5 kg. F fixed at 1 with
log-normal IIV (CV 30.3%); proportional pregnancy effect on F (-37.5%)
and linear effect of log10 admission parasitaemia on F (+27.8% per log10
unit centered at 3.98). IIV on V/F (12.8% CV); between-occasion
variability (BOV across 3 dose occasions) on MTT (50.9% CV) multiplexed
by the OCC indicator. Additive residual on natural-log concentrations
(sigma = 0.580), encoded as proportional residual on the
linear-concentration scale per Kloprogge 2018 lumefantrine precedent.
Companion file Tarning_2012_piperaquine.R models the co-administered
piperaquine arm.
|
|
Dilmapimod
(Yang 2016)
|
Three-compartment IV population PK model for dilmapimod (SB-681323, a
p38 MAPK inhibitor) coupled with an empirical indirect-response model
for the inflammatory biomarker C-reactive protein (CRP) in severe-trauma
adults at risk for acute respiratory distress syndrome (Yang 2016). BMI
is a power covariate on CL and Q2. No statistically significant
dilmapimod effect on CRP was retained in the final PD model, so the CRP
component is an empirical post-injury production-decline /
first-order-loss profile that is decoupled from dilmapimod exposure
(Yang 2016 Results section 3.3.1).
|
|
Dimethyltryptamine
alphaPower (Eckernas 2023)
|
Effect-compartment sigmoidal Imax PK/PD model for the suppression of EEG
alpha power by intravenous N,N-dimethyltryptamine (DMT) in healthy
adults (Eckernas 2023). Plasma DMT is described by a two-compartment
model with first-order elimination from the central compartment whose
parameters are fixed from the upstream population PK analysis (Eckernas
2022, reproduced in Table S1). Alpha power is driven by the effect-site
(biophase) concentration through a sigmoidal Imax function with Imax
fixed to 1, i.e. DMT is able to fully suppress alpha power.
Between-subject variability is on baseline alpha power (with a
negatively skewed Box-Cox transformation of the eta) and on the
effect-site IC50; between-occasion variability is on baseline alpha
power. Residual variability on alpha power is proportional.
|
|
Dimethyltryptamine
betaPower (Eckernas 2023)
|
Effect-compartment sigmoidal Imax PK/PD model for the suppression of EEG
beta power by intravenous N,N-dimethyltryptamine (DMT) in healthy adults
(Eckernas 2023). Plasma DMT is described by a two-compartment model with
first-order elimination from the central compartment whose parameters
are fixed from the upstream population PK analysis (Eckernas 2022,
reproduced in Table S1). Beta power is driven by the effect-site
(biophase) concentration through a sigmoidal Imax function; unlike alpha
power, suppression is only partial, with Imax estimated at 0.70.
Between-subject variability is on baseline beta power and on the
effect-site IC50 as a correlated block; between-occasion variability is
on baseline beta power. Residual variability on beta power is
proportional.
|
|
Dimethyltryptamine
LZc (Eckernas 2023)
|
Effect-compartment sigmoidal Emax PK/PD model for the increase in EEG
signal diversity, measured as the Lempel-Ziv complexity (LZc) score,
produced by intravenous N,N-dimethyltryptamine (DMT) in healthy adults
(Eckernas 2023). Plasma DMT is described by a two-compartment model with
first-order elimination from the central compartment whose parameters
are fixed from the upstream population PK analysis (Eckernas 2022,
reproduced in Table S1). The LZc score is driven by the effect-site
(biophase) concentration through a sigmoidal Emax function with a
maximum relative increase of about 10% over baseline. Between-subject
variability is on baseline LZc, on the effect-site EC50 and on Emax;
between-occasion variability is on baseline LZc. Residual variability on
the LZc score is additive.
|
|
Docetaxel
(Janssen 2023)
|
Semi-physiological enriched three-compartment population PK model for
intravenous docetaxel in pregnant cancer patients, applying gestational
changes in AAG binding, glomerular filtration, hepatic plasma flow,
CYP3A4 activity and body fluid volumes to the non-pregnant Koolen 2010
base model
|
|
Docetaxel
(Koolen 2010)
|
Five-compartment population PK model for intravenous and oral docetaxel
with concomitant oral ritonavir in 36 adults with advanced cancer.
Docetaxel: depot + single transit (Savic-style; ktr = 2/MAT) + three
disposition compartments (central, peripheral1, peripheral2) with
Bruno-style 3-compartment IV disposition (V_central, V_peripheral1,
V_peripheral2; Q1 central-peripheral1, Q2 central-peripheral2).
Clearance is parameterised via a well-stirred hepatic-extraction model
(Wilkinson 1975) so that elimination is driven by intrinsic clearance
CLi modulated by ritonavir plasma concentration via competitive
inhibition (Ki = 0.028 ug/mL); CL = Q_hep * CLi / (CLi + Q_hep) with
Q_hep fixed at 80 L/h. Hepatic bioavailability F_hep = Q_hep / (CLi +
Q_hep) multiplies the depot -> transit transition to encode oral
first-pass extraction. Gut bioavailability F_gut switches between F_doc
= 0.19 (no ritonavir) and F_RTV = 0.39 (concomitant ritonavir, gated by
the binary covariate CONMED_RTV). Polysorbate-80-driven micelle
sequestration after IV docetaxel is encoded by a route-dependent central
volume (V_central_iv = 9.8 L vs V_central_po = 44 L; gated by the binary
per-dose-record covariate ROUTE_IV). Embedded one-compartment
first-order-absorption ritonavir PK (depot_rtv + central_rtv) carries
fixed typical-value parameters from Kappelhoff 2005 (CL/F = 10.5 L/h,
V/F = 96.6 L, ka = 0.871 1/h, Tlag = 0.778 h) so that the ritonavir
concentration that drives docetaxel CLi-inhibition is simulated within
this single model file (modellib(‘Kappelhoff_2005_ritonavir’) is the
upstream source). Inter-individual variability on CLi,0, V_central_iv,
V_central_po, MAT, F_depot (shared between F_doc and F_RTV), and Ki;
correlated etas for CLi,0 ~ V_central_iv (rho = 0.446). Proportional
residual error is encoded at the final-model typical value (32%); the
source paper’s separately-estimated higher 63% proportional RUV for the
first 4 hours after oral administration is documented in the validation
vignette’s Assumptions and deviations section. Inter-occasion
variability on CLi,0 (22%), MAT (52%), and F_RTV (44%) reported in the
source is not propagated – see vignette Assumptions and deviations.
|
|
Docetaxel
(Ozawa 2007)
|
Three-compartment IV PK coupled with a modified Friberg-style
semimechanistic-physiological PK/PD model for docetaxel-induced
neutropenia in Japanese cancer patients (Ozawa 2007). The PD layer
extends Friberg 2002 with an additional zero-order input compartment
that captures the transient ANC increase attributable to dexamethasone
premedication; alpha-1 acid glycoprotein modulates the linear
drug-effect slope on the proliferating compartment via a power-law form.
Per-subject baseline ANC is supplied as a covariate and is used to
initialise the proliferation, transit, and circulating compartments.
|
|
Docetaxel
(Puisset 2007)
|
Friberg-style semi-mechanistic myelosuppression PD model for
docetaxel-induced neutropenia in adult cancer patients (Puisset 2007).
PD-only: docetaxel plasma concentration is supplied as the time-varying
CP_MGL covariate (mg/L) and drives a linear drug effect E_drug = Slope *
CP_MGL on the proliferating compartment. The five-compartment Friberg PD
chain (one proliferating pool, three transit compartments, one
circulating ANC compartment) and feedback (Circ0 / circ)^gamma reproduce
the structure of Friberg LE et al. (2002) J Clin Oncol 20(24):4713-4721.
Three covariates retained in the published final covariate model act
multiplicatively on Slope: alpha-1 acid glycoprotein (AAG) as a power
form (AAG / 1.29)^(-0.72), prior chemotherapy >= 2 lines
(PRIOR_CHEMO_LINES_GE2) as a 1.69-fold multiplier, and treatment centre
Toulouse vs Paris (STUDY_TOULOUSE) as a 1.82-fold multiplier (the centre
effect is acknowledged by the authors to most likely reflect a
between-centre HPLC-assay bias on docetaxel concentration rather than a
clinical PD covariate). The upstream docetaxel PK was held fixed at
Baille 1997 / Bruno 1996 individual posthoc profiles during the
published PD fit; users couple this model with their preferred docetaxel
popPK (e.g. modellib(‘Ozawa_2007_docetaxel’) or
modellib(‘Netterberg_2017_docetaxel’)) to drive CP_MGL.
|
|
Docetaxel
(Rietveld 2025)
|
Integrated plasma + tumour population PK model for docetaxel (DTX)
delivered as CPC634, a core-crosslinked polymeric micelle that
covalently entraps DTX via a pH-responsive sulfone-ester linker
(Rietveld 2025). Released / conventional DTX is described by a canonical
three-compartment IV plasma model (central, peripheral1, peripheral2;
CL, Vc, Q1, Vp1, Q2, Vp2). Unreleased DTX (still bound to CPC634) is
described by a two-compartment plasma model on the paper-specific
compartments entrapped + peripheral_entrapped with linear elimination
CLcpc and intercompartmental clearance Qcpc. Release of DTX from CPC634
in plasma is time-dependent: six first-order release rates K122 / K123 /
K124 / K125 / K126 / K12 active in the post-dose time windows 0-0.5 /
0.5-1 / 1-2 / 2-6 / 6-168 / 168+ hours (paper Methods 2.6 + Figure 1A).
The two tumour-tissue states tumor_entrapped (unreleased DTX in tumour)
and tumor_released (released DTX in tumour) are connected to plasma by
an influx parameter Kbtn (unreleased DTX, one-way plasma -> tumour)
and an in/efflux balance parameter KbtDTX (released DTX), and to each
other by the tumour-local release rate KrelT; both share the same tumour
distribution volume VcT (paper Methods 2.7). Inter-individual
variability on CL (released-DTX clearance), Vcpc (CPC634 central
volume), and K122 (first-window release rate). Additive-on-log residual
error (equivalent to proportional in linear space) estimated separately
for the four therapeutically relevant observation streams (released-DTX
plasma, unreleased-DTX plasma, released-DTX tumour, total-DTX tumour).
Pragmatic deviations from the published model: (1) the $MIXTURE on Qcpc (subpopulation 1, P = 0.69, Qcpc1 =
0.00122 L/h; subpopulation 2, Qcpc2 = 0.00769 L/h) is encoded as a
typical value at the dominant subpopulation 1 (Qcpc = Qcpc1); the
minority Qcpc2 = 0.00769 L/h is documented in the vignette Assumptions
and deviations section and can be plugged in by overriding lqcpc <-
log(0.00769) at simulation time. (2) The 89Zr-CPC634 radiotracer arm of
the PICCOLO PET imaging study (compartments 6 and 7 in the supplement;
fast-loss rate K002 = 0.336 1/h active in the first 2 h after the 89Zr
dose) is omitted -- the radiotracer arm shared the unreleased DTX
disposition parameters (Vcpc / VPcpc / Qcpc / CLcpc) so it added no
structural information beyond what entrapped already carries. See the
vignette Assumptions and deviations section. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Chandasana_2024_dolutegravir_lamivudine.html">Dolutegravir
(Chandasana 2024)</a> </td>
<td style="text-align:left;"> One-compartment oral population
PK model with first-order absorption and elimination for dolutegravir 50
mg once daily as the dolutegravir/lamivudine fixed-dose combination in
virologically suppressed adults living with HIV-1 (TANGO; Chandasana
2024) </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Chandasana_2024_abacavir_dolutegravir_lamivudine_pediatric.html">Dolutegravir
(Chandasana 2024b)</a> </td>
<td style="text-align:left;"> One-compartment oral population
PK model with first-order absorption, allometric weight scaling and a
postmenstrual-age enzyme-maturation function on clearance for
dolutegravir in infants, children and adolescents with HIV-1, applied
without re-estimation to the ABC/DTG/3TC fixed-dose combination
(dispersible tablet and tablet) in IMPAACT 2019 (Chandasana 2024)
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Zhang_2015_dolutegravir.html">Dolutegravir
(Zhang 2015)</a> </td>
<td style="text-align:left;"> One-compartment oral population
PK model with first-order absorption, absorption lag time, and
first-order elimination for dolutegravir (integrase strand transfer
inhibitor) in HIV-1-infected treatment-naive adults (Zhang 2015)
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Wojciechowski_2022_domagrozumab.html">Domagrozumab
(Wojciechowski 2022)</a> </td>
<td style="text-align:left;"> Quasi-steady-state TMDD
population PK/PD model for domagrozumab (anti-myostatin IgG1) in healthy
adult volunteers and pediatric patients with Duchenne muscular dystrophy
(Wojciechowski 2022): two-compartment IV/SC drug disposition with
parallel linear and Michaelis-Menten elimination, a
synthesis-degradation total-myostatin compartment with drug-mediated
internalization, and a study-population covariate (DIS_DMD) shifting
myostatin baseline and turnover. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Khwarg_2024_donepezil.html">Donepezil
im (Khwarg 2024)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model for long-acting intramuscular donepezil (GB-5001) with three-phase
absorption: two lagged parallel first-order depots plus a simultaneous
zero-order input, in healthy adult men </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Khwarg_2024_donepezil.html">Donepezil
oral (Khwarg 2024)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model for oral donepezil (Aricept 10 mg tablet) with first-order
absorption and an absorption lag time, in healthy adult men </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Diep_2026_donidalorsen.html">Donidalorsen
(Diep 2026)</a> </td>
<td style="text-align:left;"> Two-compartment population PK and
indirect-response PD model for the GalNAc3-conjugated antisense
oligonucleotide donidalorsen targeting prekallikrein (PKK) mRNA, fit to
pooled data from phase 1 to phase 3 studies in healthy volunteers and
patients with hereditary angioedema (Diep 2026). First-order SC
absorption with categorical covariates on ka (arm vs abdomen/thigh
injection site; autoinjector vs vial drug presentation), allometric
scaling of CL/F, Vc/F, Q/F, and Vp/F on total body weight with
paper-estimated exponents, multiplicative disease-status effects on Vc/F
and Q/F, full 5x5 omega block on PK random effects, and an
indirect-response model with donidalorsen-driven inhibition of PKK
production carrying multiplicative disease-status effects on baseline
PKK and IC50. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Singh_2025_donidalorsen.html">Donidalorsen
(Singh 2025)</a> </td>
<td style="text-align:left;"> Longitudinal exposure-response
model relating per-4-week normalized hereditary angioedema (HAE) attack
rate to 4-week-averaged plasma prekallikrein (PKK) concentration in
adult and adolescent HAE patients receiving subcutaneous donidalorsen
(Singh 2025). Sigmoidal Emax response driven by PKK with per-subject
covariate effects of baseline HAE attack rate on Emax (power form) and
baseline PKK on EC50 (power form). IIV on Emax (log-normal, CV 27.9%)
and Hill (log-normal, CV 131%); no IIV on EC50 in the final model (the
paper reports the EC50-IIV variant was numerically unstable during
stepwise covariate evaluation). Per-4-week attack count is drawn from a
Poisson likelihood with mean equal to the sigmoidal attack rate; the
paper's generalized-Poisson dispersion parameter is not reported so
extraction uses the standard Poisson approximation (documented in
vignette Errata). Age, body weight, sex, and treatment-emergent ADA
status were screened but not retained in the final model. Upstream PKK
trajectories are generated by the paired Diep 2026 popPK/PD model
(modellib('Diep_2026_donidalorsen')); this exposure-response model
consumes the 4-week-averaged PKK as a time-varying covariate.
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/AbdulAziz_2016_doripenem.html">Doripenem
(AbdulAziz 2016)</a> </td>
<td style="text-align:left;"> Two-compartment IV population PK
model for doripenem in 12 Malaysian critically ill adults with sepsis
receiving 500 mg as a 1-hour infusion every 8 hours (Abdul-Aziz 2016).
Reported on free (unbound) doripenem; observed total concentrations were
corrected by multiplying by 0.90 to account for ~10% protein binding.
Body-weight allometric scaling is fixed (0.75 on CL/Q, 1 on V1/V2,
reference 70 kg); Cockcroft-Gault creatinine clearance has an
exponential effect on CL centred at the cohort mean 82.5 mL/min.
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Lee_2017_doripenem.html">Doripenem
(Lee 2017)</a> </td>
<td style="text-align:left;"> One-compartment IV-infusion
population PK model for doripenem in 37 Korean adults with acute
infections (pyelonephritis, intra-abdominal infection, neutropenic
fever) and CLCR ranging 20-50 or >50 mL/min (Lee 2017). Clearance and
central volume scale linearly with body weight (CL/WT = 0.109 L/h/kg,
V/WT = 0.280 L/kg at WT=70 kg, CLCR=57 mL/min); CL additionally scales
by a power exponent on Cockcroft-Gault creatinine clearance (raw mL/min,
reference 57). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/LopezArguello_2023_pbp_binding_pseudomonas.html">Doripenem
qsp (LopezArguello 2023)</a> </td>
<td style="text-align:left;"> QSP. In vitro (Pseudomonas
aeruginosa PAO1). Whole-cell penicillin-binding protein (PBP)
covalent-binding model for doripenem (carbapenem): seven coupled ODEs
for the rate of net influx of drug across the outer membrane into
periplasm and the competitive, mass-balanced acylation of six PBPs (1a,
1b, 2, 3, 4, 5/6) counted as molecules per bacterial cell. The intact
parameter switches between the intact whole-cell assay
(penetration-limited; drug enters periplasm at Rate_Influx/access) and
the lysed isolated-membrane assay (no outer membrane; a vast excess of
drug molecules is present at time 0). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Wang_2023_dorzagliatin.html">Dorzagliatin
(Wang 2023)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model for oral dorzagliatin (HMS5552, a first-in-class dual-acting
glucokinase activator approved in China for type 2 diabetes mellitus) in
healthy subjects and patients with T2DM (Wang 2023; N = 1062 subjects,
7686 concentrations pooled from six clinical trials). Disposition is a
two-compartment model with sequential zero-order then first-order oral
absorption (dose enters the depot over a zero-order window of duration
D1 = 0.418 h, then is absorbed first-order at ka = 3.29 h^-1) and
first-order elimination from the central compartment. Typical values for
a 69 kg, 55-year-old male with AST 18 U/L enrolled in the later-phase
studies are CL/F = 10.4 L/h, Vc/F = 80.6 L, Q/F = 3.02 L/h and Vp/F =
26.5 L. CL/F carries three power covariate effects plus one study
indicator: (WT/69)^0.255, (AST/18)^-0.103, (AGE/55)^-0.135 and a
multiplicative exp(0.203) = 1.23 uplift for the three early-phase
studies (HMM0102 / HMM0103 / HMM0110), which the paper attributes to a
formulation / bioavailability difference that could not be resolved as
an F effect. Vc/F carries (WT/69)^0.553 and a multiplicative exp(-0.170)
= 0.843 factor in females (15.7% lower than males). D1 carries
exp(0.816) = 2.26 when food is consumed at least 1 h after dosing rather
than 0.5 h after dosing. Because sex acts only on Vc/F and the
meal-timing effect only on D1, neither changes steady-state AUCtau (the
paper reports 0.01% and 0% respectively) while both shift Cmax,ss and
Cmin,ss. Inter-individual variability is a correlated CL/F-Vc/F block
(approximate CV 22.5% and 14.9%; covariance 0.0181) plus independent
terms on Vp/F (48.8%) and D1 (82.8%); ka and Q/F carry no IIV. Residual
error is combined additive plus proportional (109 ng/mL and 32.9%).
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Kuchimanchi_2024_dostarlimab.html">Dostarlimab
(Kuchimanchi 2024)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model for dostarlimab (anti-PD-1 IgG4) with sigmoid I_max time-dependent
clearance, fitted to GARNET (advanced solid tumours) plus RUBY Part 1
(primary advanced or recurrent endometrial cancer with
carboplatin-paclitaxel) data (Kuchimanchi 2024) </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Melhem_2022_dostarlimab.html">Dostarlimab
(Melhem 2022)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model for dostarlimab (anti-PD-1 IgG4) with time-dependent (sigmoid
I_max) clearance in adults with advanced solid tumours (Melhem 2022)
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Freyer_2000_AVI_regimen.html">Doxorubicin
(Freyer 2000)</a> </td>
<td style="text-align:left;"> One-compartment IV population PK
model for doxorubicin in 24 small cell lung cancer patients on the AVI
regimen (Freyer 2000). Structural reduction from the paper's
three-compartment model: only central CL and V were reported in Table 2,
so the peripheral compartments are omitted. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Janssen_2023_pregnancy_cytotoxics.html">Doxorubicin
(Janssen 2023)</a> </td>
<td style="text-align:left;"> Semi-physiological enriched
two-compartment population PK model for intravenous doxorubicin in
pregnant cancer patients, applying gestational changes in albumin
binding, glomerular filtration, hepatic plasma flow, CYP3A4 activity and
body fluid volumes to the non-pregnant Joerger 2007 base model
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Kunarajah_2017_doxorubicin.html">Doxorubicin
(Kunarajah 2017)</a> </td>
<td style="text-align:left;"> Population PK/PD model for IV
doxorubicin (3-compartment) with first-order metabolism to doxorubicinol
(1-compartment) and a cardiac troponin I (cTnI) turnover sub-model in
paediatric oncology patients (Kunarajah 2017). Body surface area enters
as a linear factor on every clearance and volume parameter; age enters
as an additional power factor on doxorubicin clearance. The cTnI
turnover sub-model is driven by a saturable Emax stimulation of cTnI
synthesis by the combined doxorubicin + doxorubicinol plasma
concentration, with the cTnI baseline shifted linearly by the prior
cumulative anthracyclines dose received by the patient before the first
dose analysed. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/PerezBlanco_2016_doxorubicin.html">Doxorubicin
(PerezBlanco 2016)</a> </td>
<td style="text-align:left;"> Joint population PK model for IV
doxorubicin (DOX, 3-compartment) and its active C-13 alcohol metabolite
doxorubicinol (DOXol, 2-compartment) in adult patients with
non-Hodgkin's lymphoma receiving R-CHOP chemotherapy (Perez-Blanco
2016). DOX was administered as a 0.5-h IV infusion at the protocol dose
of 50 mg/m^2. The fraction Fm = 0.22 of total DOX clearance is routed to
DOXol formation; the remaining (1 - Fm) fraction represents non-DOXol
elimination pathways. The five volumes of distribution (V1/V2/V3 for DOX
and V4/V5 for DOXol) were held fixed during estimation: the DOX volumes
to the Kontny 2013 (doi:10.1007/s00280-013-2261-3) adult-reference
values, and the DOXol volumes to the values obtained from a sensitivity
analysis carried out for that purpose. No covariates were retained in
the final model; bilirubin and AST showed an influence on CL and CLm but
the OFV decrease was not statistically significant. Residual variability
is proportional for both DOX and DOXol. This was the first published
two-compartment DOXol popPK model. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Mody_2023_doxorubicin_dexrazoxane_breast_cancer.html">Doxorubicin
dexrazoxane clinical jimt1 (Mody 2023)</a> </td>
<td style="text-align:left;"> In vitro to clinical translation
(JIMT-1 human breast cancer cell line; HER2-expressing,
trastuzumab-resistant breast cancer) of the doxorubicin (DOX) +
dexrazoxane (DEX) anticancer pharmacodynamic model (Mody 2023 Methods,
'In vitro-in vivo translation of PD responses'; Figure 6). The in-vitro
cellular PD model of Mody_2023_doxorubicin_dexrazoxane_jimt1 is driven
here by clinically relevant TUMOUR-SITE concentrations instead of
cell-culture-medium concentrations. Clinical plasma PK is reproduced
from the companion paper (Mody 2023 Sci Rep 13:3100,
doi:10.1038/s41598-023-29964-4): DOX is a 3-compartment mammillary model
with linear elimination and DEX a 2-compartment mammillary model
parameterised by rate constants, both given as 15-min IV infusions for a
typical 1.8 m^2 body-surface-area subject. Tumour-site concentrations
are obtained by scaling the simulated plasma concentrations by a total
tumour:plasma AUC ratio, kp_tumor_dox = 57.1 (digitised from He 2018
human tumour distribution data) and kp_tumor_dexrazoxane, which is
ARBITRARY because no DEX tumour-distribution data exist (the paper
simulates 0.1, 1 and 10). Plasma concentrations in mg/L are converted to
uM at the PK-PD interface using literature molar masses. The paper's
simulated regimen is DOX 50 mg/m^2 Q3W with DEX 500 mg/m^2 (a 10:1
DEX:DOX ratio, previously identified as maximally cardioprotective) over
three cycles. For JIMT-1 the paper predicts a HIGHER AUEC of percent
cell viability for DOX + DEX than for DOX alone (about 1560-fold), i.e.
LESS tumour-cell killing when DEX is added, consistent with the
antagonistic in-vitro interaction. An arbitrary 10% CV inter-individual
variability is applied to the PD parameters and to both tumour:plasma
ratios, exactly as the paper's 500-subject population simulation does;
these are simulation conventions, not fitted variances, and are wrapped
in fixed(). Sibling models:
Mody_2023_doxorubicin_dexrazoxane_clinical_mdamb468,
Mody_2023_doxorubicin_dexrazoxane_jimt1 (the in-vitro fit these PD
parameters come from) and
Mody_2023_doxorubicin_dexrazoxane_static_jimt1. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Mody_2023_doxorubicin_dexrazoxane_breast_cancer.html">Doxorubicin
dexrazoxane clinical mdamb468 (Mody 2023)</a> </td>
<td style="text-align:left;"> In vitro to clinical translation
(MDA-MB-468 human breast cancer cell line; triple-negative breast
cancer) of the doxorubicin (DOX) + dexrazoxane (DEX) anticancer
pharmacodynamic model (Mody 2023 Methods, 'In vitro-in vivo translation
of PD responses'; Figure 6). The in-vitro cellular PD model of
Mody_2023_doxorubicin_dexrazoxane_mdamb468 is driven here by clinically
relevant TUMOUR-SITE concentrations instead of cell-culture-medium
concentrations. Clinical plasma PK is reproduced from the companion
paper (Mody 2023 Sci Rep 13:3100, doi:10.1038/s41598-023-29964-4): DOX
is a 3-compartment mammillary model with linear elimination and DEX a
2-compartment mammillary model parameterised by rate constants, both
given as 15-min IV infusions for a typical 1.8 m^2 body-surface-area
subject. Tumour-site concentrations are obtained by scaling the
simulated plasma concentrations by a total tumour:plasma AUC ratio,
kp_tumor_dox = 57.1 (digitised from He 2018 human tumour distribution
data) and kp_tumor_dexrazoxane, which is ARBITRARY because no DEX
tumour-distribution data exist (the paper simulates 0.1, 1 and 10).
Plasma concentrations in mg/L are converted to uM at the PK-PD interface
using literature molar masses. The paper's simulated regimen is DOX 50
mg/m^2 Q3W with DEX 500 mg/m^2 (a 10:1 DEX:DOX ratio, previously
identified as maximally cardioprotective) over three cycles. For
MDA-MB-468 the paper predicts a COMPARABLE AUEC of percent cell
viability across the DOX and DOX + DEX groups, consistent with the
additive in-vitro interaction. An arbitrary 10% CV inter-individual
variability is applied to the PD parameters and to both tumour:plasma
ratios, exactly as the paper's 500-subject population simulation does;
these are simulation conventions, not fitted variances, and are wrapped
in fixed(). Sibling models:
Mody_2023_doxorubicin_dexrazoxane_clinical_jimt1,
Mody_2023_doxorubicin_dexrazoxane_mdamb468 (the in-vitro fit these PD
parameters come from) and
Mody_2023_doxorubicin_dexrazoxane_static_mdamb468. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Mody_2023_doxorubicin_dexrazoxane_breast_cancer.html">Doxorubicin
dexrazoxane jimt1 (Mody 2023)</a> </td>
<td style="text-align:left;"> In vitro (JIMT-1 human breast
cancer cell line; HER2-expressing, trastuzumab-resistant breast cancer).
Cellular-level pharmacodynamic (PD) model for the single-agent and
combined anticancer effects of doxorubicin (DOX) and dexrazoxane (DEX)
on percent cell viability over 96 h (Mody 2023 Eqs 3, 3a-3e and 4a-4i;
Table 2, JIMT-1 column). Both drugs degrade in the cell culture medium
by first-order kinetics, so their driving concentrations are dosable
one-compartment states conc_dox and conc_dexrazoxane that decay with
kdeg (Mody 2023 Sci Rep Eqs 1-2, rate constants restated in this paper's
Results). Each drug stimulates cell death through a capacity-limited
Hill function whose signal is delayed by a three-compartment
signal-transduction transit chain (transit1_<drug> to
transit3_<drug>, first-order rate ktr = 1/tau). The two terminal
transit signals act ADDITIVELY on the loss term of an exponentially
growing viability state (Eq 4i). The drug-drug interaction parameter psi
multiplies the DOX half-maximal killing concentration kc50_dox ONLY (Eq
4a); psi > 1 is antagonistic, psi < 1 synergistic and psi = 1
additive. Estimated psi is 2 (antagonistic) in JIMT-1. Setting psi = 1
recovers the paper's single-agent DOX equations (Eq 3a-3e) exactly,
which is how the single-agent arms were fitted. No IIV or residual error
was estimated (Table 2 reports point estimates with %RSE only); an
arbitrary 10% CV IIV is introduced at simulation time per the paper's
Methods. Sibling models: Mody_2023_doxorubicin_dexrazoxane_mdamb468 (the
other cell line), Mody_2023_doxorubicin_dexrazoxane_static_jimt1 (the
72-h static concentration-response fit) and
Mody_2023_doxorubicin_dexrazoxane_clinical_jimt1 (the same PD model
driven by clinical tumour-site concentrations). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Mody_2023_doxorubicin_dexrazoxane_breast_cancer.html">Doxorubicin
dexrazoxane mdamb468 (Mody 2023)</a> </td>
<td style="text-align:left;"> In vitro (MDA-MB-468 human breast
cancer cell line; triple-negative breast cancer). Cellular-level
pharmacodynamic (PD) model for the single-agent and combined anticancer
effects of doxorubicin (DOX) and dexrazoxane (DEX) on percent cell
viability over 96 h (Mody 2023 Eqs 3, 3a-3e and 4a-4i; Table 2,
MDA-MB-468 column). Both drugs degrade in the cell culture medium by
first-order kinetics, so their driving concentrations are dosable
one-compartment states conc_dox and conc_dexrazoxane that decay with
kdeg (Mody 2023 Sci Rep Eqs 1-2, rate constants restated in this paper's
Results). Each drug stimulates cell death through a capacity-limited
Hill function whose signal is delayed by a three-compartment
signal-transduction transit chain (transit1_<drug> to
transit3_<drug>, first-order rate ktr = 1/tau). The two terminal
transit signals act ADDITIVELY on the loss term of an exponentially
growing viability state (Eq 4i). The drug-drug interaction parameter psi
multiplies the DOX half-maximal killing concentration kc50_dox ONLY (Eq
4a); psi > 1 is antagonistic, psi < 1 synergistic and psi = 1
additive. Estimated psi is 1 (additive) in MDA-MB-468. Setting psi = 1
recovers the paper's single-agent DOX equations (Eq 3a-3e) exactly,
which is how the single-agent arms were fitted. No IIV or residual error
was estimated (Table 2 reports point estimates with %RSE only); an
arbitrary 10% CV IIV is introduced at simulation time per the paper's
Methods. Sibling models: Mody_2023_doxorubicin_dexrazoxane_jimt1 (the
other cell line), Mody_2023_doxorubicin_dexrazoxane_static_mdamb468 (the
72-h static concentration-response fit) and
Mody_2023_doxorubicin_dexrazoxane_clinical_mdamb468 (the same PD model
driven by clinical tumour-site concentrations). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Mody_2023_doxorubicin_dexrazoxane_breast_cancer.html">Doxorubicin
dexrazoxane static jimt1 (Mody 2023)</a> </td>
<td style="text-align:left;"> In vitro (JIMT-1 human breast
cancer cell line; HER2-expressing, trastuzumab-resistant breast cancer).
Static 72-h concentration-response model for doxorubicin (DOX) and
dexrazoxane (DEX) alone and in combination (Mody 2023 Eqs 1 and 2; Table
1, JIMT-1 columns). This is the ALGEBRAIC endpoint model, not a
time-course model: it predicts percent cell viability at 72 h as a
function of the two nominal applied concentrations, which enter as the
covariates CONC_DOXORUBICIN and CONC_DEXRAZOXANE rather than as ODE
states. The combination is described by the Chakraborty-Jusko / Pawaskar
competitive interaction model (Eq 2), in which the interaction parameter
psi scales the half-maximal inhibitory concentration of BOTH drugs; psi
> 1 is antagonistic, psi < 1 synergistic and psi = 1 additive.
Estimated psi is 1.11 (modestly antagonistic) in JIMT-1. The
single-agent Imax and IC50 values were FIXED from the Eq-1 single-agent
concentration-response fits and only psi was estimated (Monolix 2016R1).
Setting either concentration to zero and psi to 1 recovers the
single-agent inhibitory Hill model of Eq 1. Sibling models:
Mody_2023_doxorubicin_dexrazoxane_static_mdamb468 (the other cell line)
and Mody_2023_doxorubicin_dexrazoxane_jimt1 (the time-course PD model
fitted to the same cells). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Mody_2023_doxorubicin_dexrazoxane_breast_cancer.html">Doxorubicin
dexrazoxane static mdamb468 (Mody 2023)</a> </td>
<td style="text-align:left;"> In vitro (MDA-MB-468 human breast
cancer cell line; triple-negative breast cancer). Static 72-h
concentration-response model for doxorubicin (DOX) and dexrazoxane (DEX)
alone and in combination (Mody 2023 Eqs 1 and 2; Table 1, MDA-MB-468
columns). This is the ALGEBRAIC endpoint model, not a time-course model:
it predicts percent cell viability at 72 h as a function of the two
nominal applied concentrations, which enter as the covariates
CONC_DOXORUBICIN and CONC_DEXRAZOXANE rather than as ODE states. The
combination is described by the Chakraborty-Jusko / Pawaskar competitive
interaction model (Eq 2), in which the interaction parameter psi scales
the half-maximal inhibitory concentration of BOTH drugs; psi > 1 is
antagonistic, psi < 1 synergistic and psi = 1 additive. Estimated psi
is 0.84 (modestly synergistic) in MDA-MB-468. The single-agent Imax and
IC50 values were FIXED from the Eq-1 single-agent concentration-response
fits and only psi was estimated (Monolix 2016R1). Setting either
concentration to zero and psi to 1 recovers the single-agent inhibitory
Hill model of Eq 1. Sibling models:
Mody_2023_doxorubicin_dexrazoxane_static_jimt1 (the other cell line) and
Mody_2023_doxorubicin_dexrazoxane_mdamb468 (the time-course PD model
fitted to the same cells). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Hopkins_2017_doxycycline.html">Doxycycline
(Hopkins 2017)</a> </td>
<td style="text-align:left;"> Two-compartment oral population
PK model for doxycycline with two transit absorption compartments,
fat-free-mass allometric scaling (CL exponent 0.75, V exponent 1.0,
reference 70 kg FFM), and Doryx tablet (reference) / Doryx MPC
delayed-release tablet / Doryx capsule formulation effects on relative
bioavailability and absorption rate, plus a food (fed-status) effect on
relative bioavailability and a formulation-dependent food effect on
transit rate, plus a 14.4% increase in CL for female sex. Pooled from
eight phase 1 healthy-volunteer trials (n = 178). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Foo_2016_droperidol.html">Droperidol
(Foo 2016)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model with first-order absorption for intramuscular droperidol in 41
acutely agitated adults presenting to the emergency department (Foo
2016). Absorption rate constant ka and its IIV are fixed (ka = 10 1/h,
omega_ka^2 = 1) because the available samples did not characterise
absorption. A single shared random effect drives both CL and Vc (Table 2
footnote a: 'The same random effect was used for both Vc and CL'); Q and
Vp have no IIV. No covariates were retained -- coingestion of alcohol
was screened but not associated with CL or Vc, and patient weight was
not available (Methods). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Kovalenko_2016_dupilumab.html">Dupilumab
(Kovalenko 2016)</a> </td>
<td style="text-align:left;"> Dupilumab exploratory population
PK model (Kovalenko 2016; 2-cmt with parallel linear + Michaelis-Menten
elimination) </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Kovalenko_2020_dupilumab.html">Dupilumab
(Kovalenko 2020)</a> </td>
<td style="text-align:left;"> Dupilumab PK model (Kovalenko
2020) </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Zhang_2021_dupilumab.html">Dupilumab
(Zhang 2021)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model for dupilumab in adult and adolescent patients with asthma (Zhang
2021), with first-order SC absorption and parallel linear plus
Michaelis-Menten elimination from the central compartment. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Kapitanov_2025_dupilumab.html">Dupilumab
3cmt qsp (Kapitanov 2025)</a> </td>
<td style="text-align:left;"> QSP. Three-compartment
physiologically-inspired PKRO (piPKRO) model of dupilumab (anti-IL4R
IgG4) with full-binding TMDD in central, a lumped-interstitial
peripheral, and an inflamed-skin site-of-action (SoA) compartment
(Kapitanov 2025 Case Study 3 Approach 2). Extends the 2-compartment Case
Study 2 model by adding a peripheral2 compartment representing 50
percent of the total interstitial skin volume (0.563 L), with dupilumab
distribution parameterised by a fixed skin partition coefficient
(P_dist,13 = 0.3) and a fixed central-to-skin distribution half-time
(t_dist,13 = 30 h). IL4R concentration in the inflamed-skin SoA
compartment is set to 2.02 nM (Table S4) reflecting higher immune-cell
infiltrate and higher per-cell IL4R expression in atopic-dermatitis skin
(Table S5). All other parameters (t_half, P_dist,12, C_R,1, C_R,2,
k_deg, k_on, k_off) are carried unchanged from the Case Study 2 fit. The
lumped peripheral volume V_2 is kept at 12.4 L per Kapitanov 2025 Table
S4 Approach 2 (note: Section 3.3 narrates that V_2 was decreased by
subtracting the SoA volume, but Table S4 Approach 2 reports V_2 = 12.4 L
identical to Case 2 -- this file follows Table S4). The
central-peripheral distribution half-time t_dist,12 = 55.9 h is
recomputed for the 3-cpt structure per Eq 22. Case Study 3 illustrates
that a specific SoA compartment with high local target burden and slow
distribution can lead to substantial local drug depletion and lower
receptor occupancy at the SoA than in the central and lumped-peripheral
compartments (Kapitanov 2025 Figure 5). Deterministic single-subject
typical-value simulation; no IIV / residual error is reported by the
paper. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Kovalenko_2020_dupilumab.html">Dupilumab
base (Kovalenko 2020)</a> </td>
<td style="text-align:left;"> Dupilumab primary base population
PK model from Kovalenko 2020 (Model 3): 2-compartment with parallel
linear + Michaelis-Menten elimination and a 3-transit-compartment SC
absorption chain; fit to Phase 3 atopic-dermatitis data with only body
weight as a covariate of central volume. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Kovalenko_2020_dupilumab.html">Dupilumab
covariate (Kovalenko 2020)</a> </td>
<td style="text-align:left;"> Dupilumab primary covariate
population PK model from Kovalenko 2020 (Model 4): 2-compartment with
parallel linear + Michaelis-Menten elimination and a
3-transit-compartment SC absorption chain; fit to Phase 3
atopic-dermatitis data with body weight + albumin on Vc and BMI + EASI +
race (White) on the linear elimination rate. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Kapitanov_2025_dupilumab.html">Dupilumab
qsp (Kapitanov 2025)</a> </td>
<td style="text-align:left;"> QSP. Two-compartment
physiologically-inspired PKRO (piPKRO) model of dupilumab (anti-IL4R
IgG4) with full-binding TMDD in both the central and lumped-interstitial
peripheral compartment (Kapitanov 2025 Case Study 2, calibrated to
digitised first-in-human single-dose IV PK in healthy volunteers from Li
2015 at 1, 3, 8, and 12 mg/kg). The piPK framework replaces the
classical (CL, Q, V1, V2) parameterisation with the physiological (V1,
V2 = 13 L interstitial, t_half, t_dist, P_dist) macroparameter set of
Kapitanov 2025 Eqs 3-7: drug elimination occurs at the same first-order
rate in every compartment (k_el = log(2)/t_half), the peripheral volume
is fixed at the total- body interstitial volume, and the peripheral
partition coefficient P_dist is a first-class parameter. IL4R is
expressed in both compartments with a bottom-up-derived concentration
(Table S5; central 0.00605 nM, peripheral 0.127 nM); free drug + free
receptor -> drug-receptor complex is described by mass-action forward
binding with k_on = 1e-3 /(nM*s) and k_off = 3.3e-5 /s (K_D = 33 pM per
Kuo 2010; Kapitanov 2025 ref 41). Complex degrades at the same rate as
the free receptor (Section 3.1). Deterministic single-subject
typical-value simulation; no IIV / residual error is reported by the
paper for Case Study 2 and none is encoded here (fixed(0) alternative
was not used because the paper reports no baseline IIV structure).
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Ogasawara_2020_durvalumab.html">Durvalumab
(Ogasawara 2020)</a> </td>
<td style="text-align:left;"> Two compartment PK model of
durvalumab (anti-PD-L1) in patients with hematologic malignancies
(Ogasawara 2020) </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Gisleskog_1999_dutasteride.html">Dutasteride
(Gisleskog 1999)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model for dutasteride (GI198745, a dual type-1/type-2 5-alpha-reductase
inhibitor) in healthy male volunteers after single oral doses, with
first-order absorption, an absorption lag-time, and parallel linear
(CL_l) plus Michaelis-Menten (Vmax / Km) elimination from the central
compartment (Gisleskog 1999). All volumes and clearances are apparent
(oral, no IV reference); bioavailability is assumed dose-independent.
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Keizer_2011_E7820.html">E7820
human (Keizer 2011)</a> </td>
<td style="text-align:left;"> Population PK/PD model for the
alpha2-integrin inhibitor E7820 in patients with advanced solid tumors
or lymphoma (Keizer 2011 clinical column). One-compartment oral PK with
first-order absorption (PK structure and parameter values inherited from
an earlier phase I popPK analysis of the same study and reproduced in
Keizer 2011 Table II; the absorption model was simplified from the
original turnover-absorption form to a first-order form to ease
multi-dose simulations). PD is an indirect-response (turnover) model for
alpha2-integrin expression on platelets, with an Emax inhibition
function (Emax fixed at 1, Hill exponent gamma fixed at 1) acting on the
input rate kin. BSV is reported on baseline integrin expression and on
drug sensitivity (IC50). No tumor-growth submodel is included in the
clinical analysis (Keizer 2011 Figure 3 caption: 'The clinical model had
the same structure, but did not incorporate a sub-model for tumor
size'). Parameter values from Keizer 2011 Tables II (clinical PK) and
III (clinical integrin PD). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Keizer_2011_E7820.html">E7820
mouse (Keizer 2011)</a> </td>
<td style="text-align:left;"> Preclinical (mouse, female nude
with subcutaneous KP-1 pancreatic-carcinoma xenograft). Sequential
PK/PD/tumor-growth model for the alpha2-integrin inhibitor E7820 (Keizer
2011). Stage 1: one-compartment oral PK with first-order absorption,
per-kg parameterisation. Stage 2: indirect-response (turnover) model for
alpha2-integrin expression on platelets, with an Emax inhibition
function (Emax fixed at 1, Hill exponent gamma fixed at 1) acting on the
input rate kin. Stage 3: exponential tumor growth on diameter with an
initial-slow-growth term (1 - exp(-beta*t)) gating the growth rate, and
a sigmoidal Emax inhibition driven by relative alpha2-integrin
inhibition ((I_base - integrin)/I_base) with Hill coefficient fixed at
5. Parameters from Keizer 2011 Tables II (preclinical PK), III
(preclinical integrin PD), and IV (tumor growth). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Lee_2024_eculizumab.html">Eculizumab
(Lee 2024)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model of eculizumab (SB12 proposed biosimilar and reference Soliris)
with a direct inhibitory sigmoid Imax model for terminal complement
activity and a direct sigmoid Emax model linking terminal complement
activity to serum LDH, in healthy subjects and patients with paroxysmal
nocturnal haemoglobinuria (Lee 2024) </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Jonsson_2015_edoxaban.html">Edoxaban
(Jonsson 2015)</a> </td>
<td style="text-align:left;"> Joint parent plus metabolite
population PK model for edoxaban and its main metabolite M4 in adults
with normal kidney function through severe renal impairment, from a
dedicated renal impairment study. Edoxaban disposition is
two-compartment with Savic 2007 analytical transit-compartment
absorption (non-integer NN, with the absorption rate constant
constrained equal to the transit rate constant ktr) and absolute oral
bioavailability estimated on the logit scale; edoxaban clearance is
split into a renal arm that is linear in creatinine clearance and drives
a urinary-excretion compartment, and a non-renal arm that is assumed to
form all of the M4 metabolite. M4 is described by a one-compartment
model with first-order formation. Fixed allometric body-weight scaling
(0.75 on all clearance terms that are not a function of kidney function,
1 on all volumes) is applied around a 70 kg reference subject.
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Niebecker_2015_edoxaban.html">Edoxaban
(Niebecker 2015)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model with first-order absorption and a lag time for edoxaban in adults;
pooled phase 1 healthy volunteers (13 studies) and Hokusai-VTE phase 3
patients with deep-vein thrombosis or pulmonary embolism (Niebecker
2015). Apparent clearance is split into a non-renal component and a
piecewise-linear renal component driven by creatinine clearance, with a
phase-3 patient effect on the upper-CLcr slope and on Q/F. Asian race
increases Vc/F; concomitant P-glycoprotein inhibitors increase phase-1
CL/F and F. The fed-state study 6 has a slower ka and higher non-renal
CL/F (FED covariate). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Stein_2018_mAb_nonlinear_PK.html">Efalizumab
(Stein 2018)</a> </td>
<td style="text-align:left;"> Two-compartment QSS TMDD
typical-value fit for efalizumab (anti-CD11a mAb) used to illustrate the
critical concentration (Ccrit) for nonlinear PK (Stein and Peletier 2018
Table 1) </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Gastonguay_2005_efaproxiral.html">Efaproxiral
(Gastonguay 2005)</a> </td>
<td style="text-align:left;"> Linear 2-compartment IV popPK
model for efaproxiral (RSR13) with an algebraic linear RBC:plasma
proportionality (Crbc = SLPRBC * Cc) and a linear PD model relating
partial pressure of oxygen at 50% hemoglobin saturation (p50, mmHg) to
RBC efaproxiral concentration (p50 = INTp50 + SLPp50 * Crbc). Population
of 451 cancer patients receiving radiation therapy pooled across six
phase I-III trials. Full covariate model: BSA and AGE on CL; BSA, AGE
and baseline albumin (BALB) on V1 and V2; BSA on Q; max administered
dose (MDOS), AGE and BALB on SLPRBC; primary cancer type indicators
(breast, glioma, other; reference = lung) on SLPp50. Three-way
correlated IIV block on CL, V1, V2 plus diagonal IIV on Q, SLPRBC,
INTp50 and SLPp50. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Bienczak_2016_efavirenz.html">Efavirenz
(Bienczak 2016)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model for oral efavirenz in African children (Bienczak 2016), with Savic
2007 transit-compartment absorption (NN = 25 fixed transit compartments
and a separate first-order absorption step ka from the depot to the
central compartment), oral bioavailability fixed to 1 (no intravenous
data), Anderson-Holford allometric scaling of all clearance and volume
parameters to a 15.4 kg reference child (exponents 0.75 on CL and Q, 1.0
on Vc and Vp), and a composite CYP2B6 516G>T (rs3745274) | 983T>C
(rs28399499) SNP-vector effect on apparent oral clearance that
distinguishes six metabolic subgroups (516GG|983TT extensive metabolizer
reference, 516GG|983TC and 516GT|983TT intermediate, 516TT|983TT and
516GT|983TC slow, 516GG|983CC ultra-slow). Encoded as log-ratio
multiplicative shifts on the 516GG|983TT EM reference so the single
etalcl IIV applies uniformly on the log-CL scale across all six
SNP-vector subgroups. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Dhoro_2015_efavirenz.html">Efavirenz
(Dhoro 2015)</a> </td>
<td style="text-align:left;"> One-compartment population PK
model for oral efavirenz in HIV-positive and HIV/TB co-infected adults
in Zimbabwe (Dhoro 2015), with apparent clearance CL/F stratified by
CYP2B6 983T>C (CYP2B6*18, rs28399499) genotype and multiplicative
fractional covariate effects of CYP2B6 516G>T (CYP2B6*6, rs3745274)
genotype, body weight, and sex on CL/F. Absorption rate constant ka and
apparent volume V/F are fixed from the upstream Nyakutira 2008
Zimbabwean cohort. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Heathman_2024_efavirenz.html">Efavirenz
(Heathman 2024)</a> </td>
<td style="text-align:left;"> Population pharmacokinetic model
for efavirenz (EFV) and its 8-hydroxy- and 7-hydroxy-metabolites in 135
healthy volunteers receiving a single 600 mg dose followed by 17 days of
600 mg/day (4594 plasma concentration samples). Each of EFV, 8-OH EFV,
and 7-OH EFV is a 2-compartment model with the metabolite central volume
fixed equal to that of EFV (lack of identifiability). EFV absorption is
sequential zero- (D1 = 1.74 h) plus first-order (KA = 0.165/h). Two
independent enzyme-turnover models drive CYP2B6 and CYP2A6
autoinduction: R(t) = kout * (1 + Emax * Cc_EFV / (EC50 + Cc_EFV));
dE/dt = R(t) - kout * E; E(0) = 1. CYP2B6 modulates the EFV-to-8-OH
formation arm (CL-EFV,2B6 = 3.64 L/h; Emax-2B6 = 15.5; EC50-2B6 = 32000
nM = 10.10 mg/L) and the 8-OH-onward CYP2B6 arm (CL-8OH,2B6 = 0.758
L/h); CYP2A6 modulates the EFV-to-7-OH formation arm (CL-EFV,2A6 =
0.0947 L/h; Emax-2A6 = 4.22; EC50-2A6 = 12500 nM = 3.95 mg/L). UGT2B7
elimination arms (CL-EFV,UGT = 0.0504 L/h; CL-8OH,UGT = 5.44 L/h) and
the 7-OH total clearance (CL-7OH = 3.39 L/h) are not autoinduced. CYP2B6
phenotype reduces the EFV-to-8-OH formation arm by 9.72% (IM) / 9.06%
(PM, encoded as canonical CYP2B6_SM) and reduces the CYP2B6 Emax by
53.5% (IM) / 93.2% (PM); NM (extensive metabolizer) is the reference. PM
subjects show essentially no autoinduction (effective Emax-2B6 ~ 1.05)
and accumulate over 2-3 weeks. IIV is exponential on PK parameters
(estimated for most; 15.1% CV fixed for several); residual variability
is proportional for all three analytes (25.8% / 28.0% / 29.9% CV).
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Hirt_2009_efavirenz.html">Efavirenz
(Hirt 2009)</a> </td>
<td style="text-align:left;"> One-compartment population PK
model with first-order absorption and elimination for once-daily oral
efavirenz (EFV) in treatment-naive HIV-1-infected West African children
(Hirt 2009). CL/F and V/F scale linearly with body weight (shared
allometric exponent fixed at 1) and CL/F additionally varies with
postnatal age via a power covariate centred at the cohort median 6.35
years (signed exponent -0.535, so apparent clearance decreases with
age); the inter-individual variability of V/F is forced to perfect
correlation with the eta of CL/F and is constructed as vc_eta_scale *
etalcl (the K parameter in Hirt 2009 Table 2); multiplicative residual
error. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Luo_2016_efavirenz.html">Efavirenz
(Luo 2016)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model with first-order absorption and elimination for oral efavirenz in
pediatric HIV-1-infected patients (Luo 2016). Capsule / capsule-sprinkle
formulation; body weight is a power covariate on CL/F, Vc/F, and Ka with
reference 20 kg. The adult cohort (n = 24 healthy adults) and
oral-solution formulation (study-specific Frel) reported in the same
paper are documented in the validation vignette but not encoded as
separate sub-models. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Mukonzo_2009_efavirenz.html">Efavirenz
(Mukonzo 2009)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model for single-dose oral efavirenz in 121 healthy Ugandan adults, with
sequential zero-order followed by first-order absorption to the central
compartment. Apparent oral clearance CL/F is reduced by 21% in
homozygous CYP2B6*6 (rs3745274 T/T) and by 20% in homozygous CYP2B6*11
(rs35303484 G/G) carriers (multiplicative fractional effects). Relative
bioavailability Frel is increased by 26% in ABCB1 rs3842 mutant carriers
(heterozygote or homozygote). Apparent peripheral volume Vp/F is
2.08-fold higher in women than in men. Concentrations are reported in
mg/L (1 mg/L efavirenz = 3.168 micromol/L). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Olagunju_2018_efavirenz.html">Efavirenz
(Olagunju 2018)</a> </td>
<td style="text-align:left;"> One-compartment population PK
model for oral efavirenz in HIV-positive pregnant women (Olagunju 2018),
with composite CYP2B6 516G>T (rs3745274) and 983T>C (rs28399499)
metaboliser status (slow / intermediate / fast) as a categorical
covariate on CL/F and fixed-exponent allometric body-weight scaling on
CL/F and V/F. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Robarge_2017_efavirenz.html">Efavirenz
(Robarge 2017)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model for a single 600 mg oral dose of efavirenz in 73 HIV-seronegative
adult volunteers (Robarge 2017), with parallel zero- and first-order
absorption (independent lag times t_lag1 and t_lag2, zero-order duration
D2), allometric fat-free-mass scaling on CL/F (exponent 3/4, fixed),
allometric fat-mass scaling on Vp/F (exponent 1, fixed), and CYP2B6
metaboliser status (normal / intermediate / slow) reducing CL/F by 0%,
25% and 51% respectively. Bioavailability is fixed to F = 1 (no IV
reference formulation); the first-order absorption fraction F1 = 0.414
was estimated and the zero-order fraction F2 = 1 - F1 = 0.586 was
assigned by mass balance. All absorption-related typical values (F1,
t_lag1, K_a, t_lag2, D2) were estimated in an interim model and then
fixed prior to covariate evaluation; the IIVs on those absorption
parameters were re-estimated in the final model. Block-structured
between-subject variability is estimated on (CL/F, Q/F, V_p/F) with
correlations rho(CL/F, V_p/F) = 0.196 and rho(Q/F, V_p/F) = 0.849;
rho(CL/F, Q/F) was fixed at 0. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Salem_2014_efavirenz.html">Efavirenz
(Salem 2014)</a> </td>
<td style="text-align:left;"> One-compartment population PK
model for oral efavirenz in HIV-1-infected children (Salem 2014).
Allometric body-weight scaling on apparent clearance (fixed exponent
0.75) and apparent volume of distribution (fixed exponent 1.0)
referenced to 70 kg; sigmoid Emax maturation of CL/F with postnatal age
(TM50 = 4.6 months, Hill = 3.4); 51% reduction in CL/F for CYP2B6-516
T/T homozygotes; Emax maturation of relative bioavailability for the
oral liquid (suspension or solution) formulations vs the capsule
reference (mature F = 0.79; TM50 = 10.6 months; Hill fixed at 1).
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Sanchez_2011_efavirenz.html">Efavirenz
(Sanchez 2011)</a> </td>
<td style="text-align:left;"> One-compartment population
PK/pharmacogenetic model for oral efavirenz in Caucasian HIV-infected
adults (Sanchez 2011), with GGT, CYP2B6*6 genotype (linked 516G>T +
785A>G), and ABCC4 (MRP4) 1497C>T carrier covariate effects on
apparent oral clearance CL/F. Absorption rate ka fixed at 0.3 h^-1
(sparse TDM data could not estimate it); no covariate effect on V/F.
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Jansson_2008_eflornithine.html">Eflornithine
rat (Jansson 2008)</a> </td>
<td style="text-align:left;"> Preclinical (rat,
Sprague-Dawley). Stereoselective two-enantiomer population PK model of
racemic eflornithine after single oral or IV doses in male
Sprague-Dawley rats (Jansson 2008). Each enantiomer (L = active, D)
carries its own 2-compartment disposition (CL, Vc) with shared Q and Vp
from the IV fit; oral absorption is modeled with a shared Savic 2007
transit-compartment chain (continuous number of compartments via
Stirling approximation) feeding per-enantiomer depots that drain to
central via saturable Michaelis-Menten kinetics (Tmax, Kt).
Bioavailability differs between enantiomers and shifts upward at the
highest oral dose level (3000 mg/kg) via a categorical indicator.
Racemic plasma concentration is the algebraic sum Cc_rac = Cc_l + Cc_d.
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/DoldanMartelli_2013_EGF_IFN_chimera.html">EGF
IFN chimera (DoldanMartelli 2013)</a> </td>
<td style="text-align:left;"> In vitro (Daudi human Burkitt
lymphoma cell line). Mechanistic kinetic model of an EGF-IFNalpha-2a
chimeric ligand binding to EGFR and IFN receptor on the cell membrane:
sequential two-subunit engagement, receptor lateral diffusion, and
internalization (Doldan-Martelli 2013). Default parameters are wild-type
IFN chimera in Daudi-EGFR cells (overexpressing EGFR ~300x parental);
k2on / k2off can be overridden for K133A and R144A IFN mutants, and R1_0
/ R2_0 for parental Daudi cells (see vignette). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Ide_2020_elotuzumab.html">Elotuzumab
(Ide 2020)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model for elotuzumab (anti-SLAMF7 humanized IgG1) in Japanese and
non-Japanese patients with multiple myeloma (Ide 2020); parallel linear
and Michaelis-Menten elimination from the central compartment plus
second-order target-mediated elimination from the peripheral compartment
driven by a non-renewable target pool, with time-varying serum M protein
on Vmax. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Farrell_2014_eltrombopag.html">Eltrombopag
(Farrell 2014)</a> </td>
<td style="text-align:left;"> Population PK/PD model for
eltrombopag in healthy male volunteers (single dose) and adult patients
with chronic liver disease (CLD; multiple daily doses) (Farrell 2014).
Two-compartment apparent disposition with dual sequential first-order
absorption: Ka1 acts on the depot from the end of the absorption lag
time (ALAG1) until time MTIME after the dose, and Ka2 acts thereafter.
CL/F is reduced in females, in East Asian subjects, and in CLD patients
with a linear-in-Child-Pugh-score gradient (HEPIMP_CP_SCORE >= 5).
Vc/F is approximately three-fold higher in South/Central Asian subjects.
Platelet dynamics use a four-compartment lifespan model (three maturing
precursor pools feeding the circulating-platelet pool) with linear
stimulation of precursor production by plasma eltrombopag; the slope
SLOP is 34% lower in East Asian CLD patients. PD parameters are
CLD-specific (median baseline platelet 41 Gi/L). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Goggin_2004_emfilermin.html">Emfilermin
(Goggin 2004)</a> </td>
<td style="text-align:left;"> One-compartment population PK
model for subcutaneous emfilermin (recombinant human leukaemia
inhibitory factor, r-hLIF) in healthy postmenopausal women and in
infertile women undergoing in vitro fertilization and embryo transfer
(IVF-ET) (Goggin 2004). Absorption is zero-order (D1 = 0.84 h,
invariant, no IIV) directly into the central compartment, followed by
first-order elimination. Apparent clearance CL/F is decreased by 35% in
IVF-ET patients (typical 37 L/h) relative to healthy postmenopausal
women (typical 57 L/h). Apparent volume V/F is linear in body weight on
the natural scale: V/F = 235 L at the median 62 kg, increasing or
decreasing by 6.7 L/kg (~29% per 10 kg) -- an absolute-linear covariate
form, not log-multiplicative. Inter-individual variability is log-normal
on CL/F (17% CV) and V/F (28% CV); inter-occasion variability is
log-normal on V/F (23% CV) across three protocol-defined occasions
(first dosing day = 1, intermediate dosing days = 2, last dosing day =
3). Residual error is proportional (20% CV). Studied weight range was
48-83 kg; the linear V/F-WT term is extrapolation-unsafe below ~27 kg
where the typical V/F would become negative. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Yoneyama_2017_emicizumab.html">Emicizumab
(Yoneyama 2017)</a> </td>
<td style="text-align:left;"> One-compartment population PK
model with first-order subcutaneous absorption and elimination for
emicizumab (ACE910), a bispecific anti-FIXa/FX humanized monoclonal
antibody mimicking the cofactor function of activated factor VIII, in
healthy male adult volunteers (Japanese and Caucasian) and Japanese male
adult/adolescent patients with severe hemophilia A with or without
factor VIII inhibitors (Yoneyama 2017). Body-weight allometric exponents
are fixed (0.75 on CL/F, 1 on Vd/F) per Yoneyama 2017 Methods.
Anti-emicizumab neutralizing antibody (ADA_POS) increases CL/F by a
factor of exp(2.01) and the effect onsets 33.4 days post the first SC
dose (NONMEM MTIME parameterisation). The companion repeated
time-to-event (RTTE) bleeding-hazard model from Yoneyama 2017 Section
2.4 is not included here; nlmixr2lib does not currently support TTE
models. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Baron_2016_empagliflozin.html">Empagliflozin
(Baron 2016)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
with lagged first-order absorption for empagliflozin in patients with
type 2 diabetes (T2DM), coupled with two indirect-response PK/PD models
for fasting plasma glucose (FPG) and glycated hemoglobin (HbA1c). The
drug effect on FPG elimination is driven by steady-state AUC (AUCss =
DOSE_EMPA_MGD * 1e6 / MW / CL) via an Emax function (Gmax, AUC50); FPG
in turn drives HbA1c production with a boundary-condition baseline
(HbA1climit). Pooled popPK/PD analysis of 4065 T2DM patients (PK n =
2761 active) from two phase I, four phase II, and four phase III studies
(Baron 2016 Diabetes Therapy). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Jiang_2024_empagliflozin.html">Empagliflozin
(Jiang 2024)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model with Savic transit-compartment absorption for oral empagliflozin
in healthy Korean adults (Jiang 2024). Pools two randomized, open-label,
two-period crossover phase 1 studies that compared a novel empagliflozin
L-proline cocrystal formulation (CKD-370) against the conventional
empagliflozin formulation at 25 mg, and as a 5 mg/1000 mg
empagliflozin/metformin fixed-dose combination. An analytical transit
chain (Ktr = 9.19 1/h, Mtt = 0.63 h, derived N = 4.79) feeds first-order
absorption (Ka) into a two-compartment disposition model.
Log-transformed body weight scales apparent clearance (exponent 0.64)
and the apparent peripheral volume (exponent 0.57). Interindividual
variability on Ka, CL, and the peripheral volume; interoccasion
variability across the two crossover periods on Ktr, Mtt, Ka, and CL.
Formulation (cocrystal vs conventional) was screened as a covariate and
was NOT retained: the paper's central finding is that the L-proline
cocrystal does not alter the absorption phase or any PK parameter, so
this single model describes both formulations. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Johnston_2019_empagliflozin.html">Empagliflozin
(Johnston 2019)</a> </td>
<td style="text-align:left;"> Exposure-response (PD-only) model
for the effect of empagliflozin on HbA1c in patients with type 1
diabetes mellitus (T1DM) on background insulin therapy (M-EASE-2;
Johnston 2019). A direct-response Emax function of individual
steady-state empagliflozin AUC (AUC_EMPA, supplied as a per-subject
covariate column from an upstream popPK analysis -- Mondick 2018 plus
EASE-2 / EASE-3 data-on-file) reduces the model-predicted baseline
HbA1c, with an additional linear placebo drift over time. Full covariate
model on baseline HbA1c, Emax, and placebo (sex, insulin delivery type,
body weight, eGFR, baseline insulin daily dose, and -- on Emax only --
baseline HbA1c). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Johnston_2021_empagliflozin.html">Empagliflozin
MEASE1 (Johnston 2021)</a> </td>
<td style="text-align:left;"> Semi-mechanistic direct-effect
exposure-response (PD-only) model for empagliflozin on total daily
insulin dose (TDID), mean daily glucose (MDG), and glycated hemoglobin
(HbA1c) in adults with type 1 diabetes (T1D) (M-EASE-1; Johnston 2021).
Individual steady-state empagliflozin AUC (AUC_EMPA, supplied as a
per-subject covariate column from the upstream Johnston 2021 popPK; see
Johnston_2021_empagliflozin_popPK) drives (i) a proportional-Emax
reduction in TDID, (ii) a direct-Emax reduction in MDG offset by a
linear time-dependent placebo drift and coupled to the TDID reduction
via a power-form insulin effect, and (iii) HbA1c as a power-form
function of MDG relative to baseline. Covariates: sex, body weight,
eGFR, insulin delivery type (CSII vs MDI), and baseline HbA1c.
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Johnston_2021_empagliflozin.html">Empagliflozin
popPK (Johnston 2021)</a> </td>
<td style="text-align:left;"> Population pharmacokinetic
(PopPK) model for empagliflozin in adults with type 1 diabetes (T1D)
enrolled in the EASE clinical program (pooled EASE-1 phase II, EASE-2
phase III, and EASE-3 phase III). Two-compartment model with first-order
elimination and a sequential zero-order (duration D1) plus first-order
(ka) oral absorption with a depot lag time (ALAG). Full covariate power
/ multiplicative model on CL/F (age via TPRO/AP/eGFR/TDID/WT + sex +
smoking), V2/F, V3/F, Q/F, and ka (Johnston 2021 Table S2). The PopPK
was adapted from a prior T2D empagliflozin analysis (Baron 2016) and
re-fit on the EASE-1 + EASE-3 dataset with EASE-2 as external
evaluation, then re-estimated on the combined EASE-1/-2/-3 data to
generate the individual AUCss inputs to the M-EASE-1 and M-EASE-2
exposure-response models. This file encodes the final full-covariate
model. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Valade_2014_emtricitabine.html">Emtricitabine
(Valade 2014)</a> </td>
<td style="text-align:left;"> Two-compartment oral population
PK model for emtricitabine (FTC) in HIV-infected pregnant and
non-pregnant women, with first-order absorption and elimination.
Creatinine clearance (Cockcroft-Gault, raw mL/min) on apparent oral
clearance via the power model CL/F = 22.3 * (CRCL/135)^0.33 captures the
18% CL/F increase observed during pregnancy as a manifestation of the
pregnancy-associated 50% rise in estimated glomerular filtration rate;
pregnancy itself, gestational age, age, weight, serum creatinine and
co-medication were screened but not retained after CLcr inclusion
(Valade 2014, BJCP). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Valade_2015_emtricitabine.html">Emtricitabine
(Valade 2015)</a> </td>
<td style="text-align:left;"> Two-compartment oral population
PK model for emtricitabine (FTC) in HIV-1-infected men on combined
antiretroviral therapy, with an asymmetric effect compartment of
negligible volume describing seminal plasma distribution via distinct
blood-plasma-to-seminal-plasma transfer rate (k1e) and seminal-plasma
elimination rate (ke1) constants (Valade 2015, EVARIST ANRS-EP 49 study)
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Steichert_2025_enalapril_enalaprilat_pediatric.html">Enalapril
enalaprilat pediatric (Steichert 2025)</a> </td>
<td style="text-align:left;"> Simultaneous parent +
active-metabolite population PK model for oral enalapril (ODMT) and
enalaprilat in ACEi-naive children with heart failure (Steichert 2025,
LENA studies). Combined one-compartment model for enalapril (first-order
absorption with a lag) coupled with a one-compartment model for
enalaprilat via a fixed fraction metabolised fm = 0.7. Allometric
scaling (fixed exponents 0.75 on CL, 1 on V) referenced to 5 kg body
weight. Covariate effects retained in the final model: age and serum
creatinine on the apparent clearance of enalaprilat, and modified Ross
score on the apparent volume of distribution of enalaprilat. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Luo_2024_CES1_cirrhosis.html">Enalapril
pbpk (Luo 2024)</a> </td>
<td style="text-align:left;"> PBPK (semi-mechanistic, custom
WinNonlin 8.1 implementation). Joint enalapril + enalaprilat disposition
in healthy adults and in liver cirrhosis (Child-Pugh A/B/C). Enalapril
is an inactive ester prodrug hydrolysed by hepatic carboxylesterase 1
(CES1) to the active diacid enalaprilat, which is cleared renally. The
semi-PBPK circuit is stomach, three small-intestinal lumen segments
(duodenum / jejunum / ileum), the matching three gut-wall segments,
portal vein, liver, kidney and a one-compartment systemic compartment.
Cirrhosis is applied by switching the Child-Pugh-specific physiology of
Table 1 (organ blood flows, functional liver volume, GI transit rates,
GFR, plasma-binding protein concentrations, hepatic CES1 content) and
rescaling CLint, CLint,K, Peff and Vsys through Eq 1-6. Deterministic:
the paper's virtual populations are uniform 80-120% draws on the drug
parameters, not lognormal random effects, so no IIV is encoded.
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Barras_2009_enoxaparin.html">Enoxaparin
(Barras 2009)</a> </td>
<td style="text-align:left;"> Two-compartment first-order
absorption population PK model of anti-factor Xa activity in 118 adults
(PE / DVT / ACS / atrial fibrillation) receiving subcutaneous enoxaparin
treatment doses (1 mg/kg BID by total or lean body weight, 1.5 mg/kg BID
for LBW-based obese dosing) under conventional vs
lean-body-weight-and-renal-function individualised dosing (Barras 2009
randomised controlled trial). CL is a composite renal + non-renal model
with LBW substituted into the Cockcroft-Gault CrCl equation; central
volume scales linearly with LBW. The paper additionally reports a
three-category proportional-odds bleeding / bruising adverse-event PD
model with logit(P[S<=1]) = 2.83 - 2.75*(Age/61) - 0.536*(cAUC/23)
and logit(P[S<=2]) = logit(P[S<=1]) + 2.05, driven by patient Age
and cumulative AUC (cAUC) of anti-Xa activity from first dose to event.
The proportional-odds PD layer is NOT encoded in this model file -- it
requires canonical parameter names for cumulative-logit /
proportional-odds PD models that are not yet registered in
references/parameter-names.md. The PD equation is reproduced in the
validation vignette, where it is applied deterministically to cAUC
values derived from the simulated PK profile (see vignette Source trace
and Assumptions and deviations sections). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Berges_2007_enoxaparin.html">Enoxaparin
(Berges 2007)</a> </td>
<td style="text-align:left;"> Two-compartment first-order
absorption population PK model of anti-factor Xa activity in elderly
patients (>75 years) receiving prophylactic subcutaneous enoxaparin
4000 IU once daily (Berges 2007 PROPHRE.75 study) </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Feng_2006_enoxaparin.html">Enoxaparin
(Feng 2006)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model for enoxaparin in adult inpatients receiving continuous
intravenous infusion (CII) or subcutaneous (SC) dosing (Feng 2006)
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Green_2003_enoxaparin.html">Enoxaparin
(Green 2003)</a> </td>
<td style="text-align:left;"> Two-compartment first-order-input
population PK model for subcutaneous enoxaparin in adults treated at the
Royal Brisbane Hospital for acute coronary syndrome, deep vein
thrombosis, pulmonary embolism, or DVT prophylaxis (Green & Duffull
2003). Anti-Xa activity is the observation; lean body weight (LBW; James
1976 formula) is the size descriptor on clearance and total body weight
is the size descriptor on the central volume. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Green_2005_enoxaparin.html">Enoxaparin
(Green 2005)</a> </td>
<td style="text-align:left;"> Two-compartment, first-order
absorption population PK model for subcutaneously administered
enoxaparin (anti-Xa activity) in 38 adults with acute coronary syndromes
and a wide range of renal function (Green 2005). Total clearance is the
sum of a renal arm scaled linearly to estimated creatinine clearance
(CRCL, Cockcroft-Gault with ideal body weight; reference 80 mL/min) and
a covariate-free non-renal arm: CL = 0.681 * (CRCL / 80) + 0.229 L/h.
Central volume of distribution scales linearly with total body weight
(reference 80 kg): Vc = 5.22 * (WT / 80) L. A constant basal anti-Xa
activity (49.9 IU/L) is added to the model prediction to represent
endogenous and assay-baseline anti-Xa activity, per the Schoemaker
parameterisation referenced in the paper. Inter-individual variability
is log-normal on total CL, Vc, Q, and basal anti-Xa activity (paper
Table 2 Covariate Model). Residual error is combined additive (52.4
IU/L) plus proportional (20.0 percent CV) on observed anti-Xa
concentrations. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Oualha_2018_enoxaparin.html">Enoxaparin
(Oualha 2018)</a> </td>
<td style="text-align:left;"> Population PK model for
subcutaneous enoxaparin in 22 children during the first post-operative
week after paediatric liver transplantation (Oualha 2018).
One-compartment open model with first-order absorption (ka fixed at 1/h)
and first-order elimination, measured as anti-Xa activity (target
0.2-0.4 IU/mL). Apparent clearance CL/F is allometrically scaled by
pre-operative bodyweight BWPREOP (fixed exponent 0.75); apparent central
volume V/F is allometrically scaled (fixed exponent 1) by a time-varying
post-operative bodyweight BW(t) that captures peri-operative fluid
resuscitation followed by post-operative diuresis: BW(t) = (BWPREOP +
PFA/1000) * (1 - (1 - fbw) * t^hill_bw / (tbw50^hill_bw + t^hill_bw)).
Bodyweight-evolution parameters fbw / hill_bw / tbw50 are jointly
estimated with the enoxaparin PK and carry their own between-subject
variability. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/SanchezPena_2005_enoxaparin.html">Enoxaparin
(SanchezPena 2005)</a> </td>
<td style="text-align:left;"> One-compartment population
pharmacokinetic model of anti-factor Xa activity after intravenous
enoxaparin in 546 adults undergoing elective percutaneous coronary
intervention (Sanchez-Pena 2005). The IV bolus is modelled as a brief
zero-order input phase of duration T0 with linear elimination. Body
weight is the only retained covariate, applied as estimated allometric
exponents on clearance (0.9) and volume (0.7) with reference 75 kg. A
fixed basal anti-Xa activity (0.0725 IU/mL) is added to the dose-driven
concentration to account for the endogenous pre-dose background measured
by the chromogenic anti-Xa assay. Doses must be entered in IU (1 mg
enoxaparin = 100 IU anti-Xa); the typical 0.5 mg/kg clinical dose
corresponds to 3830 IU for a 76 kg patient. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Schoemaker_1996_low_molecular_weight_heparin_modeling.html">Enoxaparin
(Schoemaker 1996)</a> </td>
<td style="text-align:left;"> One-compartment population PK
model with intravenous bolus input and an estimated constant basal
anti-Xa activity for the low molecular weight heparin enoxaparine (trade
name Clexane) in healthy volunteers (Schoemaker & Cohen 1996,
Example 2 / Table 3, Solution 2). Enoxaparin amount in the central
compartment plus an additive endogenous baseline reproduces the
lingering low post-dose anti-Xa activity that would otherwise force a
second compartment if pre-value subtraction were applied; the authors
recommend the basal-activity formulation over the competing
two-compartment model (Solution 1, Table 2) because it matches the dose
/ AUC clearance estimate from the upstream Stiekema 1993 paper. Anti-Xa
activity is the surrogate concentration measure; doses are in anti-Xa IU
and concentration is in IU/mL. Validation of this model and the
companion dalteparin PK/PD model share a single vignette. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Foster_2023_enrofloxacin_cat.html">Enrofloxacin
ciprofloxacin cat (Foster 2023)</a> </td>
<td style="text-align:left;"> Veterinary (domestic cat). Joint
parent + metabolite population PK model for enrofloxacin and its active
metabolite ciprofloxacin after a single 5 mg/kg intravenous enrofloxacin
dose infused over 30 minutes in 34 client-owned cats hospitalised for
clinical illness and spanning normal to markedly reduced kidney function
(Foster 2023 Figure S2 and Table 3). Each analyte gets one plasma
compartment: enrofloxacin is eliminated by a renal clearance into urine
plus a metabolic formation clearance that generates ciprofloxacin, and
ciprofloxacin is eliminated by its own clearance into urine. Retained
covariates are body weight on the enrofloxacin volume and blood urea
nitrogen on the metabolic formation clearance -- the paper's finding
that more azotemic cats form ciprofloxacin faster, which the authors
themselves argue is unlikely to be causal because serum creatinine and
SDMA were not significant. This is a SECOND, independent fit reported
alongside the paper's primary total-fluoroquinolone model
(Foster_2023_enrofloxacin_totalFluoroquinolone_cat), not a sub-model of
it. Two caveats carried from the source: the volumes and clearances are
ABSOLUTE (mL, mL/h) despite Table 3's 'mL/kg' labels, and the published
clearance pair reproduces a ciprofloxacin fraction of total
fluoroquinolone of only about 2% against the ~18% the same paper reports
-- see the lvc_cipro / lcl_met comments and the vignette Errata.
Between-subject variances and the residual-error magnitude are not
reported, so every eta and residual SD is fixed(0) and the model
simulates typical-value profiles unless the user supplies variances.
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Foster_2023_enrofloxacin_cat.html">Enrofloxacin
totalFluoroquinolone cat (Foster 2023)</a> </td>
<td style="text-align:left;"> Veterinary (domestic cat).
Two-compartment population PK model for TOTAL FLUOROQUINOLONE (the
arithmetic sum of plasma enrofloxacin and its active metabolite
ciprofloxacin, which Foster 2023 treats as one analyte because the two
compounds' antibacterial effects are additive) after a single 5 mg/kg
intravenous enrofloxacin dose infused over 30 minutes in 34 client-owned
cats hospitalised for clinical illness and spanning normal to markedly
reduced kidney function. Sparse sampling (3 samples per cat, 98 samples
total) with nonlinear mixed-effects modelling in Phoenix NLME. Body
weight, centred at the population value of 3.8 kg, is the only retained
covariate and acts as a power effect on both the central volume and the
elimination clearance; serum creatinine, symmetric dimethylarginine,
blood urea nitrogen, age and sex were screened and none was significant,
which is the paper's central finding (no dose adjustment is indicated
for azotemic cats). Foster 2023 Table 1 labels the volumes 'mL/kg' and
the clearances 'mL/kg/h', but those parameters are ABSOLUTE (mL and
mL/h), not weight-normalised: only the absolute reading reproduces the
paper's own Table 1 AUC0-24 of 46.0 ug*h/mL and the concentration range
of Figure 1 -- see the lvc comment and the vignette Errata for the
arithmetic. Between-subject variances and the residual-error magnitude
are not reported anywhere in the paper or its supplement, so every eta
and propSd is fixed(0) and the model simulates typical-value profiles
unless the user supplies variances. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Csajka_2005_ephedrine_caffeine.html">Ephedrine
caffeine (Csajka 2005)</a> </td>
<td style="text-align:left;"> Mechanistic simultaneous
population PK model for co-administered ephedrine, its N-demethylation
metabolite norephedrine, and caffeine in healthy adults after single
oral doses (Csajka 2005). Caffeine is described by a 1-compartment
first-order-absorption model with a fractional decrease in apparent
clearance during oral contraceptive therapy. Ephedrine uses a
1-compartment depot + central + cumulative-urine model with an
absorption lag time, renal clearance, and saturable Michaelis-Menten
conversion to norephedrine; norephedrine is carried as a
pseudo-concentration state because its volume of distribution V_NE is
unidentifiable, so the reported parameter is the compound Vmax/V_NE and
the norephedrine elimination is first order. The interaction term
reproduces the paper's indirect-action absorption model (equation
10b/10e final form): the caffeine amount in the absorption compartment
depresses ephedrine ka by an asymptotic fraction d, with caffeine acting
as the f(C) inhibitor on its own absorption-compartment amount.
Parameter values are the pharmaceutical-formulation defaults from Table
3; herbal-formulation alternatives (bioavailability F_E,herbal = 0.78
instead of F_E,pharm = 0.59, plus a 22.2-min caffeine absorption lag)
are documented in inline comments and can be applied by overriding
lfdepot and ltlag_caf at simulation time. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Sarashina_2005_epinastine.html">Epinastine
(Sarashina 2005)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model with first-order absorption for oral epinastine in healthy adults
and paediatric atopic dermatitis patients (Sarashina 2005), with
linear-in-WT CL/F and V1/F plus food-status and formulation covariate
effects </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Abboud_2009_epinephrine.html">Epinephrine
(Abboud 2009)</a> </td>
<td style="text-align:left;"> One-compartment population PK
model for intravenous epinephrine (adrenaline) infusion in adults with
septic shock, with a constant endogenous epinephrine production rate
(R0) feeding the central compartment and body weight and SAPS II
severity score as power covariates on clearance (Abboud 2009).
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Oualha_2014_epinephrine.html">Epinephrine
(Oualha 2014)</a> </td>
<td style="text-align:left;"> Population PK/PD model for
continuous IV epinephrine in critically ill children following
cardiopulmonary bypass for repair of congenital heart defects (Oualha
2014). One-compartment open PK with first-order elimination plus an
endogenous zero-order production rate q0 and circulating-volume-anchored
Vc = 0.08*WT; allometric scaling of CL and q0 on body weight (exponents
fixed to 3/4). Hemodynamic Emax sub-models for heart rate (HR) and the
stroke-volume * systemic-vascular-resistance product (SV*SVR) with age
power effects on basal HR and SV*SVR and a RACHS-1 categorical effect on
SV*SVR_max. Glucose/lactate turnover sub-model: epinephrine stimulates
the zero-order plasma glucose production rate via an Emax function;
plasma lactate is produced at the rate of glucose elimination and itself
follows first-order elimination. kGLY and kLAC are derived at steady
state (Eq. 12-13). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Janssen_2023_pregnancy_cytotoxics.html">Epirubicin
(Janssen 2023)</a> </td>
<td style="text-align:left;"> Semi-physiological enriched
three-compartment population PK model for intravenous epirubicin in
pregnant cancer patients, applying gestational changes in albumin
binding, glomerular filtration, hepatic plasma flow, CYP3A4 activity and
body fluid volumes to the non-pregnant Sandstrom 2006 base model
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Diep_2022_eplontersen.html">Eplontersen
(Diep 2022)</a> </td>
<td style="text-align:left;"> Two-compartment population PK and
indirect-response PD model for the GalNAc3-conjugated antisense
oligonucleotide eplontersen targeting transthyretin (TTR) mRNA, fit to
pooled data from two phase 1 studies in healthy volunteers (Diep 2022).
First-order SC absorption with site-specific typical ka (arm vs
abdomen), allometric scaling on CL by lean body mass, on Vc/Q/Vp by
total body weight, and an indirect-response model with
eplontersen-driven inhibition of TTR production. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/PerezRuixo_2008_epoetinAlfa.html">EpoetinAlfa
(PerezRuixo 2008)</a> </td>
<td style="text-align:left;"> Population PK/PD model for
subcutaneous recombinant human erythropoietin (rHuEPO / epoetin alfa) in
healthy adult male volunteers (Perez-Ruixo 2008). PK is the
Olsson-Gisleskog 2007 prior (two-compartment with linear +
Michaelis-Menten elimination and dual subcutaneous absorption: a fast
sequential zero-order infusion into the depot of duration D1 feeding
first-order absorption ka into central, plus a slower zero-order direct
infusion into central of duration D2 after lag time tlag2;
dose-dependent absolute bioavailability F = F0 +
Emax(F)*Dose/(ED50(F)+Dose)). Endogenous EPO is maintained at the
baseline BSL by a constant input rate kEPO derived from the steady-state
balance against linear + MM elimination (equation 4). The PD layer is
the maturation-structured cytokinetic model D: rHuEPO stimulates the
progenitor production rate kin*C/(SC50+C) into a 10-stage bone-marrow
precursor age chain (transfer rate Np/Tp), which feeds a 10-stage
circulating reticulocyte age chain whose transfer rate (NR/TR)*(S0/SM)
is inhibited by a 5-stage signal transduction (transit time tau) driven
by C/(EC50+C). Output RET = sum of reticulocyte compartments reproduces
the percentage of reticulocytes in % units. No demographic covariate
effects were retained in either layer. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Hayashi_1998_epoetinBeta.html">EpoetinBeta
(Hayashi 1998)</a> </td>
<td style="text-align:left;"> One-compartment population PK
model for subcutaneous recombinant human erythropoietin (epoetin beta)
in healthy adult male Japanese volunteers with a constant endogenous EPO
production rate carrying a fixed circadian sinusoid (acrophase near
midnight) feeding the central compartment, and body weight as a power
covariate on apparent absorption rate ka and apparent central volume
V/F, plus serum creatinine and age as power covariates on the
elimination rate constant k_e (reparameterised here onto canonical CL/F
so the k_e covariates ride on CL/F together with the V/F weight
exponent); apparent V/F and E/F throughout because bioavailability was
not separately estimable from this SC-only study (Hayashi 1998).
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Kawamura_2018_eribulin.html">Eribulin
(Kawamura 2018)</a> </td>
<td style="text-align:left;"> Three-compartment IV PK driver
coupled with a Friberg-style semi-mechanistic PD model for
eribulin-induced neutropenia in Japanese patients with recurrent or
metastatic breast cancer (Kawamura 2018). Plasma eribulin concentrations
are produced by a 3-compartment model with linear elimination from the
central compartment whose parameters are FIXED from the Majid 2014 popPK
analysis (reproduced verbatim in Kawamura 2018 section 2.3): CL depends
on body weight (allometric 0.75), serum albumin, alkaline phosphatase,
and total bilirubin; V1, V2, V3 scale linearly with body weight; Q2 and
Q3 scale allometrically with body weight. The PD layer (proliferation +
three transit compartments + circulating neutrophils + feedback) is
estimated on 401 patients / 5199 ANC measurements (Table 2): MTT = 104.5
h, Kprol = 0.0377 /h, Kout = 0.0295 /h, Gamma = 0.203, Slope = 0.0413
mL/ng (linear drug effect). Serum albumin influences Kprol (negative
exponent), MTT (positive exponent), and Kout (positive exponent); a
binary low-baseline-ANC indicator (BNEU3 = 1 when baseline ANC <
3000/uL) multiplies Kprol. IIV is reported on Kprol, Kout, and Slope (no
IIV on MTT or Gamma). Additive residual error on circulating ANC (sigma
= 1.15 cells/nL = 1150 cells/uL). Eribulin doses must be supplied in
milligrams of eribulin-FREE-BASE equivalent (1.4 mg/m^2 mesilate = 1.23
mg/m^2 free base, conversion factor 1.23/1.4). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/vanHasselt_2013_eribulin.html">Eribulin
(vanHasselt 2013)</a> </td>
<td style="text-align:left;"> Three-compartment IV PK driver
coupled with a Friberg-style semi-physiological PD model for
eribulin-induced neutropenia in adult patients with late-stage
metastatic breast cancer (van Hasselt 2013). The PK layer parameters are
FIXED from the Majid 2014 popPK analysis (J Clin Pharmacol 54:1134); van
Hasselt 2013 cites the same Eisai popPK analysis as unpublished data on
file and does not report PK parameter values in the paper. CL depends on
body weight (allometric 0.75), serum albumin, alkaline phosphatase, and
total bilirubin; V1, V2, V3 scale linearly with body weight; Q2 and Q3
scale allometrically with body weight. The PD layer (proliferation +
three transit compartments + circulating neutrophils + feedback) is
estimated on 1579 patients / 23 427 ANC measurements from a pool of 12
phase I / II / III studies (Table 3 final covariate model): ANC0 =
4.03e9 cells/L, MTT = 109 h, Gamma = 0.216, SLOPE = 0.0451 L/ug (linear
drug effect). Albumin, bilirubin, alkaline phosphatase, LDH, and
G-CSF-receival covariates enter MTT; albumin, AST, and G-CSF-receival
covariates enter SLOPE. IIV on ANC0, MTT, Gamma, and SLOPE (diagonal;
off-diagonal covariances were not computationally feasible per the
paper). Proportional residual error on circulating ANC. Eribulin doses
must be supplied in milligrams of eribulin FREE BASE (conversion factor
1.23/1.4 from the mesilate dose). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/vanHasselt_2015_eribulin.html">Eribulin
(vanHasselt 2015)</a> </td>
<td style="text-align:left;"> Disease-progression (DP) model
for prostate-specific antigen (PSA) dynamics in metastatic
castration-resistant prostate cancer (CRPC) patients treated with
eribulin mesilate (van Hasselt 2015). K-PD framework: the per-dose
predicted eribulin AUC enters a single transient drug-effect compartment
depot_kpd that decays with rate KP (fixed to 6000 /day so the effect is
nearly instantaneous after each dose); PSA evolves under a first-order
growth rate KG counteracted by an inhibition rate KD0 multiplied by the
K-PD state depot_kpd and an exponentially decaying resistance factor
exp(-k_res*t). PSA0, KD0, KG, k_res have correlated lognormal IIV;
proportional residual error on PSA (log-transform-both-sides). Prior
taxane treatment (binary PRIOR_TAXANE) multiplies PSA0; cumulative
number of days of prior taxane treatment (continuous PRIOR_TAXANE_DAYS)
enters KD0 as (1 + NTRT/720)^theta. The companion parametric Weibull
survival sub-model fit in R survreg is documented in the vignette but
not encoded here (not an ODE / nlmixr2 structure). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Saleh_2023_leicns_pk30_mouse_brain.html">Erlotinib
mouse pbpk (Saleh 2023)</a> </td>
<td style="text-align:left;"> PBPK (LeiCNS-PK3.0 CNS
physiologically-based model, mouse version). Preclinical (mouse, FVB).
Nine-compartment CNS PBPK model predicting unbound erlotinib
concentrations in brain extracellular fluid (brain ECF) after a single
50 mg/kg oral dose. The CNS structure is the mouse re-parameterisation
of LeiCNS-PK3.0: brain microvasculature (brain_vascular), brain ECF, a
phospholipid brain-cell-membrane binding compartment
(brain_cell_membrane), brain intracellular fluid (brain_icf), lysosomes
(brain_lysosome), and the four CSF compartments (lateral ventricles,
third + fourth ventricles, cisterna magna, subarachnoid space) draining
in series back to plasma. Transport across the BBB and BCSFB is the sum
of a paracellular clearance (Qp, charged + neutral drug) and a
transcellular clearance (Qt, neutral drug only, scaled by pH-dependent
neutral fractions PHF and by asymmetry factors AF that encode active
transport). Every CNS parameter is fixed to mouse physiology (Table III)
or derived from the drug's physicochemical properties (Table I); none
was fitted here. The BBB asymmetry factors are back-calculated from
Kp,uu,BBB = 0.628 (estimated by the authors; Table V). The plasma PK
model is the empirical one-compartment model of Table IV (in-house
NONMEM fit) and acts purely as a forcing function: brain uptake does not
deplete plasma, exactly as published. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Eyler_2014_ertapenem.html">Ertapenem
(Eyler 2014)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model for intravenous ertapenem in critically ill adults with acute
kidney injury receiving continuous venovenous hemodialysis (CVVHD) or
hemodiafiltration (CVVHDF). PK is parameterised on unbound drug; total
serum concentrations are reconstructed via a single-site saturable
albumin-binding equation Cb = Bmax * Cu / (KD + Cu). Systemic (body)
clearance and a separate dialytic clearance arm are estimated as primary
parameters; the dialytic arm is added to body clearance only while the
CRRT circuit is running, gated by the time-varying RRT_HEMODIAL_ACTIVE
covariate. Eyler 2014, n = 8 subjects, single 1 g IV dose over 30 min.
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Lakota_2018_ertapenem.html">Ertapenem
(Lakota 2018)</a> </td>
<td style="text-align:left;"> Three-compartment population PK
model for ertapenem in adults across a wide range of body sizes (Lakota
2018) </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/LopezArguello_2023_pbp_binding_pseudomonas.html">Ertapenem
qsp (LopezArguello 2023)</a> </td>
<td style="text-align:left;"> QSP. In vitro (Pseudomonas
aeruginosa PAO1). Whole-cell penicillin-binding protein (PBP)
covalent-binding model for ertapenem (carbapenem): seven coupled ODEs
for the rate of net influx of drug across the outer membrane into
periplasm and the competitive, mass-balanced acylation of six PBPs (1a,
1b, 2, 3, 4, 5/6) counted as molecules per bacterial cell. The intact
parameter switches between the intact whole-cell assay
(penetration-limited; drug enters periplasm at Rate_Influx/access) and
the lysed isolated-membrane assay (no outer membrane; a vast excess of
drug molecules is present at time 0). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Nielsen_2011_antibacterial_efficacy.html">Erythromycin
(Nielsen 2011)</a> </td>
<td style="text-align:left;"> In vitro (Streptococcus pyogenes
M12 NCTC P1800). Semimechanistic PKPD model of erythromycin time-kill
kinetics; two-stage bacterial life-cycle (proliferating drug-sensitive S
and non-growing drug-insensitive R) with sigmoidal Emax killing of S via
an effect compartment; first-order drug elimination (ke set per in vitro
kinetic-system flow rate); drug-specific degradation kdeg fixed at zero.
Parameter values are from the combined static and dynamic estimation in
Table 3. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Areberg_2006_escitalopram.html">Escitalopram
(Areberg 2006)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model with first-order absorption and lag time for escitalopram in
healthy and hepatic-impaired adults (Areberg 2006) </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/PerezRuixo_2020_esketamine.html">Esketamine
(PerezRuixo 2020)</a> </td>
<td style="text-align:left;"> Joint three-compartment
esketamine + two-compartment apparent noresketamine population PK model
with a hepato-portal first-pass compartment (well-stirred model) and
three parallel absorption routes (intranasal direct,
intranasal-swallowed via PO depot, and PO solution via PO depot)
developed from 9784/9397 esketamine/noresketamine plasma observations in
820 healthy volunteers and patients with treatment-resistant depression
receiving intranasal, intravenous, and oral esketamine (Perez-Ruixo
2020). Asian race decreases esketamine kel (x0.36) and noresketamine
apparent CLn/F (x0.81); Japanese race increases the
nasal-cavity-absorbed fraction FRn (x1.34); and hepatic blood flow Qh
declines linearly by 2.19 L/h per year of age above 60. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Fang_2010_etanercept.html">Etanercept
(Fang 2010)</a> </td>
<td style="text-align:left;"> One-compartment population PK
model for rhTNFR-Fc (recombinant human TNF receptor-Fc fusion protein;
etanercept-class molecule from Celgen Bio-Pharmaceutical) with
first-order subcutaneous absorption, absorption lag time, and linear
elimination in healthy Chinese volunteers (single SC doses 12.5-50 mg)
and Chinese male patients with ankylosing spondylitis (multiple SC doses
25 mg BIW or 50 mg QW) (Fang 2010). Female sex is the typical-value
reference: males have 0.655x lower CL/F. Single-dose administration is
the typical-value reference: multi-dose administration in AS patients
has 0.674x lower apparent bioavailability F. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Horita_2018_ethambutol.html">Ethambutol
(Horita 2018)</a> </td>
<td style="text-align:left;"> Two-compartment population
pharmacokinetic model with zero-order absorption (lag time + zero-order
duration) and first-order elimination for oral ethambutol in Ghanaian
children with active tuberculosis (Horita 2018); allometric weight
scaling on CL/F, Q/F, V1/F, V2/F with non-canonical estimated exponents
(0.382, 0.474, 0.228, 0.858) normalised to the cohort median 14.3 kg.
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Jonsson_2011_ethambutol.html">Ethambutol
(Jonsson 2011)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model for oral ethambutol in adult South African pulmonary tuberculosis
patients (Jonsson 2011), with one transit compartment preceding
first-order absorption, allometric scaling on clearance (3/4) and volume
(1) terms relative to a 50 kg reference, an HIV-status effect on
bioavailability (15.4% reduction), and 4-occasion inter-occasion
variability on apparent oral clearance. Parameter values are taken from
the publication's Table 2 (NONMEM final estimates column); see
inst/modeldb/ddmore/Jonsson_2011_ethambutol_ddmore.R for the
DDMoRE-bundle replicate of the same fit. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Ramachandran_2023_tuberculosis_eptb_pbpk.html">Ethambutol
pbpk (Ramachandran 2023)</a> </td>
<td style="text-align:left;"> PBPK (whole-body, 18 ODEs, MATLAB
ode15s). Oral ethambutol disposition at extrapulmonary tuberculosis
(EPTB) sites in a 70-kg reference adult male (Ramachandran and Gadgil
2023, CPT Pharmacometrics Syst Pharmacol). Seventeen perfusion-limited
well-stirred tissue compartments connected by blood and lymph flow, plus
a gut-lumen state for enterohepatic recycling. The model's two novel
states are a pleural-fluid compartment (a filtrate of the lung that
drains via lymphatics) and a consolidated lymph-node compartment that
collects afferent lymph from every organ except bone and spleen and
returns it to venous blood - the two most common EPTB sites.
Physiological volumes, blood flows, and lymph flows are fixed literature
fractions of body weight, cardiac output (5200 mL/min), and afferent
lymph flow (8 L/day) respectively (Appendix S1 Tables S2 and S3).
Tissue:plasma partition coefficients were computed by the Rodgers and
Rowland method from the drug physicochemistry in Table S4 and are
tabulated in Table S5. Only the first-order oral absorption rate ka and
total systemic clearance CL were estimated, by weighted least squares
against reported plasma concentrations after a 400 mg oral dose
(Appendix S1 Table S7). Clearance is split into a renal component fR *
CL driven by arterial concentration and a hepatic component (1 - fR) *
CL driven by the hepatic inlet concentration; the hepatic output enters
the gut lumen, which for ethambutol is a terminal sink cleared only by
faecal transit at kF = 0.252 /h (the paper assigns a non-zero gut
reabsorption rate only to rifampicin). The model is a deterministic
typical-value simulation: the paper reports no interindividual
variability and no residual error model, so propSd is fixed at 0.
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Nemoto_2017_ethanol.html">Ethanol
(Nemoto 2017)</a> </td>
<td style="text-align:left;"> Bayesian population PK model for
orally ingested ethanol (alcohol) in 34 healthy Japanese adults (Nemoto
2017). One-compartment model with first-order absorption and
Michaelis-Menten elimination; covariates: sex, age, body weight, ALDH2
and ADH1B genotypes. Final model fit by a fully conditional MCMC
Bayesian analysis with informative priors derived from Seng et al. 2014
(Chinese + Indian cohort). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Ye_2017_ethaselen.html">Ethaselen
(Ye 2017)</a> </td>
<td style="text-align:left;"> Preclinical (mouse, BALB/c nude
with A549 NSCLC xenograft). Integrated dose-biomarker-response PD model
for the thioredoxin reductase (TrxR) inhibitor ethaselen (Ye et al.
2017). The TrxR biomarker is described by an indirect-response (IDR)
turnover in which the zero-order production Kin is linearly amplified by
the instantaneous natural tumor growth rate (linear correction factor
gamma1) and the first-order degradation Kout is increased by a sigmoidal
Emax function of the current administered ethaselen dose (Smax, SC50,
Hill = gamma2). Tumor volume follows a smooth exponential-to-linear
growth law (paper Eq 5: dX/dt = 2*lambda0*lambda1*X / (lambda1 +
2*lambda0*X)) tempered by a zero-order Emax killing rate driven by the
TrxR-inhibition ratio P = 1 - TrxR_treatment / TrxR_control (paper Eq
7). The control TrxR trajectory is carried internally as a shadow state
(trxr_ctrl) so P is defined per-subject without requiring an external
control-arm simulation. No pharmacokinetic compartment is included; the
paper acknowledges ethaselen plasma concentrations were not measured.
The current daily dose enters the model through the time-varying
covariate DOSE (mg/kg/day), which the published study toggles between 0
(vehicle / off-treatment) and one of {36, 72, 108} mg/kg/day for days
0-9 (oral gavage QD x10 d). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Freyer_2000_AVI_regimen.html">Etoposide
(Freyer 2000)</a> </td>
<td style="text-align:left;"> One-compartment IV population PK
model for etoposide in 24 small cell lung cancer patients on the AVI
regimen (Freyer 2000), with a linear serum creatinine effect on
clearance. Structural reduction from the paper's two-compartment model:
only central CL and V were reported in Table 2, so the peripheral
compartment is omitted. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Toffoli_2001_etoposide.html">Etoposide
(Toffoli 2001)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model for oral and IV etoposide in adult patients with solid tumours
(Toffoli 2001). Additive-linear creatinine-clearance covariate on CL
from Equation 2. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Moein_2022_etrolizumab.html">Etrolizumab
(Moein 2022)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model for etrolizumab with first-order SC absorption and time-decreasing
clearance in adults with moderately-to-severely active ulcerative
colitis (Moein 2022) </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/deWit_2016_everolimus.html">Everolimus
(deWit 2016)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model with first-order oral absorption for everolimus 10 mg once-daily
in 40 adult patients with advanced thyroid carcinoma (de Wit 2016).
Bioavailability F is structurally fixed at 1 (absolute F unknown), so
reported CL, V1, Q, and V2 are apparent (oral / F). Allometric scaling
on apparent clearance (exponent 0.75) and apparent central volume
(exponent 1.0) using a 70 kg reference weight per the Anderson and
Holford theory cited by the paper. Apparent peripheral volume V2/F was
held fixed at 400 L in the final model. Bioavailability is multiplied by
0.792 in subjects who carry at least one ABCB1 TTT haplotype (CYP3A /
P-gp efflux marker). Inter-occasion variability on F captures the
day-1-vs-day-15 sampling occasion contrast (CV 19.2%). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/TerHeine_2018_everolimus.html">Everolimus
(TerHeine 2018)</a> </td>
<td style="text-align:left;"> Semi-mechanistic two-compartment
population PK model for everolimus in pooled adult oncology (metastatic
thyroid or breast cancer) and renal transplant patients (ter Heine
2018). Oral absorption is modelled with a chain of four transit
compartments parameterised by the mean absorption time MAT and the Savic
2007 convention ktr = (n + 1) / MAT (n = 4 transit compartments).
Hepatic disposition uses a well-stirred liver model: hepatic plasma flow
QHP = QH * (1 - HCT); hepatic extraction EH = fu * CLint / (QHP + fu *
CLint) with FIXED unbound fraction fu = 0.27; oral bioavailability F = 1
- EH and systemic plasma clearance CLH = QHP * EH. Volume parameters
(VC, VP) and flow parameters (QH = 90 L/h FIXED, Q) are allometrically
scaled to fat-free mass FFM at a 57.2 kg reference (equivalent to a 70
kg, 1.80 m adult male) with theory-based exponents 0.75 on flows and 1.0
on volumes (Anderson and Holford). Concomitant high-dose oral
prednisolone (PRED_DOSE >= 20 mg/day, a CYP3A4 inducer) increases
apparent CLint by 31%. Modelled plasma concentrations were derived
externally from observed whole-blood concentrations and HCT via a
Langmuir-plus-linear erythrocyte binding model (Bmax = 0.964 mg/L, Kd =
0.0920 mg/L, Kns = 0.153); the vignette uses the same back-calculation
to compare simulated plasma concentrations against the paper's
whole-blood trough targets. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Pu_2021_evinacumab.html">Evinacumab
(Pu 2021)</a> </td>
<td style="text-align:left;"> Population PK/PD model for
evinacumab in healthy volunteers and adults / pediatric patients with
homozygous familial hypercholesterolemia (Pu 2021): two-compartment PK
with first-order SC absorption (with lag time) and parallel linear plus
Michaelis-Menten elimination from the central compartment, linked to a
Type 1 indirect-response model for low-density lipoprotein cholesterol
(LDL-C) where evinacumab inhibits LDL-C production. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Kuchimanchi_2018_evolocumab.html">Evolocumab
(Kuchimanchi 2018)</a> </td>
<td style="text-align:left;"> One-compartment population PK
model for evolocumab with first-order SC absorption and parallel linear
plus Michaelis-Menten (target-mediated) elimination from the central
compartment, in healthy adults and patients with hypercholesterolemia
(Kuchimanchi 2018) </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Kuchimanchi_2018_evolocumab.html">Evolocumab
ldlc (Kuchimanchi 2018)</a> </td>
<td style="text-align:left;"> Joint population PK + static
Emax-on-AUC exposure-response model for evolocumab LDL-C lowering in
adults with hypercholesterolemia (Kuchimanchi 2018). The PK layer (Table
3) is the one-compartment model with parallel linear and
Michaelis-Menten elimination and SC bioavailability from the companion
Kuchimanchi_2018_evolocumab.R file. The PD layer (Table 4) is an
algebraic Emax model linking AUC over weeks 8-12 of dosing to the mean
week-10-and-12 LDL-C reduction, with statin / ezetimibe / HeFH covariate
effects on baseline LDL-C, a statin covariate effect on Emax, and a
regimen-effect multiplier on EC50 distinguishing once-monthly (QM) from
once-every-2-weeks (Q2W) dosing. AUC of evolocumab is integrated inside
an extra rxode2 state over the 56-84-day window; the LDLC observable is
meaningful only at t >= 84 (vignette documents the time-window
discipline). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Wang_2024_evorpacept_qsp.html">Evorpacept
qsp (Wang 2024)</a> </td>
<td style="text-align:left;"> QSP. Quantitative systems
pharmacology platform for immuno-oncology in advanced non-small cell
lung cancer (NSCLC), extended with a pharmacokinetic and pharmacodynamic
module for the anti-CD47 antibody evorpacept (ALX-148) in combination
with the anti-PD-L1 antibody durvalumab. Four physiological compartments
(central, peripheral, tumour, tumour-draining lymph node) plus an
endothelial endosomal compartment for FcRn recycling, APC endosomal /
surface compartments and three immunological-synapse compartments
(T-cell:cancer-cell, T-cell:APC and macrophage:cancer-cell). The
evorpacept module adds target-mediated drug disposition through CD47 on
red blood cells with cross-arm (bivalent) binding, FcRn-mediated
recycling, and CD47-SIRP-alpha plus PD-1/PD-L1 control of macrophage
phagocytosis. The surrounding platform covers naive and activated
CD4+/CD8+ T cell trafficking and proliferation, logistic tumour growth,
antigen release, uptake, endosomal processing and MHC-I presentation for
a self-antigen and a neo-antigen, TCR kinetic proofreading,
PD-1/PD-L1/PD-L2/CTLA-4/CD28/CD80/CD86 checkpoint binding, M1/M2
macrophage recruitment and polarisation, MDSC recruitment with
arginase-I and nitric-oxide suppression, Th-to-Treg
transdifferentiation, and TGF-beta / IFN-gamma / IL-2 / IL-10 / IL-12 /
CCL2 dynamics. 153 ODE states, 6 algebraic species, 40
repeated-assignment rules and 276 parameters, translated from the
SimBiology export in Supplementary Tables S2-S6 and cross-checked
against the authors' MATLAB source (Zenodo doi:10.5281/zenodo.11093921).
Deterministic mechanism model: the authors generated virtual patients by
sampling the parameter distributions in Supplementary Table S1 rather
than by fitting IIV or residual error, so no etas and no error model are
encoded. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Valle_2005_exemestane.html">Exemestane
(Valle 2005)</a> </td>
<td style="text-align:left;"> Three-compartment population PK
with first-order absorption + lag time, coupled to an indirect-response
PD model on plasma estrone sulphate (E1S), for oral exemestane (25 mg
single dose) in healthy postmenopausal women. Crossover study comparing
a sugar-coated tablet (SCT) under fasting versus an extemporaneous
tablet-suspended-in-water suspension under fasting versus a SCT taken
after a standard high-fat breakfast. Disposition is independent of
formulation and food; absorption rate ka and apparent bioavailability F
depend on formulation (suspension: ka 7.6 vs SCT 2.35 1/h, F 1.2x) and
on the high-fat meal (ka 1.13 1/h, F 1.6x). Exemestane inhibits E1S
synthesis via a sigmoid Imax function with IC50 22.1 pg/mL and Hill
coefficient 1.73. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Cirincione_2017_exenatide.html">Exenatide
(Cirincione 2017)</a> </td>
<td style="text-align:left;"> Population PK model for exenatide
immediate-release (Cirincione 2017): two-compartment, parallel linear
and Michaelis-Menten elimination, sequential zero-order then saturable
first-order absorption after SC dosing. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Cirincione_2017_exenatide_er.html">Exenatide
er (Cirincione 2017)</a> </td>
<td style="text-align:left;"> Population PK model for
extended-release (ER) microsphere SC exenatide in patients with type 2
diabetes (Cirincione 2017 AAPS J): two-compartment disposition with
three parallel SC-absorption processes (initial first-order release plus
two Savic 2007 analytical transit-compartment chains for the second- and
third-phase microsphere release) and parallel linear plus saturable
Michaelis-Menten elimination. Disposition parameters (CL, Q, Vc, Vp,
Vmax, Km) and the eGFR-on-CL and WT-on-Vc covariate effects are fixed
from the IR companion model (Cirincione 2017 BJCP). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Ng_2018_exendin939.html">Exendin939
(Ng 2018)</a> </td>
<td style="text-align:left;"> Two-compartment
intravenous-infusion population PK model for exendin-(9-39) in patients
with congenital hyperinsulinism (Ng 2018). Pooled paediatric (neonates
and children) and adult cohort with allometric scaling fixed at 0.75 on
CL and Q and 1.0 on Vc and Vp (reference WT 70 kg); inter-individual
variability retained only on CL. Residual variability follows the NONMEM
Poisson error model (Var(Y|F) = F * sigma^2), encoded as a power-error
with fixed exponent 0.5. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Hazendonk_2016_factor_viii.html">Factor
viii (Hazendonk 2016)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model for factor VIII (FVIII) concentrates in severe and moderate
hemophilia A patients (adults and children, FVIII plasma concentration
< 0.05 IU/mL) undergoing elective / minor / major surgery (Hazendonk
2016). PK parameters are allometrically scaled to a 68 kg reference body
weight with fixed exponents of 0.75 on clearances and 1.0 on volumes;
typical CL, V1, Q, V2 at the reference body weight are 150 mL/h, 2810
mL, 160 mL/h, 1900 mL. Clearance carries three covariate effects (age
with power exponent -0.17 centered at 40 years; +26% for blood group O;
-7% for a major surgical procedure) and central volume carries an age
effect (power exponent -0.09 centered at 40 years). B-domain-deleted
recombinant FVIII products (Refacto AF) are under-detected by the
one-stage clotting assay by a fixed 34%, encoded as a multiplicative
correction on the predicted concentration. IIV on CL and V1 is 37% and
27% (exponential); IIV on Q and V2 was not estimable. Residual error is
combined (proportional 18% + additive 0.15 IU/mL) using the values
reported for the majority center cluster (centers 1, 2, 3). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Noe_1996_factor_viii.html">Factor
viii (Noe 1996)</a> </td>
<td style="text-align:left;"> Deterministic mechanistic model
of coagulation factor VIII kinetics with von Willebrand factor (vWF)
binding equilibrium in adult humans; captures endogenous synthesis,
reversible binding to vWF, and differential elimination of the free and
vWF-bound forms of factor VIII </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Brekkan_2016_factorIX.html">FactorIX
(Brekkan 2016)</a> </td>
<td style="text-align:left;"> Three-compartment population PK
model for plasma-derived factor IX (FIX) activity in patients with
moderate or severe haemophilia B, developed by Brekkan et al. 2016 to
support pharmacokinetic dose individualisation. Disposition is described
by linear three-compartment kinetics with intravenous input and
first-order elimination from the central compartment; allometric
body-weight scaling on CL/Q (0.75) and V1/V2/V3 (1.0) is fixed with a
reference weight of 70 kg, and an endogenous baseline FIX activity is
estimated as a structural parameter. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Koopman_2023_factorix.html">Factorix
(Koopman 2023)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model for recombinant factor IX-Fc fusion concentrate (rFIX-Fc,
eftrenonacog alfa) in haemophilia B patients aged 2-71 years (Koopman
2023) </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Larsen_2018_haemophilia_animal_popPK.html">Factorviia
dog (Larsen 2018)</a> </td>
<td style="text-align:left;"> Preclinical (beagle dog).
Two-compartment population PK model for activated recombinant factor VII
(rFVIIa) in male beagle dogs following single IV bolus administration,
from the Larsen 2018 preclinical scaling programme (n=10).
Body-weight-normalised allometric scaling (exponents 1 for V/V2, 0.75
for CL/Q; scaling principle I) is applied within-species around the
median weight of 12.8 kg. IIV is estimated on V and CL. Endogenous
rFVIIa was not detectable in dogs. Parameter values from Larsen 2018
Table 2 (Dog column). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Larsen_2018_haemophilia_animal_popPK.html">Factorviia
monkey (Larsen 2018)</a> </td>
<td style="text-align:left;"> Preclinical (cynomolgus monkey).
Two-compartment population PK model for activated recombinant factor VII
(rFVIIa) in cynomolgus monkeys following single IV bolus administration,
from the Larsen 2018 preclinical scaling programme (n=27; 16 males and
11 females). Endogenous rFVIIa was detectable in monkeys and is carried
as an additive baseline (0.287 IU/mL) on the observation. Body-weight-
normalised allometric scaling (exponents 1 for V/V2, 0.75 for CL/Q;
scaling principle I) is applied within-species around the median weight
of 2.78 kg. IIV is estimated on V, CL, and the endogenous baseline.
Parameter values from Larsen 2018 Table 2 (Monkey column). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Larsen_2018_haemophilia_animal_popPK.html">Factorviia
mouse (Larsen 2018)</a> </td>
<td style="text-align:left;"> Preclinical (mouse).
Two-compartment population PK model for activated recombinant factor VII
(rFVIIa) in male C57BI/6 and NMRI mice following single IV bolus
administration, developed as part of the Larsen 2018 preclinical scaling
programme (n=51 mice pooled across two strains). Strain enters as a
fractional multiplier on both V and CL (C57BI/6 = 0.588 x V, 0.87 x CL
relative to the NMRI reference), and body-weight-normalised allometric
scaling (exponents 1 for V/V2, 0.75 for CL/Q; scaling principle I) is
applied within-species around the median weight of 0.026 kg. IIV is
estimated only on CL. Endogenous rFVIIa was not detectable in mice.
Parameter values from Larsen 2018 Table 2 (Mouse column). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Larsen_2018_haemophilia_animal_popPK.html">Factorviia
rat (Larsen 2018)</a> </td>
<td style="text-align:left;"> Preclinical (rat).
Two-compartment population PK model for activated recombinant factor VII
(rFVIIa) in male Sprague-Dawley rats following single IV bolus
administration, from the Larsen 2018 preclinical scaling programme (n=37
rats). Body-weight-normalised allometric scaling (exponents 1 for V/V2,
0.75 for CL/Q; scaling principle I) is applied within-species around the
median weight of 0.24 kg. IIV is estimated on V and CL. Endogenous
rFVIIa was not detectable in rats. Parameter values from Larsen 2018
Table 2 (Rat column). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Nestorov_2014_factorviii.html">Factorviii
(Nestorov 2014)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model for recombinant factor VIII Fc fusion protein (rFVIIIFc,
efmoroctocog alfa) in previously treated patients with severe hemophilia
A (Nestorov 2014; final covariate model with VWF on CL and WT and HCT on
V1) </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Valke_2024_factorviii_thrombin_plasmin.html">Factorviii
(Valke 2024)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model for factor VIII (FVIII) activity (IU/dL) after a single
intravenous bolus of plasma-derived von Willebrand factor / factor VIII
concentrate (pdVWF/FVIII, Humate-P) in 29 adults with severe hemophilia
A (Valke 2024). The model was newly estimated after the earlier Bukkems
2022 popPK model over-predicted FVIII activity in this cohort (MPE
60.9%). CL, V1, Q and V2 are allometrically scaled to a 70 kg reference
with exponents fixed at 0.75 on clearances and 1 on volumes; typical
values are CL 3.07 dL/h, V1 39.1 dL, Q 1.09 dL/h, V2 9.16 dL, giving a
terminal half-life of 12.7 h. Clearance is 1.53x higher in patients with
a Nijmegen-modified Bethesda assay inhibitor. FVIII activity was
measured by both the one-stage clotting assay (OSA, the reference scale
of this model) and the chromogenic substrate assay (CSA); CSA samples
read 0.939x the OSA value and carry their own residual-error magnitudes.
IIV on CL (57.3%) and V1 (38.2%) is correlated at 77.0%. Residual error
is combined proportional plus additive, with assay-specific magnitudes.
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Larsen_2018_haemophilia_animal_popPK.html">Factorviii
dog (Larsen 2018)</a> </td>
<td style="text-align:left;"> Preclinical (haemophilia A dog).
Two-compartment population PK model for B-domain truncated recombinant
factor VIII (rFVIII) in haemophilia A dogs (1 male, 2 female) following
single IV bolus administration, from the Larsen 2018 preclinical scaling
programme (n=3). Body- weight-normalised allometric scaling (exponents 1
for V/V2, 0.75 for CL/Q; scaling principle I) is applied within-species
around the median weight of 19.55 kg. No IIV was estimated (only 3
subjects). Endogenous FVIII is not present (haemophilia A background).
Parameter values from Larsen 2018 Table 3 (Dog column). Note: Q is
estimated with high RSE (83%), reflecting the small sample size.
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Chelle_2019_factorviii_fanhdi.html">Factorviii
fanhdi (Chelle 2019)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model for Fanhdi/Alphanate (plasma-derived factor VIII concentrate,
Grifols) in hemophilia A patients pooled from 12 hemophilia centers in
the WAPPS-Hemo platform (Chelle 2019). Final model has fat-free mass
(FFM) as a power-form covariate on CL, V1, and V2, and a
piecewise-linear age effect on CL above the median age of 25 years;
between-subject variability is a BLOCK(2) on CL and V1 with correlation
0.797; residual error is proportional only. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Larsen_2018_haemophilia_animal_popPK.html">Factorviii
monkey (Larsen 2018)</a> </td>
<td style="text-align:left;"> Preclinical (cynomolgus monkey).
One-compartment population PK model for B-domain truncated recombinant
factor VIII (rFVIII) in male cynomolgus monkeys with
concentration-dependent (nonlinear) clearance, from the Larsen 2018
preclinical scaling programme (n=35). Clearance rises exponentially with
total FVIII activity (Larsen 2018 Eq. 1: CL(C) = CL_0 * exp(beta_cl *
C)) to capture saturation of the von Willebrand factor buffer at
supraphysiological doses. Body-weight-normalised allometric scaling
(exponents 1 for V, 0.75 for CL; scaling principle I) is applied within-
species around the median weight of 2.96 kg. IIV is estimated on CL and
the endogenous baseline. Endogenous FVIII (1.75 IU/mL) is carried as an
additive baseline on the total observed activity. Parameter values from
Larsen 2018 Table 3 (Monkey column). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Larsen_2018_haemophilia_animal_popPK.html">Factorviii
mouse (Larsen 2018)</a> </td>
<td style="text-align:left;"> Preclinical (mouse).
One-compartment population PK model for B-domain truncated recombinant
factor VIII (rFVIII) in FVIII-knockout (FVIII KO) mice following single
IV bolus administration, from the Larsen 2018 preclinical scaling
programme (n=132; 71 males, 61 females). Sex enters as a fractional
multiplier on CL (females clear rFVIII 24% faster than males), and body-
weight-normalised allometric scaling (exponents 1 for V, 0.75 for CL;
scaling principle I) is applied within-species around the median weight
of 0.021 kg. IIV is estimated on CL. Endogenous FVIII is not present
(KO). Parameter values from Larsen 2018 Table 3 (Mouse column).
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Valke_2024_factorviii_thrombin_plasmin.html">Factorviii
plasminPeak (Valke 2024)</a> </td>
<td style="text-align:left;"> Sequential PK-PD model relating
factor VIII (FVIII) activity to normalized plasmin peak height (% of
normal pooled plasma) measured with the Nijmegen hemostasis assay, after
a single intravenous bolus of plasma-derived von Willebrand factor /
factor VIII concentrate (pdVWF/FVIII, Humate-P) in 29 adults with severe
hemophilia A (Valke 2024). The PK layer is the two-compartment
allometric model of Valke 2024 Table 2 (see
modellib('Valke_2024_factorviii')); the PD layer is an inhibitory
proportional-baseline Imax model, E = Ebase * (1 - Imax * C^n / (EC50^n
+ C^n)), with baseline 81.2% of normal pooled plasma and EC50 256 IU/dL,
and Imax and the Hill coefficient both fixed at 1. FVIII replacement
therefore suppresses the raised fibrinolytic activity of untreated
severe hemophilia A. Inter-individual variability is carried on the
baseline (26.4%); residual error on the PD readout is proportional
(16.3%). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Larsen_2018_haemophilia_animal_popPK.html">Factorviii
rat (Larsen 2018)</a> </td>
<td style="text-align:left;"> Preclinical (rat).
One-compartment population PK model for B-domain truncated recombinant
factor VIII (rFVIII) in male and female Sprague-Dawley rats with
concentration-dependent (nonlinear) clearance, from the Larsen 2018
preclinical scaling programme (n=60; 30 males, 30 females). Clearance
rises exponentially with total FVIII activity (Larsen 2018 Eq. 1: CL(C)
= CL_0 * exp(beta_cl * C)) to capture saturation of the von Willebrand
factor buffer at supraphysiological doses. Sex enters as a fractional
multiplier on CL (females clear rFVIII 39% faster than males), and
body-weight-normalised allometric scaling (exponents 1 for V, 0.75 for
CL; scaling principle I) is applied within-species around the median
weight of 0.32 kg. Endogenous FVIII (1.12 IU/mL) is carried as an
additive baseline on the total observed activity. Parameter values from
Larsen 2018 Table 3 (Rat column). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Valke_2024_factorviii_thrombin_plasmin.html">Factorviii
thrombinPeak (Valke 2024)</a> </td>
<td style="text-align:left;"> Sequential PK-PD model relating
factor VIII (FVIII) activity to normalized thrombin peak height (% of
normal pooled plasma) measured with the Nijmegen hemostasis assay, after
a single intravenous bolus of plasma-derived von Willebrand factor /
factor VIII concentrate (pdVWF/FVIII, Humate-P) in 29 adults with severe
hemophilia A (Valke 2024). The PK layer is the two-compartment
allometric model of Valke 2024 Table 2 (see
modellib('Valke_2024_factorviii')); the PD layer is a
proportional-baseline Emax model, E = Ebase * (1 + Emax * C^n / (EC50^n
+ C^n)), with baseline 11.2% of normal pooled plasma, Emax 8.06 as a
factor of baseline, EC50 51.6 IU/dL and the Hill coefficient fixed at 1.
Inter-individual variability is carried on the baseline (34.7%);
residual error on the PD readout is additive (17.4% of normal pooled
plasma). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Valke_2024_factorviii_thrombin_plasmin.html">Factorviii
thrombinPotential (Valke 2024)</a> </td>
<td style="text-align:left;"> Sequential PK-PD model relating
factor VIII (FVIII) activity to normalized thrombin potential (% of
normal pooled plasma) measured with the Nijmegen hemostasis assay, after
a single intravenous bolus of plasma-derived von Willebrand factor /
factor VIII concentrate (pdVWF/FVIII, Humate-P) in 29 adults with severe
hemophilia A (Valke 2024). The PK layer is the two-compartment
allometric model of Valke 2024 Table 2 (see
modellib('Valke_2024_factorviii')); the PD layer is an additive-baseline
Emax model, E = Ebase + Emax * C^n / (EC50^n + C^n), with baseline 21.9%
of normal pooled plasma, Emax 65.3% of normal pooled plasma, EC50 1.93
IU/dL and the Hill coefficient fixed at 1. The very low EC50 means
thrombin potential stays near normal for 24 h after a bolus even as
FVIII activity falls. Inter-individual variability is carried on Emax
(33.1%); residual error on the PD readout is additive (16.2% of normal
pooled plasma). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Farrell_2012_farletuzumab.html">Farletuzumab
(Farrell 2012)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model for farletuzumab (humanized IgG1 anti-folate-receptor-alpha
monoclonal antibody) with first-order linear elimination after IV
infusion in women with advanced epithelial ovarian cancer (Farrell
2012). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Naik_2013_fasiglifam.html">Fasiglifam
(Naik 2013)</a> </td>
<td style="text-align:left;"> Joint population PK / FPG / HbA1c
model of fasiglifam (TAK-875, a novel GPR40 / free-fatty-acid-receptor-1
agonist) in adults with type 2 diabetes mellitus (T2DM) inadequately
controlled on metformin (Naik 2013 CPT PSP). Structural PK is a
two-compartment model with first-order absorption and linear elimination
(Q/F, V2/F, ka FIXED to values estimated in an earlier
multiple-rising-dose study because the phase-2 sparse-sampling design
could not identify them). Sex is an additive covariate on CL/F (males
~41 pct higher). Drug effect on fasting plasma glucose (FPG) is a
semi-mechanistic indirect-response model with Emax stimulation of Kout;
Emax depends exponentially on baseline FPG (BFPG) and on baseline
aspartate aminotransferase (AST = SGOT). HbA1c is driven by FPG via a
first-order production / elimination pair, with a placebo factor LIFE(t)
= 1 - MPL * (1 - exp(-ln(2) * t / HL_pl)) that scales HbA1c production
down over the 12-week trial (MPL half-life FIXED to 720 h from graphical
analysis). Baseline HbA1c depends linearly on disease duration
(T_DIAG_DIAB) and exponentially on BFPG. MPL has an additive sex effect
(males have larger placebo response). Data: 1211 PK samples from 286
T2DM patients and 2710 FPG + 1381 HbA1c samples from 346 T2DM patients
on 6.25-200 mg oral once-daily fasiglifam for 12 weeks. Fasiglifam was
subsequently withdrawn from phase-3 development in December 2013 for
hepatotoxicity signals; this popPK/PD model characterises the phase-2
dose-selection analysis that preceded that finding. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Yoshida_2024_fazpilodemab.html">Fazpilodemab
(Yoshida 2024)</a> </td>
<td style="text-align:left;"> Population PK + longitudinal
gastrointestinal-adverse-event (GIAE) discrete-time Markov +
treatment-discontinuation logistic model for the anti-FGFR/KLB
bispecific antibody fazpilodemab (BFKB8488A) in adults with type 2
diabetes mellitus or non-alcoholic fatty liver disease (Yoshida 2024).
The PK structure is a 2-compartment disposition with parallel direct
(ka) plus transit-mediated (ka2 via the depot2 absorption compartment,
transit rate ktr) subcutaneous absorption; linear plus Michaelis-Menten
elimination acting on free drug; target-mediated quasi-steady-state
binding to a constant target concentration rmax; and a sigmoidal
time-onset ADA-mediated clearance arm cl_ada that activates when ADA_POS
= 1. The DTMM transition probabilities (grade 0 / grade 1 / grade 2-3)
and the treatment-discontinuation probability are emitted as algebraic
outputs conditional on the time-varying PREV_AE_SCORE covariate (the
previous-day GIAE grade); the actual Markov-chain stochastic simulation
is performed downstream in R using these probabilities (matching the
mrgsolve plus Rcpp framework of the source paper supplement S2.3).
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Chen_2024_febuxostat.html">Febuxostat
(Chen 2024)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model for febuxostat in 128 healthy Chinese adult volunteers (Chen
2024), with a dual-depot parallel first-order absorption model built to
reproduce the multiple-peak plasma profiles of this BCS class II
compound. A fraction F1 of the dose is absorbed from a first depot (rate
ka1, lag time Tlag1) and the remaining 1 - F1 from a second depot (rate
ka2, lag time Tlag2). A standardised high-fat high-calorie meal slows
both absorption rate constants and lengthens Tlag1; body weight scales
the apparent central and peripheral volumes. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Hirai_2016_febuxostat.html">Febuxostat
(Hirai 2016)</a> </td>
<td style="text-align:left;"> Semi-mechanistic PK-PD model for
the hypouricemic effect of febuxostat (non-purine xanthine oxidase
inhibitor) in hyperuricemic patients with or without chronic kidney
disease. Combines a 2-compartment first-order absorption PK model for
febuxostat (literature-digitized, WinNonlin-fit) with (i) a reversible
mixed-type inhibition of xanthine oxidase (parameters transferred from
Takano 2005 in vitro bovine XO study), (ii) a 2-compartment endogenous
uric acid disposition model (adapted from Scott 1969), and (iii) a
1-compartment endogenous xanthine model. Renal uric acid clearance is a
power function of creatinine clearance (Tykarski 1991). Non-renal uric
acid clearance is assumed constant. All parameters are
literature-derived and fixed (deterministic mechanistic model; no
population-PK fit). Reproduces Figure 2 of Hirai 2016 (10 mg febuxostat
QD in a normouricemic 60 kg patient with CrCl 100 mL/min). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/HillMcManus_2017_febuxostat_lesinurad.html">Febuxostat
lesinurad (HillMcManus 2017)</a> </td>
<td style="text-align:left;"> Semi-mechanistic dual-drug PKPD
model for the impact of non-adherence to febuxostat (xanthine oxidase
inhibitor) plus lesinurad (URAT1 uricosuric) urate-lowering therapy in
gout; combines published 2-compartment first-order absorption PK for
each drug with a 4-compartment xanthine / uric-acid PD system
(Hill-McManus 2017) </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Henin_2012_gastrointestinal_transit_time_absorption.html">Felodipine
(Henin 2012)</a> </td>
<td style="text-align:left;"> Semi-mechanistic
Gastro-Intestinal Transit Time (GITT) absorption model applied to
extended-release felodipine (Henin 2012; the AAPS Journal 14:155-163).
The tablet moves through five GI regions (fundus -> antrum ->
proximal small intestine -> distal small intestine -> colon)
governed by sigmoid step functions with per-subject inflection points
IP_FA, IP_APSI, IP_PSI_DSI, IP_DSI_C supplied as covariates (population
distributions from Table II). Zero-order drug release from the tablet
into the current GI region at rates D1 (fundus 0.68 mg/h), D2/D3 (antrum
+ PSI 1.91 mg/h), D4/D5 (DSI + colon 1.16 mg/h); dissolved drug flows
downstream via K23 (fundus -> antrum, 0.43 1/h) and K34 (antrum ->
PSI, 3.48 1/h fasted or 0.81 1/h fed) with both K23 and K34 increased by
5 1/h once the tablet reaches the small intestine (Table I footnote a).
Dissolved drug in PSI, DSI, and colon is absorbed to a
semi-physiological liver compartment (Vliver 0.0143 L/kg, QH 3.5
L/h/kg^0.75) at rates K47 = K57 = 2.87 1/h and K67 = 1.15 1/h with
gut-wall bioavailability FA (0.23 fasted or 0.39 fed). Hepatic
extraction ratio EH = 0.50 and blood flow QH set the first-pass loss;
systemic distribution is a 3-compartment model (Vcentral,
Qperiph1/Vperiph1, Qperiph2/Vperiph2). This extraction encodes only the
'no return to fundus' subpopulation (7/12 felodipine subjects in the
paper); the 3-component antrum-fundus-return mixture is documented in
the vignette Assumptions and deviations. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Back_2018_fenofibrate.html">Fenofibrate
(Back 2018)</a> </td>
<td style="text-align:left;"> Mechanism-based oral absorption /
disposition model for fenofibrate (parent) and fenofibric acid (active
form, measured analyte) in healthy Korean adults under fasted,
standard-meal, and high-fat-meal conditions. Three drug compartments
(stomach -> duodenum -> central) coupled to a 2-compartment
calorie sub-model (stomach -> duodenum) via a bile-acid-driven
coupling: the combined fenofibrate-metabolism /
fenofibric-acid-absorption rate constant km&a is multiplied by (1 +
Ebile * calories_in_duodenum), and a time-varying gastric emptying rate
constant kg is multiplied by (1 + Efood) for the first 6.94 h after a
meal. Meal-type-specific shifts on Vc/F encode the additional
bioavailability change between fasted, standard, and high-fat meals.
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Bista_2015_fentanyl.html">Fentanyl
(Bista 2015)</a> </td>
<td style="text-align:left;"> One-compartment population PK
model for transdermal fentanyl (Durogesic patch) in adult cancer
patients with first-order absorption from the patch and allometric
body-weight scaling on CL/F and V/F (Bista 2015) </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Oosten_2016_fentanyl.html">Fentanyl
(Oosten 2016)</a> </td>
<td style="text-align:left;"> One-compartment population PK
model for fentanyl administered by continuous subcutaneous infusion and
transdermal matrix patch in adult cancer patients, with separate
first-order absorption for each route, transdermal lag time, allometric
body-weight scaling on CL/F and V/F (V/F fixed at 280 L), IIV on Ka (sc
and td), F (td), and CL/F, IOV on transdermal Ka multiplexed by
occasion, and proportional residual error (Oosten 2016). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Laffont_2025_opioid_overdose_reversal_simulation.html">Fentanyl
iv (Mann 2022)</a> </td>
<td style="text-align:left;"> Three-compartment IV fentanyl
population PK with a first-order biophase (effect-site) equilibrium
compartment, used as the agonist input layer of the Mann 2022
translational opioid-overdose model. Parameter values are the Algera
2021 popPK fit re-tabulated in Mann 2022 Supplement 1 Table S1
(intravenous fentanyl, healthy opioid- naive and chronic opioid-user
volunteers pooled, n = 30). Allometric scaling: CL and
inter-compartmental clearances on (WT/70)^0.75, volumes on (WT/70).
Outputs plasma concentration Cc in ng/mL and effect-site Ce in both
ng/mL and pM for downstream consumption by the Mann 2022 mu-opioid
receptor binding model. Intended for use as the IV-fentanyl agonist
input in a simulated overdose-rescue chain; no residual error is
reported in the source supplement. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Plock_2014_ferumoxytol.html">Ferumoxytol
(Plock 2014)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model with Michaelis-Menten elimination for IV ferumoxytol in healthy
adults and adults with chronic kidney disease (Plock 2014). Encodes the
typical non-dialysing-patient form; the haemodialysis-driven
time-varying central volume (VSLOPE) and the within-session weight-loss
effect on V1 (WLO) are described in the vignette but not enabled in this
model file. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Oishi_2014_fesoterodine.html">Fesoterodine
(Oishi 2014)</a> </td>
<td style="text-align:left;"> One-compartment population PK
model with first-order absorption and a lag time for the active
metabolite 5-hydroxymethyl tolterodine (5-HMT) following oral
administration of the prodrug fesoterodine as a sustained-release tablet
(Oishi 2014). Pooled analysis of 10 pharmacokinetic and 3
efficacy/safety studies in Western and East Asian healthy volunteers and
adult patients with overactive bladder. Dose entered as mg of
fesoterodine fumarate; CL/F and V/F are reported by the paper as
molecular-weight-adjusted values for 5-HMT so that dose (mg fumarate)
can be used directly with the reported parameters to yield 5-HMT
concentrations. CL/F varies with Cockcroft-Gault creatinine clearance
(power exponent 0.303 centred at 80 mL/min), moderate hepatic impairment
(Child-Pugh Class B multiplier 0.422), CYP2D6 poor-metaboliser phenotype
(multiplier 0.626), concomitant CYP3A inhibitor coadministration
(multiplier 0.504, source population coadministered ketoconazole),
concomitant CYP3A inducer coadministration (multiplier 3.90, source
population coadministered rifampicin), female sex (multiplier 0.903),
and Japanese ethnicity (multiplier 1.12). Inter-individual variability
is a full block on CL/F, V/F, and ka; Tlag IIV was fixed to zero by the
source authors. Residual variability is a combined additive +
proportional error model on 5-HMT plasma concentrations (LOQ 0.02 ng/mL
for most studies). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Sano_2023_fesoterodine.html">Fesoterodine
(Sano 2023)</a> </td>
<td style="text-align:left;"> Population pharmacokinetic model
for 5-hydroxymethyl tolterodine (5-HMT), the active metabolite of
fesoterodine, in pediatric patients aged 6-17 years with overactive
bladder or neurogenic detrusor overactivity. One-compartment disposition
with first-order absorption, a first-order absorption lag and
first-order elimination, fitted to 428 5-HMT concentrations from 142
patients pooled across the phase II study 1066 (NCT00857896) and the
phase III study 1047 (NCT01557244). Body weight is allometrically scaled
onto CL/F (exponent 0.75 FIXED) and Vd/F (exponent 1 FIXED) referenced
to 35 kg; CYP2D6 poor metabolizers carry 0.546-fold CL/F, female
patients 0.862-fold CL/F and 0.634-fold Vd/F, and the beads-in-capsule
(BIC) formulation carries 0.648-fold bioavailability relative to the
tablet reference. Absorption is flip-flop (ka 0.0897 1/h is far slower
than kel = CL/Vd = 1.05 1/h), so the reported 7.73 h terminal half-life
is absorption-rate-limited. Inter-individual variability on CL/F, Vd/F
and ka is a full 3x3 covariance block and residual error is additive on
the log-transformed concentration scale (i.e. log-normal). Doses are
supplied in micrograms so that amount/volume yields ng/mL, matching the
source NM-TRAN dataset. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Sano_2023_fesoterodine.html">Fesoterodine
mcc (Sano 2023)</a> </td>
<td style="text-align:left;"> Population
pharmacokinetic/pharmacodynamic exposure-response model relating
5-hydroxymethyl tolterodine (5-HMT, the active metabolite of
fesoterodine) average steady-state plasma concentration to maximum
cystometric capacity (MCC) in pediatric patients aged 6-16 years with
neurogenic detrusor overactivity. An Emax model in which the maximum
attainable MCC is the age-based expected bladder capacity (EBC) rather
than an estimated parameter: MCC = BASE + (Emax - BASE) * Cavg,ss /
(EC50 + Cavg,ss), with Emax = 30 * (AGE + 1) mL up to age 12 and a 390
mL plateau thereafter (FIXED, not estimated), and typical baseline MCC
scaling with age by the same (AGE + 1)/13 factor from a 190 mL plateau.
Fitted to 242 MCC observations (baseline and week 12) from 121 patients
in the phase III study 1047 (NCT01557244); EC50 is 6.22 ng/mL. This is
the pharmacodynamic half of a sequential PK-then-PD analysis: Cavg,ss is
supplied as the CAV covariate from individual empirical-Bayes estimates
of the companion population PK model, available in this library as
modellib('Sano_2023_fesoterodine'). This is a PD-only model with no dose
events and no ODE states; correlated inter-individual variability is
carried on baseline MCC and Emax, and residual error is combined
proportional plus additive. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Harrold_2020_filgrastim_ars.html">Filgrastim
(Harrold 2020)</a> </td>
<td style="text-align:left;"> Semi-mechanistic population PK /
absolute-neutrophil-count / overall-survival model for subcutaneous
filgrastim treatment of hematopoietic syndrome of acute radiation
syndrome (HS-ARS) in adult and pediatric humans. PK is one-compartment
(subcutaneous depot -> central drug amount) with target-mediated
disposition through quadratic-equilibrium free / bound filgrastim
partitioning against the time-varying G-CSF receptor pool. PD is a
5-stage granulopoiesis cascade (progenitor stem -> mitotic stem ->
two precursor stages -> circulating neutrophils); bound drug
stimulates receptor production (ST1) and transit between bone-marrow
stages (ST2). Acute radiation effect is a kinetic-pharmacodynamic depot
(depot_kpd) seeded by the radiation dose in Gy that decays first-order
at rate kpde and kills the mitotic-stem stage at rate kpdkill * kpd ^
gamma; gamma depends on the radiation dose rate via a Hill-type function
gamma = tgamma * DR / (DR + dr50). Overall survival is integrated as a
Cox cumulative hazard (cumhaz_os) on a Box-Cox transformation of an
effect-compartment ANC. All structural and IIV parameters fixed at the
values from Harrold 2020 Table 2 (granulopoiesis values from Melhem 2018
popPK / ANC in healthy adults and chemotherapy-induced neutropenia;
radiation / OS values scaled from rhesus-macaque NHP study with kpde and
kpdkill multiplied by 0.72 to match the human LD50 and the kpdkill IIV
omega halved per Harrold 2020 Methods 1.3 to address NHP-data sparsity).
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Kim_2017_fimasartan.html">Fimasartan
(Kim 2017)</a> </td>
<td style="text-align:left;"> Population PK-PD model for
fimasartan (an angiotensin II receptor blocker) in healthy adult Korean
men and men with mild or moderate hepatic impairment (Kim 2017). Plasma
fimasartan is described by a 2-compartment model with parallel
mixed-input absorption: a first-order arm with rate Ka and absorption
lag time LAG (fraction F1 = (1 - alpha) * F of the dose) running in
parallel with a zero-order arm of virtual duration D2 (fraction F2 =
alpha * F of the dose), where the total relative bioavailability F is
fixed at 0.18 in healthy subjects (Kim 2008) and incremented to 0.18 +
IL1 in mild and 0.18 + IL2 in moderate hepatic impairment to capture the
markedly higher Cmax observed in cirrhotic patients via reduced
first-pass extraction and intrahepatic shunting. The PD model describes
systolic and diastolic blood pressures as indirect-response (turnover)
compartments with zero-order synthesis Kin inhibited by fimasartan via a
sigmoid-Imax function E(C) = 1 - Emax * Cc / (EC50 + Cc) and first-order
loss Kout = Kin / Base; the steady-state baseline rides a fixed cosinor
circadian rhythm Bsl(t) = MESOR * (1 + Amp1% * cos(2*pi*(t - AC1)/24) +
Amp2% * cos(2*pi*(t - AC2)/12)) with amplitudes and phases inherited
from Park 2014 (healthy Korean reference). EC50 is stratified by
hepatic-impairment severity: for SBP, healthy versus any-impairment
pooled (mild + moderate); for DBP, healthy + mild versus moderate alone,
reflecting the contrasting impact of hepatic dysfunction on the two
pressure outputs. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Taubert_2018_finafloxacin.html">Finafloxacin
(Taubert 2018)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model for finafloxacin (a novel fluoroquinolone with enhanced
antibacterial activity at acidic pH) with linear elimination, parallel
first-order plus zero-order oral absorption (each with its own
absorption lag time), an additive renal + non-renal clearance
decomposition, and a cumulative-urinary excretion compartment. Built
from pooled data of 266 subjects across three trials: 127 healthy
volunteers (Trial I oral 25-1,000 mg/day; Trial II IV 200-1,000 mg/day)
and 139 patients with complicated urinary tract infections (Trial III IV
800 mg/day, 60-min infusions). Covariates: body surface area on the
central volume of distribution (power form, exponent 1.50, reference
1.829 m^2) and healthy / patient cohort status (DIS_HEALTHY) on both the
renal and non-renal clearance arms. The paper-reported total apparent
clearance (20.9 L/h healthy; -29% in patients) and population-specific
fraction renally excreted (FER1 = 0.40 healthy, FER2 = 0.21 patient) are
re-parameterised into the canonical lcl_renal + lcl_nonren additive
decomposition; the typical values are anchored to DIS_HEALTHY = 0
(patient reference) per the inst/references/covariate-columns.md
DIS_HEALTHY convention. The IIV translation between the paper and the
re-parameterised forms is documented in the validation vignette
Assumptions and deviations (Taubert 2018). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Eissing_2024_finerenone.html">Finerenone
(Eissing 2024)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model with a 4-transit-compartment delayed first-order absorption for
finerenone in adults with chronic kidney disease and type 2 diabetes
(FIGARO-DKD final PK model; Eissing 2024) </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Goulooze_2022_finerenone.html">Finerenone
(Goulooze 2022)</a> </td>
<td style="text-align:left;"> Population PKPD turnover model
for serum potassium response to finerenone in patients with chronic
kidney disease and type 2 diabetes (FIDELIO-DKD Phase III).
Indirect-response model with an Emax effect of finerenone steady-state
AUC on the potassium dissipation rate Kout, with a linear annual
disease-progression slope on serum K (different typical value for
active-treatment vs placebo arms). Finerenone PK is upstream (van den
Berg 2022) and reduced here to AUCss = DOSE / CL with typical apparent
clearance 28.0 L/h. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/vandenBerg_2021_finerenone.html">Finerenone
(vandenBerg 2021)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model for oral finerenone (Bayer BAY 94-8862, a non-steroidal selective
mineralocorticoid receptor antagonist) in adults with chronic kidney
disease and type 2 diabetes, developed on n=2284 subjects / 5057 sparse
PK observations from the FIDELIO-DKD Phase III trial (NCT02540993).
Absorption is modelled via a chain of four sequential first-order steps
(depot + three transit buffers, all at common rate Ka = 22.5 1/h, mean
transit time MTT = n_steps / Ka = 0.178 h with the depot counted as the
first compartment in the chain) preceded by a fixed 0.215 h absorption
lag time; the central-peripheral disposition is two-compartment with the
peripheral volume fixed equal to the central volume Vp/F = Vc/F (ratio
fixed at 1). Covariates retained in the final model are body weight and
Korean ethnicity on Vc/F; time-varying eGFR-CKD-EPI, body height, serum
creatinine, smoking status (current or former vs never), long-term
(>=50% of treatment period) SGLT2 inhibitor use, gamma
glutamyl-transferase, and a two-tier CYP3A4-inhibitor coadministration
categorisation (strong/moderate/weak inhibitor >=50% of treatment
period vs any other inhibitor exposure) on CL/F; with each of the CL/F
covariates (except GGT) ALSO applied inversely to the relative
bioavailability F1 in the paper's NONMEM control stream (so the
covariate appears on both CL/F and F simultaneously, the net effect on
steady-state AUC scales as 1 / covariate-factor^2 and the net effect on
Cmax scales as 1 / covariate-factor). Inter-individual variability is a
2x2 block on CL/F and Vc/F (omega^2 0.0961 / 0.104, covariance 0.0442,
correlation ~0.44); no IIV on Ka or absorption. Residual error is
proportional (sigma^2 = 0.313, propSd = sqrt(0.313) ~= 0.5595).
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Goulooze_2022_finerenone_uacr_egfr.html">Finerenone
egfr (Goulooze 2022)</a> </td>
<td style="text-align:left;"> Population PKPD
disease-progression model for the estimated glomerular filtration rate
(eGFR) response to finerenone in patients with chronic kidney disease
and type 2 diabetes (FIDELIO-DKD Phase III). eGFR declines at a constant
chronic slope that is flattened by an exponential stabilisation function
as eGFR approaches 16.1 mL/min/1.73 m^2, and the chronic slope is driven
by the model-predicted UACR time course from the companion UACR model
rather than by baseline UACR. Finerenone acts twice: an acute fully
reversible eGFR decline through a power function of steady-state daily
AUC acting via its own effect compartment, and, via its UACR reduction,
a sustained flattening of the chronic slope. Finerenone PK is upstream
(van den Berg 2022) and reduced here to AUCss = DOSE / CL with typical
apparent clearance 29.9 L/h. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Goulooze_2022_finerenone_uacr_egfr.html">Finerenone
uacr (Goulooze 2022)</a> </td>
<td style="text-align:left;"> Population PKPD
disease-progression model for the urine albumin-to-creatinine ratio
(UACR) response to finerenone in patients with chronic kidney disease
and type 2 diabetes (FIDELIO-DKD Phase III). UACR is integrated as a
state whose fractional progression rate is corrected by the
model-predicted UACR and by UACR over baseline; the finerenone effect is
a power function of steady-state daily AUC acting through an effect
compartment, and concomitant SGLT2 inhibitor use gives a direct
proportional shift. Finerenone PK is upstream (van den Berg 2022) and
reduced here to AUCss = DOSE / CL with typical apparent clearance 29.9
L/h. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Landersdorfer_2007_flucloxacillin.html">Flucloxacillin
(Landersdorfer 2007)</a> </td>
<td style="text-align:left;"> Three-compartment population PK
model for IV flucloxacillin in healthy adult volunteers (Landersdorfer
2007) with linear renal and non-renal elimination. The structural model
splits total clearance into a renal arm (CL_R = 5.37 L/h) and a
non-renal arm (CL_NR = 2.73 L/h); their sum reproduces the derived total
clearance CL_T = 8.10 L/h reported in Table 2. The renal arm also drives
a cumulative urinary excretion compartment that the paper fits jointly
with plasma. Distribution uses a shallow peripheral (V_2 = 2.61 L,
CLic_shallow = 15.3 L/h) and a deep peripheral (V_3 = 2.17 L, CLic_deep
= 1.23 L/h); central volume V_1 = 4.79 L. Between-subject variability is
reported as a full 5x5 variance-covariance matrix (Table 3, natural-log
scale) on CL_R, CL_NR, V_1, V_2, V_3; no BSV is included on the
inter-compartmental clearances. Residual error is combined additive +
proportional on both plasma concentrations (9.4% CV, 0.155 mg/L) and
cumulative urinary amounts (20.9% CV, 1.04 mg). The 5-min infusion
duration used in the study is supplied via dose records (DUR / RATE)
rather than as a model parameter. No structural covariates were
retained: the cohort was 10 healthy Caucasian adults (5 M / 5 F, weight
52-83 kg, age 23-34 years) and demographics are not used inside the
model. Monte Carlo dose-attainment simulations in the paper (continuous,
4-h, 0.5-h infusions) reuse these PK parameters together with 96%
protein binding. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Han_2013_fluconazole.html">Fluconazole
(Han 2013)</a> </td>
<td style="text-align:left;"> One-compartment IV population PK
model for fluconazole in adult burn-ICU patients with suspected or
confirmed Candida infection, with a piecewise CL covariate model that
switches between a fixed CRRT-cohort CL and a Cockcroft-Gault-CrCl /
postburn-recency / sepsis-shifted non-CRRT CL plus an additive WT /
edema / postburn-recency model on volume (Han 2013) </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Leroux_2018_fluconazole_micafungin.html">Fluconazole
(Leroux 2018)</a> </td>
<td style="text-align:left;"> One-compartment population PK
model of intravenous fluconazole in preterm and term neonates with
suspected or proven systemic candidiasis (Leroux 2018), with linear
current-weight scaling of CL and V. Typical-value structural model only:
the source paper and Data S1 supplement (goodness-of-fit plots only) do
not report inter-individual variability magnitudes, residual error
structure, or a maturation covariate functional form, so IIV and RUV are
encoded as fixed(0) and no postmenstrual / corrected gestational age
effect is encoded. See vignette Errata. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/McLachlan_1996_fluconazole.html">Fluconazole
(McLachlan 1996)</a> </td>
<td style="text-align:left;"> One-compartment population PK
model for fluconazole in adults with HIV/AIDS, fit to 770 plasma
concentrations from 113 male subjects pooled across an
intensive-sampling sub-study (Study 1, n=13, 12-17 samples per dose) and
a sparse routine-care sub-study (Study 2, n=100, single sample per
subject). Oral capsules (Diflucan, 50-800 mg) and 50 mg per 15 min IV
infusions are described by a single linear central compartment with
first-order absorption from a depot and zero-order input during IV
infusion. The final NONMEM clearance model is an additive
intercept-plus-slopes regression on Cockcroft-Gault creatinine clearance
(raw, not BSA-normalized) and absolute CD4+ T-lymphocyte count: CL (L/h)
= 0.25 + 0.0057 * CLcr (mL/min) + 0.00068 * CD4 (cells/mm^3); volume of
distribution, absorption rate, and bioavailability are not modulated by
covariates. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Momper_2016_fluconazole.html">Fluconazole
(Momper 2016)</a> </td>
<td style="text-align:left;"> One-compartment population PK
model for fluconazole with first-order oral absorption and IV
administration in extremely premature infants with birth weights <
750 g (Momper 2016) </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Patel_2011_fluconazole.html">Fluconazole
(Patel 2011)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model for intravenous fluconazole in 10 critically ill anuric adults
receiving continuous venovenous hemodiafiltration (CVVHDF) (Patel 2011).
Total fluconazole clearance from the central compartment is partitioned
into a CVVHDF-route arm (CL_CVVHDF, 1.66 L/h typical, encoded as
lcl_renal) and a non-CVVHDF arm (CL_NCVVHDF, 1.01 L/h typical, encoded
as lcl_nonren) that are fitted simultaneously to the plasma
concentration-time profile and the cumulative amount of fluconazole in
the CVVHDF effluent. Dialysis-filter membranes in use for more than 48
hours reduce CVVHDF efficiency to 36.8 percent of the fresh-filter
baseline (FILT_AGE_HI indicator on the CL_CVVHDF arm, multiplicative
effect 0.368, bootstrap 95 percent confidence interval 0.326 to 0.426;
informed by 1 of 10 patients with a > 48 h filter). Input into the
central compartment is zero-order over an estimated infusion duration D1
(typical 0.689 h, near the 60-min nominal infusion). No subject-level
covariates (age, total body weight, sex, APACHE II score) reached the
OFV-3.84 retention threshold on CL, Vc, Q, or Vp, so no demographic
covariates are encoded in this file. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Wade_2008_fluconazole.html">Fluconazole
(Wade 2008)</a> </td>
<td style="text-align:left;"> One-compartment intravenous
population PK model for fluconazole in preterm and term infants
(gestational age 23-40 weeks, postnatal age <120 days) with
allometric body weight on CL and V (fixed exponents 0.75 and 1.0,
reference 1 kg), power effects of gestational age at birth (reference 26
weeks) and postnatal age (reference 2 weeks) on CL, and an on/off power
effect of serum creatinine on CL gated when SCR > 1 mg/dL (Wade
2008). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Watt_2015_fluconazole.html">Fluconazole
(Watt 2015)</a> </td>
<td style="text-align:left;"> One-compartment population PK
model for intravenous fluconazole in critically ill children (1 day to
17 years; n=40) supported with extracorporeal membrane oxygenation
(ECMO) or matched non-ECMO controls (Watt 2015). Clearance scales
linearly with body weight and is modulated by serum creatinine via a
power function (CREAT/0.4)^-0.29 centered at the cohort median initial
SCR of 0.4 mg/dL; allometric 3/4- power scaling on CL was tested and
rejected (delta-OFV +9.7) so a linear weight scaling was retained.
Central volume scales linearly with body weight and is increased
1.39-fold in subjects on ECMO support via a multiplicative power factor
1.39^ECMO_STATUS. Proportional residual error (15.3% CV); diagonal Omega
with IIV on CL (33.2% CV) and V (22.2% CV) only -- the paper retained
the proportional-only error model after showing the
proportional-plus-additive form could not precisely estimate the
additive component. Used by the authors to derive dosing recommendations
for invasive candidiasis prevention (12 mg/kg loading then 6 mg/kg
daily) and treatment (35 mg/kg loading then 12 mg/kg daily) in children
on ECMO. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Langenhorst_2019_fludarabine.html">Fludarabine
(Langenhorst 2019)</a> </td>
<td style="text-align:left;"> Three-compartment IV population
PK model for the circulating fludarabine metabolite F-ara-A in children
and adults (n = 258, age 0.3-74 years) receiving fludarabine phosphate
as part of myeloablative conditioning prior to allogeneic hematopoietic
cell transplantation (Langenhorst 2019). Total clearance is decomposed
into a non-renal component (3.2 L/h at 70 kg) and an eGFR-driven renal
component with slope 0.78 (unitless), both allometrically scaled to
actual body weight at a fixed 0.75 exponent referenced to 70 kg: CL =
(3.2 + eGFR_L_per_h * 0.78) * (BW/70)^0.75 L/h, where eGFR is expressed
in L/h (converted from Cockcroft-Gault / Schwartz eGFR in mL/min/1.73
m^2 by * 60/1000). Central volume V1 (39 L), first peripheral V2 (20 L),
and second peripheral V3 (50 L) all scale allometrically at a fixed 1.0
exponent to 70 kg. Inter-compartmental clearances Q2 (8.6 L/h, V1-V2)
and Q3 (3.8 L/h, V1-V3) scale at a fixed 0.75 exponent to 70 kg. Because
the random effects on the volume triplet (V1, V2, V3) and on the
clearance triplet (CL, Q2, Q3) were highly correlated in the original
NONMEM fit, the paper encodes a SINGLE shared eta on {V1, V2, V3} (48%
CV) and a SINGLE shared eta on {CL, Q2, Q3} (23% CV) -- implemented here
as identical eta terms across the three parameters in each group
(perfect correlation, matching the paper's coding). Inter-occasion
variability (12% CV on CL/Q2/Q3, 31% CV on V1/V2/V3, one occasion per
dose) reported by Langenhorst 2019 Table 2 is NOT encoded structurally:
the source paper defines each dose as an occasion but nlmixr2lib omits
IOV when no operational occasion column is defined for downstream use
(Brooks 2021 / Andrews 2017 precedent); downstream users can add an OCC
indicator and per-occasion etas in rxode2. Residual error is
proportional (6.3% CV) on the linear concentration scale. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Polito_2016_fludrocortisone.html">Fludrocortisone
(Polito 2016)</a> </td>
<td style="text-align:left;"> One-compartment population PK
model for oral fludrocortisone with first-order absorption, an
absorption lag time, and first-order elimination, estimated in 14 adults
with septic shock (out of 21 enrolled; 7 had undetectable plasma
concentrations) receiving a single 50 ug oral dose of fludrocortisone
acetate via naso-gastric tube (Polito 2016). The Simplified Acute
Physiology Score II (SAPS II) is retained as a positive power covariate
on both apparent oral clearance CL/F (exponent 0.019) and absorption lag
time Tlag (exponent 0.036), normalised to the cohort median SAPS II =
53. Inter-individual variability is exponential on every PK parameter
(ka, V/F, CL/F, Tlag) with a diagonal OMEGA matrix; residual error is
proportional. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Luo_2024_CES1_cirrhosis.html">Flumazenil
pbpk (Luo 2024)</a> </td>
<td style="text-align:left;"> PBPK (semi-mechanistic, custom
WinNonlin 8.1 implementation). flumazenil disposition in healthy adults
and in liver cirrhosis (Child-Pugh A/B/C). Flumazenil is a direct-acting
benzodiazepine-receptor antagonist that CES1 INACTIVATES to flumazenil
acid, so no active metabolite is tracked. Renal clearance is negligible
(CLint,K 1.67 mL/min). Section 4 notes enzymes other than CES1 also
metabolise flumazenil, which the paper cites as a reason its cirrhosis
AUCR was underpredicted. The semi-PBPK circuit is stomach, three
small-intestinal lumen segments (duodenum / jejunum / ileum), the
matching three gut-wall segments, portal vein, liver, kidney and a
two-compartment systemic compartment. Cirrhosis is applied by switching
the Child-Pugh-specific physiology of Table 1 (organ blood flows,
functional liver volume, GI transit rates, GFR, plasma-binding protein
concentrations, hepatic CES1 content) and rescaling CLint, CLint,K, Peff
and Vsys through Eq 1-6. Deterministic: the paper's virtual populations
are uniform 80-120% draws on the drug parameters, not lognormal random
effects, so no IIV is encoded. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Kumpulainen_2010_flurbiprofen.html">Flurbiprofen
(Kumpulainen 2010)</a> </td>
<td style="text-align:left;"> Three-compartment population PK
model with a separate cerebrospinal-fluid (CSF) compartment for
flurbiprofen in 64 healthy children aged 3 months to 13 years
(Kumpulainen 2010). Two parallel absorption routes: oral syrup via an
absorption compartment with lag time (K12) and a single first-order ka,
and IV flurbiprofen axetil prodrug via a separate dosing compartment
that converts to flurbiprofen with a first-order rate constant (K42).
Plasma kinetics scaled allometrically by weight (exponents fixed at 0.75
for CL and 1 for all volumes, including the CSF volume held fixed at
0.15 L/70 kg per literature). The paper's QCSF + UPTK parameterisation
is encoded as canonical influx / efflux clearances clin = QCSF * UPTK
and clef = QCSF, with fraction unbound (fu) gating only the
central-to-CSF flux. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Zhang_2018_flurbiprofen.html">Flurbiprofen
(Zhang 2018)</a> </td>
<td style="text-align:left;"> One-compartment IV population PK
plus Holford-Sheiner effect-compartment for cerebrospinal fluid (CSF)
disposition of flurbiprofen, the active metabolite of flurbiprofen
axetil, in Chinese adults with postoperative pain receiving 1 mg/kg IV
flurbiprofen axetil (Zhang 2018, Tables 1-2, Eq. 3 covariate form).
Final-model typical values CL = 1.55 L/h, Vd = 7.91 L, plasma-CSF
equilibration rate Ke = 0.0015/h; linear-multiplicative covariate
effects of weight and height on Ke centered on the population medians
(68.5 kg, 165 cm). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Weber_2015_fluticasone_inhaled.html">Fluticasone
inhaled (Weber 2015)</a> </td>
<td style="text-align:left;"> Semi-mechanistic. Population PK
model for inhaled fluticasone propionate (FP) in healthy adult
volunteers (Weber 2015), used for Monte-Carlo simulation of PK-based
bioequivalence trials. Separate central (LC1 -> LC2) and peripheral
(LP1 -> LP2) lung deposition compartments hold undissolved drug
particles (LC1, LP1) and dissolved drug (LC2, LP2); mucociliary
clearance kmuc removes undissolved particles from central lung regions
only; dissolved drug is absorbed into a two-compartment systemic
disposition with central-to-peripheral rate constants k12 and k21. Each
administration splits across LC1 (bioavailability flung * fc) and LP1
(bioavailability flung * (1 - fc)); the remaining (1 - flung) fraction
is assumed to have negligible oral bioavailability. F_Lung and F_C are
logit-transformed; all other parameters are log-transformed. Structural
parameters and BSV were taken from the validated FP inhalation model of
Weber and Hochhaus 2013 (reference 13 of Weber 2015); BOV on F_Lung,
F_C, and kmuc described as a paper-specific extension for
crossover-trial simulation is NOT encoded in this model file (see
vignette Assumptions and deviations). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Geldof_2008_fluvoxamine_rat.html">Fluvoxamine
rat (Geldof 2008)</a> </td>
<td style="text-align:left;"> Preclinical (rat, male Wistar).
Non-linear pharmacokinetic brain distribution model for fluvoxamine in
plasma, brain extracellular fluid (ECF) and total brain tissue, fit by
Geldof et al. (2008, Pharm Res 25(4):792-804) using simultaneous
analysis of microdialysate ECF (n = 26 rats, frontal-cortex CMA/12
probe) and total brain tissue (n = 35 rats, destructive brain sampling)
after a single 30 min IV infusion of 1, 3.7 or 7.3 mg/kg fluvoxamine.
The structural model is a three-compartment plasma disposition (central
+ 2 peripherals, with PK parameters fixed at the mean post-hoc estimates
from the upstream Geldof 2007 rat population PK model, Table I
'Microdialysis + brain sampling' row) coupled to a single-state lumped
brain compartment (brain_total) whose dynamics follow dCT/dt = kin*Cp -
kout*CSP (paper Eq 10), with the shallow perfusion-limited CSP and deep
brain CDB (= ECF) concentrations recovered algebraically at every time
step from CT via the rapid-equilibrium saturable-efflux quadratic (paper
Appendix Eq 47). The single lumped efflux parameter N***max (NstarMax in
this file) and C50 govern the saturation of the active (Pgp /
MRP-mediated) removal flux from the deep brain back to the shallow
brain. Inter-individual variability is on kin and kout only, with the
correlation reported in Table II. The proportional residual error
sigma^2 = 0.042 is shared between the ECF (Cecf) and total- brain
(Cbrain) observations per Table II. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Rose_2016_follitropin_delta.html">Follitropin
delta (Rose 2016)</a> </td>
<td style="text-align:left;"> One-compartment population PK
model for FE 999049 (recombinant human FSH; INN follitropin delta) with
first-order subcutaneous absorption through a single transit compartment
and first-order elimination, in 27 healthy pituitary-suppressed female
subjects after a single subcutaneous dose of 37.5-450 IU (2.2-26.3 ug).
Body weight enters as an allometric covariate on apparent clearance
(exponent 0.75) and apparent volume of distribution (exponent 1) with
reference weight 65 kg. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Zufferey_2018_fondaparinux.html">Fondaparinux
(Zufferey 2018)</a> </td>
<td style="text-align:left;"> Parametric time-to-event model
for major bleeding after major orthopaedic surgery under fondaparinux
thromboprophylaxis (POP-A-RIX 2.5 mg once daily and PROPICE 1.5 mg once
daily pooled cohorts; n = 1393, 64 adjudicated bleeding events). The
hazard is hz(t) = h0(t) * exp(beta1*SEX + beta2*AUCinf/8.5 +
beta3*LBM/44), with gamma-shaped baseline h0(t) =
theta1*theta2*(t-theta3)*exp(-theta2*(t-theta3)) for t > theta3 and 0
otherwise (lag time theta3 ~= 17.6 h, peak ~4 days post-surgery). AUCinf
is derived inside the model from daily dose and clearance using the
paper's PK equation CL = 0.34 * (CRCL/60)^0.485 * exp(eta)
(lean-body-weight Cockcroft-Gault CrCl). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Fisher_2008_fosamprenavir.html">Fosamprenavir
(Fisher 2008)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model with first-order absorption for orally administered fosamprenavir
(FPV), measured as the active amprenavir (APV) metabolite, in
HIV-1-infected pediatric patients aged 4 weeks to 18 years (Fisher
2008). Allometric scaling on apparent clearance (CL/F, Q) at a fixed
exponent of 0.75 and on apparent volumes (V2/F, V3) at a fixed exponent
of 1.0 (reference 70 kg). Apparent CL/F is reduced ~60% by concomitant
ritonavir (RTV) co-administration (maximal CYP3A4 inhibition assumed at
the RTV doses used), and is further modified by a piecewise
age-maturation factor (linearly declining additive offset for AGE <=
2*AG50, zero above), by sex (lower in females), by race (separate
multipliers for Black and for the non-Black non-White composite vs the
White reference), and by a power effect of serum alpha-1-acid
glycoprotein (AAG, centred at 0.77 g/L). Apparent V2/F also carries a
power effect of AAG. Bioavailability is anchored on suspension-under-fed
conditions (F=1), with a separate relative bioavailability for the
tablet formulation (F_tab) and a separate relative bioavailability for
the suspension administered fasted (F_food,sus). Inter-occasion
variability on CL/F (~34% CV) reported by the source poster is NOT
structurally encoded here (no operational occasion column is defined for
the model-library use case); downstream users who want to simulate IOV
can add an OCC indicator and a per-occasion eta in rxode2. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Weatherley_2018_fosdagrocorat.html">Fosdagrocorat
(Weatherley 2018)</a> </td>
<td style="text-align:left;"> Simultaneous parent-metabolite
population PK model for oral fosdagrocorat (PF-04171327, a
phosphate-ester prodrug of the dissociated glucocorticoid receptor
agonist PF-00251802) in adult rheumatoid-arthritis patients receiving
stable background methotrexate (Weatherley 2018). The prodrug is fully
cleaved by alkaline phosphatase in the gut wall before absorption; only
the active Metabolite-1 (PF-00251802) and its circulating N-oxide
Metabolite-2 (PF-04015475) are modelled. Metabolite-1 is described by a
two-compartment disposition (apparent CL, V2, Q, V4 fixed at 209 L) with
first-order absorption (K12) and bioavailability F1 fixed at 1 (apparent
F absorbed via the prodrug-to-Metabolite-1 conversion). Metabolite-2 is
described by a one-compartment disposition (apparent Vm, CLm) with Fm
fixed at 1 (assumed 100 percent molar conversion of Metabolite-1 to
Metabolite-2). Standard allometric weight scaling is fixed on
Metabolite-1 disposition (exponent 0.75 on CL and Q; exponent 1.00 on V2
and V4); body-weight scaling on Metabolite-2 CLm is estimated as a
power-form covariate (exponent 0.450) and no weight effect is applied to
Vm (rejected in stepwise covariate testing). Retained covariates on
Metabolite-1 CL are female-vs-male (-26.8 percent) and a small linear
age effect (-0.00633 L/h per year above 40). Retained covariates on
Metabolite-2 CLm are female-vs-male (-34.1 percent) and body weight.
Inter-individual variability is reported on Metabolite-1 CL (33 percent
CV) and absorption rate K12 (249 percent CV), and on Metabolite-2 Vm (44
percent CV) and CLm (26 percent CV). The publication's interoccasion
variability on Metabolite-1 F1 (23.8 percent CV across dosing occasions)
is encoded here as IIV on F1 because nlmixr2lib simulation does not
carry an occasion column; this approximation is documented in the
vignette Assumptions section. Residual error is combined additive plus
proportional on the linear-concentration scale separately for each
analyte (Metabolite-1 proportional 19.9 percent + additive 0.305 ng/mL;
Metabolite-2 proportional 7.8 percent + additive 0.10 ng/mL).
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Shoji_2017_fosdagrocorat_oc.html">Fosdagrocorat
oc (Shoji 2017)</a> </td>
<td style="text-align:left;"> Kinetic-pharmacodynamic (K-PD)
model for serum osteocalcin (OSTCALC) bone-formation biomarker following
once-daily oral fosdagrocorat (PF-04171327, a dissociated agonist of the
glucocorticoid receptor) or oral prednisone comparator in adults with
rheumatoid arthritis on background methotrexate (Shoji 2017). Sister
model to Shoji_2017_fosdagrocorat_p1np: identical K-PD structure
(virtual K-PD depot with zero-order Input mg/week and first-order KDE;
sigmoid Emax inhibition of biomarker synthesis with Hill coefficient
fixed to 1; empirical dose-and-time-dependent rebound multiplier;
additive placebo-period slope). For the OSTCALC fit Shoji 2017 fixed KDE
to the P1NP-derived estimates and fixed Imax to 1 for both drugs, and
used independent (not block) IIV on KDE, EDK50, and BL. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Shoji_2017_fosdagrocorat_p1np.html">Fosdagrocorat
p1np (Shoji 2017)</a> </td>
<td style="text-align:left;"> Kinetic-pharmacodynamic (K-PD)
model for serum amino-terminal propeptide of type I collagen (P1NP)
bone-formation biomarker following once-daily oral fosdagrocorat
(PF-04171327, a dissociated agonist of the glucocorticoid receptor) or
oral prednisone comparator in adults with rheumatoid arthritis on
background methotrexate (Shoji 2017). A virtual K-PD depot for the drug
(zero-order Input mg/week, first-order elimination KDE) feeds a sigmoid
Emax inhibition of biomarker synthesis (Hill coefficient fixed to 1);
the synthesis rate carries an empirical dose-and-time-dependent rebound
multiplier and an additive linear placebo-period slope captures the
methotrexate-only time trend. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Huppe_2023_fosfomycin.html">Fosfomycin
(Huppe 2023)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model for multiple-dose intravenous fosfomycin in critically ill adults
with renal insufficiency during continuous venovenous hemodialysis
(CVVHD). Total clearance is the sum of a renal arm driven linearly by
measured urinary creatinine clearance (gated off in anuric patients) and
a CVVHD arm given by the Michaels hemodialyzer equation as a function of
blood flow rate, dialysate flow rate, and a mass transfer-area
coefficient. Central volume increases linearly with time since first
dose (Huppe 2023). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Gibiansky_2005_fospropofol.html">Fospropofol
(Gibiansky 2005)</a> </td>
<td style="text-align:left;"> Joint two-compartment fospropofol
(GPI 15715, AQUAVAN) prodrug + intermediate delay compartment +
two-compartment propofol active-metabolite population PK model in adults
receiving IV bolus AQUAVAN for procedural sedation (Gibiansky 2005,
ASCPT poster, colonoscopy sedation Phase II study). The model assumes
complete metabolism of GPI 15715 to propofol via systemic
alkaline-phosphatase hydrolysis; the intermediate compartment captures
the appearance delay between GPI 15715 elimination from plasma and the
corresponding rise in propofol concentration. Lean body mass (LBM,
reference 55 kg) was retained as a linear-fractional covariate on GPI
15715 central volume Vc_GPI, GPI 15715 metabolic clearance CL_GPI, and
propofol central volume Vc_PR; fentanyl premedication exposure, age,
sex, and other demographics/laboratory covariates were tested but not
retained. Propofol Vc_PR (6.91 L) was fixed as the data were
insufficient for joint estimation with CL_PR (the model is identifiable
on CL_PR = K10_PR * Vc_PR = 4.53 L/min). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Fiedler-Kelly_2019_fremanezumab.html">Fremanezumab
(Fiedler-Kelly 2019)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model for fremanezumab (anti-CGRP IgG2 delta-a/kappa mAb) with
first-order SC absorption, absorption lag time, and route-specific
central volume / residual error supporting both IV and SC administration
in healthy adults and adults with chronic or episodic migraine
(Fiedler-Kelly 2019). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/FiedlerKelly_2020_fremanezumab_cm.html">Fremanezumab
cm (FiedlerKelly 2020)</a> </td>
<td style="text-align:left;"> Population PD exposure-response
model relating fremanezumab average plasma concentration (Cav) to
monthly moderate-to-severe headache days in adults with chronic
migraine. Placebo time-course is a Hill (sigmoid) function in months and
the drug effect is a power function of Cav centered on the population
median Cav. Fitted to 5312 monthly observations from 1361
chronic-migraine patients pooled across the LBR-101-021 phase 2b and
TV48125-CNS-30049 phase 3 studies (Fiedler-Kelly 2020). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/FiedlerKelly_2020_fremanezumab_em.html">Fremanezumab
em (FiedlerKelly 2020)</a> </td>
<td style="text-align:left;"> Population PD exposure-response
model relating fremanezumab average plasma concentration (Cav) to
monthly migraine days in adults with episodic migraine. Placebo
time-course is an exponential growth in months (predicted reduction =
exp(exponent * t)) and the drug effect is an Emax/EC50 of Cav scaled by
individual baseline migraine days. Fitted to 4444 monthly observations
from 1142 episodic-migraine patients pooled across the LBR-101-022 phase
2b and TV48125-CNS-30050 phase 3 studies (Fiedler-Kelly 2020).
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Zou_2022_furmonertinib.html">Furmonertinib
(Zou 2022)</a> </td>
<td style="text-align:left;"> Semi-mechanistic joint
parent-metabolite population PK model for oral furmonertinib (AST2818, a
third-generation irreversible EGFR TKI) and its active metabolite
AST5902 (Zou 2022). The parent has two-transit-compartment absorption
(rate constant ka shared for depot and both transits) feeding a
two-compartment parent disposition (CL/F, Vc/F, Q/F, Vp/F). The parent
is eliminated through the central compartment; a fraction Fm of the
parent elimination becomes AST5902, which is described by a
two-compartment metabolite (Clm/(F*Fm), Vcm/(F*Fm), and
inter-compartment rate constants k67 and k76). Because no intravenous
data were available, the absolute parent bioavailability F and the
fraction Fm are non-identifiable and are absorbed into the apparent
parameters. Autoinduction of furmonertinib metabolism (mediated by
CYP3A4) is modelled as an indirect-response (IDR III) enzyme pool with
unity baseline: d(A_ENZ)/dt = kENZ * (1 + S * Cc) - kENZ * A_ENZ, and
the apparent parent clearance is CLbase/F * A_ENZ. Covariates: alkaline
phosphatase (ALP, U/L) via power effect on CLbase/F and on Clm/(F*Fm)
(median 77.2 U/L); body weight (WT, kg) via power effect on Clm/(F*Fm)
(median 65 kg); and a categorical food-with-a-high-fat-meal effect on
parent oral bioavailability (+22.4%) and on the fraction converted to
AST5902 (-33.5%). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Yoshioka_2018_FXa_inhibitors_mbma.html">FXa
inhibitors mbma (Yoshioka 2018)</a> </td>
<td style="text-align:left;"> MBMA. PT-ratio-driven logistic
event-rate model for direct oral factor Xa inhibitors (rivaroxaban,
apixaban, edoxaban) in non-valvular atrial fibrillation. Inputs a
population-mean prothrombin-time ratio (PTR) supplied per observation
time; outputs per-arm probability of ischemic stroke/SE (p_isse) and of
major bleeding (p_mb), plus a derived per-arm mortality probability. Fit
by NONMEM 7.3 to per-arm event counts from 5 large RCTs (Yoshioka 2018;
57,655 patients). Suitable for simulating per-arm summary outcomes only;
the upstream popPK -> PT-ratio layer for each FXa inhibitor is out of
scope and PTR must be supplied externally. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Willmann_2021_fxi_aso.html">FxiLica
(Willmann 2021)</a> </td>
<td style="text-align:left;"> Population PK/PD model for the
GalNAc-conjugated FXI antisense oligonucleotide FXI-LICA (BAY2976217,
formerly ION-957943) after subcutaneous administration in healthy
volunteers (study LICA-CS1), pooled with IONIS-FXIRX data to fit the
FXI-activity indirect- response arm (Willmann 2021). Pharmacokinetics:
two-compartment model with parallel first-order (fraction F1, rate ka)
and zero-order (fraction 1 - F1, duration D2) subcutaneous absorption
and first-order elimination from the central compartment. The final PK
model retained an OMEGA block for the correlations between IIV on CL,
V2, and Q (rho ~ 0.6-0.7; Table S3). Pharmacodynamics: indirect-response
model on FXI activity with sigmoid-Imax inhibition (Imax fixed to 1) of
the zero-order synthesis rate Kin = baseline * kout, driven by an
effect-site concentration linked to the plasma central compartment via
first- order equilibration ke0. FXI-LICA has an approximately 20-fold
higher hepatocyte potency than IONIS-FXIRX (IC50 = 2.59 vs 167 ng/mL)
owing to GalNAc-mediated ASGPR uptake into hepatocytes. The
main-analysis FXI-LICA PK model was fitted to healthy-volunteer data
only; the authors' ESRD simulations for FXI-LICA (Figures 3a, 4) borrow
the IONIS-FXIRX ESRD covariate effects on CL, V3, and the effect-site
driving concentration (keoPAT) under the assumption that the
receptor-mediated hepatic uptake pathway is not altered in ESRD. These
borrowed ESRD factors are exposed as fixed parameters in this model so
that the FXI-LICA-in-ESRD scenario can be reproduced. The FXI-activity
arm was fitted simultaneously with pooled ASO-CS1 + ASO-CS4 + LICA-CS1
data (shared kout, baseline, ke0, and Hill). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Melhem_2018_g_csf.html">G
csf (Melhem 2018)</a> </td>
<td style="text-align:left;"> Semi-mechanistic population PK/PD
model for filgrastim and pegfilgrastim in healthy adult volunteers and
adult cancer patients undergoing chemotherapy-induced neutropenia (CIN).
Subcutaneous drug enters a depot compartment, absorbed at first-order
rate KSC into a total-drug compartment (DT). Target-mediated disposition
uses a quasi-equilibrium quadratic between total drug and total G-CSFR
pool (circ), giving free drug (FDC) and bound complex (RDC). Free drug
is cleared linearly (CLD/VD) and bound drug is internalised (KINT). The
granulopoiesis PD cascade is a five-state receptor chain (SM stem ->
MT mitotic -> PM1 -> PM2 -> RB blood receptors) with baseline
set by KP/KTR (bone-marrow pools) and KP/KC (blood pool); ANC = RB / SR.
Drug binding stimulates receptor production (ST1 = 1 + STM1*driver) and
bone-marrow transit (ST2 = 1 + STM2*driver). Chemotherapy is modelled as
a KPD virtual compartment with lag LAG9; its output (KCHM*CHM) scaled by
CHMSL adds to the mitotic-cell elimination rate. Corticosteroid is a
second KPD compartment with lag LAG8; its output drives an Emax
stimulation modulating ST1 and ST2 through CRTM =
KCRT*CRT/(CRT50+KCRT*CRT). Filgrastim and pegfilgrastim differ on FSC,
KSC, VD, CLD and KD (categorical covariate FORM_GCSF_PEG); pegfilgrastim
at 300 ug/kg has an additional lower CLD (categorical DOSE_PEG_300UGKG);
patient vs healthy-volunteer status shifts KINT and STM2 (categorical
DIS_HEALTHY); body weight allometrically scales CLD (exponent 0.641) and
VD (exponent 0.943) with reference 70 kg. Filgrastim (2.6 h) and
pegfilgrastim (10.1 h) apparent half-lives. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Kielbasa_2020_galcanezumab.html">Galcanezumab
(Kielbasa 2020)</a> </td>
<td style="text-align:left;"> One-compartment population PK
model for galcanezumab (humanized IgG anti-CGRP mAb) with first-order SC
absorption, linear elimination, and allometric body weight scaling on
CL/F (Kielbasa 2020) </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Yang_2023_ganciclovir_model_repository.html">Ganciclovir
(Acosta 2007)</a> </td>
<td style="text-align:left;"> One-compartment population PK
model for ganciclovir after IV ganciclovir and an oral liquid
valganciclovir formulation in neonates with symptomatic congenital CMV
disease (Acosta 2007), with first-order absorption, estimated
bioavailability, and a steep un-normalized body-weight power effect on
clearance. Parameters transcribed from the Yang 2023 ganciclovir /
valganciclovir population-PK model repository (Table 3), not from the
primary publication; re-verify against Acosta 2007 when the primary is
obtained. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Caldes_2009_ganciclovir.html">Ganciclovir
(Caldes 2009)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model for ganciclovir after IV ganciclovir and oral valganciclovir
administration in solid organ transplant patients infected with
cytomegalovirus, with first-order absorption, lag time,
logit-transformed bioavailability, and creatinine-clearance scaling on
CL (Caldes 2009) </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Chen_2021_ganciclovir.html">Ganciclovir
(Chen 2021)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model for oral ganciclovir (the active metabolite of valganciclovir) in
adult Chinese renal allograft recipients (Chen 2021), with first-order
absorption after a lag time and a linear creatinine-clearance effect on
apparent oral clearance (CL/F). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Yang_2023_ganciclovir_model_repository.html">Ganciclovir
(Facchin 2019)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model for ganciclovir after oral valganciclovir in children with a renal
transplant (Facchin 2019), parameterized in apparent oral clearances and
volumes, with first-order absorption after a lag time and
serum-creatinine, body-surface-area and sex effects on CL/F and Vc/F.
Parameters transcribed from the Yang 2023 ganciclovir / valganciclovir
population-PK model repository (Table 3), not from the primary
publication; re-verify against Facchin 2019 when the primary is
obtained. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Yang_2023_ganciclovir_model_repository.html">Ganciclovir
(Franck 2021)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model for ganciclovir after IV ganciclovir and oral valganciclovir in
pediatric solid-organ and stem-cell transplant recipients (Franck 2021),
with first-order absorption after a lag time, estimated bioavailability,
allometric body-weight scaling, a creatinine-clearance power effect on
clearance, and a purely additive residual error. Parameters transcribed
from the Yang 2023 ganciclovir / valganciclovir population-PK model
repository (Table 3), not from the primary publication; re-verify
against Franck 2021 when the primary is obtained. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Yang_2023_ganciclovir_model_repository.html">Ganciclovir
(Horvatits 2014)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model for IV ganciclovir in critically ill patients receiving continuous
venovenous hemodiafiltration (Horvatits 2014). No covariates were
retained because of the small cohort (n = 9), so every disposition
parameter is a covariate-free typical value with between-subject
variability. Parameters transcribed from the Yang 2023 ganciclovir /
valganciclovir population-PK model repository (Table 3), not from the
primary publication; re-verify against Horvatits 2014 when the primary
is obtained. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Koloskoff_2025_ganciclovir.html">Ganciclovir
(Koloskoff 2025)</a> </td>
<td style="text-align:left;"> Indirect-response viral turnover
PD model for cytomegalovirus (CMV) viral load decline in pediatric
solid-organ and hematopoietic-stem-cell transplant recipients receiving
(val)ganciclovir (Koloskoff 2025). The model treats the q12h-interval
ganciclovir AUC (AUC_0-12) as a time-varying covariate input AUC_GCV
that stimulates first-order viral degradation through an Emax-EC50
relationship. The upstream popPK that produces AUC_0-12 (Franck 2021
Bayesian estimator) is NOT included here; AUC_GCV must be supplied per
record by the user, either from the Franck 2021 model or any other AUC
source. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Yang_2023_ganciclovir_model_repository.html">Ganciclovir
(Krens 2020)</a> </td>
<td style="text-align:left;"> One-compartment population PK
model for IV ganciclovir in critically ill adults (Krens 2020), with a
CKD-EPI eGFR power effect on clearance and a fixed central volume.
Parameters transcribed from the Yang 2023 ganciclovir / valganciclovir
population-PK model repository (Table 3), not from the primary
publication; re-verify against Krens 2020 when the primary is obtained.
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Yang_2023_ganciclovir_model_repository.html">Ganciclovir
(Lalagkas 2023)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model for ganciclovir after IV ganciclovir and oral valganciclovir in
Caucasian solid-organ transplant recipients with established CMV
infection (Lalagkas 2023), with first-order absorption after a lag time,
estimated bioavailability, allometric body-weight scaling, and a CKD-EPI
eGFR power effect on clearance. Parameters transcribed from the Yang
2023 ganciclovir / valganciclovir population-PK model repository (Table
3), not from the primary publication; re-verify against Lalagkas 2023
when the primary is obtained. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Yang_2023_ganciclovir_model_repository.html">Ganciclovir
(Li 2021)</a> </td>
<td style="text-align:left;"> One-compartment population PK
model for IV ganciclovir in critically ill children (Li 2021), with a
kidney-function power effect and near-linear body-weight scaling on
clearance. Parameters transcribed from the Yang 2023 ganciclovir /
valganciclovir population-PK model repository (Table 3), not from the
primary publication; re-verify against Li 2021 when the primary is
obtained. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Yang_2023_ganciclovir_model_repository.html">Ganciclovir
(Nguyen 2021)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model for IV ganciclovir and oral valganciclovir in a pediatric
population (Nguyen 2021), with allometric body-weight scaling on all
disposition parameters, a power effect of eGFR on clearance, and a
multiplicative critical-illness factor on clearance. Parameters
transcribed from the Yang 2023 ganciclovir / valganciclovir
population-PK model repository (Table 3), not from the primary
publication; re-verify against Nguyen 2021 when the primary is obtained.
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Perrottet_2009_ganciclovir.html">Ganciclovir
(Perrottet 2009)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model for ganciclovir (administered as oral valganciclovir prodrug) in
adult solid-organ transplant recipients (Perrottet 2009) </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Yang_2023_ganciclovir_model_repository.html">Ganciclovir
(Yuen 1995)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model for IV ganciclovir in patients with CMV retinitis, asymptomatic
CMV urine shedding, or a solid-organ transplant with renal dysfunction
(Yuen 1995), with an additive-intercept clearance whose
renal-elimination term scales with body weight and creatinine clearance
and is reduced in transplant recipients and in CMV-retinitis patients.
Parameters transcribed from the Yang 2023 ganciclovir / valganciclovir
population-PK model repository (Table 3), not from the primary
publication; re-verify against Yuen 1995 when the primary is obtained.
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Yang_2023_ganciclovir_model_repository.html">Ganciclovir
(Zhao 2009)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model for ganciclovir after oral valganciclovir in pediatric renal
transplant patients (Zhao 2009), parameterized in apparent oral
clearances and volumes, with first-order absorption after a lag time and
a two-component additive apparent clearance built from a steep
creatinine-clearance power term plus a weight-proportional term.
Parameters transcribed from the Yang 2023 ganciclovir / valganciclovir
population-PK model repository (Table 3), not from the primary
publication; re-verify against Zhao 2009 when the primary is obtained --
the transcribed creatinine-clearance exponent of 2.93 is unusually steep
and is flagged in the validation vignette. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Yang_2023_ganciclovir_model_repository.html">Ganciclovir
(Zhou 1996)</a> </td>
<td style="text-align:left;"> One-compartment population PK
model for IV ganciclovir in newborns with acute symptomatic congenital
CMV disease (Zhou 1996), with additive-linear renal-function scaling on
clearance, additive-linear body-weight scaling on the central volume,
and correlated between-subject variability on CL and Vc. Parameters
transcribed from the Yang 2023 ganciclovir / valganciclovir
population-PK model repository (Table 3), not from the primary
publication; re-verify against Zhou 1996 when the primary is obtained.
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Grimm_2023.html">Gantenerumab
(Grimm 2023)</a> </td>
<td style="text-align:left;"> Gantenerumab PK model in
cynomolgus monkeys (Grimm 2023): two-compartment plasma PK with brain
extracellular distribution across six brain regions (brain_cerebellum,
brain_hippocampus, brain_striatum, brain_cortex, choroid plexus, CSF).
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/VanWart_2004_garenoxacin.html">Garenoxacin
(VanWart 2004)</a> </td>
<td style="text-align:left;"> One-compartment population
pharmacokinetic model with first-order absorption and first-order
elimination for oral garenoxacin (a des-F(6) quinolone) in adults with
community-acquired respiratory tract infections (Van Wart 2004); CL/F
covariates are creatinine clearance, ideal body weight, age, obesity (WT
> 130% IBW), and concomitant pseudoephedrine; V/F covariates are body
weight and male sex. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Smythe_2013_gatifloxacin.html">Gatifloxacin
(Smythe 2013)</a> </td>
<td style="text-align:left;"> One-compartment population PK
model for oral gatifloxacin in adult African pulmonary tuberculosis
patients co-administered rifampin, isoniazid, and pyrazinamide (Smythe
2013). Savic transit-compartment absorption (analytical form, N = 12.6,
MTT = 0.65 h) feeds first-order absorption into a one-compartment
disposition model. Apparent oral clearance is split into a GFR-mediated
component scaled linearly with Cockcroft-Gault creatinine clearance and
a non-GFR (other) component scaled allometrically with fat-free mass
(FFM, Janmahasatian formula); apparent volume is scaled linearly with
FFM. Age, sex, and HIV status modify the absorption rate constant.
Relative bioavailability is fixed at 1 on the first dose and 11.7% lower
at steady state. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Chawla_2023_gefapixant.html">Gefapixant
(Chawla 2023)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model with first-order absorption and an absorption lag time for the
P2X3-receptor antagonist gefapixant in healthy volunteers and adults
with refractory or unexplained chronic cough (Chawla 2023) </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Jiang_2008_gemcitabine.html">Gemcitabine
(Jiang 2008)</a> </td>
<td style="text-align:left;"> Population PK model for
intravenous gemcitabine and its primary inactive metabolite
2',2'-difluorodeoxyuridine (dFdU) in 94 adult patients with cancer
pooled from three clinical studies (Jiang 2008 Br J Clin Pharmacol
65(3):326-333). Both gemcitabine and dFdU are described by a
two-compartment model with first-order elimination, joined by a
first-order formation step. The fraction of gemcitabine converted to
dFdU (F) is not identifiable, so dFdU parameters are apparent (CL/F,
Q/F, Vc/F, Vp/F); the NONMEM ADVAN6 parent-metabolite encoding treats
the total gemcitabine clearance as the apparent formation flux into the
dFdU central compartment. Retained covariates after forward inclusion /
backward elimination (Table 4): estimated creatinine clearance on
apparent dFdU clearance via a linear-additive scaling CL_dFdU/F = 0.04 *
(1 + 0.48 * CRCL/70); body surface area (power exponent 0.93, reference
1.73 m^2), oxaliplatin co-administration order (multiplicative factors
0.65 when gemcitabine is given first and 0.54 when oxaliplatin is given
first), and a non-small-cell lung cancer indicator (multiplicative
factor 1.24) on apparent dFdU central volume. Residual error is
proportional for both analytes. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Landersdorfer_2009_gemifloxacin.html">Gemifloxacin
(Landersdorfer 2009)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model for gemifloxacin in healthy adults with first-order absorption +
lag time, additive renal (filtration + saturable Michaelis-Menten
tubular secretion with competitive probenecid inhibition) and non-renal
clearance, and treatment-arm-static probenecid effects on absorption
rate, absorption lag, and non-renal clearance (Landersdorfer 2009
gemifloxacin / probenecid DDI study). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Abbasi_2023_gentamicin.html">Gentamicin
(Abbasi 2023)</a> </td>
<td style="text-align:left;"> One-compartment intravenous
pooled meta-analytic population PK model for gentamicin in critically
ill adult ICU patients (n=1215 pooled from 21 published studies; Abbasi
2023). Vd (0.33 +/- 0.20 L/kg), CL (4.70 +/- 2.89 L/h) and total body
weight (70.8 +/- 19.9 kg) were pooled as mean +/- SD across the 21
studies and used as normal-distribution inputs to a Monte Carlo
Simulation (10,000 virtual patients, Crystal Ball, Oracle) for
probability-of-target-attainment (PTA) analysis of gentamicin once-daily
doses 5-10 mg/kg (0.5-h IV infusion, 24-h dosing interval) against
AUC24h/MIC and Cmax/MIC efficacy targets. The reported variability
reflects combined between-study and between-patient effects rather than
a NONMEM-fitted OMEGA. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Bijleveld_2016_gentamicin.html">Gentamicin
(Bijleveld 2016)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model of intravenous gentamicin in term neonates with hypoxic-ischaemic
encephalopathy undergoing controlled hypothermia (Bijleveld 2016), with
fixed allometric body-weight scaling (exponents 0.75 on CL and Q, 1 on
Vc and Vp), an estimated gestational-age power effect on CL, and a
categorical post-rewarming (study-day-5, > 96 h PNA) multiplicative
increase in CL. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Bijleveld_2017_gentamicin.html">Gentamicin
(Bijleveld 2017)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model of intravenous gentamicin in (pre)term neonates with suspected or
proven Gram-negative sepsis (Bijleveld 2017), with fixed allometric
body-weight scaling (exponents 0.75 on CL and Q, 1 on Vc and Vp) and an
estimated postmenstrual-age power effect on CL. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Frymoyer_2013_gentamicin.html">Gentamicin
(Frymoyer 2013)</a> </td>
<td style="text-align:left;"> One-compartment IV population PK
model for gentamicin in 29 term neonates with hypoxic ischemic
encephalopathy (HIE) receiving therapeutic hypothermia (Frymoyer 2013),
with fixed allometric birth-weight scaling (exponent 0.75 on CL, 1 on
Vc, reference 3.3 kg) and a power effect of serum creatinine on PNA day
1 on CL (reference 0.9 mg/dL). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Fuchs_2014_gentamicin.html">Gentamicin
(Fuchs 2014)</a> </td>
<td style="text-align:left;"> Two-compartment IV population PK
model for gentamicin in 1449 preterm and term neonates (Fuchs 2014) with
fixed allometric body-weight scaling (0.75 on CL/Q, 1 on Vc/Vp), linear
centred-on-median effects of gestational age on CL and Vc, postnatal age
on CL, and dopamine co-administration on CL. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Hodiamont_2017_gentamicin.html">Gentamicin
(Hodiamont 2017)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model of intravenous gentamicin in critically ill adult ICU patients
(Hodiamont 2017) estimated without retained covariates, with correlated
between-subject variability on CL and central volume V1, combined
additive plus proportional residual error, and substantial
inter-occasion variability on CL and V1 reported in the source
(documented in the vignette assumptions, not encoded structurally).
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Llanos_2017_gentamicin.html">Gentamicin
(Llanos 2017)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model of gentamicin in pediatric oncology patients with febrile
neutropenia (Llanos-Paez 2017) </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Llanos-Paez_2017_gentamicin.html">Gentamicin
(Llanos-Paez 2017)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model for gentamicin in pediatric oncology patients (Llanos-Paez 2017
AAC) extended with a renal-cortex accumulation compartment and an Emax
model of relative renal-function reduction (Llanos-Paez 2017 AAPS J).
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Llanos-Paez_2020_gentamicin.html">Gentamicin
(Llanos-Paez 2020)</a> </td>
<td style="text-align:left;"> Two-compartment IV population PK
model for gentamicin in pediatric oncology and nononcology patients
(Llanos-Paez 2020); body composition is described by normal fat mass
(NFM = FFM + Ffat * (TBW - FFM)) with separate Ffat estimates for CL
(0.48) and V1 (0.10) and Ffat fixed to 0 for Q and V2; CL is driven by
Holford 2017 GFR-maturation (PMA-based Hill function) and a power ratio
of age/sex-matched physiological mean serum creatinine (Ceriotti 2008)
over individual SCR; oncology cohort has 15.4% lower V1 and 32.1% lower
Q than nononcology. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/MedellinGaribay_2015_gentamicin.html">Gentamicin
(MedellinGaribay 2015)</a> </td>
<td style="text-align:left;"> Two-compartment IV population PK
model for gentamicin in infants 1-24 months (Medellin-Garibay 2015) with
linear body-weight scaling on CL and central volume Vc and an additive
(CLCR/75)-driven term on CL; intercompartmental clearance Q and
peripheral volume Vp are not weight-scaled in the published
parameterisation. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Mohamed_2012_gentamicin.html">Gentamicin
(Mohamed 2012)</a> </td>
<td style="text-align:left;"> In vitro (Escherichia coli ATCC
25922). Semi-mechanistic PKPD model of gentamicin bactericidal activity
with adaptive resistance: drug-susceptible growing bacteria
(bact_growing) plus insusceptible resting bacteria (bact_resting), with
a binding model (ar_off / ar_on) by which gentamicin reduces its own
Emax. Fit jointly to static and dynamic in-vitro time-kill curves.
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Sampson_2014_gentamicin.html">Gentamicin
(Sampson 2014)</a> </td>
<td style="text-align:left;"> One-compartment IV population PK
model of gentamicin in term neonates with hypoxic-ischaemic
encephalopathy undergoing whole-body hypothermia, as reported (model
originally developed by Frymoyer 2013; this model file reproduces the
parameter values stated by Sampson 2014 during the model's external
predictive-performance evaluation). Allometric body-weight scaling on CL
(fixed exponent 0.75) and linear body-weight scaling on V (exponent 1)
referenced to a 3.3 kg neonate, with a power effect of serum creatinine
on CL (exponent -0.566); inter-individual variability on CL only and
proportional residual error. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Singu_2024_gentamicin.html">Gentamicin
(Singu 2024)</a> </td>
<td style="text-align:left;"> One-compartment IV population PK
model for gentamicin in 50 PK-evaluable Namibian neonates (82.7%
preterm) with suspected or confirmed sepsis receiving 5 mg/kg every 24
h, developed from a truncated (7.5 h) two-sample informative-block
randomised sampling design (Singu 2024). Clearance carries an allometric
birth-weight effect (exponent 1.30, reference 1.57 kg), a power effect
of log-transformed white blood cell count (exponent -0.560, reference
log-WBC 2.39), and a logistic postnatal-age maturation function FMAT =
PNA^GAMMA / (PNA^GAMMA + PNA50^GAMMA) with GAMMA and PNA50 fixed at
0.551 and 0.0332 years; volume carries an allometric birth-weight effect
(exponent 1.76, reference 1.57 kg). Residual variability is a log-scale
combination (additive + proportional) model with two
concentration-dependent magnitudes switched at a predicted concentration
of 2264.25 ng/mL (log(concentration) = 7.725), an approach the authors
take from Hussein 2005; see modellib('Hussein_2005_levocetirizine').
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Staatz_2005_gentamicin_vancomycin.html">Gentamicin
(Staatz 2005)</a> </td>
<td style="text-align:left;"> Two-compartment IV population PK
model for gentamicin in adult cardiothoracic-surgery patients with
unstable renal function (Staatz 2005). Clearance scales linearly with
raw Cockcroft-Gault creatinine clearance centred at the population
baseline median (63 mL/min); central and peripheral volumes scale
linearly with body weight; intercompartmental clearance is a population
constant. Operator-resolved sidecar (request-001) replaced the paper's
Wahlby 2004 baseline-CrCl + change-from-baseline (BCOV+DCOV)
decomposition with the simpler CrCl-only covariate form to avoid adding
a new canonical baseline-CrCl column; for stable-CrCl subjects the
published final-model parameters reproduce the paper's CL exactly
because DCOV is zero (see vignette Errata). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Thomson_2003_gentamicin.html">Gentamicin
(Thomson 2003)</a> </td>
<td style="text-align:left;"> One-compartment population PK
model of intramuscular gentamicin in African infants with suspected
severe sepsis (Thomson 2003). The 8 mg/kg i.m. dose is modelled as an IV
bolus into the central compartment because first-order absorption could
not be characterised from the sparse 1 h / next-morning sampling (the
paper documents that ka estimates were poorly identified and absorption
appeared complete by 1 h). Apparent clearance scales linearly with body
weight and as a power function of (postnatal age + 1 day) normalised to
the cohort median + 1 day; apparent volume of distribution scales
linearly with body weight relative to the cohort median 3 kg. Reported
CL and V are apparent values (CL/F, V/F) because all doses were
administered by intramuscular injection and bioavailability could not be
estimated. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Veinstein_2013_gentamicin.html">Gentamicin
(Veinstein 2013)</a> </td>
<td style="text-align:left;"> One-compartment population PK
model for intravenous gentamicin in critically ill adult ICU patients
with acute kidney injury undergoing 4-hour intermittent hemodialysis
(n=10, all male; 6 mg/kg infused over 30 min, with hemodialysis starting
30 min after the end of the infusion; Veinstein 2013). Disposition is
parameterised in terms of non-hemodialysis (interdialytic body)
clearance, an additive hemodialysis-arm clearance, and volume of
distribution. The dialysis arm is gated on/off by the time-varying
RRT_HEMODIAL_ACTIVE covariate. Body weight enters the model as a linear
(exponent = 1) structural scaler on all three parameters because the
published Table 4 estimates are reported per kg; weight was tested as an
explicit covariate on V and not retained. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Wahlby_2004_time_varying_covariates.html">Gentamicin
(Wahlby 2004)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model for intravenous gentamicin in 210 cancer patients, demonstrating
Wahlby 2004's extended covariate-model formulation in which the within-
and between-subject components of a time-varying covariate are entered
as separate model terms. Final-model clearance depends on baseline
creatinine clearance (CRCL_BASE) and the time-varying
delta-from-baseline (CRCL - CRCL_BASE); central volume depends on
baseline body surface area (BSA_BASE) and the time-varying albumin (ALB)
ratio (ALB/34)^-0.41. Underlying structural PK (compartment count,
IIV/residual-error structure) follows Rosario et al. 1998 (Br J Clin
Pharmacol 46:229-236). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Kelman_1984_gentamicin.html">Gentamicin
glasgow (Kelman 1984)</a> </td>
<td style="text-align:left;"> One-compartment population PK
model for gentamicin in neonates and very young infants (Kelman 1984,
Glasgow I cohort; n=43, postnatal age 2-120 days, body weight 0.8-3.7
kg). Clearance is a linear-additive function of body weight, postnatal
age, and serum creatinine (paper Equation 4, Model 1: CL = theta1*WT +
theta2*AGE + theta3*CREAT); volume of distribution is proportional to
body weight (Equation 5: V = theta4*WT). Encoded from Kelman 1984 Table
2 Model 1 (FULL model, paper's best by NONMEM objective function).
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Kelman_1984_gentamicin.html">Gentamicin
manchester1 (Kelman 1984)</a> </td>
<td style="text-align:left;"> One-compartment population PK
model for gentamicin in neonates and young infants (Kelman 1984,
Manchester I cohort; n=32, postnatal age 1-153 days, body weight 1.6-9.1
kg). Clearance is a linear-additive function of body weight, postnatal
age, and serum creatinine (paper Equation 4, Model 1: CL = theta1*WT +
theta2*AGE + theta3*CREAT); volume of distribution is proportional to
body weight (Equation 5: V = theta4*WT). Encoded from Kelman 1984 Table
3 Model 1 (FULL model, paper's best by NONMEM objective function for
this cohort). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Kelman_1984_gentamicin.html">Gentamicin
manchester2 (Kelman 1984)</a> </td>
<td style="text-align:left;"> One-compartment population PK
model for gentamicin in older children and adolescents (Kelman 1984,
Manchester II cohort; n=68, age 6 months-15 years, body weight 5.7-62
kg). Clearance is a linear-additive function of body weight, age (in
years), and serum creatinine (paper Equation 4, Model 1: CL = theta1*WT
+ theta2*AGE + theta3*CREAT); volume of distribution is proportional to
body weight (Equation 5: V = theta4*WT). Encoded from Kelman 1984 Table
4 Model 1 (FULL model, paper's best by NONMEM objective function for
this cohort). For Manchester II the paper's theta2 coefficient is in L/h
per year (sign negative), implying age units are years rather than the
days used in the Glasgow I and Manchester I cohorts; encoded here with
the canonical AGE-in-years covariate. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Cao_2013_gevokizumab.html">Gevokizumab
(Cao 2013)</a> </td>
<td style="text-align:left;"> Second-generation minimal
physiologically-based PK (mPBPK) model for gevokizumab in adults (Cao
2013 Model A; clearance from plasma) </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Karakitsios_2024_gevokizumab.html">Gevokizumab
(Karakitsios 2024)</a> </td>
<td style="text-align:left;"> mPBPK. Second-generation minimal
physiologically-based population PK model for gevokizumab
(anti-interleukin-1beta humanized IgG2) in adults with type 2 diabetes,
with between-subject variability estimated from AGGREGATE (mean and SD
versus time) plasma concentration data rather than individual records.
Karakitsios and Dokoumetzidis re-estimated the three drug-specific
parameters of the Cao 2013 second-generation mPBPK structure (the tight-
and leaky-tissue vascular reflection coefficients and plasma clearance)
plus two IIV terms, using a Bayesian
reconstruct-the-likelihood-from-aggregate-data method implemented in
RStan: at each MCMC iteration a Latin-hypercube virtual population is
solved, its mean and SD versus time are computed, and those summaries
are fitted to the digitised published mean and SD profiles. This file
holds the SINGLE dosage-group fit (7 mg IV, n = 10; Table 3). A single
lognormal body-size random effect (etalvc) is shared by all four
physiologic volumes, per the authors' assumption that a larger patient
has proportionally larger plasma, tight-tissue ISF, leaky-tissue ISF and
lymph volumes. The five-dosage-group meta-analysis from the same paper
is a separate model; see modellib('Karakitsios_2024_gevokizumab_mbma').
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Karakitsios_2024_gevokizumab.html">Gevokizumab
mbma (Karakitsios 2024)</a> </td>
<td style="text-align:left;"> mPBPK / MBMA. Five-dosage-group
meta-analysis of gevokizumab (anti-interleukin-1beta humanized IgG2) in
adults with type 2 diabetes, fitted to AGGREGATE (mean and SD versus
time) plasma concentration data from five dose arms simultaneously. The
structural model is the Cao 2013 second-generation minimal PBPK model;
Karakitsios and Dokoumetzidis estimated its three drug-specific
parameters (tight- and leaky-tissue vascular reflection coefficients and
plasma clearance) hierarchically, with an exponential INTER-GROUP
variability (IGV) term on each, following a log-Student's t distribution
with 5 degrees of freedom to down-weight outlying dose arms. The random
effects in this file are therefore DOSAGE-GROUP-level (eta_study_*), not
between-subject: the model simulates group-mean concentration-time
profiles and is NOT suitable for individual-subject simulation.
Between-subject variability was estimated separately for each of the
five arms (a semi-hierarchical design with no distribution assumed
across arms), so no single population IIV exists; the five per-arm pairs
are tabulated in population$notes. For an individual-level
version of the same structure, see the single dosage-group fit
modellib(‘Karakitsios_2024_gevokizumab’).
|
|
Givosiran
(Ayyar 2024)
|
Mechanistic translational PK model for the GalNAc-siRNA givosiran (Ayyar
& Song 2024) parameterized for human (70 kg adult). 22-ODE system
covering SC depot, central plasma (parent + AS(N-1)3’ active
metabolite), competitive ASGPR receptor binding (free target,
parent-target complex, metabolite-target complex), receptor-mediated
hepatocyte internalization, endolysosomal sequestration / degradation /
endosomal escape, free cytoplasmic siRNA, RISC-loaded siRNA (combined
parent + metabolite), kidney vascular and tissue distribution with a
deep bound pool and GFR elimination - for parent and metabolite.
Pharmacodynamic ALAS1 mRNA silencing (rat-only in the paper) is not
included in the human parameterization.
|
|
Glasdegib
QTcF (Fostvedt 2021)
|
Population PD model for glasdegib concentration-driven prolongation of
the QT interval corrected for heart rate using Fridericia’s formula
(QTcF) in 70 adult patients with advanced cancer pooled from two phase 1
dose-escalation trials (B1371001 in hematologic malignancies; B1371002
in solid tumors). The exposure-response form is a linear mixed-effects
model: QTcF = theta1 + theta2 * (CP_GLASDEGIB_NGML / 1000) + eta1 + W *
eps, with an additive random effect on the intercept (eta1 ~ N(0,
omega2_1)) and a ‘thetarized’ additive residual error (W is a fitted
scalar; eps ~ N(0, 1)). The covariate analysis (age, sex, study)
retained no covariates; a random effect on the slope was considered and
dropped because shrinkage exceeded 20%. PD-only model: plasma glasdegib
concentration is supplied as a time-varying covariate CP_GLASDEGIB_NGML
(ng/mL). The slope is reported in the source publication on the
microgram-per-mL scale (4.3 msec per microgram per mL) which is
equivalent to 0.0043 msec per ng/mL; this file keeps the slope in the
paper’s microgram-per-mL form and applies the unit conversion
CP_GLASDEGIB_NGML / 1000 inside model(). The source
publication does not fit a population PK model; users wishing to drive
the PD model from a simulated PK source must supply their own
concentration trajectory (no glasdegib popPK model exists in the
nlmixr2lib registry).
|
|
Glasdegib
QTcS (Fostvedt 2021)
|
Population PD model for glasdegib concentration-driven prolongation of
the QT interval corrected for heart rate using a population- specific
Fridericia-style correction factor (QTcS; beta estimated at 0.312 in
this cohort versus the fixed beta = 1/3 of QTcF) in 70 adult patients
with advanced cancer pooled from two phase 1 dose- escalation trials
(B1371001 in hematologic malignancies; B1371002 in solid tumors). The
exposure-response form is the same linear mixed-effects model as the
companion QTcF extraction: QTcS = theta1 + theta2 * (CP_GLASDEGIB_NGML /
1000) + eta1 + W * eps, with additive random intercept (eta1 ~ N(0,
omega2_1)) and a ‘thetarized’ additive residual error (W is a fitted
scalar; eps ~ N(0, 1)). Covariate analysis (age, sex, study) retained no
covariates; a random effect on the slope was considered and dropped
because shrinkage exceeded 20%. PD-only model: plasma glasdegib
concentration is supplied as a time-varying covariate CP_GLASDEGIB_NGML
(ng/mL). The slope is reported in the source publication on the
microgram-per-mL scale (4.31 msec per microgram per mL); this file keeps
that scaling and applies the unit conversion
CP_GLASDEGIB_NGML / 1000 inside model(). The source
publication does not fit a population PK model; users wishing to drive
the PD model from a simulated PK source must supply their own
concentration trajectory (no glasdegib popPK model exists in the
nlmixr2lib registry).
|
|
Glibenclamide
(Rambiritch 2016)
|
Two-compartment population PK model with first-order oral absorption for
glibenclamide in poorly controlled South African adults with type 2
diabetes (Rambiritch 2016). All disposition parameters are apparent
(CL/F, Vc/F, Vp/F, Q/F); F is not estimated. Concentration data were
log-transformed prior to NONMEM fitting (LTBS), giving an effectively
proportional residual error in linear space. No covariate effects were
retained in the final model.
|
|
Glp1ra
bodyweight (Bosch 2024)
|
QSP. GLP-1R agonist body composition model (Bosch 2024) extending the
Hall 2009 three-compartment energy-balance model with (1) an
inverse-Bateman lifestyle-change effect on energy intake, (2) a
body-weight-dependent activity effect on physical activity energy
expenditure for studies that included weight management and intensive
behavioural treatment, and (3) a GLP-1R agonist drug effect driven by
the in-vitro EC50- normalised free drug concentration, with a
time-dependent tolerance term that shifts the in-vivo EC50 upward.
Liraglutide and semaglutide PK are encoded inline as fixed
one-compartment first-order absorption models (parameters from the Bosch
2024 supplement S10 reproducing FDA clinical pharmacology review
(liraglutide, 17 Dec 2018) and Carlsson Petri et al. 2018 (semaglutide);
both PK paths share the body composition machinery, and the total
normalised free concentration drives the GLP-1R effect so a user
simulating a single drug doses to that drug’s depot only. Body weight
(kg) and percent change from baseline are the primary observation
outputs. Initial conditions are derived from baseline body weight, BMI,
age, sex and height via the Jackson body-fat regression and the Mifflin
resting-metabolic-rate equation; baseline energy intake is set to
maintain steady state at PAL = 1.6 (low-active-to-active). 11 active
ODEs (3 macronutrient stores, 2 extracellular-water states, lipolysis
diet target, adaptive thermogenesis, plus 2 first-order PK chains for
each drug).
|
|
Glp1ra
hba1c (Bosch 2025)
|
QSP. Integrated glucose-red blood cell-HbA1c (IGRH) sub-model from the
Bosch 2025 4GI-HbA1c systems framework, used to predict long-term HbA1c
response from a time-varying plasma glucose driver in adults with type 2
diabetes mellitus receiving GLP-1R / GLP-1R + glucagon receptor agonists
(cotadutide, liraglutide). The model is a 24-state transit chain (12
unglycated red blood cell age cohorts + 12 glycated cohorts; NC = 12
transit compartments per Bosch 2025 supplement model code S2) with a
glucose-concentration-dependent shortening of the RBC life span; the
HbA1c output is the percentage glycated fraction of the total RBC pool.
All structural parameters are fixed from the Lledo-Garcia 2013 /
Kjellsson 2015 IGRH publications and held constant during the Bosch 2025
calibration; only the residual error and the IIV on the RBC life span
were estimated on the cotadutide Ph2a HbA1c dataset (Bosch 2025 Table 2,
third-block ‘IGRH model’). Plasma glucose drive is supplied as the
time-varying regressor GLU in mmol/L (linearly interpolated by rxode2
between dataset rows) and the per-subject baseline glucose anchor FPG is
in mmol/L; both are converted to mg/dL inside model() to match the
published IGRH parameterisation (KG in dL/mg/day, reference glucose 149
mg/dL = 8.27 mmol/L).
|
|
Glucarpidase
(Kimura 2023)
|
Modified Michaelis-Menten PK/PD simulation model for glucarpidase (CPG2)
rescue after high-dose methotrexate (Kimura 2023). MTX disposition is
2-compartment IV with renal-only first-order elimination (Kr fixed at
~10% of literature total MTX CL from Fukahara 2008); the remaining
elimination is captured by a saturable hydrolysis term coupled to a
1-compartment IV CPG2 disposition. All structural parameters are
literature-sourced point values (no estimation in the source paper).
|
|
Glutamine
(Sadaf 2024)
|
One-compartment population PK model with first-order absorption for oral
L-glutamine (Endari) in children and adults with sickle cell disease and
in healthy adult volunteers (Sadaf 2024). The model is fitted to
baseline-subtracted plasma L-glutamine, i.e. the exogenous increment
above each participant’s own endogenous pre-dose concentration, so the
predicted Cc is zero before the first dose. Apparent oral clearance and
apparent central volume are allometrically scaled to body weight with
the theoretical exponents 0.75 and 1 (70 kg reference). Apparent
clearance falls as the pre-dose endogenous L-glutamine baseline rises
(power -0.96, reference 683 umol/L), interpreted as competition between
endogenous and exogenous glutamine for elimination. Apparent volume
rises with the administered dose per kg (power 0.27, reference 0.1
g/kg), which is how the paper captures the capacity-limited,
less-than-dose-proportional rise in exposure seen at 0.3 and 0.6 g/kg
after a Michaelis-Menten base model proved unstable. Inter-occasion
variability is carried on clearance across the four study visits;
inter-individual variability on clearance and on the absorption rate
constant, and the additive residual error, were all held at zero in the
published final model.
|
|
GNbAC1
(Cao 2013)
|
Second-generation minimal physiologically-based PK (mPBPK) model for
GNbAC1 in adults (Cao 2013 Model A; clearance from plasma)
|
|
Granisetron
(Li 2023)
|
One-compartment population PK model for the granisetron transdermal
delivery system (GTDS, Sancuso 34.3 mg/52 cm2 patch) in healthy
Caucasian volunteers, with first-order absorption from the patch (no lag
time) and first-order elimination; no covariates retained (Li 2023)
|
|
Guselkumab
(Chen 2022)
|
One-compartment population PK model with first-order SC absorption for
guselkumab (anti-IL-23 human IgG1 lambda mAb) in patients with active
psoriatic arthritis (DISCOVER-1 and DISCOVER-2 phase 3 trials; Chen
2022)
|
|
Guselkumab
(Yao 2018)
|
One-compartment population PK model with first-order SC absorption and
first-order elimination for guselkumab (anti-IL-23 p19 human IgG1-lambda
mAb) in adults with moderate-to-severe plaque psoriasis (pooled phase 2
X-PLORE and phase 3 VOYAGE 1 / VOYAGE 2 trials; Yao 2018)
|
|
Haloperidol
(Franken 2017)
|
One-compartment population PK model for haloperidol in 28 terminally ill
adult palliative-care patients (Franken 2017). Two parallel first-order
absorption routes (oral and subcutaneous) with route-specific absorption
rate constants fixed from literature (Ka oral = 0.236 1/h, Ka SC = 20
1/h derived from intramuscular Tmax = 20 min). Oral bioavailability F =
0.861 is estimated; SC F is assumed to be 1. IIV is included on F, CL,
and Vd; the IIV on F and CL was 99% correlated and is encoded with
correlation fixed to unity (BLOCK pattern). Residual variability is
additive on log-transformed concentrations (LTBS). Covariate analysis
(body weight, age, sex, primary diagnosis, plasma creatinine, urea,
bilirubin, GGT, ALP, ALT, AST, CRP, albumin, concomitant CYP2D6 / CYP3A
inducers and inhibitors, time-to-death) did not retain any covariate in
the final model.
|
|
Haloperidol
panss subscales (PillaReddy 2013)
|
Population pharmacokinetic / pharmacodynamic (PK/PD) model for
haloperidol against the three PANSS subscales (positive, negative,
general) in adults with schizophrenia from Pilla Reddy 2013 Part II
(pooled dataset of 1338 placebo-treated patients with subscale data
available for n=741 of them; 12 industry-sponsored Phase II/III trials
between 1989 and 2009 plus one open-label study). The PK sub-model uses
the haloperidol structural model inherited from Part I (PMID 23473810):
a simplified one-compartment representation parameterised with the
typical apparent oral clearance CL/F = 88 L/h, apparent central volume
Vc/F = 669 L, and first-order absorption rate ka = 0.23 1/h reported in
Part I Table 2 (Pilla Reddy 2012a originally described the haloperidol
PK as two-compartment with Q/F = 233 L/h and Vp/F = 2500 L; the
one-compartment simplification preserves the steady-state average
concentration Css = Dose / (CL * tau) used as the PD driver and is
documented as a deliberate Part II simplification in the vignette
Assumptions and deviations). The PD sub-model has three outputs that
share the Weibull placebo time-course form Pplacebo = Pmax * (1 -
exp(-(t/TD)^POW)) but each subscale carries its own placebo baseline,
Pmax, TD, and POW (Pilla Reddy 2013 Part II Table 1) and haloperidol’s
own Emax / EC50 / KT triplet per subscale (Part II Table 2). The
combined PANSS subscale prediction is BASL * (1 - Pplacebo) * (1 -
Drug), where Drug = Emax * Cc / (EC50 + Cc) * (1 - exp(-KT * t)) with
the KT delay capturing the onset time to the maximum drug effect.
Concentration drives the PD with a steady-state assumption: the paper
uses Css from the PK model and feeds it into the Emax equation; in the
rxode2 implementation Cc is the time-varying plasma concentration
derived from the one-compartment ODE, which is approximately constant at
steady state for the once- and twice-daily regimens studied here. An
exponential time-to-event dropout sub-model with subscale- and
drug-specific baseline hazards (Part II Table 4) is reported in the
paper but is not encoded in this nlmixr2lib model body; the dropout
parameters are documented in population$dropout_model and discussed in the vignette.
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Feng_2012_higenamine.html">Higenamine
(Feng 2012)</a> </td>
<td style="text-align:left;"> Population PK/PD model for
intravenous higenamine in 10 healthy Chinese subjects (Feng 2012).
Two-compartment disposition with Michaelis-Menten (saturable)
elimination from the central compartment, plus a direct-effect Emax
sub-model for the cardiovascular-stress heart-rate response (E = E0 +
Emax * Cc / (EC50 + Cc)). No demographic covariates were retained in the
final model (sex, height, weight, BMI, and age were graphically screened
but did not influence PK or PD). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Ngo_2020_HL2351.html">HL2351
(Ngo 2020)</a> </td>
<td style="text-align:left;"> Population PK model for HL2351
(hIL-1Ra-hyFc, ~97 kDa) in healthy adult Korean men: a
quasi-steady-state target-mediated drug disposition (QSS-TMDD) model
coupled with FcRn-mediated recycling. The injection-site depot feeds a
separate distribution space where free drug equilibrates with FcRn (QSS
dissociation constant AKSS1, total FcRn AFcRn_t); free drug moves to the
central compartment either directly (Ka2) or by FcRn-mediated recycling
of the FcRn-drug complex (Krec). In the central compartment free drug
equilibrates with IL1R (QSS dissociation constant KSS2, total IL1R
CIL1R_t), is taken up back to the distribution space (Kup), exchanged
with one peripheral compartment (Q/F), and eliminated linearly (CL/F).
The IL1R-drug complex degrades at Kdeg2. All drug amounts and
concentrations are in nmol / nmol/L; convert mg dosing using molecular
weight 97 kDa (1 mg HL2351 = approximately 10306 nmol). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Royer_2010_HuHMFG1.html">HuHMFG1
(Royer 2010)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model with linear elimination for HuHMFG1 (AS1402), a humanised
anti-MUC1 monoclonal antibody, in patients with metastatic breast
cancer; serum AST enters the typical clearance equation additively
(Royer 2010) </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Carmichael_2003_hydroxychloroquine.html">Hydroxychloroquine
(Carmichael 2003)</a> </td>
<td style="text-align:left;"> One-compartment
first-order-absorption population PK model with an absorption lag time
for oral hydroxychloroquine (HCQ) whole-blood concentrations in 123
adult rheumatoid arthritis patients (74 on HCQ alone plus 49 on HCQ +
methotrexate) pooled from four Australian studies, with bioavailability
fixed at the value 0.746 estimated from a nine-patient IV/oral crossover
sub-study and a linear additive shift in central volume of distribution
for concomitant methotrexate coadministration (V_MTX = 1070 L added to
the base V of 605 L when MTX is present) (Carmichael 2003). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Sharma_2016_hydroxyprogesteroneCaproate.html">HydroxyprogesteroneCaproate
(Sharma 2016)</a> </td>
<td style="text-align:left;"> Population PK model for
17alpha-hydroxyprogesterone caproate (17-OHPC) in pregnant women with
singleton gestation receiving 250 mg weekly IM injections for prevention
of recurrent preterm birth (Sharma 2016). Structural model is a maternal
central compartment with first-order IM absorption (ka fixed to 3 /day)
and first-order elimination, linked by reversible first-order rate
constants kMF / kFM to a fetal compartment whose amount is tracked as a
dynamic state. Allometric (power) scaling on apparent CL/F (exponent
0.80) and apparent Vmaternal/F (exponent 0.84) around the cohort median
weight of 68 kg. Inter-individual variability is encoded as a shared
random effect on log(CL) with an estimated scale factor (Theta6 = 1.90)
applied to the same eta on log(Vmaternal), preserving the > 0.9 ETA
correlation reported in the source. Inter-occasion variability (PK1 =
20-24 weeks gestation, PK2 = 31-34 weeks gestation) on CL and Vmaternal
is encoded as paired per-occasion etas keyed to OCC. Residual error is
combined proportional + additive on linear-scale ng/mL concentrations.
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Chen_2024_guhongInjection.html">HydroxysafflorYellowA
rat (Chen 2024)</a> </td>
<td style="text-align:left;"> Preclinical (rat).
Two-compartment intravenous pharmacokinetic model for hydroxysafflor
yellow A (HSYA), one of eight constituents of guhong injection (GHI)
quantified in plasma, in male Sprague-Dawley rats subjected to 30 min
left-anterior-descending ligation followed by 1 h reperfusion
(myocardial ischemia/reperfusion, MI/R) (Chen 2024). GHI was given as a
single tail-vein injection of 2.5, 5 or 10 mL/kg; the hydroxysafflor
yellow A dose is the GHI volume dose times its content in GHI (1 mg/mL),
i.e. 2.5 mg/kg, 5 mg/kg, 10 mg/kg. Disposition was fitted separately in
each dose group with Drug and Statistics (DAS) v3.2.6, so V1, V2, CL1
and Q are selected from the covariate DOSE_GHI_MLKG rather than through
a dose-covariate function the authors did not fit. Direct-effect
sigmoid-Emax models link the hydroxysafflor yellow A plasma
concentration to the GHI-minus-model-group difference in creatine
kinase-MB (CK-MB), ischemia-modified albumin (IMA), cardiac troponin I
(cTn I) and alpha-hydroxybutyrate dehydrogenase (alpha-HBDH) (E = Emax *
C^gamma / (ED50^gamma + C^gamma); Tables 12, 13, 14, 15). Chen 2024
fitted a PK/PD model only for the analyte/biomarker/dose combinations
whose PLSR coefficient was negative, so the effect of an unfitted
combination is returned as zero rather than extrapolated. No
between-subject variability or residual error was reported; every
parameter is fixed at the published mean and the residual SDs are fixed
at zero. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Dong_2016_hydroxyurea.html">Hydroxyurea
(Dong 2016)</a> </td>
<td style="text-align:left;"> One-compartment population PK
model for oral hydroxyurea in pediatric patients with sickle cell
anaemia (Dong 2016, HUSTLE trial NCT00305175; n = 96 children aged
1.2-16.6 years on a 20 mg/kg starting dose, all African-American).
Saturable Michaelis-Menten elimination from the central compartment
(Vmax 490 mg/h per 70 kg, Km fixed at 25 mg/L based on a prior report)
with allometric scaling of Vmax (exponent 0.75 fixed) and apparent
central volume V/F (exponent 1.0 fixed) on total body weight (reference
70 kg). Cystatin C is a power-model covariate on Vmax (exponent -0.509,
reference 0.74 mg/L), and was the only covariate retained over serum
creatinine, eGFR, and direct 99mTc-DTPA-measured GFR. Oral absorption is
described by a Savic 2007 transit-compartment chain (NN = 12.4 transit
compartments fitted, MTT = 0.158 h) feeding a depot with first-order
absorption Ka = 8.19 /h. Residual error is combined additive (0.117
mg/L) and proportional (39.7% CV). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Paule_2011_hydroxyurea.html">Hydroxyurea
(Paule 2011)</a> </td>
<td style="text-align:left;"> Two-compartment population PK +
indirect-response PD models for hydroxyurea (HU) in adults with sickle
cell anemia (Paule 2011): bicompartmental oral PK with first-order
absorption and elimination, allometric scaling on CL/F and Vc/F;
turnover models for HbF percentage and mean corpuscular volume (MCV)
where HU inhibits the elimination rate of each PD response. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Chen_2024_guhongInjection.html">Hyperoside
rat (Chen 2024)</a> </td>
<td style="text-align:left;"> Preclinical (rat).
Two-compartment intravenous pharmacokinetic model for hyperoside (HYP),
one of eight constituents of guhong injection (GHI) quantified in
plasma, in male Sprague-Dawley rats subjected to 30 min
left-anterior-descending ligation followed by 1 h reperfusion
(myocardial ischemia/reperfusion, MI/R) (Chen 2024). GHI was given as a
single tail-vein injection of 2.5, 5 or 10 mL/kg; the hyperoside dose is
the GHI volume dose times its content in GHI (3.4 ug/mL), i.e. 8.5
ug/kg, 17 ug/kg, 34 ug/kg. Disposition was fitted separately in each
dose group with Drug and Statistics (DAS) v3.2.6, so V1, V2, CL1 and Q
are selected from the covariate DOSE_GHI_MLKG rather than through a
dose-covariate function the authors did not fit. Chen 2024 fitted no
concentration-effect model for hyperoside: its weighted PLSR regression
coefficients against all four myocardial biomarkers were positive (Table
10), so the paper's PK/PD tables (Tables 12-15) contain no entry for it
and this file carries the PK layer only. No between-subject variability
or residual error was reported; every parameter is fixed at the
published mean and the residual SDs are fixed at zero. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Pillai_2004_ibandronate.html">Ibandronate
(Pillai 2004)</a> </td>
<td style="text-align:left;"> Kinetic-pharmacodynamic (K-PD)
model for ibandronate (a nitrogen-containing bisphosphonate) suppression
of urinary C-telopeptide of type-I collagen (uCTX) in postmenopausal
women with osteoporosis. A virtual K-PD effect compartment receives the
administered dose and decays at rate KDE, producing a dose-driving rate
(DODR = KDE * central * F) that inhibits the uCTX synthesis rate KS via
a sigmoid Emax (inhibition-fraction form). uCTX follows an
indirect-response synthesis-degradation turnover (KS, KD). A
multiplicative placebo disease-progression drift (1 + SLOPE * t) and a
calcium + vitamin D supplementation suppression term (1 - VIT * [1 -
exp(-KVIT * t)]) modify the observed uCTX. The supplementation indicator
CONMED_CAVITD also switches KDE between the no-supplement (0.112 /day)
and with-supplement (0.014 /day) typical values. The model handles
intravenous and oral routes via the bioavailability factor F (default
F=1 for IV; oral users override lfdepot to log(0.008) for 2.5 mg oral or
log(0.007) for 20 mg oral, both fixed from a separate
absolute-bioavailability study). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Ibrahim_2023_ibrutinib.html">Ibrutinib
competing risk (Ibrahim 2023)</a> </td>
<td style="text-align:left;"> Competing-risk multistate model
for study dropout and death in patients with chronic lymphocytic
leukemia treated with ibrutinib (phase Ib/II PCYC-1102). Three ODE
states track the marginal probability of being alive and on study
(s_alive, the only transient state), of having dropped out (s_dropout),
and of having died (s_death); both terminal states are absorbing. The
transition rate to dropout falls as the model-predicted leukocyte count
rises (hazard ratio 4.92 for every 10-unit decrease in leukocyte count
-- patients whose predicted count fell below normal, potentially
reflecting neutropenia, were the most likely to leave the study), while
the transition rate to death rises with the model-predicted lymph-node
burden (hazard ratio 1.35 for every 10-unit increase in SPD) and with
the deletion(17p) chromosomal abnormality (hazard ratio 4.16). The two
time-varying predictors are supplied as covariates and are intended to
be the model-predicted leukocyte count and SPD from the sister efficacy
model, held constant between visits as in the source analysis. There are
no drug-dosing events in this model and ibrutinib exposure does not
enter it directly. Sister model files from the same paper:
modellib('Ibrahim_2023_ibrutinib_leukocyte_spd'),
modellib('Ibrahim_2023_ibrutinib_sbp'),
modellib('Ibrahim_2023_ibrutinib_dbp'). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Ibrahim_2023_ibrutinib.html">Ibrutinib
dbp (Ibrahim 2023)</a> </td>
<td style="text-align:left;"> Ibrutinib-induced diastolic blood
pressure (dBP) turnover model in patients with chronic lymphocytic
leukemia, from the phase Ib/II PCYC-1102 study. A zero-order production
/ first-order loss turnover model preceded by a single transit
compartment reproduces the slow onset of ibrutinib-associated
hypertension; ibrutinib stimulates the zero-order dBP production rate
through an Emax function of the daily AUC(0-24). The transit rate
constant and the turnover rate constant are equal, both set to (n + 1) /
MTT with n = 1 transit compartment. Baseline age lowers the dBP
baseline. Structurally identical to the sister systolic model but fitted
independently, with a smaller Emax (0.0694 vs 0.113), a lower AUC50
(63.1 vs 91.7 h*ng/mL), a roughly 2-fold slower onset (MTT 161 vs 79.9
days), no random effect on MTT, and the age effect placed on the
baseline rather than on MTT. Ibrutinib enters only through the
time-varying covariate AUC_IBRU; there are no drug-dosing events in this
model. Sister model files from the same paper:
modellib('Ibrahim_2023_ibrutinib_sbp'),
modellib('Ibrahim_2023_ibrutinib_leukocyte_spd'),
modellib('Ibrahim_2023_ibrutinib_competing_risk'). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Ibrahim_2023_ibrutinib.html">Ibrutinib
leukocyte spd (Ibrahim 2023)</a> </td>
<td style="text-align:left;"> QSP / semi-mechanistic PK-PD.
Integrated ibrutinib exposure-response model for leukocyte count and
lymph-node burden (sum of the products of perpendicular diameters, SPD)
in chronic lymphocytic leukemia (CLL), from the phase Ib/II PCYC-1102
study. Five ODEs: one relative-quantity turnover compartment for
phosphorylated Bruton tyrosine kinase (pBtk) whose zero-order production
is inhibited by an Imax function of the daily ibrutinib AUC(0-24), plus
four CLL cell subpopulations that reproduce the Calissano CLL life cycle
-- two proliferating stroma-attached colonies in lymphoid tissue with
different detachment sensitivities (cll_subpop1, cll_subpop2), a
released/activated tissue pool that exits to blood (cll_subpop3), and a
resting peripheral-blood pool (cll_bld). Free (unphosphorylated) Btk
drives four simultaneous drug effects: inhibition of CLL proliferation,
ibrutinib-induced apoptosis of cll_subpop3, enhanced detachment of
cll_subpop1/cll_subpop2 from the stroma, and blockade of homing from
blood back to tissue -- the last of which produces the characteristic
treatment-related lymphocytosis. Resistance is an exponential decay of
the proliferation and apoptosis effects with time (t1/2 = 761 days). Two
observed outputs: leukocyte count (10^9 cells/L) and total SPD (cm^2).
Ibrutinib enters only through the time-varying covariate AUC_IBRU; there
are no drug-dosing events in this model. Sister model files from the
same paper: modellib('Ibrahim_2023_ibrutinib_sbp'),
modellib('Ibrahim_2023_ibrutinib_dbp'),
modellib('Ibrahim_2023_ibrutinib_competing_risk'). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Ibrahim_2023_ibrutinib.html">Ibrutinib
sbp (Ibrahim 2023)</a> </td>
<td style="text-align:left;"> Ibrutinib-induced systolic blood
pressure (sBP) turnover model in patients with chronic lymphocytic
leukemia, from the phase Ib/II PCYC-1102 study. A zero-order production
/ first-order loss turnover model preceded by a single transit
compartment reproduces the slow onset of ibrutinib-associated
hypertension; ibrutinib stimulates the zero-order sBP production rate
through an Emax function of the daily AUC(0-24). The transit rate
constant and the turnover rate constant are equal, both set to (n + 1) /
MTT with n = 1 transit compartment. Baseline age lowers the mean transit
time (older patients reach the new steady state faster). Ibrutinib
enters only through the time-varying covariate AUC_IBRU; there are no
drug-dosing events in this model. Sister model files from the same
paper: modellib('Ibrahim_2023_ibrutinib_dbp'),
modellib('Ibrahim_2023_ibrutinib_leukocyte_spd'),
modellib('Ibrahim_2023_ibrutinib_competing_risk'). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Hirt_2008_ibuprofen.html">Ibuprofen
(Hirt 2008)</a> </td>
<td style="text-align:left;"> One-compartment population PK
model with linear elimination for intravenous ibuprofen-lysine (15-min
infusion) administered for closure of patent ductus arteriosus in
preterm neonates (Hirt 2008). Total-body clearance increases with
postnatal age via a power function (CL = 9.49 mL/h x (PNA / 96.3
h)^1.49) anchored at the cohort median PNA of 96.3 h; the apparent
volume of distribution is not influenced by postnatal age, gestational
age, body weight, Apgar score, or baseline serum sodium / creatinine /
albumin / urine output. Exponential inter-individual variability on CL
and V; proportional residual error. The PK-PD link reported by the
authors (AUC1D > 600 mg L^-1 h or AUC3D > 900 mg L^-1 h associated
with >= 91% PDA closure) is illustrated in the validation vignette
rather than carried in this model file. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Lodise_2018_iclaprim.html">Iclaprim
(Lodise 2018)</a> </td>
<td style="text-align:left;"> Two-compartment IV-infusion
population PK model for iclaprim, a bacterial dihydrofolate reductase
inhibitor, in adult patients with complicated skin and skin-structure
infections from the pooled ASSIST-1 and ASSIST-2 phase 3 trials (Lodise
2018). Structural typical-value equations are additive-linear (NONMEM
theta-sum form rather than power form): central volume V1 carries a
body-weight slope; clearance CL carries age + sex (male shift) +
sampling-occasion (day 1-2 vs day 4 +/- 1) shifts; peripheral volume V2
has no covariates; inter-compartmental clearance Q carries a
severe-cSSSI-infection shift. Block-correlated log-normal IIV on V1, CL,
V2 was retained in the source paper but only diagonal CV% values are
tabulated -- off-diagonal covariances are not reported and are
implemented here as diagonal-only (documented in the vignette
Assumptions and deviations section). Combined proportional + additive
residual error. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Brain_2008_ifosfamide.html">Ifosfamide
(Brain 2008)</a> </td>
<td style="text-align:left;"> Joint population PK / PD model
for ifosfamide in adults with advanced solid tumours (Brain 2008, n=17,
single-agent ifosfamide 9 g/m^2 per cycle by either 3 h x 3 daily or 72
h continuous infusion, n=1 randomised crossover, NONMEM VI FOCE
INTERACTION). One-compartment ifosfamide PK with Kerbusch 2000-style
autoinduction of clearance via a relative enzyme-pool state (drug
inhibits enzyme degradation), three coupled apparent-volume metabolite
states (4-hydroxy-ifosfamide, 3-dechloroethyl-ifosfamide,
2-dechloroethyl-ifosfamide), an indirect-response model for urinary
beta-2-microglobulin (BMG, renal tubular toxicity) with linear
stimulation of production by parent ifosfamide concentration, and a
five-compartment Friberg-style myelosuppression chain for absolute
neutrophil count (ANC) with linear inhibition of proliferation by parent
ifosfamide concentration and (CIRC0 / circ)^gamma feedback. No
covariates were retained in the final model (one outlier patient on
carbamazepine was excluded prior to the final analysis). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Freyer_2000_AVI_regimen.html">Ifosfamide
(Freyer 2000)</a> </td>
<td style="text-align:left;"> One-compartment IV population PK
model for ifosfamide in 24 small cell lung cancer patients on the AVI
regimen (Freyer 2000), with day-1/day-2 clearance collapsed to the mean
per operator instruction. Structural reduction from the paper's
two-compartment model: only central CL and V were reported in Table 2,
so the peripheral compartment is omitted; the paper's day-1 to day-2
autoinduction of clearance is also not represented in this extraction.
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Kerbusch_2000_ifosfamide.html">Ifosfamide
(Kerbusch 2000)</a> </td>
<td style="text-align:left;"> One-compartment population PK
model for ifosfamide with autoinduction of CYP3A4-mediated metabolism
implemented as ifosfamide-driven inhibition of enzyme-pool degradation
(no lag time); estimated in 15 adults with soft tissue sarcoma receiving
9 or 12 g/m^2 as a 72-h continuous IV infusion. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/ParraGuillen_2013_tumor_immunotherapy.html">Il12
(ParraGuillen 2013)</a> </td>
<td style="text-align:left;"> Preclinical (mouse, female
C57BL/6 with subcutaneous MC38 tumor). Applicability re-fit of the
Parra-Guillen 2013 semi-mechanistic K-PD tumor-growth-dynamics model to
a single dose of murine IL-12 delivered by hydrodynamic plasmid
injection. Structural equations are identical to the CyaA-E7 build
(ParraGuillen_2013_cyaaE7); cell-line and immunotherapeutic-kinetics
parameters (Ts0, lambda, k1, REG50) are re-estimated against the
Medina-Echeverz 2014 dataset, while vaccine- efficacy and
regulator-shape parameters (k3, k4, gamma) and the mixture probability
P(1) = 0.844 are carried fixed from the CyaA-E7 fit. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Yu_2024_ilaprazole.html">Ilaprazole
(Yu 2024)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model with first-order elimination for ilaprazole, a proton-pump
inhibitor, after 0.75 h intravenous infusion in Chinese healthy subjects
and patients with duodenal ulcer (Yu 2024). Pooled analysis of 1,560
plasma concentrations from 58 subjects across four phase I studies
(healthy) and one phase IIa study (duodenal ulcer), fit in Phoenix NLME
8.3 by FOCE-ELS. Female sex lowers clearance (exp(-0.213)) and
duodenal-ulcer disease status raises both clearance (exp(0.290)) and
peripheral volume (exp(0.356)); peripheral volume additionally scales
with body weight by a power of 1.545 around a 60.6 kg median. Typical
values are for a healthy male at 60.6 kg. Inter-individual variability
on the inter-compartmental clearance (CLp) was fixed in the final model
because of 84% eta-shrinkage and no numeric variance was reported, so it
is encoded as fixed(0). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Pei_2016_iloperidone.html">Iloperidone
(Pei 2016)</a> </td>
<td style="text-align:left;"> Population PK model for
iloperidone and its two major plasma metabolites P-88 (M1, contributes
to the therapeutic profile via D2 / 5-HT2A binding affinity comparable
to the parent) and P-95 (M2, CYP2D6-mediated hydroxylation metabolite,
pharmacologically less active) in 70 Chinese patients with schizophrenia
or schizoaffective disorder receiving oral iloperidone 12-24 mg/day
twice daily (Pei 2016). One-compartment first-order absorption (Ka FIXED
at 2.26 1/h, estimated in a separate forward analysis of
healthy-volunteer concentration-time data digitised from Pei 2016 ref
[23] and fixed for the patient model to stabilize absorption
identification under sparse sampling) and first-order parallel-pathway
elimination of iloperidone via three rate constants: K20 (other
elimination pathways), K23 (formation of M1), and K24 (formation of M2).
Each metabolite then occupies its own one-compartment model with FIXED
apparent volume V3 = V4 = 10 L (the fractions of iloperidone converted
to each metabolite are not identifiable from the cohort because no
co-administered tracer was available, so K23, K30 and K24, K40 are
estimated against the FIXED apparent metabolite volume per Methods) and
first-order elimination (K30 for M1, K40 for M2). Inter-occasion
variability was retained on K20 in the published final model but is NOT
carried as a separate eta in this nlmixr2lib extraction (see Errata in
the validation vignette). Mass units (mg) rather than molar units are
used per the source's convention because the molecular weights of
iloperidone (427.3 g/mol), M1 (429.4 g/mol), and M2 (429.2 g/mol) are
within 0.5%. CYP2D6*10 (rs1065852) polymorphism affects both metabolite
formation rate constants: T/T homozygotes have K23 1.34-fold the C/C +
C/T pooled reference; C/T heterozygotes and T/T homozygotes have K24
reduced to 0.693 and 0.492 of the C/C wild-type reference respectively.
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Chien_2022_imatinib.html">Imatinib
(Chien 2022)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model for oral imatinib in healthy adult volunteers (Chien 2022);
first-order absorption preceded by a Savic 2007-style analytical
transit-compartment chain (mean transit time and number of transit
compartments estimated), first-order elimination, and an OMEGA BLOCK
between the IIV on CL and V1 motivated by their estimated correlation r
> 0.9. No covariates were retained in the final model. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Jiang_2023_imatinib.html">Imatinib
(Jiang 2023)</a> </td>
<td style="text-align:left;"> One-compartment population PK
model with first-order absorption and first-order elimination for oral
adjuvant imatinib in postoperative Chinese adults with gastrointestinal
stromal tumors (Jiang 2023). The absorption rate constant is fixed at
1.22 1/h. Apparent oral clearance CL/F carries two covariate effects: a
power-form red blood cell count effect ((RBC/3.7)^0.49) and a
three-level ABCG2 rs2231142 genotype effect encoded with paired binary
indicators (GG wild-type reference = 1, GT heterozygote = 0.879, TT
homozygous variant = 0.976). Inter-individual variability is estimated
on CL/F only; the apparent volume of distribution V/F is a typical value
with no IIV because only trough concentrations were collected. Residual
error is proportional. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Schindler_2017_imatinib.html">Imatinib
(Schindler 2017)</a> </td>
<td style="text-align:left;"> Joint tumor-dynamics PD model for
imatinib-treated GIST liver metastases (Schindler 2017). Three size
metrics (maximum transaxial diameter MTD in mm, software-segmented
actual volume Vactual in mL, calculated ellipsoidal volume Vellipsoid in
mL) follow a logistic tumor-growth model with a linear DOSE-dependent
shrinkage term and a mono-exponential drug-effect washout (resistance
development). Tumor density (Hounsfield units) follows an
indirect-response model in which imatinib linearly stimulates the loss
rate. Each subject can carry up to two liver lesions (lesion 1 has the
larger baseline by convention); the binary covariate MIX_LARGE_BASE
selects between a mixture subpopulation with larger lesion baselines
(MIX_LARGE_BASE = 1, P = 0.348) and a smaller-baseline subpopulation
(MIX_LARGE_BASE = 0). Drug exposure enters via the daily dose normalized
to the median 400 mg, so DOSE is supplied as a per-record time-varying
covariate (in mg/day). The OS and PFS time-to-event arms of the source
publication are not encoded as ODE compartments here (see vignette
Assumptions and deviations). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/GonzalezSales_2024_imetelstat.html">Imetelstat
(GonzalezSales 2024)</a> </td>
<td style="text-align:left;"> Three-compartment population PK
model for imetelstat (GRN163L), a 13-mer N3'-P5' thio-phosphoramidate
oligonucleotide telomerase inhibitor, fit to 4375 plasma concentrations
from 424 adults with hematologic malignancies (lower-risk MDS,
myelofibrosis, multiple myeloma, ET/PV, CLD) or solid tumors who
received IV imetelstat 0.4-11.7 mg/kg weekly to every-4-weeks
(Gonzalez-Sales 2024). Imetelstat is described by a two-compartment
nonlinear disposition model with saturable binding/distribution to a
peripheral binding (BIND) compartment (Snoeck 1999 / Peletier 2017
parameterisation): free drug binds reversibly to a target pool with
capacity Bmax (Kon, Koff); bound drug is internalised to a deep
peripheral tissue (Kint) and returns to central as free drug (Kback);
free drug also undergoes linear elimination from central (CL).
Theory-based allometric exponents for body weight (1 on Vc, 0.75 on CL,
-0.25 on Kback) are fixed. Final covariates: sex, dose, time, and MF /
MM malignancy on CL; sex and MM malignancy on Vc; MF malignancy and
baseline spleen volume on Bmax. The time effect encodes a hyperbolic
decay of baseline CL: CL(t) = CL * cl_hill_t50 / (t + cl_hill_t50).
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Admiraal_2023_iminobiotin.html">Iminobiotin
(Admiraal 2023)</a> </td>
<td style="text-align:left;"> Two-compartment IV population PK
model for 2-iminobiotin (2-IB, a selective neuronal nitric oxide
synthase inhibitor) in adults after out-of-hospital cardiac arrest, with
a power-model eGFR-on-clearance covariate effect. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Vos_2025_iminobiotin.html">Iminobiotin
(Vos 2025)</a> </td>
<td style="text-align:left;"> Two-compartment intravenous
population PK model for the selective neuronal and inducible nitric
oxide synthase inhibitor 2-iminobiotin (2-IB) in adults with acute
large-vessel-occlusion (LVO) ischemic stroke treated with endovascular
thrombectomy (Vos 2025). Central, peripheral, and inter-compartmental
clearance are fixed at the upstream TIBOHCA-trial values (Vc = 10.2 L, Q
= 15.0 L/h, Vp = 10.4 L); clearance is the only estimated structural
parameter. Two typical clearance values are reported, one for patients
who did not receive concomitant intravenous thrombolysis (alteplase)
(9.29 L/h) and one for patients who did (15.3 L/h, a +65% increase).
Baseline estimated glomerular filtration rate enters as an allometric
power-form covariate on CL with exponent 0.817 and reference 90
mL/min/1.73 m^2. IIV is estimated on CL only (omega^2 = 0.046, ~22% CV);
Vc had no IIV because the volume was fixed. Residual error is a single
proportional component with SD 12.3%. The 24-hour continuous infusion
uses an eGFR-stratified pump-speed table (Supplemental Table S2) so that
all subjects regardless of renal function target the same average
exposure (AUC_avg_4h ~ 365 ng*h/mL). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Couffignal_2014_imipenem.html">Imipenem
(Couffignal 2014)</a> </td>
<td style="text-align:left;"> Two-compartment IV population PK
model for imipenem in 51 critically ill adult ICU patients with
suspected ventilator-associated pneumonia due to Gram-negative bacilli
(Couffignal 2014). All patients received imipenem as a 0.5 h IV infusion
every 8 hours; the protocol dose (500, 750 or 1000 mg) was chosen by
Cockcroft-Gault creatinine clearance per the European Medicine Agency
renal-adjustment table. Central clearance scales as a power of measured
4-hour creatinine clearance (reference 86.4 mL/min, the cohort median);
central volume scales jointly with total bodyweight (reference 77 kg)
and serum albumin (reference 18 g/L). The model was fitted in Monolix
4.1.2 using the SAEM algorithm with M3-equivalent BQL handling.
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Lamoth_2009_imipenem.html">Imipenem
(Lamoth 2009)</a> </td>
<td style="text-align:left;"> One-compartment IV population PK
model for imipenem in adult febrile neutropenic patients with
hematological malignancies (Lamoth 2009). Total clearance is the
additive sum of a non-renal arm and a renal arm linear in
Cockcroft-Gault GFR; the central volume of distribution scales linearly
with total body weight referenced to 70 kg. A single log-normal
inter-individual variability term is applied multiplicatively to the
total clearance (TVCL = CL_nonren + CL_renal * GFR / 100), and residual
error is proportional. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Yadav_2017_imipenem_aminoglycoside_pseudomonas.html">Imipenem
amikacin PA001 (Yadav 2017)</a> </td>
<td style="text-align:left;"> In vitro (static-concentration
time-kill). Mechanism-based PK/PD (Bulitta life-cycle growth) model of
bacterial killing and resistance for imipenem combined with amikacin
against carbapenem- and amikacin-resistant clinical Pseudomonas
aeruginosa isolate FADDI-PA001 (MIC_IPM = 32 mg/L, MIC_AMK = 32 mg/L).
Three pre-existing bacterial subpopulations with signal-molecule growth
inhibition and aminoglycoside-mediated outer-membrane permeabilisation
(mechanistic synergy) </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Yadav_2017_imipenem_aminoglycoside_pseudomonas.html">Imipenem
amikacin PA088 (Yadav 2017)</a> </td>
<td style="text-align:left;"> In vitro (static-concentration
time-kill). Mechanism-based PK/PD (Bulitta life-cycle growth) model of
bacterial killing and resistance for imipenem combined with amikacin
against carbapenem- and tobramycin-resistant clinical Pseudomonas
aeruginosa isolate FADDI-PA088 (MIC_IPM = 16 mg/L, MIC_AMK = 4 mg/L).
Three pre-existing bacterial subpopulations with signal-molecule growth
inhibition and aminoglycoside-mediated outer-membrane permeabilisation
(mechanistic synergy) </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/LopezArguello_2023_pbp_binding_pseudomonas.html">Imipenem
qsp (LopezArguello 2023)</a> </td>
<td style="text-align:left;"> QSP. In vitro (Pseudomonas
aeruginosa PAO1). Whole-cell penicillin-binding protein (PBP)
covalent-binding model for imipenem (carbapenem): seven coupled ODEs for
the rate of net influx of drug across the outer membrane into periplasm
and the competitive, mass-balanced acylation of six PBPs (1a, 1b, 2, 3,
4, 5/6) counted as molecules per bacterial cell. The intact parameter
switches between the intact whole-cell assay (penetration-limited; drug
enters periplasm at Rate_Influx/access) and the lysed isolated-membrane
assay (no outer membrane; a vast excess of drug molecules is present at
time 0). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Yadav_2017_imipenem_aminoglycoside_pseudomonas.html">Imipenem
tobramycin PA001 (Yadav 2017)</a> </td>
<td style="text-align:left;"> In vitro (static-concentration
time-kill). Mechanism-based PK/PD (Bulitta life-cycle growth) model of
bacterial killing and resistance for imipenem combined with tobramycin
against carbapenem- and amikacin-resistant clinical Pseudomonas
aeruginosa isolate FADDI-PA001 (MIC_IPM = 32 mg/L, MIC_TOB = 4 mg/L).
Three pre-existing bacterial subpopulations with signal-molecule growth
inhibition and aminoglycoside-mediated outer-membrane permeabilisation
(mechanistic synergy) </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Yadav_2017_imipenem_aminoglycoside_pseudomonas.html">Imipenem
tobramycin PA022 (Yadav 2017)</a> </td>
<td style="text-align:left;"> In vitro (static-concentration
time-kill). Mechanism-based PK/PD (Bulitta life-cycle growth) model of
bacterial killing and resistance for imipenem combined with tobramycin
against carbapenem-resistant and aminoglycoside-resistant clinical
Pseudomonas aeruginosa isolate FADDI-PA022 (MIC_IPM = 16 mg/L, MIC_TOB =
8 mg/L). Three pre-existing bacterial subpopulations with
signal-molecule growth inhibition and aminoglycoside-mediated
outer-membrane permeabilisation (mechanistic synergy) </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Yadav_2017_imipenem_aminoglycoside_pseudomonas.html">Imipenem
tobramycin PA088 (Yadav 2017)</a> </td>
<td style="text-align:left;"> In vitro (static-concentration
time-kill). Mechanism-based PK/PD (Bulitta life-cycle growth) model of
bacterial killing and resistance for imipenem combined with tobramycin
against carbapenem- and aminoglycoside-resistant clinical Pseudomonas
aeruginosa isolate FADDI-PA088 (MIC_IPM = 16 mg/L, MIC_TOB = 32 mg/L).
Three pre-existing bacterial subpopulations with signal-molecule growth
inhibition and aminoglycoside-mediated outer-membrane permeabilisation
(mechanistic synergy) </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Pardridge_2023_brain_plasma_protein_binding.html">Imipramine
pbpk (Pardridge 2023)</a> </td>
<td style="text-align:left;"> PBPK (brain, semi-mechanistic).
Pardridge 2023 Pharmaceutical Research partly-flow /
partly-compartmental model of imipramine delivery to brain that resolves
plasma-protein binding as an explicit kinetic process inside the brain
capillary. Seven brain states carry albumin-bound,
alpha-1-acid-glycoprotein (AGP)-bound and free drug in the brain
capillary, free AGP in the capillary, free drug in brain, and free /
drug-occupied brain cytoplasmic binding protein. Drug crosses the
blood-brain barrier by bi-directional first-order permeation and may be
metabolised in brain. Imipramine shows a high degree of
plasma-protein-mediated uptake from BOTH the AGP-bound and the
albumin-bound pools (KG in vivo 90 uM vs KG in vitro 1.2 uM; KA in vivo
>1,000 uM vs KA in vitro 42 uM), so free imipramine in brain is 18-
to 31-fold higher than equilibrium dialysis of plasma predicts. Arterial
input is a constant total plasma concentration (steady-state IV-infusion
model, c_plasma_ss, Table II LT0 = 100 nM); the paper did not run a
non-steady-state oral model for imipramine because detailed oral
pharmacokinetic parameters were not available, so this model has no
dosing compartment. All parameters are FIXED at the paper's
literature-sourced values; the paper reports no IIV and no residual
error because it is a deterministic simulation study rather than a fit
to individual data. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Cheng_2026_immunoglobulin.html">Immunoglobulin
(Cheng 2026)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model for intravenous immunoglobulin (IVIG) replacement therapy in
pediatric primary-immunodeficiency and secondary-antibody-deficiency
patients (Cheng 2026) </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Byrne_2022_imr687.html">Imr687
(Byrne 2022)</a> </td>
<td style="text-align:left;"> One-compartment population PK
model with first-order absorption for IMR-687 (a selective PDE9
inhibitor) in healthy subjects and patients with sickle cell disease
(SCD), coupled with a repeated time-to-event (RTTE) exposure-response
model for vaso-occlusive crisis (VOC) events. The PD hazard uses a
saturable (Michaelis-Menten) drug effect on a constant baseline hazard.
The model supports forward simulation of typical-value PK and
cumulative-VOC hazard at any once-daily dose; the published covariate
effects (body weight on CL/F and V/F; capsule formulation, capsule daily
dose, and high-fat meal on absorption) are NOT encoded because the
source conference poster reports the covariate point estimates without
the functional forms or reference values needed to apply them.
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Renard_2011_indacaterol.html">Indacaterol
(Renard 2011)</a> </td>
<td style="text-align:left;"> MBMA. Study-level Bayesian Emax
meta-analysis of trough FEV1 dose-response to once-daily inhaled
indacaterol in adults with moderate-to-severe chronic obstructive
pulmonary disease (COPD), pooled from 11 placebo-controlled trials
(7,476 patients; indacaterol doses 18.75 to 600 ug once daily).
Algebraic Emax dose-response on placebo-corrected steady-state trough
FEV1 (mL); the model is constrained to a null response at dose = 0
because the source data are contrasts to placebo. The original Bayesian
analysis included between-study (delta_i) and between-arm-within-study
(gamma_ij) random effects on Emax with unif(0, 0.25) priors; the paper
reports only the posterior means of the structural Emax and ED50, not
the random-effect posterior summaries, comparator mean effects
(formoterol, salmeterol, tiotropium), or a per-observation residual
sigma. The model file therefore encodes the indacaterol-only structural
Emax curve with between-study and between-arm variances fixed to zero
following the Vargo 2014 MBMA precedent. Suitable for simulating
typical-trajectory study-arm-mean trough FEV1 improvement vs placebo at
steady state (Week 2 to Month 6); not suitable for individual-subject
simulation. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Csajka_2004_indinavir.html">Indinavir
(Csajka 2004)</a> </td>
<td style="text-align:left;"> One-compartment
first-order-absorption population PK model for oral indinavir 800 mg
three-times-daily (alone) or 800 mg twice-daily with low-dose ritonavir
in HIV-infected adults; concomitant ritonavir, sex, and body weight
enter apparent oral clearance as multiplicative covariate effects
(Csajka 2004). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Kappelhoff_2005_indinavir.html">Indinavir
(Kappelhoff 2005)</a> </td>
<td style="text-align:left;"> One-compartment
first-order-absorption popPK model for oral indinavir in HIV-1-infected
adults, with multiplicative covariate effects of concomitant ritonavir
(CL/F x 0.354) and concomitant NNRTI (efavirenz/nevirapine; CL/F x 1.41)
on apparent clearance and of female sex on apparent bioavailability (F x
1.48). A 0.485 h absorption lag-time is applied only when ritonavir is
co-administered (Kappelhoff 2005). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Berends_2019_infliximab.html">Infliximab
(Berends 2019)</a> </td>
<td style="text-align:left;"> Two-compartment TMDD-QSS
population PK/target-dynamics model of infliximab and free TNF in adults
with moderate-to-severe ulcerative colitis (Berends 2019) </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Faelens_2021_infliximab.html">Infliximab
(Faelens 2021)</a> </td>
<td style="text-align:left;"> One-compartment IV population PK
model of infliximab in adults with moderate-to-severe ulcerative colitis
(Faelens 2021 adapted model; baseline-covariate-only re-fit of Dreesen
2019) </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Fasanmade_2009_infliximab.html">Infliximab
(Fasanmade 2009)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model of infliximab (anti-TNF-alpha) in patients with ulcerative colitis
(Fasanmade 2009) </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Frymoyer_2017_infliximab.html">Infliximab
(Frymoyer 2017)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model of intravenous infliximab in children and adults with Crohn's
disease (Frymoyer 2017; structural model and parameter values from the
Fasanmade et al. REACH + ACCENT I analysis reproduced in Frymoyer 2017
Methods) </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Hanzel_2021_infliximab.html">Infliximab
(Hanzel 2021)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model of subcutaneous and intravenous infliximab CT-P13 (biosimilar) in
adults with Crohn's disease and ulcerative colitis (Hanzel 2021)
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Marcantonio_2022_efa.html">Infliximab
(Marcantonio 2022)</a> </td>
<td style="text-align:left;"> QSP. One-compartment monospecific
anti-ligand mechanistic PKPD model of infliximab-TNF-alpha binding in
adults with rheumatoid arthritis (Marcantonio 2022 Early Feasibility
Assessment, Case Study 1). Structure identical to the Marcantonio 2022
adalimumab model; differs only in the drug-specific parameters (KD,
half-life, molecular weight, route). Infliximab is administered IV (dose
directly into Ab_00), binds soluble TNF-alpha monovalently (effective
valency = 1 per Tran 2017 / Lim 2018), and blocks the reversible
TNF:TNFR interaction. All parameters are FIXED from paper Table 2 (no
fitting, no IIV, no residual error reported). Run in the Applied BioMath
Assess Monospecific Anti-Ligand model. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Wu_2024_inotuzumab.html">Inotuzumab
(Wu 2024)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model for inotuzumab ozogamicin in pediatric and adult patients with
relapsed/refractory B-cell precursor acute lymphoblastic leukemia
(BCP-ALL) and adult patients with B-cell non-Hodgkin's lymphoma (NHL);
linear plus time-dependent (target-mediated) clearance with covariate
effects on CL_SS, Vc, CL_TIME, and cl_exp_kdes (Wu 2024, ITCC-059
pediatric trial pooled with 11 adult studies). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Chatelut_1999_interferon_alfa_2b.html">Interferon
alfa 2b (Chatelut 1999)</a> </td>
<td style="text-align:left;"> One-compartment population PK
model for subcutaneous alpha-2b interferon (Intron A) in adults with
chronic hepatitis C virus infection (Chatelut 1999), with sequential
zero-order then first-order absorption (a fraction Fz of the
bioavailable dose is absorbed at zero-order over duration tk0, the
remaining (1 - Fz) is absorbed at first-order rate ka after tk0) and
first-order elimination. Apparent oral clearance CL/F is reduced by
63.8% in chronic-haemodialysis patients relative to patients with normal
renal function (RRT_HEMODIAL_STATUS = 1 vs 0); apparent central volume
of distribution V/F scales linearly with body surface area (BSA).
Proportional residual error. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Jeon_2013_interferonAlfa2a.html">InterferonAlfa2a
(Jeon 2013)</a> </td>
<td style="text-align:left;"> Joint PK-PD model for a
sustained-release subcutaneous formulation of interferon alfa-2a
(SR-IFN-alpha) and the serum neopterin response in healthy adult male
volunteers (Jeon 2013). Pharmacokinetics: one-compartment with
first-order elimination and a parallel mixture of zero- and first-order
absorption. A fraction Fz = exp(RF)/(1 + exp(RF)) of the dose is
absorbed by a zero-order process with duration D2 entering the central
compartment directly; the remaining 1 - Fz is absorbed by a first-order
process (rate Ka) from a depot compartment with lag time ALAG,
accounting for the second concentration peak observed around 100 h
post-injection. Pharmacodynamics: indirect-response (turnover) model for
serum neopterin (baseline BASE = Kin/Kout) with a single transit
compartment placed between the stimulus and the observed neopterin,
delaying the neopterin response through mean transit time MTT. The drug
stimulates the zero-order production rate of neopterin through a sigmoid
Emax function E(C) = EMAX * C^GA / (EC50(t)^GA + C^GA), where EC50 is
time-dependent and increases monotonically over time as EC50(t) = ECB *
(1 + CA * (1 - exp(-CB * t))) -- an empirical saturation device that
captures the observed loss of the neopterin dose-response between groups
(9, 18, 27, 36 MIU) over the 0-264 h observation window. No covariate
effects were retained in the final model. Doses are entered in MIU (10^6
IU); the published apparent clearance (CL/F = 12.2 L/h) and apparent
volume of distribution (V/F = 691 L) match values previously reported
for IFN-alpha in healthy subjects (Reference [19] of Jeon 2013). The
model uses an explicit specific-activity conversion (1 MIU = 4 ug = 4e6
pg, from the WHO IFN-alpha-2a International Standard at 2.5e8 IU/mg) so
the doses in user data can be entered in MIU and the simulated Cc is
returned in pg/mL. The specific-activity conversion is not stated in the
paper itself; it is documented in the validation vignette's Assumptions
and deviations section. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Willmann_2021_fxi_aso.html">IonisFxirx
(Willmann 2021)</a> </td>
<td style="text-align:left;"> Population PK/PD model for the
unconjugated FXI antisense oligonucleotide IONIS-FXIRX (BAY2306001)
after subcutaneous administration in healthy volunteers (study ASO-CS1)
and patients with end-stage renal disease requiring hemodialysis (study
ASO-CS4), pooled with FXI-LICA data to fit the FXI-activity
indirect-response arm (Willmann 2021). Pharmacokinetics: two-compartment
model with parallel first-order (fraction F1, rate ka) and zero-order
(fraction 1 - F1, duration D2) subcutaneous absorption and first-order
elimination from the central compartment. Covariates on PK: end-stage
renal disease reduces CL by 53% and peripheral volume V3 by 38%
(proportional NONMEM form); body weight enters V2 as a power (V2 propto
(WT/70)^0.967). Pharmacodynamics: an indirect-response model on FXI
activity with sigmoid-Imax inhibition (Imax fixed to 1) of the
zero-order synthesis rate Kin = baseline * kout, driven by an
effect-site concentration linked to the plasma central compartment via
first- order equilibration ke0. An additional multiplicative factor
keoPAT modulates the effect-site concentration in ESRD patients (Ce_ESRD
= keoPAT * Cc at steady state; keoPAT = 0.329 reduces the effective
driving concentration to ~one third of the healthy-volunteer value). The
PK arm was fitted separately per compound; the FXI-activity arm was
fitted simultaneously to pooled ASO-CS1 + ASO-CS4 + LICA-CS1 data with
shared kout, baseline, ke0, and Hill exponent (Table S4). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Yoshida_2021_ipatasertib.html">Ipatasertib
(Yoshida 2021)</a> </td>
<td style="text-align:left;"> Joint parent + metabolite
population pharmacokinetic model for oral ipatasertib (AKT kinase
inhibitor under development for breast and prostate cancer) and its
primary active metabolite M1 (G-037720) in 342 adult patients with
cancer from five Phase 1 and 2 studies (Yoshida 2021). Each analyte is
described by a 3-compartment disposition model with sequential
zero-order then first-order absorption from its own depot. The two
depots receive the oral parent dose simultaneously (the user supplies
one event per depot with the same amount and time); both bioavailability
anchors are fixed at F = 1 because absolute parent F and the fraction of
parent metabolised to M1 are not separately identifiable from oral data
alone, and the apparent M1 absorption parameters (kf, Dur, F) subsume
formation, first-pass survival, and metabolite bioavailability per the
source. Retained parent covariates: power effect of age on apparent
CL/F, linear-additive effect of abiraterone coadministration on apparent
CL/F, power effect of body weight on apparent F, and a +20.1%
multiple-dose increment in apparent F representing CYP3A auto-inhibition
by ipatasertib. Retained metabolite covariates: power effects of body
weight on apparent V3 and Q3 of M1, a +33.1% multiple-dose increment in
apparent F_M1, and an additional +61.5% abiraterone-by-multiple- dose
effect on apparent F_M1. The paper fitted parent and metabolite in TWO
SEPARATE NONMEM runs (Yoshida 2021 Discussion); this file collapses them
into one rxode2 model with NO mechanistic fractional-conversion linkage,
mirroring the paper's simulation strategy. See vignette Assumptions and
deviations. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Feng_2014_ipilimumab.html">Ipilimumab
(Feng 2014)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model for intravenous ipilimumab (anti-CTLA-4 IgG1) in patients with
unresectable stage III or IV melanoma (Feng 2014) </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Sanghavi_2020_ipilimumab.html">Ipilimumab
(Sanghavi 2020)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model for intravenous ipilimumab (anti-CTLA-4 IgG1) with time-varying
clearance via a sigmoid cl_hill_max function in patients with advanced
solid tumors receiving ipilimumab alone or in combination with nivolumab
(Sanghavi 2020) </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Zhu_2023_oxaliplatin_irinotecan_colorectal_cancer.html">Irinotecan
(Zhu 2023)</a> </td>
<td style="text-align:left;"> Minimal-PBPK. Joint irinotecan
and SN-38 population PK model in adults with metastatic colorectal
cancer: two-compartment plasma disposition for each of irinotecan and
its active metabolite SN-38, plus an explicit tumour compartment.
Irinotecan enters the tumour interstitial space by tumour plasma flow
and permeates into tumour cells at a permeability-surface-area product;
SN-38 enters a single lumped tumour-tissue space governed by a
tumour/plasma partition coefficient. Zhu 2023 uses the tumour SN-38
concentration as the driver of an in vitro-derived tumour-killing model;
that in vivo tumour-growth layer is NOT included here because its growth
equation and limiting parameter are not reported anywhere in the paper -
see the vignette Errata. The tumour-distribution parameters are
transferred from the tumour-bearing-mouse fit, see
modellib('Zhu_2023_irinotecan_mouse'); the in vitro drug-effect half is
modellib('Zhu_2023_sn38_organoid'). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Zhu_2023_oxaliplatin_irinotecan_colorectal_cancer.html">Irinotecan
mouse (Zhu 2023)</a> </td>
<td style="text-align:left;"> Preclinical (tumour-bearing
mouse). QSP / minimal-PBPK. Joint irinotecan and SN-38 minimal-PBPK
model: two-compartment plasma disposition for each of irinotecan and its
active metabolite SN-38, plus an explicit tumour compartment. Irinotecan
enters the tumour interstitial space by tumour plasma flow and permeates
into tumour cells at a permeability-surface-area product; SN-38 enters a
single lumped tumour-tissue space governed by a tumour/plasma partition
coefficient. This is the preclinical fit that supplied the
tumour-distribution parameters (KP_IRI, KP_SN, PS_IRI) for the human
model, see modellib('Zhu_2023_irinotecan'); it carries no PD component
because Zhu 2023 took the drug effect from patient-derived tumour
organoids rather than from mouse tumour growth. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Brillac_2025_isatuximab.html">Isatuximab
(Brillac 2025)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model with linear elimination for isatuximab in pediatric and adult
patients with relapsed/refractory acute leukemias (Brillac 2025)
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Fau_2020_isatuximab.html">Isatuximab
(Fau 2020)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model for intravenous isatuximab (anti-CD38 IgG1) in adults with
relapsed/refractory multiple myeloma, with parallel time-varying linear
and Michaelis-Menten eliminations from the central compartment (Fau
2020). The linear clearance follows a sigmoidal Emax decay from baseline
to steady state; the magnitude of the decay differs by multiple-myeloma
immunoglobulin type. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Desai_2016_isavuconazole.html">Isavuconazole
(Desai 2016)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model for isavuconazole (administered as the prodrug isavuconazonium
sulfate) in healthy adults and adults with mild (Child-Pugh A) or
moderate (Child-Pugh B) hepatic impairment, following single 100 mg oral
or 2-h intravenous doses (Desai 2016). Weibull absorption for the oral
route; hepatic-impairment-group-specific typical CL and Q; linear BMI
effect on peripheral volume. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Horita_2018_isoniazid.html">Isoniazid
(Horita 2018)</a> </td>
<td style="text-align:left;"> Two-compartment population
pharmacokinetic model with first-order absorption and linear elimination
for oral isoniazid in Ghanaian children with active tuberculosis (Horita
2018); NAT2 slow-vs-nonslow acetylator phenotype on apparent oral
clearance with separate typical-value clearances and separate IIV
omegas; allometric weight scaling on CL/F and Q/F (fixed 0.75) and V1/F
and V2/F (fixed 1.0) normalised to the cohort median 14.3 kg.
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Seng_2015_isoniazid.html">Isoniazid
(Seng 2015)</a> </td>
<td style="text-align:left;"> Parent + two-metabolite
population pharmacokinetic model for oral isoniazid (INH),
acetylisoniazid (AcINH), and isonicotinic acid (INA) in 33 healthy Asian
adults (Seng 2015; Singapore single-dose 300 mg oral INH study with
crossover rifampin / efavirenz arms). Two-compartment INH disposition
with first-order absorption, linked to a two-compartment AcINH
disposition and a one-compartment INA disposition; metabolite formation
splits via the fraction-of- clearance parameters F_AcINH (INH ->
AcINH) and F_INA (AcINH -> INA), with the complementary (1 - F_AcINH)
routing INH directly to INA. The NAT2-derived acetylator phenotype
(rapid / intermediate / slow) selects between three typical-value INH
clearances (65.2 / 32.6 / 6.52 L/h at 63 kg). Creatinine clearance
enters as a power- law covariate on AcINH clearance with exponent 0.4
referenced to the cohort median 113 mL/min. All clearance and volume
terms are allometrically scaled by total body weight (0.75 exponent on
clearance, 1.0 on volume) with reference weight 63 kg. AcINH and INA
central volumes are fixed at 17 L (apparent central volume of AcINH from
Boxenbaum & Riegelman 1976) to keep the metabolite model
identifiable in the absence of intravenous data. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Wilkins_2011_isoniazid.html">Isoniazid
(Wilkins 2011)</a> </td>
<td style="text-align:left;"> Two-compartment population
pharmacokinetic model for oral isoniazid in South African pulmonary
tuberculosis patients (Wilkins 2011; 235 patients, 2352 plasma
concentrations). First-order absorption with an absorption lag time,
first-order elimination, and allometric scaling on all clearance and
volume terms (WT exponent 0.75 on CL and Q, exponent 1 on Vc and Vp,
reference weight 70 kg). A two-class mixture model on apparent clearance
characterises the bimodal isoniazid elimination phenotype that arises
from N-acetyltransferase-2 (NAT2) polymorphism: typical CL/F is 21.6 L/h
in fast eliminators (13.2 % of subjects) and 9.70 L/h in slow
eliminators (86.8 %). Two covariate effects were retained: female sex
reduces Vc/F by 10.3 % and HIV-positive comorbidity reduces CL/F by 17.4
%. Inter-individual variability is reported on CL/F, Vc/F, Q/F, relative
bioavailability F, and lag time; inter-occasion variability on ka (90.1
%) and F (8.4 %) is not propagated -- see the validation vignette
Assumptions and deviations section for the single-occasion
approximation. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Ramachandran_2023_tuberculosis_eptb_pbpk.html">Isoniazid
pbpk (Ramachandran 2023)</a> </td>
<td style="text-align:left;"> PBPK (whole-body, 18 ODEs, MATLAB
ode15s). Oral isoniazid disposition at extrapulmonary tuberculosis
(EPTB) sites in a 70-kg reference adult male (Ramachandran and Gadgil
2023, CPT Pharmacometrics Syst Pharmacol). Seventeen perfusion-limited
well-stirred tissue compartments connected by blood and lymph flow, plus
a gut-lumen state for enterohepatic recycling. The model's two novel
states are a pleural-fluid compartment (a filtrate of the lung that
drains via lymphatics) and a consolidated lymph-node compartment that
collects afferent lymph from every organ except bone and spleen and
returns it to venous blood - the two most common EPTB sites.
Physiological volumes, blood flows, and lymph flows are fixed literature
fractions of body weight, cardiac output (5200 mL/min), and afferent
lymph flow (8 L/day) respectively (Appendix S1 Tables S2 and S3).
Tissue:plasma partition coefficients were computed by the Rodgers and
Rowland method from the drug physicochemistry in Table S4 and are
tabulated in Table S5. Only the first-order oral absorption rate ka and
total systemic clearance CL were estimated, by weighted least squares
against reported plasma concentrations after a 300 mg oral dose
(Appendix S1 Table S7). Slow and fast acetylators are modelled as two
discrete cases selected by the NAT2_SLOW covariate, each with its own
ka, CL, and fractional renal clearance fR; the partition coefficients
are identical for the two groups. Clearance is split into a renal
component fR * CL driven by arterial concentration and a hepatic
component (1 - fR) * CL driven by the hepatic inlet concentration; the
hepatic output enters the gut lumen, which for isoniazid is a terminal
sink cleared only by faecal transit at kF = 0.252 /h (the paper assigns
a non-zero gut reabsorption rate only to rifampicin). The model is a
deterministic typical-value simulation: the paper reports no
interindividual variability and no residual error model, so propSd is
fixed at 0. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Abuhelwa_2015_itraconazole.html">Itraconazole
(Abuhelwa 2015)</a> </td>
<td style="text-align:left;"> Population PK model for oral
itraconazole and its active metabolite hydroxy-itraconazole in healthy
adults (Abuhelwa 2015). Two-compartment parent with
4-transit-compartment Savic-style absorption and a one-compartment
hydroxy-itraconazole metabolite eliminated by mixed linear and
Michaelis-Menten kinetics. Encodes the SUBA-itraconazole vs Sporanox
formulation effect on relative bioavailability (with
formulation-dependent scaling of the F variability) and the
fed-vs-fasted effect on both relative bioavailability and the
transit-absorption rate constant; the metabolic conversion ratio fm is
assumed = 1 so all parent clearance becomes metabolite, and the
metabolite CL/V are apparent values scaled by the unknown fm.
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Hennig_2006_itraconazole.html">Itraconazole
(Hennig 2006)</a> </td>
<td style="text-align:left;"> Population PK model for oral
itraconazole and its active metabolite hydroxy-itraconazole in
paediatric cystic-fibrosis and bone-marrow-transplant patients (Hennig
2006). One-compartment parent + one-compartment metabolite with
first-order absorption, first-order metabolic conversion (fm fixed to
1), allometric weight scaling on parent CL/F (0.75) and Vd/F (1.0), and
formulation-specific ka and relative bioavailability for capsule vs oral
solution. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Hennig_2007_itraconazole.html">Itraconazole
(Hennig 2007)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model for oral itraconazole and its one-compartment hydroxy-itraconazole
metabolite in adult cystic fibrosis patients (Hennig 2007), with
first-order absorption from a depot, formulation-specific absorption
rate constants and bioavailability for capsule vs. oral solution
selected by the binary FORM_CAPSULE covariate, and a single absorption
lag-time shared across both formulations. The fraction of itraconazole
metabolised to hydroxy-itraconazole is fixed to 1; metabolite parameters
are reported as CL_m/(F*f_m) and V_m/(F*f_m). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Alshehri_2023_ivermectin.html">Ivermectin
(Alshehri 2023)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model for ivermectin (IVM) in 56 adults (32 Wuchereria
bancrofti-infected, 24 uninfected) in Cote d'Ivoire given a single 200
ug/kg oral dose as part of ivermectin + diethylcarbamazine + albendazole
(IDA) triple-drug therapy for lymphatic filariasis, taken after a
high-fat breakfast (724 plasma samples). Absorption is a zero-order
input into the depot compartment (TK0 = 3.74 h) preceded by a lag time
(Tlag = 0.757 h), followed by first-order transfer into the central
compartment (Ka = 0.718 1/h) and linear elimination. Body weight enters
as allometric scaling with exponents fixed at 1 on Vc/F and Vp/F and
0.75 on CL/F and Q/F, centered on the study population's body weight.
Sex is the only covariate retained by the stepwise selection: Vp/F is
53% lower in men than in women (424.3 L in women, 201.8 L in men).
Lymphatic filariasis infection status was screened and had no effect on
any PK parameter. Residual variability is combined additive (0.461
ng/mL) plus proportional (22.8%). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Gupta_2015_ixazomib.html">Ixazomib
(Gupta 2015)</a> </td>
<td style="text-align:left;"> Three-compartment population
pharmacokinetic model for the oral proteasome inhibitor ixazomib
(MLN9708) developed from pooled data of 226 adult patients with advanced
multiple myeloma, lymphoma, or solid tumours across four phase I
dose-escalation studies (Gupta 2015). Combined intravenous and oral data
are described by a three-compartment model with first-order absorption
and linear elimination; IV and oral data share the same disposition
kinetics. Inter-individual variability is estimated on clearance,
central volume V2, the second peripheral volume V4, absorption rate
constant Ka, and bioavailability F; IIV on Q3, V3, and Q4 was fixed to
zero. Body surface area on V4 (reference 1.90 m^2, exponent 2.3) is the
only retained covariate; weight, age, gender, race, creatinine
clearance, ALT, AST, albumin, and bilirubin had no clinically relevant
effect on ixazomib pharmacokinetics. Residual error is additive on
log-transformed concentration (NONMEM Y = LOG(F) + EPS(1)) which maps to
a proportional error in linear concentration space. This analysis
supported the switch from BSA-based to fixed (4 mg) dosing in subsequent
ixazomib clinical studies. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Gupta_2017_ixazomib.html">Ixazomib
(Gupta 2017)</a> </td>
<td style="text-align:left;"> Three-compartment population
pharmacokinetic model for the oral proteasome inhibitor ixazomib
(Ninlaro) in 755 adult patients with multiple myeloma, lymphoma, solid
tumours, or light-chain amyloidosis pooled across ten phase I, I/II, and
III trials including TOURMALINE-MM1 (Gupta 2017). First-order linear
absorption with a 13 min lag time describes oral dosing; intravenous and
oral data share the same disposition kinetics. Inter-individual
variability is estimated on clearance, bioavailability F, and the second
peripheral volume V4, with a strong (82%) correlation between log CL and
log F. Body surface area on V4 (reference 1.87 m^2, exponent 2.06) is
the only retained covariate; sex, age, race, mild/moderate renal
impairment, mild hepatic impairment, smoking status, and CYP-modulatory
concomitant medications had no clinically relevant effect on systemic
exposure. Residual error is additive on log-transformed concentration
with a time-after-dose-varying standard deviation declining
exponentially from SD1 = 1.90 to SD0 = 0.46 with rate KSD = 0.84/h
(Karlsson 1995 model 3). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Jackson_2022_ixekizumab.html">Ixekizumab
(Jackson 2022)</a> </td>
<td style="text-align:left;"> Two-compartment linear population
PK model for subcutaneous ixekizumab in paediatric patients with
moderate-to-severe plaque psoriasis (IXORA-PEDS; Jackson 2022)
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Chen_2024_guhongInjection.html">Kaempferol3OGlucoside
rat (Chen 2024)</a> </td>
<td style="text-align:left;"> Preclinical (rat).
Two-compartment intravenous pharmacokinetic model for
kaempferol-3-O-glucoside (K-3-G), one of eight constituents of guhong
injection (GHI) quantified in plasma, in male Sprague-Dawley rats
subjected to 30 min left-anterior-descending ligation followed by 1 h
reperfusion (myocardial ischemia/reperfusion, MI/R) (Chen 2024). GHI was
given as a single tail-vein injection of 2.5, 5 or 10 mL/kg; the
kaempferol-3-O-glucoside dose is the GHI volume dose times its content
in GHI (8.7 ug/mL), i.e. 21.75 ug/kg, 43.5 ug/kg, 87 ug/kg. Disposition
was fitted separately in each dose group with Drug and Statistics (DAS)
v3.2.6, so V1, V2, CL1 and Q are selected from the covariate
DOSE_GHI_MLKG rather than through a dose-covariate function the authors
did not fit. Direct-effect sigmoid-Emax models link the
kaempferol-3-O-glucoside plasma concentration to the
GHI-minus-model-group difference in cardiac troponin I (cTn I) (E = Emax
* C^gamma / (ED50^gamma + C^gamma); Tables 14). Chen 2024 fitted a PK/PD
model only for the analyte/biomarker/dose combinations whose PLSR
coefficient was negative, so the effect of an unfitted combination is
returned as zero rather than extrapolated. No between-subject
variability or residual error was reported; every parameter is fixed at
the published mean and the residual SDs are fixed at zero. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Chen_2024_guhongInjection.html">Kaempferol3ORutinoside
rat (Chen 2024)</a> </td>
<td style="text-align:left;"> Preclinical (rat).
Two-compartment intravenous pharmacokinetic model for
kaempferol-3-O-rutinoside (K-3-R), one of eight constituents of guhong
injection (GHI) quantified in plasma, in male Sprague-Dawley rats
subjected to 30 min left-anterior-descending ligation followed by 1 h
reperfusion (myocardial ischemia/reperfusion, MI/R) (Chen 2024). GHI was
given as a single tail-vein injection of 2.5, 5 or 10 mL/kg; the
kaempferol-3-O-rutinoside dose is the GHI volume dose times its content
in GHI (65.7 ug/mL), i.e. 164.25 ug/kg, 328.5 ug/kg, 657 ug/kg.
Disposition was fitted separately in each dose group with Drug and
Statistics (DAS) v3.2.6, so V1, V2, CL1 and Q are selected from the
covariate DOSE_GHI_MLKG rather than through a dose-covariate function
the authors did not fit. Direct-effect sigmoid-Emax models link the
kaempferol-3-O-rutinoside plasma concentration to the
GHI-minus-model-group difference in creatine kinase-MB (CK-MB) (E = Emax
* C^gamma / (ED50^gamma + C^gamma); Tables 12). Chen 2024 fitted a PK/PD
model only for the analyte/biomarker/dose combinations whose PLSR
coefficient was negative, so the effect of an unfitted combination is
returned as zero rather than extrapolated. No between-subject
variability or residual error was reported; every parameter is fixed at
the published mean and the residual SDs are fixed at zero. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Park_2001_ketoprofen.html">Ketoprofen
(Park 2001)</a> </td>
<td style="text-align:left;"> One-compartment oral PK plus
Holford-Sheiner effect-compartment for synovial fluid disposition of
ketoprofen in adults with arthritis at steady state on 100 mg oral
twice-daily dosing (Park 2001 Tables 2-3, Eq. 1; effect-compartment
elimination rate keo = 0.16 1/h, peak synovial:plasma ratio 0.77 with
3.1 h time lag). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Valitalo_2017_ketorolac.html">Ketorolac
(Valitalo 2017)</a> </td>
<td style="text-align:left;"> Three-compartment population PK
model for IV ketorolac in adults, jointly fit to R-ketorolac and
S-ketorolac plasma concentrations after racemic IV dosing in women at
delivery, postpartum women, nonpregnant women, and men (Valitalo 2017
BJCP). Body-weight allometric scaling on clearance and volumes
(reference 71 kg) plus proportional pregnancy-at-delivery and male-sex
effects on clearance (and pregnancy-at-delivery on volumes), shared
between enantiomers. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Granda_2024_kidney_pbpk.html">Kynurenicacid
pbpk (Granda 2024)</a> </td>
<td style="text-align:left;"> PBPK (mechanistic kidney, 35
states). Individualised prediction of kynurenic acid renal clearance
from per-subject biomarker measurements of kidney blood flow and
OAT1/3-mediated tubular secretory capacity, on top of tracer-measured
GFR (Granda 2024, Clin Transl Sci). The kidney is resolved into 11
longitudinal subsegments (proximal tubule S1-S3, descending and
ascending loop of Henle, distal tubule, and five collecting-duct
subsegments), each with a tubular lumen, a tubular epithelial cell and a
peritubular blood subspace (33 states), plus a systemic blood
compartment and a bladder. Mechanisms: unbound glomerular filtration,
OAT1/3-mediated active secretion in the proximal tubule only,
pH-dependent bidirectional passive diffusion along the whole nephron,
and CKD tubular-flow adaptation. The structural equations, segment
volumes, surface areas, tubular pH profile and adaptive flow factors are
the Huang & Isoherranen 2018 / 2020 framework; Granda 2024 replaces
the framework population defaults for kidney blood flow and secretory
clearance with per-subject measured / fitted values. The biomarker leg
of the workflow: for each subject the unbound intrinsic secretory
clearance is fitted so that the model reproduces that subject's MEASURED
kynurenic acid renal clearance (Table 3). The fitted value is then
carried into the tenofovir and oseltamivir carboxylate models via a
drug-specific scalar. Deterministic typical-value model: the paper
reports no IIV and no residual error. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Lindauer_2017_lacosamide.html">Lacosamide
dropout (Lindauer 2017)</a> </td>
<td style="text-align:left;"> Repeated time-to-event dropout
model (dropout not because of a lack of efficacy) for adult patients
newly diagnosed with focal or generalized tonic-clonic epilepsy on
lacosamide (LCM) or carbamazepine controlled-release (CBZ-CR)
monotherapy, from Lindauer 2017 (SP0993 trial; NCT01243177). The base
hazard is a smoothed 4-breakpoint step function h0(t) = k1 + (k2-k1)*S1
+ (k3-k2)*S2 + (k4-k3)*S3 + (k5-k4)*S4 where S_i is a logistic sigmoid
centred at breakpoint BP_i with steepness GAM=50 (paper Frobel et al.
parameterisation). Covariate effects are multiplicative on the hazard:
hazard_drop = h0(t) * exp(e_sexf_drop*SEXF +
e_conmed_lcm_drop*CONMED_LCM). Sister time-to-seizure model for the same
trial: modellib('Lindauer_2017_lacosamide_seizure'). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Lindauer_2017_lacosamide.html">Lacosamide
seizure (Lindauer 2017)</a> </td>
<td style="text-align:left;"> Repeated time-to-seizure model
for adult patients newly diagnosed with focal or generalized
tonic-clonic epilepsy on lacosamide (LCM) or carbamazepine
controlled-release (CBZ-CR) monotherapy, from Lindauer 2017 (SP0993
trial; NCT01243177). Two Weibull sub-model hazards are exposed as
separate outputs: hazard_1st for the time to the first seizure and
hazard_2nd for the time to the second and subsequent seizures. Base
Weibull hazard h(t) = lam * p * (lam * t)^(p - 1) with distinct scale
(lam) and shape (p) for each sub-model. Baseline disease severity
(NSP3M: number of seizures in the previous 3 months, categorised <2 /
2-6 reference / 7-50 / >50), daily AUC of the assigned drug (LCM or
CBZ-CR; centred at 104 mg*h/L for LCM and 132 mg*h/L for CBZ), and age
(LCM-only, on the first-seizure hazard) enter as log-linear covariate
effects on lam. IIV on ln(lam_2nd) with SD 2.03 captures the substantial
between-subject variability in the subsequent-seizure hazard. Sister
dropout model for the same trial:
modellib('Lindauer_2017_lacosamide_dropout'). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Archary_2019_lamivudine.html">Lamivudine
(Archary 2019)</a> </td>
<td style="text-align:left;"> One-compartment population PK
model for lamivudine in severely malnourished HIV-infected children
(Archary 2019); CL/F matures with age via a sigmoid Emax function, Vc/F
decreases linearly with serum triglyceride, and ka steps up between day
1 and day 14 of antiretroviral treatment </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Bouazza_2010_lamivudine.html">Lamivudine
(Bouazza 2010)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model for once-daily oral lamivudine in HIV-infected West African
children (Bouazza 2010); allometric weight scaling on CL/F, Q/F, Vc/F,
and Vp/F with reference body weight 16.8 kg, and absorption rate
constant Ka structurally fixed to the disposition distribution-phase
eigenvalue (Ka = alpha = 0.71 1/h) from the literature </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Bouazza_2011_lamivudine.html">Lamivudine
(Bouazza 2011)</a> </td>
<td style="text-align:left;"> Two-compartment oral popPK model
for lamivudine in HIV-infected children from neonates to adolescents
(Bouazza 2011) </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Chandasana_2024_dolutegravir_lamivudine.html">Lamivudine
(Chandasana 2024)</a> </td>
<td style="text-align:left;"> Two-compartment oral population
PK model with first-order absorption and elimination for lamivudine 300
mg once daily as the dolutegravir/lamivudine fixed-dose combination in
virologically suppressed adults living with HIV-1 (TANGO; Chandasana
2024) </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Chandasana_2024_abacavir_dolutegravir_lamivudine_pediatric.html">Lamivudine
(Chandasana 2024b)</a> </td>
<td style="text-align:left;"> One-compartment oral population
PK model with first-order absorption, an absorption lag time and
formulation-dependent absolute bioavailability for lamivudine in
children with HIV-1 weighing 6 to 40 kg, applied without re-estimation
to the ABC/DTG/3TC fixed-dose combination (dispersible tablet and
tablet) in IMPAACT 2019 (Chandasana 2024) </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Moore_1999_lamivudine.html">Lamivudine
(Moore 1999)</a> </td>
<td style="text-align:left;"> One-compartment population PK
model for oral lamivudine in HIV-1-infected adults pooled from the
NUCA3001 and NUCA3002 phase III trials (Moore 1999); CL/F scales with a
Cockcroft-Gault-style renal function index ((140 - AGE)/(CREAT * 100), *
0.85 if female) raised to an estimated power and with linear body
weight, V/F and ka carry no covariates </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/He_2012_lamotrigine.html">Lamotrigine
(He 2012)</a> </td>
<td style="text-align:left;"> One-compartment population PK
model for oral lamotrigine in Chinese paediatric patients with epilepsy
aged 0.5-17 years (He 2012). First-order absorption with Ka fixed at 1.0
1/h and bioavailability fixed at 1 (lamotrigine steady-state trough
therapeutic-drug-monitoring data, which do not identify Ka or F), and
first-order elimination from a single central compartment. Apparent oral
clearance is scaled by an estimated power of total body weight (exponent
0.635) and modified exponentially by concomitant antiepileptic
comedication: valproate (CONMED_VPA) reduces CL, while the
enzyme-inducers carbamazepine (CONMED_CBZ) and phenobarbital (CONMED_PB)
increase CL. Apparent central volume is fixed at 16.7 L at the 27.87 kg
reference weight, scaled linearly with total body weight (allometric
exponent fixed at 1.0). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Hussein_1997_lamotrigine.html">Lamotrigine
(Hussein 1997)</a> </td>
<td style="text-align:left;"> One-compartment population PK
model for oral lamotrigine monotherapy in adults and adolescents newly
diagnosed with epilepsy; apparent oral clearance carries a first-order
auto-induction term that decays toward a steady-state value over
treatment duration and a multiplicative race effect for Asians vs
Caucasians; apparent volume of distribution and absorption rate constant
are time-invariant with no covariate effects retained in the final model
(Hussein 1997). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Milosheska_2016_lamotrigine.html">Lamotrigine
(Milosheska 2016)</a> </td>
<td style="text-align:left;"> One-compartment
first-order-absorption parent + one-compartment metabolite population
pharmacokinetic model for oral lamotrigine (LTG) and its N-2-glucuronide
(LTG-glu) in 100 adult Slovenian epilepsy patients on stable mono- or
adjunctive therapy (Milosheska 2016). Complete conversion of parent to
metabolite is assumed (LTG-N-5-glucuronide is a minor route, < 10%
urinary excretion of unchanged drug per the paper's Discussion citing
Ref [5]). Parent apparent oral clearance (CL/F) carries a power effect
of total body weight and additive-in-fraction effects of smoking,
concomitant enzyme-inducing antiepileptic drugs (carbamazepine,
phenobarbital, or phenytoin, pooled as CONMED_EIAED), concomitant UGT2B7
inhibitors (valproic acid or sertraline, pooled as CONMED_UGT_INH),
Cockcroft-Gault estimated creatinine clearance (deviation from 110
mL/min), and two UGT2B7 SNP genotype categoricals (-161C>T rs7668258
and 372A>G rs28365063). Parent apparent volume (V/F) carries a linear
deviation-from-reference weight effect. Metabolite apparent clearance
(CL_LTG-glu / F_metab) carries a power weight and linear Cockcroft-Gault
CLcr effect; metabolite apparent volume (V_LTG-glu / F_metab) is
estimated as a typical value only (no IIV supported by the sparse
metabolite data). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Le_2015_lampalizumab.html">Lampalizumab
(Le 2015)</a> </td>
<td style="text-align:left;"> Combined ocular-serum
target-mediated drug-disposition (TMDD) model with quasi-steady-state
binding approximation for intravitreally administered lampalizumab
(anti-complement factor D Fab) and total complement factor D (CFD) in
adults with geographic atrophy secondary to age-related macular
degeneration. Vitreous humor is the dosing compartment (depot) and the
site of drug-target binding; aqueous humor lampalizumab and aqueous
humor total CFD observations are derived from vitreous via constant
partition coefficients; serum lampalizumab is the central elimination
compartment with linear first-order clearance. Age and female sex modify
ocular and systemic elimination rates respectively (Le 2015 Table 1, Eq.
1-7). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Le_2015_lampalizumab_cyno.html">Lampalizumab
cyno (Le 2015)</a> </td>
<td style="text-align:left;"> Preclinical (cynomolgus monkey).
Semi-mechanistic and integrated ocular-systemic target-mediated
drug-disposition (TMDD) PK/PD model of lampalizumab (anti-complement
factor D antigen-binding fragment) and complement factor D (CFD) after
intravenous or bilateral intravitreal (ITV) administration. Uses the
quasi-steady-state (QSS) approximation of Gibiansky 2008. States:
vitreous total lampalizumab amount (depot), serum total lampalizumab
amount (central), a lampalizumab peripheral distribution compartment
(peripheral1), and total CFD concentrations in vitreous (total_target),
serum (total_target_central) and a target peripheral distribution
compartment (total_target_peripheral1). Total lampalizumab
concentrations in aqueous humor and retina are algebraic partitions of
vitreous total drug. The model represents one eye; vitreous-to-serum
flows in the serum ODEs carry a factor of 2 to reflect bilateral ITV
dosing. Naive-pool fit (no IIV); residual error was reported
qualitatively (proportional) but no numeric variance is given in the
paper, so residual SDs are encoded as fixed(0) so deterministic
simulation reproduces the paper exactly (see vignette Errata).
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Kunisawa_2015_landiolol.html">Landiolol
(Kunisawa 2015)</a> </td>
<td style="text-align:left;"> Two-compartment intravenous
population PK model with lag time for landiolol hydrochloride (an
ultra-short-acting cardioselective beta1-adrenergic receptor blocker) in
adult patients with peripheral arterial disease undergoing peripheral
arterial surgery, with linear body-weight normalization on CL, Vc, Q and
Vp (Kunisawa 2015) </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Buil-Bruna_2015_lanreotide.html">Lanreotide
(Buil-Bruna 2015)</a> </td>
<td style="text-align:left;"> One-compartment population PK
model with parallel first- and zero-order subcutaneous absorption for
lanreotide Autogel/Depot in patients with gastroenteropancreatic
neuroendocrine tumors (Buil-Bruna 2015). A linear effect of body weight
on apparent clearance and a small categorical effect of sex on the
first-order absorbed fraction are retained; absolute bioavailability F
is not identifiable and is structurally anchored at 1, so apparent CL/F
and Vd/F are reported. Concentrations are predicted in ng/mL; residual
error is additive on the log-transformed observations (LTBS), mapped to
proportional in linear space. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Sakurai_2007_lansoprazole.html">Lansoprazole
(Sakurai 2007)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model for intravenously administered lansoprazole in 56 healthy Japanese
adult males (Sakurai 2007). Volumes (V1, V2) and clearances (CL, Q)
scale linearly with body weight via per-kg reference values; systemic
clearance is stratified by CYP2C19 metabolizer phenotype using two
binary indicators (homoEM reference; heteroEM and PM groups carry
multiplicative factors of 0.612 and 0.212 respectively).
Inter-individual variability is log-normal on V1, CL, V2 (no IIV on Q);
residual error is combined proportional plus additive. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Zhu_2017_lebrikizumab.html">Lebrikizumab
(Zhu 2017)</a> </td>
<td style="text-align:left;"> Lebrikizumab population PK model
(Zhu 2017): two-compartment model with first-order absorption after SC
dosing in adults with moderate-to-severe asthma. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Hopkins_2015_leflunomide.html">Leflunomide
(Hopkins 2015)</a> </td>
<td style="text-align:left;"> Parametric time-to-event (TTE)
model for cessation of daily oral leflunomide due to toxicity in adult
rheumatoid-arthritis patients. Two piecewise-exponential hazards
describe (i) the toxicity-cessation hazard h0(t) with four intervals
(< 50, 50-112, 112-204, > 204 days after leflunomide initiation)
and (ii) a parallel random-censoring hazard h0ran(t) with five intervals
(< 147, 147-210, 210-314, 314-350, > 350 days). CYP1A2 rs762551
C-allele carrier status is the single retained covariate: it multiplies
the cessation hazard by (1 + 1.29 * SNP_CYP1A2_RS762551_C_CARRIER), a
2.29-fold increase for C-carriers vs AA homozygotes. Teriflunomide
steady-state trough concentrations (total and free), leflunomide dose,
CYP2C19 phenotype, and 20 other covariates were screened but not
retained in the final model. Outputs sur / hazard / cumhaz (cessation)
and sur_cens / hazard_cens / cumhaz_cens (random censoring) are exposed
for forward simulation. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Gupta_2016_lenvatinib.html">Lenvatinib
(Gupta 2016)</a> </td>
<td style="text-align:left;"> Three-compartment population PK
model for lenvatinib in healthy subjects and patients with cancer (Gupta
2016). Simultaneous first-order plus zero-order oral absorption into the
central compartment, linear elimination, and covariate effects of body
weight (allometric on CL/F and Q/F with exponent 0.75 and linear on
V/F), CYP3A4 inducers (+30 percent on CL/F), CYP3A4 inhibitors (-7.8
percent on CL/F), serum albumin < 30 g/L (-16.3 percent on CL/F),
alkaline phosphatase > ULN (-11.7 percent on CL/F), healthy-subject
cohort (+15 percent on CL/F vs cancer patients), and capsule vs tablet
formulation (relative bioavailability 0.896). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Majid_2024_lenvatinib.html">Lenvatinib
(Majid 2024)</a> </td>
<td style="text-align:left;"> Three-compartment population PK
model for lenvatinib pooled across healthy subjects and patients with
differentiated thyroid cancer (DTC), renal cell carcinoma (RCC),
hepatocellular carcinoma (HCC), and other solid tumors (Majid 2024).
Zero-order input into the absorption depot over a duration D1 followed
by first-order absorption (ka) into the central compartment, linear
elimination, and covariate effects of body weight (allometric exponent
0.75 on CL/F and Q/F, 1.0 on the volumes), concomitant CYP3A4 inhibitors
(-10.4 percent on CL/F), serum albumin < 30 g/L (-10.0 percent),
alkaline phosphatase > ULN (-9.0 percent), healthy-subject cohort
(+19 percent), and tumor type (DTC -4.9 percent, HCC -13.8 percent, RCC
-14.9 percent versus the other-solid-tumor reference), plus a
capsule-versus-tablet relative bioavailability of 0.882. This is the
updated successor to the Gupta 2016 lenvatinib popPK model; see
modellib('Gupta_2016_lenvatinib'). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Majid_2024_lenvatinib.html">Lenvatinib
biomarkers (Majid 2024)</a> </td>
<td style="text-align:left;"> Simultaneous four-biomarker
population PK/PD indirect-response model for serum VEGF, Tie-2, Ang-2
and FGF-23 during lenvatinib treatment of radioiodine-refractory
differentiated thyroid cancer (Majid 2024). Each biomarker is a turnover
pool with its own baseline, mean residence time and Hill coefficient; a
single common Emax, a single common EC50 and a single common linear
disease-progression slope are shared across all four. Lenvatinib
exposure enters as the steady-state daily AUC covariate AUC_LEN and acts
through a sigmoid Emax function that inhibits Kout for VEGF and FGF-23
(levels rise) and inhibits Kin for Tie-2 and Ang-2 (levels fall). There
is no PK ODE: AUC_LEN is supplied as a data column, as in the source
sequential fit. Companion models: modellib('Majid_2024_lenvatinib') for
the PK layer and modellib('Majid_2024_lenvatinib_tumor') for the
tumor-growth-inhibition layer. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Majid_2024_lenvatinib.html">Lenvatinib
tumor (Majid 2024)</a> </td>
<td style="text-align:left;"> Integrated
tumor-growth-inhibition and serum-biomarker PK/PD model for lenvatinib
in radioiodine-refractory differentiated thyroid cancer (Majid 2024).
First-order tumor growth (rate KG) is opposed by three shrinkage terms
acting on the RECIST 1.1 sum of longest diameters: an Emax function of
lenvatinib average daily AUC whose potency decays exponentially with an
acquired-resistance rate lambda, and two linear terms proportional to
the model-predicted relative change from baseline of Tie-2 and Ang-2.
The Tie-2 and Ang-2 time courses are re-integrated inside this model
from the companion four-biomarker turnover model with their parameters
fixed. Lenvatinib exposure enters as the AUC_LEN covariate; there is no
PK ODE. Time is in weeks. Companion models:
modellib('Majid_2024_lenvatinib') and
modellib('Majid_2024_lenvatinib_biomarkers'). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Majid_2024_lenvatinib.html">Lenvatinib
tumor asdeposited (Majid 2024)</a> </td>
<td style="text-align:left;"> AS-DEPOSITED variant of the Majid
2024 integrated tumor-growth-inhibition and serum-biomarker PK/PD model
for lenvatinib in radioiodine-refractory differentiated thyroid cancer:
a literal transcription of the deposited NONMEM control stream
(Supplementary Text S3), including the copy-paste slip in its Tie-2
drug-effect line. Text S3 defines Tie-2-specific effect variables
(IMAX1T, HILLT, IC50T) and then never uses them; the EFFT line picks up
the VEGF-indexed IMAX1, HILL and IC50 instead, so the Tie-2 arm is
driven by the VEGF Hill coefficient of 1 and by an EC50 left on the
ng*h/mL scale while the stream's AUC has been rescaled to ug*h/mL. The
resulting 1000-fold mismatch makes the Tie-2 pool essentially
drug-insensitive, so its contribution to tumor dynamics is a pure
disease-progression term. This is the code that produced the published
Table 3 estimates and Figure 4; modellib('Majid_2024_lenvatinib_tumor')
is the companion variant that instead follows the paper's printed
Equations 2 and 4. Lenvatinib exposure enters as the AUC_LEN covariate;
there is no PK ODE. Time is in weeks. Companion models:
modellib('Majid_2024_lenvatinib') and
modellib('Majid_2024_lenvatinib_biomarkers'). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Jaworowicz_2006_levalbuterol.html">Levalbuterol
(Jaworowicz 2006)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model for (R)-albuterol following inhaled levalbuterol (90 ug) or
racemic albuterol (180 ug) via a hydrofluoroalkane metered-dose inhaler
in pediatric (4-11 years) and adult (12-81 years) asthma patients.
First-order absorption, linear elimination, body-weight effects on
apparent clearance (linear-additive) and central volume (power), and a
pediatric-vs-adult split on absorption rate. The reference parameters
are the Adult / Study 051-353 / single-dose levalbuterol-visit values
(bioavailability anchor F1 = 1). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/KreeftmeijerVegter_2015_levamisole.html">Levamisole
(KreeftmeijerVegter 2015)</a> </td>
<td style="text-align:left;"> One-compartment oral PK model for
levamisole in 38 children with steroid-sensitive nephrotic syndrome
(Kreeftmeijer-Vegter 2015, EudraCT 2005-005745-18). First-order
absorption, first-order elimination, allometric scaling of CL/F
(exponent 0.75) and V/F (exponent 1) to 70 kg, and a linear proportional
age effect on CL/F centred on the population median age of 6.28 years
(-10.1% per additional year). The typical ka (1.2 1/h) was fixed in the
final model with IIV retained. IIV on V/F was modelled as perfectly
correlated with IIV on CL/F (single eta scaled to V/F), encoded here as
a full omega block with covariance equal to sqrt(var_CL * var_V).
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Shin_2017_levetiracetam.html">Levetiracetam
(Shin 2017)</a> </td>
<td style="text-align:left;"> One-compartment population PK
model for levetiracetam in Korean neonates with seizures (Shin 2017).
Structural parameters (V, CL) reported on a per-kg-body-weight basis
(linear scaling by body weight). Drug absorption was not modelled
because trough-style sampling between 6 and 23 hours after dose did not
capture the absorption phase; intravenous and oral doses are therefore
modelled as bolus inputs directly into the central compartment with
bioavailability fixed at 1. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Wang_2012_levetiracetam.html">Levetiracetam
(Wang 2012)</a> </td>
<td style="text-align:left;"> One-compartment population PK
model for levetiracetam (LEV) in Chinese pediatric epilepsy patients
(Wang 2012). First-order oral absorption and linear elimination (NONMEM
ADVAN2 TRANS2). Body weight is the only retained covariate; it enters
CL/F as a power-style allometric term with reference weight 25 kg
(cohort median). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Hussein_2005_levocetirizine.html">Levocetirizine
(Hussein 2005)</a> </td>
<td style="text-align:left;"> One-compartment population PK
model with first-order absorption and first-order elimination for orally
administered levocetirizine in atopic young children (12-48 months, 8-20
kg) receiving 0.125 mg/kg twice-daily levocetirizine (administered as
0.25 mg/kg twice-daily racemic cetirizine) for 18 months in the ETAC
study (Hussein 2005). CL/F and V/F are linear functions of body weight
(CL/F = 0.244 + 0.0442 * WT L/h; V/F = 0.639 * WT L). The absorption
rate constant ka is parameterised as ka = theta_ka + CL/V to guard
against flip-flop kinetics, with theta_ka = 1.140 1/h and CL/V
contributing on average less than 5% to ka. Residual variability is
additive with two concentration-dependent magnitudes: 53.5 ng/mL for Cc
<= 400 ng/mL and 316 ng/mL for Cc > 400 ng/mL (the 400 ng/mL
threshold was selected by sensitivity analysis and has no clinical or
therapeutic implication). Bioavailability is anchored at F = 1 here; the
paper additionally estimated F_noncomp = 0.281 applied to 12% of records
flagged as suspected noncompliance and recorded in the vignette
Assumptions and deviations. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Denti_2018_levofloxacin.html">Levofloxacin
(Denti 2018)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model for oral levofloxacin in South African children with
multidrug-resistant tuberculosis (MDR-TB) disease or exposure (Denti
2018; n = 109; median age 2.1 yr; median weight 12.4 kg). First-order
absorption with an absorption lag time, allometric scaling fixed to 0.75
on CL / Q and 1 on Vc / Vp with the population-median 12 kg as the
reference weight, and a Hill-type maturation function on CL driven by
postmenstrual age (PMAGE_50 = 10.6 mo, gamma = 3.39; PMAGE = postnatal
age + 9 mo assuming term gestation). Covariate effects: HIV-positive
children have 15.9% lower CL; nasogastric-tube (NGT) administration
shortens the absorption lag time by 85.6% relative to the oral
reference. F is fixed at 1; the additive residual error is fixed at 20%
of the LLOQ (0.0160 mg/L). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Hurtado_2014_levofloxacin_rat.html">Levofloxacin
rat (Hurtado 2014)</a> </td>
<td style="text-align:left;"> Preclinical (rat).
Three-compartment population PK model for unbound levofloxacin in plasma
and prostate interstitial fluid in male Wistar rats after a single 7
mg/kg IV bolus, with simultaneous fitting of total plasma concentrations
(central, Vc) and free prostate ISF concentrations measured by
microdialysis (effect compartment, apparent volume V3* = V_prostate /
fu_prostate). Prostate kinetics are asymmetric: uptake from central is
first-order (k13), efflux back to central combines a linear first-order
term (k31) with a saturable Michaelis-Menten efflux (Vmax, kM)
consistent with active transporter involvement. The standard central
<-> peripheral1 disposition uses macro-constants CL, Q, Vc, Vp
(Hurtado 2014). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Adeojo_2024_levonorgestrel.html">Levonorgestrel
(Adeojo 2024)</a> </td>
<td style="text-align:left;"> MBMA. Two-compartment population
PK model for levonorgestrel fit to pooled MEAN plasma concentration-time
profiles digitised from four published trials (Adeojo 2024). The four
trials span single 0.25 mg oral, single 0.25 mg intravenous, single 0.75
mg oral, two-dose 0.75 mg oral, and 150 mg subdermal implant
administration in women, with two of the trials contributing arms
co-administered with efavirenz 600 mg orally once daily. Absorption is
first-order and applies to oral dosing only (ka fixed at 4.15 /h); the
intravenous and subdermal-implant routes enter the central compartment
directly, so the estimated bioavailability F is an oral bioavailability.
Concomitant efavirenz enters as a single binary covariate with two
effects: clearance rises from 5.86 to 10.1 L/h (+72.4%) through CYP3A4
induction and oral bioavailability falls from 0.837 to 0.533 (-36.3%)
through gut-wall CYP3A4 induction. The model carries BETWEEN-STUDY
variability on oral bioavailability only (21.2% CV) and no
between-subject variability, because it was fit to study-level mean
profiles rather than individual concentrations; it therefore simulates
study-level mean concentration-time curves, NOT individual patient
concentrations. This is the reference mixed-effects model of the source
paper, used there to anchor a Simcyp physiologically-based model by
retrograde determination; the Simcyp PBPK model itself is not
reproducible from the published sources and is not packaged here (see
the validation vignette Assumptions and deviations). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Bienczak_2025_ligelizumab.html">Ligelizumab
(Bienczak 2025)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model for ligelizumab in adolescent and adult patients with chronic
spontaneous urticaria and healthy adult volunteers (Bienczak 2025)
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Retlich_2015_linagliptin.html">Linagliptin
(Retlich 2015)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model with concentration-dependent (saturable) binding of linagliptin to
dipeptidyl peptidase-4 in both central and peripheral compartments,
coupled with a population sigmoid Emax PK/PD model relating total
linagliptin plasma concentration to plasma DPP-4 activity, in adults
with type 2 diabetes mellitus (Retlich 2015 Tables 4 and 5). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Tadayasu_2014_linagliptin.html">Linagliptin
(Tadayasu 2014)</a> </td>
<td style="text-align:left;"> Two-compartment target-mediated
drug disposition population PK model for linagliptin with
quasi-equilibrium concentration-dependent binding to DPP-4 in both the
central and peripheral compartments, coupled with an occupancy-based
DPP-4-inhibition pharmacodynamic model (DPP-4 inhibition = Emax *
Cbound/BMAX in the central compartment), in Japanese patients with type
2 diabetes mellitus (Tadayasu 2014 Table 3). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Abdelgawad_2024_linezolid.html">Linezolid
(Abdelgawad 2024)</a> </td>
<td style="text-align:left;"> One-compartment population PK
model for oral linezolid in plasma and lumbar cerebrospinal fluid (CSF)
in adults with HIV-associated tuberculous meningitis receiving high-dose
rifampicin (35 mg/kg) co-treatment (LASER-TBM PK substudy, Abdelgawad
2024). Absorption is a Savic transit chain (mean transit time 0.211 h,
estimated chain length 5.68) feeding a first-order depot (ka 1.21 1/h);
elimination from the central compartment is saturable Michaelis-Menten
with maximal clearance 7.25 L/h and Michaelis-Menten constant 27.2 mg/L,
so Vmax = CLmax * km = 197 mg/h. CLmax and central volume (40.8 L) are
allometrically scaled on fat-free mass with a 45 kg reference and fixed
0.75 / 1 exponents (FFM beat total body weight by dOFV -30 vs -7.7). CSF
is a Sheiner-style effect compartment holding a concentration,
equilibrating with plasma at 0.198 1/h (equilibration half-life 3.5 h)
toward a pseudo-partition coefficient PPC; PPC rises linearly with CSF
total protein and plateaus at PPCmax = 0.365 once CSF protein reaches an
estimated 1.18 g/L breakpoint (a broken-stick whose intercept and
amplitude were fixed to 0 and 1, so the slope 0.847 = 1/1.18 is fully
determined by the breakpoint). Random effects are between-subject
variability on CLmax (9.60%), between-visit variability on CLmax across
the day-3 and day-28 PK visits (20.3%), and five-occasion
between-occasion variability on ka (87.9%) and mean transit time (110%);
all reported percentages are the omega standard deviation on the log
scale. Residual error is combined proportional plus additive, separately
for plasma (21.5%, 0.173 mg/L) and CSF (91.5%, 0.02 mg/L). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Boak_2014_linezolid.html">Linezolid
(Boak 2014)</a> </td>
<td style="text-align:left;"> Population PK/toxicodynamic model
for linezolid in 41 critically ill adult patients (Australia + USA, 42
treatment courses of 600 mg linezolid q12h IV and/or oral for 5-54
days). PK is a one-compartment model with three serial absorption-lag
compartments (lat1 -> lat2 -> lat3) followed by a gut compartment
(depot) before the central compartment; oral bioavailability is fixed at
100%. Renal function is described by a weight-normalised Cockcroft-Gault
GFR expressed as the ratio RF = GFR / 120, driving an additive
renal-plus-nonrenal total clearance CL = F_Size_CL * (CL_NR + CL_R * RF)
with fixed allometric exponents F_Size_CL = (WT/65)^0.75 and F_Size_V =
(WT/65)^1. The toxicodynamic model represents platelet turnover with a
15-compartment bone-marrow precursor chain (precursor1..precursor15,
rate ktr = 15/MTT_Pre) feeding a 15-compartment circulating platelet
chain (transit1..transit15, rate kout = 15/MTT_PL, Friberg-Bulitta
life-span distribution). The observed platelet count is the average of
the 15 circulating compartments. Linezolid inhibits synthesis of
platelet precursor cells (Imax fixed to 1, so the inhibitory factor
simplifies to IC50 / (IC50 + Cc)) with IC50 = 8.06 mg/L, and a
homeostatic feedback (Base_PL/PL)^gamma with gamma = 1.02 stimulates
precursor synthesis when circulating platelets fall below baseline.
Initial-condition scaling factors F_Ini_Pre and F_Ini_PL (typical values
fixed to 1, BSV estimated) allow the model to describe subjects whose
platelet counts were not at steady state at the start of therapy.
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Milakovic_2024_linezolid.html">Linezolid
(Milakovic 2024)</a> </td>
<td style="text-align:left;"> One-compartment population PK
model with first-order elimination for intravenous linezolid in nine
critically ill adults with COVID-19-associated acute respiratory
distress syndrome (CARDS) supported by veno-venous extracorporeal
membrane oxygenation (vv ECMO), who received a higher-than-standard 600
mg dose as a 30-min infusion every 8 h. Between-subject variability is
exponential on both clearance and volume of distribution, estimated as a
correlated 2x2 block with a strong negative CL-Vd covariance; residual
variability is proportional. No covariate was retained: the automated
covariate search found none significant, which the authors attribute to
the small, deliberately homogeneous sample. The model was used for Monte
Carlo probability of target attainment (PTA) and cumulative fraction of
response (CFR) analyses comparing 600 mg every 8 h against the standard
600 mg every 12 h. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Schmidt_2009_oxazolidinones.html">Linezolid
(Schmidt 2009)</a> </td>
<td style="text-align:left;"> In vitro (Staphylococcus aureus
MRSA strain OC2878). Mechanism-based PD model of bacterial-killing
time-kill curves for linezolid, the first-in-class FDA-approved
oxazolidinone (Schmidt 2009). Susceptibility-based two-subpopulation
structure: an active self-replicating susceptible pool with logistic
carrying-capacity limit and a dormant persister pool that is
insusceptible to killing; first-order S->P conversion (P->S held
fixed at 0), natural-death loss from both pools, exponential turn-on of
growth and of drug-induced killing, and Emax killing of the susceptible
subpopulation by the antibiotic. Linezolid was experimentally stable
over 24 h so the published model carries kdeg = 0; for dynamic
syringe-replacement experiments the user supplies the
dilution-equivalent rate (~log(2)/5 1/h for a t1/2 ~ 5 h linezolid
regimen) via rxSolve(..., params = c(kdeg = ...)). The same joint fit is
shared with Schmidt_2009_rwj416457 (only EC50 and kdeg differ).
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Taubert_2016_linezolid.html">Linezolid
(Taubert 2016)</a> </td>
<td style="text-align:left;"> Population PK model for linezolid
in critically ill ICU patients (Taubert 2016). Two-compartment model
with first-order absorption from a depot, first-order elimination,
complete oral bioavailability (F = 1), and a combined proportional +
additive residual error model. Covariate effects: body weight (power on
Vc, exponent 1.31) and peritonitis (multiplier on Vc, factor 1.53);
fibrinogen concentration (power on CL, exponent 0.04), serum lactate
concentration (power on CL, exponent -0.21), and ARDS (multiplier on CL,
factor 1.82). All continuous covariates are normalised to the
patient-group-1 median (WT = 76 kg, FIB = 13.0 umol/L, LACT = 1.91
mmol/L). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Tsuji_2017_linezolid.html">Linezolid
(Tsuji 2017)</a> </td>
<td style="text-align:left;"> Population PK/PD model for
linezolid in hospitalized adult and pediatric patients with MRSA or
gram-positive cocci infections (Tsuji 2017). PK is a two-compartment
model with first-order oral absorption and an additive
renal-plus-non-renal clearance structure (CL = CL_nonren + CL_renal *
RF, where RF = CrCl / 100 mL/min/70 kg standardized to 70 kg by
allometry); plasma total and unbound concentrations are modelled
simultaneously with an estimated fraction-unbound (FU = 0.823) linking
the two. PD is a Friberg-style semi-mechanistic platelet turnover model
(one proliferating compartment, three transit compartments, one
circulating compartment) with an empirical (PLTZERO/PLT)^gamma feedback
term and a published mixture model of two thrombocytopenia mechanisms:
linear inhibition of platelet synthesis (PDI, 97% of patients, SLOPE on
RFORM) and saturable stimulation of platelet elimination (PDS, 3% of
patients, Emax on Kcirc), selected per subject by the binary covariate
MIX_PDI. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Litjens_2023_linezolid_tuberculous_meningitis.html">Linezolid
cns pbpk (Litjens 2023)</a> </td>
<td style="text-align:left;"> PBPK (permeability-limited
4-compartment CNS model, adapted from the Simcyp Simulator V19R1 brain
module). Linezolid disposition in plasma, brain blood, brain mass,
cranial cerebrospinal fluid (CSF) and spinal CSF in adults and children,
developed to predict cranial CSF exposure and AUC0-24:MIC target
attainment in tuberculous meningitis (Litjens et al. 2023, Antibiotics).
The four CNS ODEs, the CNS physiological volumes and the CSF/brain fluid
flows are those of the upstream framework paper Verscheijden et al. 2019
(PLoS Comput Biol; Eqs 2-5, S1 Table), which Litjens 2023 adapted with
permission; the linezolid drug-specific inputs (Vss, plasma clearance,
ka, fa, B:P, fu, fu-brain, PSB, PSC, PSE, and the BCRP / P-gp efflux
clearances measured in-house in MDCKII monolayers) are from Litjens 2023
Supplementary Table S1 and S2. Adult and paediatric brain physiology
branch on AGE (< 18 y uses the paediatric equations of Verscheijden
2019 S1 Table). IMPORTANT DEVIATION: the systemic side of the published
model is the proprietary Simcyp full-PBPK whole-body distribution model
(Method 2, Rodgers and Rowland) whose tissue:plasma partition
coefficients are not reported anywhere in the paper or its supplement;
here it is replaced by a single well-stirred plasma compartment
parameterised with the exact aggregate values the paper does report -
Vss (L/kg) and the per-study total plasma clearance carried in the
Simcyp 'additional clearance' slot. Plasma AUC (= Dose * F / CL, the
quantity every PK-PD conclusion of the paper rests on) is preserved
exactly; the distribution phase of the plasma curve is approximate. See
the vignette Assumptions and deviations section. Typical-value
forward-simulation model: the paper reports no IIV or residual-error
estimates. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/CarlssonPetri_2021_liraglutide.html">Liraglutide
(CarlssonPetri 2021)</a> </td>
<td style="text-align:left;"> Liraglutide PK model in
adolescents (Carlsson Petri 2021) </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Overgaard_2016_liraglutide.html">Liraglutide
(Overgaard 2016)</a> </td>
<td style="text-align:left;"> Liraglutide 3.0 mg population PK
model in overweight and obese adults with and without type 2 diabetes
(Overgaard 2016 SCALE Obesity/Prediabetes + SCALE Diabetes pooled
analysis) </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Watson_2010_liraglutide.html">Liraglutide
(Watson 2010)</a> </td>
<td style="text-align:left;"> One-compartment population PK
model for subcutaneous liraglutide (once-daily human GLP-1 analog) with
sequential zero-order-then- first-order (sequential dual) absorption,
pooled across four Phase 1 studies (Studies A-D) in healthy volunteers
and adults with type 2 diabetes (Watson 2010). The combined-data final
model estimates apparent clearance and volume (CL/F, V/F) on a per-kg
body-weight basis. Absolute bioavailability F=0.51 was identifiable only
in the Study A submodel (with IV data) and is documented in the
vignette. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Bosch_2022_liraglutide_qsp.html">Liraglutide
qsp (Bosch 2022)</a> </td>
<td style="text-align:left;"> QSP. Integrated
four-hormone-plus-glucose (4GI) model of human glucose regulation
coupling glucose, insulin, GLP-1, glucagon, and glucose-dependent
insulinotropic peptide (GIP) dynamics after meal and drug perturbation,
with liraglutide (GLP-1RA) PK+PD baked in as the training drug. Glucose
disposition is a two-compartment model with insulin-dependent and
-independent elimination fed by an oral-meal dose compartment plus a
buffer and three serial gut transit compartments; insulin, GLP-1,
glucagon, and GIP each have one-compartment (GIP two-compartment)
turnover with steady-state baseline production. Feedbacks: glucose
stimulates insulin production (amplified by GLP-1 and GIP); insulin
drives insulin-dependent glucose clearance through an effect
compartment; glucose inhibits glucagon production (a below-baseline
glucose-on-glucagon effect is estimable in healthy volunteers only);
glucagon and GIP each stimulate glucagon and glucose production; GLP-1
inhibits gastric emptying and glucagon production, and stimulates
insulin secretion. Liraglutide PK is the Watson 2010 body-weight-scaled
one-compartment model (KAdrug 0.154 /h, CL/F 0.013 L/h/kg, V/F 0.16
L/kg, fu 0.005) and drives the three GLP-1 receptor pathways via
unbound-liraglutide EC50s derived from the in vitro EC50 ratio between
endogenous GLP-1 (1.919 pM) and liraglutide (6 pM). Population-mean fits
only (no IIV per Bosch 2022 Methods; five proportional residual errors,
one per biomarker output). Healthy volunteer (HV) vs type 2 diabetes
mellitus (T2DM) subjects differ in glucose clearance, insulin-dependent
glucose clearance, the below-baseline glucose-on-glucagon exponent, and
the GIP-on-insulin-secretion exponent, switched by the DIS_DIAB
indicator (1 = T2DM, 0 = HV). 18 ODE states; 5 outputs. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Thomson_1989_lisinopril.html">Lisinopril
(Thomson 1989)</a> </td>
<td style="text-align:left;"> One-compartment population PK
model for oral lisinopril (an ACE inhibitor) at steady state in elderly
and renal-disease hypertensive adults (Thomson 1989). First-order
absorption with apparent clearance CL/F driven by body weight, serum
creatinine, age, and a binary compensated-cardiac-failure indicator;
apparent volume V/F and absorption rate ka are population means without
retained covariate effects. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Jensen_2023_lngIus52mg.html">LngIus52mg
(Jensen 2023)</a> </td>
<td style="text-align:left;"> Eight-year population PK /
SHBG-turnover model for levonorgestrel (LNG) released from the
LNG-releasing intrauterine system (LNG-IUS) 52 mg (Mirena). In-vivo
release from the reservoir is described as a mixture of a first-order
term (rate coefficient c12), a constant zero-order term (c13), and a
time-dependent first-order term with time-decay constant t1, giving
DADT(depot) = -c12 * depot - c13 * (1 + depot / (t1 + t)). Two-
compartment LNG disposition treats only unbound drug as distributable /
eliminable via K20 * fuLNG * central and K23 * fuLNG * central, where
fuLNG is the closed-form free-fraction solution to reversible LNG
binding to albumin (constant, KDA = 18209 nmol/L, ALB = 700000 nmol/L)
and to SHBG (KDS = 1.82 nmol/L). SHBG serum concentration is modelled
with an indirect-response turnover (zero-order kin, first-order kout)
whose synthesis is linearly inhibited by a delay-compartment-smoothed
unbound LNG signal (delay time-constant tau). Body weight enters as an
allometric-style power on apparent (free) LNG clearance and on the SHBG
baseline. Bioavailability of the loaded LNG reservoir is fixed via a
logit anchor (F1 ~ 0.971 of the 52 mg reservoir). All rate constants are
expressed per hour. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Archary_2018_lopinavir.html">Lopinavir
(Archary 2018)</a> </td>
<td style="text-align:left;"> One-compartment
first-order-absorption population PK model for oral lopinavir/ritonavir
in severely malnourished HIV-infected children, with FFM allometric
scaling and a linear total-cholesterol effect on apparent clearance
(Archary 2018). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Crommentuyn_2005_lopinavir.html">Lopinavir
(Crommentuyn 2005)</a> </td>
<td style="text-align:left;"> One-compartment
first-order-absorption population PK model for oral lopinavir
co-administered with ritonavir in 122 HIV-1-infected adults on BID
lopinavir/ritonavir 400-666/100-166 mg. Apparent oral clearance CL/F
follows an inverse-saturable function of per-subject ritonavir AUC over
the 12 h dosing interval (CONMED_RTV_AUC_12h, mg*h/L, computed from the
upstream Kappelhoff 2005 ritonavir popPK model) plus a pooled +39% NNRTI
co-medication factor (efavirenz or nevirapine, encoded as the
CONMED_NNRTI class indicator). IIV is estimated on ka, CL/F, and V/F as
a full 3x3 correlated block; residual error is combined additive plus
proportional. The reported IOV on relative bioavailability F (17.5% CV)
is NOT encoded structurally (Brooks 2021 precedent); downstream users
who want IOV can add an OCC covariate and a per-occasion eta in rxode2
(Crommentuyn 2005). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Jullien_2006_lopinavir.html">Lopinavir
(Jullien 2006)</a> </td>
<td style="text-align:left;"> One-compartment population PK
model for oral lopinavir (boosted with ritonavir) in HIV-infected
children from birth to 18 years, with the absorption and elimination
rate constants constrained to a single shared rate constant k = CL/F
divided by V/F (Jullien 2006, simplified parameterisation per Wahlby
2002). Body weight is allometrically scaled on CL/F and V/F (reference
27 kg), nevirapine coadministration increases CL/F by 34%, and male sex
increases CL/F by 39% in children older than 12 years. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Schipani_2012_lopinavir.html">Lopinavir
(Schipani 2012)</a> </td>
<td style="text-align:left;"> Population PK model for boosted
lopinavir (lopinavir/ritonavir 400/100 mg) in HIV-infected adults from
the Liverpool Therapeutic Drug Monitoring Registry. One-compartment with
first-order absorption; apparent clearance is modified additively by
body weight (deviation from median 72 kg) and by SLCO1B1 521T>C
(rs4149056) genotype, encoded via the paired SLCO1B1_HAP15_HET /
SLCO1B1_HAP15_HOM indicators (the source paper genotyped only 521T>C
so *5- and *15-haplotype carriers are pooled, per the canonical's
documented pooling rule). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Thoueille_2023_lopinavir.html">Lopinavir
(Thoueille 2023)</a> </td>
<td style="text-align:left;"> One-compartment
first-order-absorption population PK model for oral ritonavir-boosted
lopinavir (LPV/r) in HIV-negative individuals receiving 5-day COVID-19
post-exposure prophylaxis (COPEP study) pooled with people living with
HIV followed by routine therapeutic drug monitoring; body weight enters
apparent oral clearance as a linear deviation from a 70 kg reference
(Thoueille 2023). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Fauchet_2015_lopinavir.html">Lopinavir
placental (Fauchet 2015)</a> </td>
<td style="text-align:left;"> One-compartment
first-order-absorption population PK model for total lopinavir in
HIV-infected pregnant and nonpregnant women with a maternal-to-fetal
effect-compartment placental-transfer chain and a downstream
fetal-to-amniotic-fluid distribution-and-elimination chain; a 39%
pregnancy effect is applied multiplicatively to apparent maternal CL
(Fauchet 2015 MFLA submodel). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Zhang_2012_lopinavir_ritonavir.html">Lopinavir
ritonavir (Zhang 2012)</a> </td>
<td style="text-align:left;"> Simultaneous integrated
population pharmacokinetic model of oral lopinavir (LPV, parent) and
ritonavir (RTV, sibling-drug suffix _rtv) in 21 HIV-infected South
African adults with and without concomitant antitubercular rifampicin
(Zhang 2012). Structure: LPV one-compartment with first-order absorption
(ka 0.991 1/h) and LPV CL/F dynamically inhibited by RTV plasma
concentration via a sigmoid Imax (Imax = 0.953, IC50 = 0.0351 mg/L); RTV
two-compartment with a Savic transit- compartment absorption chain (NN =
2.03, MTT = 1.44 h) feeding RTV depot at rate ktr = (NN+1)/MTT and
absorbed to RTV central at ka_rtv = 3.28 1/h. Allometric scaling fixed
at the Holford / Anderson literature values: fat-free mass
(Janmahasatian) drives CL/F (exponent 0.75) and total body weight drives
Vc/F and Vp/F (exponent 1.0). Rifampicin (CONMED_RIF) increases LPV CL/F
by 71.0% and RTV CL/F by 36.0%, reduces LPV F by 20.0% and RTV F by
45.0% (at the 100 mg reference RTV dose), and the RTV F when on
rifampicin scales upward with RTV dose at 8.1% per 10 mg above the 100
mg reference (saturation of first-pass metabolism / P-gp
self-inhibition; identifiable only within the RIF-coadministered arm of
the source study). Diurnal variation is encoded via the simulation
convention t = clock-hours- from-midnight: doses given during the
overnight window (clock 20:00 to 08:00) carry +42.0% (LPV) and +45.0%
(RTV) relative bioavailability vs morning doses, and oral CL/F of both
drugs is reduced by 32.7% overnight. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Zhang_2013_lopinavir_ritonavir.html">Lopinavir
ritonavir (Zhang 2013)</a> </td>
<td style="text-align:left;"> Integrated population PK model
for lopinavir (1-compartment, first-order absorption) and ritonavir
(2-compartment, transit-chain absorption with N=2 transit compartments)
co-administered to HIV-infected adults (n=21) and children (n=74; 35 of
whom received rifampicin-based antitubercular treatment). Ritonavir
plasma concentration inhibits lopinavir apparent clearance via a
sigmoidal Emax DDI (Emax=0.82, EC50=0.098 mg/L, Hill=2.8). Rifampicin
coadministration increases apparent clearance and reduces relative
bioavailability of both drugs, with separate magnitudes for adults vs
children. Ritonavir dose (mg/kg) drives a linear increase in relative
bioavailability of both drugs; lopinavir-on-adults is the only
dose-effect cell not supported by the data. Diurnal variation is encoded
as a step function with overnight reduction in apparent clearance
(adults 51%, children 27%) and increased bioavailability at the evening
lopinavir dose for adults (+19%). Allometric scaling on apparent CL/Q
(exponent 0.75) and apparent V/Vp (exponent 1) with reference body
weight 65 kg (Zhang 2013). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Zhang_2012_lopinavir_ritonavir_pedi.html">Lopinavir
ritonavir pedi (Zhang 2012)</a> </td>
<td style="text-align:left;"> Integrated one-compartment popPK
model for oral lopinavir (LPV) and ritonavir (RTV) in 74 HIV-infected
children (6 months to 4.5 years) treated with LPV/r oral solution with
or without concomitant rifampicin-based antitubercular treatment (Zhang
2012). LPV uses a one-compartment model with first-order absorption; RTV
uses a one- compartment model with a Savic-style 10-transit-compartment
absorption chain followed by a separate first-order absorption step from
the last transit to central. Apparent CL/F and V/F are allometrically
scaled to the cohort median 10 kg with fixed exponents 0.75 / 1. The
dynamic LPV-RTV interaction is encoded as direct sigmoid-Emax inhibition
of LPV apparent clearance by RTV plasma concentration (Emax = 0.9 fixed,
EC50 = 0.0519 mg/L). Lopinavir bioavailability is modulated by
concomitant rifampicin-based antitubercular treatment (-83.2% at the
no-extra-ritonavir reference) and by the concomitant ritonavir dose in
mg/kg (+2.1% per mg/kg above the 3 mg/kg reference). Ritonavir apparent
clearance is +50% in subjects on rifampicin-based antitubercular
treatment. Both drugs share random effects modelled as log-normal
between- subject variability with selected inter-occasion variabilities
folded in as BSV-equivalent (see vignette Assumptions and deviations).
Residual error is proportional on the linear scale (implemented via
NONMEM exponential error on log-transformed data). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Fauchet_2015_lopinavir.html">Lopinavir
unbound (Fauchet 2015)</a> </td>
<td style="text-align:left;"> One-compartment
first-order-absorption population PK model for lopinavir in HIV-infected
pregnant and nonpregnant women parameterised on the unbound fraction,
with total LPV reconstructed from a linear HSA binding term plus a
saturable single-site AAG binding term (Fauchet 2015 unbound submodel).
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Swart_2004_lorazepam_midazolam.html">Lorazepam
(Swart 2004)</a> </td>
<td style="text-align:left;"> Two-compartment IV population PK
model for lorazepam by continuous infusion in mechanically ventilated
critically ill adult ICU patients. Clearance is selected by chronic
alcohol-abuse status (a flat 0.74 L/h for alcohol-abuse subjects; a
PEEP-adjusted 4.13 - (PEEP - 5) * 0.417 L/h otherwise). Steady-state
volume of distribution decreases linearly with age above 58 years.
Fitted by NONMEM V in the Swart 2004 learning cohort (n = 28).
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Ahmed_2016_lorenzosOil.html">LorenzosOil
(Ahmed 2016)</a> </td>
<td style="text-align:left;"> Population pharmacodynamic model
of Lorenzo's oil effect on plasma C26:0 in asymptomatic boys with
X-linked adrenoleukodystrophy: inhibitory fractional Emax model relating
observed plasma erucic acid concentration to plasma C26:0. The paper
does not develop a PK model for erucic acid; observed erucic acid plasma
concentration is supplied as a time-varying covariate. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Chen_2021_lorlatinib.html">Lorlatinib
(Chen 2021)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model for oral lorlatinib (a third- generation ALK/ROS1 tyrosine kinase
inhibitor) in adult patients with advanced ALK-positive or ROS1-positive
non-small cell lung cancer and healthy participants (Chen 2021; N = 425
across seven studies). Disposition is a two-compartment model with
sequential zero-order and first-order oral absorption (dose enters the
depot via a zero-order window of duration D1 = 1.15 h followed by
first-order absorption at ka = 3.11 h^-1) and time-varying metabolic
auto-induction of clearance: CL(t) = CLI + (CLMX - CLI) * (1 -
exp(-cl_exp_kdes * t)), rising from a single-dose CLI = 9.04 L/h to a
steady-state CLMX = 14.5 L/h with induction rate constant cl_exp_kdes =
0.020 h^-1 (~7.25 d to functional steady state; Chen 2021 abstract,
Table 4). CLI and CLMX share a fixed allometric exponent 0.75 on body
weight (reference 70 kg) and both are modulated by a shared
multiplicative covariate block: 1 + e_alb_cl * (ALB - 40 g/L) with
e_alb_cl = 0.00670 per g/L, 1 + e_dose_lor_cl * (DOSE_LOR_MGD - 100
mg/day) with e_dose_lor_cl = 0.00100 per mg/day, and a power effect
(CRCL / 100)^e_crcl_cl with e_crcl_cl = 0.235. V2 = 121 L carries a
fixed allometric exponent 1.0 on body weight; V3 = 155 L and Q = 22.0
L/h have no allometric scaling. ka is modulated by proton-pump inhibitor
co-administration: ka x (1 - 0.675 * CONMED_PPI), i.e. a 67.5% ka
reduction on PPI (which reduces Cmax by ~30% with no effect on AUCinf
per the Chen 2021 Discussion). Bioavailability F1 = 0.759.
Inter-individual variability is a correlated CL/F block (log-scale
variances 0.030 and 0.022; covariance -0.006), a correlated V2/V3 block
(0.086, -0.017, 0.101), and an independent ka block (2.33). Residual
error is a route-specific log-scale additive term (approximately
proportional in linear space): propSd 11.5% CV for IV data (Study
B7461007 absolute bioavailability arm) and 43.8% CV for oral data.
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Yang_2013_losmapimod.html">Losmapimod
(Yang 2013)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model with first-order elimination and time-dependent first-order
absorption (change-point MTIME between two absorption rate constants
XKA1 and XKA2) plus an absorption lag time ALAG1, for oral losmapimod (a
p38 alpha/beta mitogen-activated protein kinase inhibitor). Data pooled
from 30 healthy volunteers, 23 patients with rheumatoid arthritis, and
24 patients with chronic obstructive pulmonary disease across four GSK
studies (Yang 2013). Retained covariates on inter-individual variability
are sex on CL/F (males reference; females get a lower CL/F), age on V1
(power exponent centred at median age 54 years), and body weight on both
absorption rate constants (shared power exponent centred at median 74
kg). Residual error is proportional and larger in COPD patients than in
the pooled healthy + RA reference. Doses were 5, 7, 7.5, 10, and 20 mg
oral single- or repeat-dose; 60 mg data were excluded from the analysis
due to lack of dose-proportionality (possible saturable absorption).
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Siebinga_2023_lu177psma617.html">Lu177psma617
(Siebinga 2023)</a> </td>
<td style="text-align:left;"> Six-compartment population PK
dosimetry model for the PSMA-targeted radioligand [177Lu]Lu-PSMA-617 in
men with low-volume metastatic prostate cancer, built from
SPECT/CT-derived organ and tumor activity plus blood samples over two
treatment cycles (~3 and ~6 GBq). States are blood (1), salivary gland
(2), kidney (3), liver (4), tumor (5) and a lumped other-tissue
compartment (6); every state carries a decay-corrected radioactivity
amount (MBq) and only the blood compartment has an estimated volume (V1
= 10.3 L), so blood is observed as a concentration (MBq/L) and the
tissues as amounts. Salivary-gland uptake is saturable in the bound
amount (Bmax 40.4 MBq, IIV 59.3% CV); all other tissue exchange is first
order. The tumor uptake rate constant carries a power effect of total
tumor volume (exponent 0.705), interindividual variability (58.8% CV)
and interoccasion variability across the two cycles (43.5% CV), and the
blood excretion rate constant is scaled a priori by Cockcroft-Gault
creatinine clearance under an assumption of complete renal elimination.
The blood compartment has two observation channels with separate
residual error: blood samples, and SPECT-derived blood activity linearly
recalibrated to the blood-sample scale. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Siebinga_2024_lu177psmaIT.html">Lu177psmaIT
(Siebinga 2024)</a> </td>
<td style="text-align:left;"> Five-compartment population PK
model with a sequentially fitted PSA pharmacodynamic layer for the
PSMA-targeted radioligand [177Lu]Lu-PSMA-I&T in men with metastatic
castration-resistant prostate cancer treated with ~7.4 GBq per cycle. PK
states are central (1), salivary glands (2), kidneys (3), tumor lesions
(4) and a lumped remaining-tissue compartment (5); the tissue states
carry radioactivity amounts (MBq) and the central state is observed as a
concentration (MBq/L) through a fixed volume V1 = 10.3 L. Renal
excretion leaves the central compartment (k10 = 0.253 1/h, i.e. 2.61
L/h). Salivary-gland uptake is saturable (Bmax 134 MBq); all other
exchange is first order. Tumor uptake carries a power effect of
segmented tumor volume (exponent 1.08), a structural decline over
treatment cycles (73%, 50% and 44% of the cycle-1 rate in cycles 2, 3
and 4-7), interindividual variability (63.4% CV) and interoccasion
variability across cycles (37.8% CV), and salivary-gland uptake carries
a weak tumor-volume power effect. All PK parameters are allometrically
scaled to the 79 kg median body weight. The PD layer is a single PSA
state growing exponentially (kG 0.000408 1/h) and eliminated by a direct
effect linear in the physical tumor activity concentration plus a
delayed effect linear in an effect-compartment concentration (ke0
0.00128 1/h). Baseline PSA is fixed at 140 ug/L with a linear
tumor-volume effect. Every state carries a decay-corrected radioactivity
amount, matching the source SPECT/CT data and the predecessor
[177Lu]Lu-PSMA-617 model. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Hietala_2010_artemether_lumefantrine_malaria.html">Lumefantrine
(Hietala 2010)</a> </td>
<td style="text-align:left;"> Population PK model for oral
lumefantrine (LUM) in 50 Tanzanian children (ages 1-10 years, weights
8-30 kg) with uncomplicated Plasmodium falciparum malaria treated with
the standard six-dose weight-based Coartem (artemether 20 mg +
lumefantrine 120 mg per tablet) regimen at 0, 8, 24, 36, 48, and 60
hours (Hietala 2010). One-compartment disposition with first-order
absorption preceded by an absorption lag time. The paper tested
co-administration with full-fat (3.4%) cow's milk as a categorical
covariate on the PK parameters of LUM; the effect did not improve the
model fit and is not encoded here (Discussion: 'the resulting number of
doses actually administered with an adequate amount of milk may have
been too small to allow the detection of a difference'). All PK
parameters are reported per kg body weight (linear weight normalisation
applied inside model()). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Hoglund_2015_artemether_lumefantrine.html">Lumefantrine
(Hoglund 2015)</a> </td>
<td style="text-align:left;"> Joint parent-metabolite
population PK model for oral lumefantrine and its major oxidative
metabolite desbutyl-lumefantrine in 89 HIV-infected Ugandan adults
receiving artemether-lumefantrine (Coartem) with or without concomitant
antiretroviral therapy (efavirenz, nevirapine, or lopinavir/ritonavir)
(Hoglund 2015). 1-transit-compartment absorption with ka = ktr feeds a
2-compartment lumefantrine disposition; complete in-vivo conversion of
lumefantrine to a 1-compartment desbutyl-lumefantrine disposition with
stoichiometric molar conversion. Relative bioavailability F is anchored
at 1 (fixed) with log-normal IIV (47.4 % CV). Three antiretroviral
drug-drug interactions are encoded as linear-deviation effects on parent
clearance and on bioavailability: efavirenz increases LF CL/F by 72.6 %,
lopinavir/ritonavir decreases LF CL/F by 62.1 % and increases
desbutyl-lumefantrine CL/F by 392 %, nevirapine decreases relative
bioavailability by 24.8 %. IIV is retained on LF CL, the mean transit
time, and the relative bioavailability F. NONMEM additive residual error
on log-transformed concentrations is encoded as a proportional residual
in linear concentration space for both parent and metabolite.
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Kay_2020_lumefantrine.html">Lumefantrine
(Kay 2020)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model for oral lumefantrine in 277 HIV- infected and HIV-uninfected
Ugandan children (3 months to ~10 years) with uncomplicated malaria
receiving artemether-lumefantrine alone or with concomitant ART
(efavirenz, lopinavir/ritonavir, or nevirapine) (Kay 2020, ASTMH poster
2167). First-order absorption (depot -> central) feeds a
2-compartment lumefantrine disposition (central + peripheral1).
Body-weight allometric scaling enters on all clearance and volume terms
with a fixed volume exponent of 1 and a piecewise age-dependent
clearance exponent (0.75 for age >60 mo, 0.9 for >24-60 mo, 1.0
for >3-24 mo, 1.2 for <=3 mo). Age also enters as a covariate on
relative bioavailability F (younger children have reduced F). Three ART
drug-drug interactions are encoded as linear- deviation effects on
apparent oral clearance CL/F and on first-order absorption KA:
efavirenz, lopinavir/ritonavir, and nevirapine. Diagonal IIV is retained
on CL/F, V2/F, Q/F, V3/F, and KA. The NONMEM additive-on-log-scale
residual is encoded as a proportional residual in linear concentration
space (consistent with the related Hoglund 2015 Ugandan-adult
lumefantrine model). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Kay_2022_lumefantrine.html">Lumefantrine
(Kay 2022)</a> </td>
<td style="text-align:left;"> Population PK model for oral
lumefantrine in 277 Ugandan children (186 HIV-uninfected, 178
HIV-infected on efavirenz-, nevirapine-, or lopinavir/ritonavir-based
antiretroviral therapy plus daily trimethoprim-sulfamethoxazole
prophylaxis) ages ~2 months to 8.6 years treated with six-dose
weight-based Coartem Dispersible (20 mg artemether + 120 mg lumefantrine
per tablet) for uncomplicated Plasmodium falciparum malaria (Kay 2022).
Two-compartment disposition with first-order absorption. Body-weight
fixed effects scale all clearance and volume terms with a reference
weight of 15 kg; volumes use an allometric exponent of 1, clearances use
an age-dependent exponent (1.2 for age <= 3 months, 1.0 for >3 to
24 months, 0.9 for >24 to 60 months, 0.75 for >60 months) from
Anderson & Holford 2009 (paper ref 34). A power-form age effect on
relative bioavailability captures reduced lumefantrine bioavailability
in young children (F = (age_months / 50)^0.204). Concomitant
antiretroviral therapy enters as mutually-exclusive linear-deviation
effects on apparent oral CL/F and ka: efavirenz increases CL/F by 98.2%
and ka by 48.4%, lopinavir/ritonavir decreases CL/F by 51.4% and ka by
21.2%, nevirapine has no statistically significant effect (both CIs
cross zero). Q/F IIV is fixed at 15.9% CV; the remaining four structural
parameters carry estimated log-normal IIV (104%, 112%, 127%, and 16.9%
CV for CL/F, V2/F, V3/F, and ka respectively). NONMEM proportional
residual error on linear concentration (sigma^2 = 0.200, 44.7% CV).
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Kloprogge_2013_lumefantrine.html">Lumefantrine
(Kloprogge 2013)</a> </td>
<td style="text-align:left;"> Population PK model for oral
lumefantrine in pregnant and non-pregnant women with uncomplicated
Plasmodium falciparum malaria in Uganda after the standard fixed-dose
oral artemether-lumefantrine treatment (Kloprogge 2013). Flexible
five-compartment transit absorption chain into a two-compartment
disposition model with relative bioavailability F1 fixed at 1,
log-normal IIV on CL / Vp / MTT / F, and covariate effects of pregnancy
on intercompartmental clearance (-36.5%, categorical) and body
temperature on mean absorption transit time (+16.5% per degC over
36.0-39.8 degC, linear-deviation centered at the cohort median 36.9
degC). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Kloprogge_2015_lumefantrine.html">Lumefantrine
(Kloprogge 2015)</a> </td>
<td style="text-align:left;"> Simultaneous parent +
active-metabolite (desbutyl-lumefantrine, DLF) population PK model for
oral lumefantrine in 116 pregnant women (second or third trimester) with
uncomplicated Plasmodium falciparum malaria on the Thailand-Myanmar
border treated with the standard fixed-dose artemether-lumefantrine
regimen (Kloprogge 2015). First-order absorption with lag time into a
two-compartment LF disposition with relative bioavailability F fixed at
1 and Box-Cox-transformed IIV on F (Box-Cox shape -0.394 not encoded --
see Errata); DLF is formed mole-for-mole from LF central elimination
(linear drug-metabolite chain, fraction metabolised assumed = 1) and
disposes through its own two- compartment chain with apparent CL/F = 197
L/h and Vc/F = 6,490 L. Retained covariates: estimated gestational age
(power on LF ka, linear-deviation on LF Q/F, both centered on the cohort
median 22.8 weeks) and admission parasitaemia (log10-exponential on DLF
CL/F, centered on cohort median log10(3,260) = 3.513). Venous-only
residual error encoded; capillary-residual variance components and
capillary conversion factors (LF 0.878, DLF 0.464) NOT encoded -- see
Errata. Time-to-event PD layer (Gompertz hazard with E_max LF effect on
recrudescent malaria, Table 4) NOT encoded -- see Errata. Parameter
values from Kloprogge 2015 Table 2. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Kloprogge_2018_lumefantrine.html">Lumefantrine
(Kloprogge 2018)</a> </td>
<td style="text-align:left;"> Population PK model for oral
lumefantrine in 1,347 patients (children, non-pregnant adults, and
second-/third-trimester pregnant women) from 26 studies in 12 African,
Oceanian, and Southeast Asian countries with uncomplicated Plasmodium
falciparum malaria treated with the standard fixed-dose
artemether-lumefantrine regimen (Kloprogge 2018 PLOS Medicine).
Two-compartment disposition with first-order absorption; F fixed at 1
with log-normal IIV (Box-Cox shape -0.343 on the F IIV departure from
log-normal not reproduced here -- see Errata); allometric scaling of
CL/F and Q/F (power 3/4) and of Vc/F and Vp/F (power 1) on body weight
centered at the model-building median 42 kg; dose-saturable absorption
on F with Dose50 = 3.86 mg/kg; exponential effect of log10 admission
parasitaemia on F centered at log10(15,800/uL) = 4.2 (coefficient -0.643
per log10 unit); proportional pregnancy effect on ka (+35.2% in second
and third trimester). IIV on Vc/F (CV 144%) and F (CV 70.3%); additive
log-scale residual SD 0.323. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Mosha_2014_artemether_lumefantrine.html">Lumefantrine
(Mosha 2014)</a> </td>
<td style="text-align:left;"> Population PK model for oral
lumefantrine in 33 pregnant (2nd or 3rd trimester) and 22 non-pregnant
women with uncomplicated Plasmodium falciparum malaria in Rufiji,
Tanzania after standard fixed-dose artemether-lumefantrine (Mosha 2014).
One-compartment disposition with first-order absorption and ka fixed at
0.54 1/h. Relative bioavailability F1 is fixed at 1 (structural anchor)
with a categorical pregnancy effect of -33% on F1 (linear-deviation
form) and log-normal IIV around the typical F1 (65% CV). The published
model used a logit transformation on individual F1 to constrain
individuals to (0, 1); this encoding uses log-normal IIV on F (matching
the established Kloprogge 2013 / 2018 lumefantrine precedents in
nlmixr2lib). Structural CL and Vc do not carry IIV in the final model;
the F1 IIV absorbs the joint CL/Vc variability via the AUC = D x F / CL
relationship. The desbutyl-lumefantrine (DLF) metabolite arm of the
published joint model is not encoded; see the validation vignette for
the rationale. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Simpson_2013_lumefantrine.html">Lumefantrine
(Simpson 2013)</a> </td>
<td style="text-align:left;"> In vitro (P. falciparum). Sigmoid
Emax inhibition model of lumefantrine effect on hypoxanthine uptake by
clinical Plasmodium falciparum isolates from the Thai-Myanmar border
(Shoklo Malaria Research Unit, 1993-2005), with pfmdr1 genotype
covariate effects on EC50. The 'subject' in the NLME framework is a
parasite isolate (n=324 isolates with lumefantrine data).
STIM_LUMEFANTRINE_NM is the per-well drug concentration in the in vitro
hypoxanthine-uptake-inhibition assay; the model has no PK and no time
evolution. E0 and Emax are fixed per Simpson 2013 Table 3 footnote.
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/VasquezBahena_2009_lumiracoxib_rat.html">Lumiracoxib
rat (VasquezBahena 2009)</a> </td>
<td style="text-align:left;"> Preclinical (rat).
Two-compartment population PK plus indirect-response PK/PD model for the
antinociceptive effect of oral lumiracoxib in carrageenan-induced
thermal hyperalgesia in female Wistar rats (Vasquez-Bahena 2009). PK:
first-order absorption with lag time and dose-dependent relative
bioavailability. PD: time-variant (gamma function) carrageenan-induced
COX-2 synthesis with first-order COX-2 degradation; lumiracoxib
reversibly inactivates COX-2 via a competitive binding model (COX-2_act
= KD * COX-2 / (KD + Cp)). The level of inflammatory mediators (MED)
equals the active COX-2 amount and drives the paw withdrawal latency
response LT = LT0 / (1 + MED). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/VelezdeMendizabal_2012_lumiracoxib_rat.html">Lumiracoxib
rat (VelezdeMendizabal 2012)</a> </td>
<td style="text-align:left;"> Preclinical (rat).
Semi-mechanistic PD model of the formalin-induced antinociceptive
response to lumiracoxib in adult female Wistar rats (Velez de Mendizabal
2012). No PK measurements were made: lumiracoxib was tracked through two
virtual compartments -- intraplantar local (lumxLocal) and intrathecal
central (lumxCns) -- each decaying monoexponentially at first-order
rates K_D_Local and K_D_CNS from a bolus equal to the administered dose
(10, 30, 100, or 300 ug per route). The biphasic formalin-induced
nociceptive response (flinch count per 1-min window) is modeled as the
sum of an early phase PN1, a monoexponential decay from an initial pain
load PN1_0 with rate K_PN1 (insensitive to lumiracoxib), and a delayed
phase PN2 built from upregulated COX-2 in the local and CNS
compartments. Both COX-2 species are taken proportional to a
pain-mediator signal MED whose time course is the analytical
Erlang-transit kernel of Savic 2007 (MED0 = 1; chain length NC = 6.5;
transit rate K_TR = 0.233 min^-1), and the proportionality constants
theta_COX2_L / theta_COX2_CNS scale MED to flinch units in the local and
CNS arms respectively. Lumiracoxib inhibits upregulated COX-2 in each
arm via E = 1 / (1 + LUMX) with an implicit IC50 of one dose unit (an
IC50 parameter was tested and found not significant). Model is the
second-pass selection (Table I of Velez de Mendizabal 2012); the IC50,
delayed-COX-2, and Emax variants were rejected during model development.
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Chen_2020_luspatercept.html">Luspatercept
(Chen 2020)</a> </td>
<td style="text-align:left;"> One-compartment population PK
model for luspatercept (activin receptor type IIB / IgG1 Fc-fusion) in
adults with anemia due to myelodysplastic syndromes (Chen 2020), with
first-order subcutaneous absorption, first-order linear elimination
parameterised in CL/F and V1/F, body weight + age + baseline albumin
power covariates on CL/F, and body weight + baseline albumin power
covariates on V1/F. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Xie_2000_m3g_rat.html">M3g
rat (Xie 2000)</a> </td>
<td style="text-align:left;"> Preclinical (rat, male
Sprague-Dawley). Blood-brain barrier (BBB) distributional model for
morphine-3-glucuronide (M3G) in rat as published by Xie et al. (2000, Br
J Pharmacol): a one-compartment plasma PK driven by an unbound systemic
clearance CL_u = 3.8 mL/min from the paper's Model A, coupled to a
two-compartment brain model (brain 1 = sampled brain extracellular fluid
via striatal microdialysis, brain 2 = deeper redistribution compartment)
with asymmetric BBB exchange (separate unbound influx CL_u,in and efflux
CL_u,out across the BBB) and a symmetric intercompartmental clearance
Q_br between the two brain compartments. The model captures a
probenecid-sensitive organic-anion transport contribution to BBB influx:
CL_u,in is 1.55-fold higher under co-administered probenecid
(CONMED_PROBENECID = 1) while CL_u,out, Q_br, and the two brain volumes
are unchanged. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Lignet_2023_m8891.html">M8891
human (Lignet 2023)</a> </td>
<td style="text-align:left;"> Predicted-human translational
PK/PD model for M8891, a selective and reversible methionine
aminopeptidase 2 (MetAP2) inhibitor. One-compartment oral PK whose
disposition (CL, Vss) is the mean of three preclinical-to-human scaling
methods and whose absorption rate constant ka comes from a GastroPlus
PBPK model, coupled to the effect-compartment plus Met-EF1a turnover PD
model estimated in Caki-1 xenograft-bearing mice. No human subjects were
dosed in this analysis; the model is the forward projection that was
used to select the M8891 dose for the Phase Ia study NCT03138538. PD
parameters are carried over unchanged from the mouse model on the
hypothesis that the same Met-EF1a modulation level is associated with
efficacy in humans. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Lignet_2023_m8891.html">M8891
mouse (Lignet 2023)</a> </td>
<td style="text-align:left;"> Preclinical (mouse, Caki-1
renal-carcinoma xenograft). One-compartment oral PK of M8891, a
selective and reversible methionine aminopeptidase 2 (MetAP2) inhibitor,
with first-order absorption and elimination, linked through an effect
compartment to a turnover model for the tumour target-engagement
biomarker Met-EF1a (uncleaved methionine-elongation-factor-1-alpha).
M8891 inhibits the first-order degradation of Met-EF1a, so the biomarker
accumulates above its kin/kout baseline. Naive-pooled fit (Phoenix
WinNonlin 6.4) to single-dose and 4-day repeated-dose PK/PD data at 10,
25, and 100 mg/kg p.o.; the authors report no inter-individual
variability because a nonlinear mixed-effects fit did not converge on
this dataset. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Betts_2018_mAb_linear_PK.html">MAb
combined (Betts 2018)</a> </td>
<td style="text-align:left;"> Preclinical + human. Class-level
typical two-compartment population PK model with body-weight allometric
scaling for monoclonal antibodies with linear clearance, jointly fitted
across human, cynomolgus monkey and hFcRn Tg32 mouse (Betts 2018
combined all-species dataset, n=27 mAbs). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Betts_2018_mAb_linear_PK.html">MAb
cyno (Betts 2018)</a> </td>
<td style="text-align:left;"> Preclinical (cynomolgus monkey).
Class-level typical two-compartment population PK model for monoclonal
antibodies with linear clearance in cynomolgus monkeys (Betts 2018, n=23
mAbs). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Betts_2018_mAb_linear_PK.html">MAb
human (Betts 2018)</a> </td>
<td style="text-align:left;"> Class-level typical
two-compartment population PK model for monoclonal antibodies with
linear clearance in adult humans (Betts 2018, n=18 mAbs). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Muliaditan_2025_mab_mpbpk.html">Mab
mpbpk human (Muliaditan 2025)</a> </td>
<td style="text-align:left;"> Human-scaled. Translational
minimal physiologically based pharmacokinetic (mPBPK) model for
transferrin-receptor (TfR) mediated brain delivery of monoclonal
antibodies, projected forward from the cynomolgus monkey fit
Muliaditan_2025_mab_mpbpk_nhp by replacing the Bloomingdale 2017 NHP
physiology with the human physiology (Muliaditan 2025 Supplementary
Table S1, human column), allometrically scaling the bsAb-TfR
internalization rate kint by (70/6.2)^(-0.25) = 0.546 (paper Methods:
standard rate-constant exponent -0.25), and recalibrating the luminal
BCSFB unbound TfR baseline uTFR0_BCSFB to be 3-fold higher than the NHP
estimate (0.256 -> 0.768 nM) per the paper Results. The other TfR-
related parameters (TfRpt, uTFR0_BBB, FACQ_BECF, TfRtotn, ktrans,
kdeg_uTfR_BBB, kdeg_uTfR_BCSFB, FACBR) are assumed identical to the NHP
estimates per paper Methods. Per-compound TfR binding parameters (kon_T,
koff_T) MUST be set per simulated antibody from biophysical measurements
(paper Table S2); the default ini() encodes kon_T = 0 (non-TfR control
IgG). For trontinemab in human, the paper reports KD,TfR = 131 nM
(versus 249 nM in NHP) with kon_T = 1.0548 nM^-1 h^-1 and koff_T =
138.24 h^-1 (Table S2, Grimm 2023 column for human). Clinical validation
in the paper was against single ascending doses 0.1-7.2 mg/kg IV
trontinemab in healthy human subjects (NCT04023994; Grimm 2023).
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Muliaditan_2025_mab_mpbpk.html">Mab
mpbpk nhp (Muliaditan 2025)</a> </td>
<td style="text-align:left;"> Preclinical (cynomolgus monkey).
Translational minimal physiologically based pharmacokinetic (mPBPK)
model for transferrin-receptor (TfR) mediated brain delivery of
monoclonal antibodies in non-human primates. 26-compartment NONMEM
ADVAN8 structure combining the Bloomingdale 2017 mAb mPBPK framework
(plasma, tissue vascular / endosomal / interstitial / FcRn, brain
vascular, BBB endosomal (unbound + FcRn-bound), brain ISF, BCSFB
endosomal (unbound + FcRn-bound), CSF, lymph, with FcRn recycling) and
the Chang 2022 whole-body-plasma + brain-vascular + ISF + neuronal TfR
binding with empirical TMDD-style elimination of the bsAb-TfR complex
(kint). Two TfR binding sites on the brain barriers (luminal BBB,
luminal BCSFB) transcytose bound complex into the abluminal side (brain
ISF and CSF respectively), where it may dissociate or be degraded.
Parameters were fit to 395 plasma, 81 CSF, and 102 brain mean
concentrations digitised from eight literature studies in cynomolgus
monkey (7 non-TfR mAbs + 10 anti-TfR bsAbs with KD,TfR 36-1900 nM). The
kint mixture (POP1 fast 0.0329 h^-1 fraction 0.437; POP2 slow 0.0125
h^-1) is selected per subject via the MIX_FAST_ELIM covariate (1 = POP1,
0 = POP2). Per-compound TfR binding parameters (kon_T, koff_T) are NOT
estimated population values - they are set per simulated antibody from
biophysical measurements (paper Table S2); the default ini() encodes
kon_T = 0 (non-TfR control IgG). Plasma observation is TOTAL drug (free
+ TfR-bound complex), CSF observation is unbound CBCSF, brain
observation is whole-brain homogenate (simplified volume-weighted
average across BBB + ISF + BCSFB endosomal spaces, scaled by the
estimated FACBR correction factor 0.05). No inter-individual variability
was estimated (dataset was mean digitised profiles). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Betts_2018_mAb_linear_PK.html">MAb
tg32mouse (Betts 2018)</a> </td>
<td style="text-align:left;"> Preclinical (hFcRn Tg32
transgenic mouse). Class-level typical two-compartment population PK
model for monoclonal antibodies with linear clearance in mice expressing
human neonatal Fc receptor (Betts 2018, n=11 mAbs). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Zheng_2012_minipig_mab.html">MAb1
(Zheng 2012)</a> </td>
<td style="text-align:left;"> Preclinical (Gottingen minipig).
Two-compartment population PK model for the non-disclosed humanized IgG
antibody mAb1 (Zheng 2012; pI 6.1) with first-order SC absorption and
linear central clearance in Gottingen minipigs (Table 1 population mean
parameter estimates). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Zheng_2012_minipig_mab.html">MAb2
(Zheng 2012)</a> </td>
<td style="text-align:left;"> Preclinical (Gottingen minipig).
Two-compartment population PK model for the non-disclosed humanized IgG
antibody mAb2 (Zheng 2012; pI 8.7; unusually fast systemic clearance in
minipig) with first-order SC absorption and linear central clearance in
Gottingen minipigs (Table 1 population mean parameter estimates).
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Zheng_2012_minipig_mab.html">MAb3
(Zheng 2012)</a> </td>
<td style="text-align:left;"> Preclinical (Gottingen minipig).
Two-compartment population PK model for the non-disclosed humanized IgG
antibody mAb3 (Zheng 2012; pI 9.1) with first-order SC absorption and
linear central clearance in Gottingen minipigs (Table 1 population mean
parameter estimates). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Zheng_2012_minipig_mab.html">MAb4
(Zheng 2012)</a> </td>
<td style="text-align:left;"> Preclinical (Gottingen minipig).
Two-compartment population PK model for the non-disclosed humanized IgG
antibody mAb4 (Zheng 2012; pI 9.3) with first-order SC absorption and
linear central clearance in Gottingen minipigs (Table 1 population mean
parameter estimates). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Zheng_2012_minipig_mab.html">MAb5
(Zheng 2012)</a> </td>
<td style="text-align:left;"> Preclinical (Gottingen minipig).
Two-compartment population PK model for the non-disclosed humanized IgG
antibody mAb5 (Zheng 2012; pI 9.4) with first-order SC absorption and
linear central clearance in Gottingen minipigs (Table 1 population mean
parameter estimates). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Zheng_2012_minipig_mab.html">MAb6
(Zheng 2012)</a> </td>
<td style="text-align:left;"> Preclinical (Gottingen minipig).
Two-compartment population PK model for the non-disclosed humanized IgG
antibody mAb6 (Zheng 2012; pI 9.2) with first-order SC absorption and
linear central clearance in Gottingen minipigs (Table 1 population mean
parameter estimates). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Zheng_2012_minipig_mab.html">MAb7
(Zheng 2012)</a> </td>
<td style="text-align:left;"> Preclinical (Gottingen minipig).
Two-compartment population PK model with first-order SC absorption plus
parallel linear and saturable (Michaelis-Menten) central elimination for
the non-disclosed humanized IgG antibody mAb7 (Zheng 2012; pI 8.9) in
Gottingen minipigs (Table 1 population mean parameter estimates).
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Zheng_2012_minipig_mab.html">MAb8
(Zheng 2012)</a> </td>
<td style="text-align:left;"> Preclinical (Gottingen minipig).
Two-compartment IV-only population PK model for the non-disclosed
humanized IgG antibody mAb8 (Zheng 2012; pI 8.7) with linear central
clearance in Gottingen minipigs (Table 1 population mean parameter
estimates). No SC arm was run for mAb8, so no Ka or F is defined.
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Easterling_2018_magnesium_sulfate.html">Magnesium
sulfate (Easterling 2018)</a> </td>
<td style="text-align:left;"> One-compartment population PK
model of magnesium sulfate (MgSO4-7H2O) with intravenous administration
and an endogenous baseline magnesium term added to the administered
drug, in pregnant women with severe preeclampsia comparing continuous IV
infusion vs serial IV bolus dosing (Easterling 2018). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Salinger_2013_magnesiumSulfate.html">MagnesiumSulfate
(Salinger 2013)</a> </td>
<td style="text-align:left;"> One-compartment population PK
model of magnesium sulphate (MgSO4-7H2O) with first-order intramuscular
absorption, IV dosing into the central compartment, and an endogenous
baseline magnesium term added to the administered drug, in pregnant
women with pre-eclampsia (Salinger 2013). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Chan_2008_maraviroc.html">Maraviroc
(Chan 2008)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
meta-analysis model for oral maraviroc (CCR5 antagonist) in healthy
volunteers and asymptomatic HIV-infected adults, with
hepatic-extraction-ratio parameterisation of clearance, dose-dependent
absorption (sigmoid-Emax F_ABS and power-function ka), food effect on
both, Asian-race covariates on hepatic extraction / peripheral volume /
inter-compartmental clearance, an age effect on Q, and a TAD-dependent
residual error (Chan 2008) </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Davis_2008_maraviroc.html">Maraviroc
(Davis 2008)</a> </td>
<td style="text-align:left;"> Concentration-QT mixed-effects
regression model relating single-dose oral maraviroc plasma
concentrations to individual heart-rate-corrected QT intervals in
healthy adult male and female volunteers (Davis 2008). No structural
pharmacokinetic component is fit: the model is the one-stage NONMEM
mixed-effects regression of observed QT on observed RR interval and
observed maraviroc plasma concentration (Cp), with a fractional
female-sex multiplier on the population QT intercept, a population QT/RR
correction-factor exponent (Fridericia-style), and a linear
concentration-QT slope. The single-dose population slope estimate (0.970
us mL/ng, 95% CI -0.571 to 2.48) was not significantly different from
zero across the studied concentration range up to 2363 ng/mL. For
simulation, supply observed or simulated maraviroc plasma concentration
as the time-varying covariate CP_MVC_NGML and the RR interval as RR.
Interoccasion variability on the QT intercept reported by the paper
(13.4 ms^2) is not encoded (Hong_2015_moxifloxacin precedent: nlmixr2lib
has no idiomatic IOV encoding for distributed models). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Rosario_2008_maraviroc.html">Maraviroc
(Rosario 2008)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model with first-order absorption and lag time for maraviroc (CCR5
antagonist) coupled with a direct Emax CCR5 receptor occupancy model in
healthy adults and HIV-1-positive patients (Rosario 2008). PK is
parameterised with dose-dependent relative bioavailability F1 and
dose-dependent elimination rate constant K across six dose groups (3,
10, 25, 100 (reference), 300 mg b.i.d. and 600 mg q.d.); receptor
occupancy on CD4 T cells is modelled as Occ = E0 + Emax * Cp / (KD + Cp)
with a background binding baseline. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Weatherley_2009_maraviroc_iv.html">Maraviroc
iv (Weatherley 2009)</a> </td>
<td style="text-align:left;"> Four-compartment IV maraviroc
population PK in 20 healthy young adult males receiving 3, 10, or 30 mg
as a 1-hour IV infusion (Weatherley & McFadyen 2009 Br J Clin
Pharmacol). NONMEM ADVAN7 + FOCE-I fit to log- transformed plasma
concentrations from study A4001009 only. Exponential inter-subject
variability on CL, V1, V2, Q3 and V3; proportional residual error
(additive on the log scale). No dose effect on clearance over the 3-30
mg range. This file extracts only the IV disposition analysis (paper
Analysis 1, Table 3); the paper's two companion analyses (sigmoid Emax
NAUC meta-regression of oral phase 1 data, and the S-PLUS closed-form
mass balance model) are not ODE PK models and are described in the
vignette but not implemented here. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Sun_2023_maribavir.html">Maribavir
(Sun 2023)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model for oral maribavir with first-order absorption, an absorption lag
time, and dose-dependent absorption rate in adult transplant recipients
with cytomegalovirus infection/disease (Sun 2023) </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Kuester_2008_matuzumab.html">Matuzumab
(Kuester 2008)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model for matuzumab (humanised anti-EGFR IgG1 monoclonal antibody) in
adults with advanced carcinoma (Kuester 2008), with parallel first-order
linear and Michaelis-Menten elimination from the central compartment;
body weight on linear CL and central volume. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Stein_2018_mAb_nonlinear_PK.html">Mavrilimumab
(Stein 2018)</a> </td>
<td style="text-align:left;"> Two-compartment QSS TMDD
typical-value fit for mavrilimumab (anti-GM-CSF receptor mAb) used to
illustrate the critical concentration (Ccrit) for nonlinear PK (Stein
and Peletier 2018 Table 1) </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Xu_2023_MBG453.html">MBG453
(Xu 2023)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model for sabatolimab (MBG453, anti-TIM-3 IgG4) with parallel linear and
Michaelis-Menten elimination from the central compartment, fit to pooled
adult patients with advanced solid tumors and hematologic malignancies
(Xu 2023). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Koumaki_2023_mecillinam.html">Mecillinam
(Koumaki 2023)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model for intravenous mecillinam (amdinocillin) in healthy adults, used
to determine systemic MIC breakpoints against Enterobacterales for
intermittent, extended, and continuous infusion regimens (Koumaki 2023).
CL, Q, Vc and Vp are parameterised per kilogram of body weight (linear
exponent 1, not allometric). The unbound concentration Cu = fu * Cc (fu
= 0.9, i.e. 10 percent protein binding) is the driver of the PK/PD
target fT>MIC >= 40 percent of the dosing interval used for
probability of target attainment. Parameters were obtained by MCMC
(Stan) reanalysis of published AGGREGATE concentration mean and SD data,
not individual-level data; no residual error was estimated. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Cao_2013_MEDI528.html">MEDI528
(Cao 2013)</a> </td>
<td style="text-align:left;"> Second-generation minimal
physiologically-based PK (mPBPK) model for MEDI-528 in adults (Cao 2013
Model A; clearance from plasma) </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Hood_2021_medi7836.html">Medi7836
(Hood 2021)</a> </td>
<td style="text-align:left;"> Population PK-PD binding model
for MEDI7836 (anti-IL13 IgG1 lambda-YTE mAb) in healthy adult males
(Hood 2021): two-compartment SC PK with first-order absorption,
ADA-on-CL covariate, plus IL13 turnover, fixed Kon/Koff binding to
MEDI7836:IL13 complex, complex distribution sharing CL/Q/V3 with parent
drug, and a serum PD observation modelled as the molar sum of free IL13
and a small fraction of complex. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Hoglund_2018_mefloquine.html">Mefloquine
(Hoglund 2018)</a> </td>
<td style="text-align:left;"> Population PK model for oral
mefloquine in Burmese adults with uncomplicated Plasmodium falciparum
malaria treated with the standard 3-day artesunate-mefloquine
combination (Hoglund 2018). One-transit-compartment absorption with ka =
ktr feeds a two-compartment disposition model. No covariates were
retained in the final model: body-weight allometric scaling (fixed
exponents 0.75 / 1.0), sex, admission parasitaemia, and validated
molecular markers of mefloquine and artemisinin resistance (pfmdr1,
pfcrt, atp6, pfk13) were tested in a step-wise covariate search but did
not significantly improve the model. Relative bioavailability F is
implicitly 1 (the paper tested adding an estimated F with IIV and
excluded it from the final model). NONMEM additive residual error on the
log-transformed observation is encoded here as a proportional residual
in the linear concentration space. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Ramharter_2019_mefloquine.html">Mefloquine
(Ramharter 2019)</a> </td>
<td style="text-align:left;"> Population PK model for the two
mefloquine enantiomers and their carboxy-metabolite carboxymefloquine
(CMQ) in pregnant African women receiving intermittent preventive
treatment for malaria (Ramharter 2019, MIPPAD trial, Gabon). Each parent
enantiomer ((+)-mefloquine = '_r' = (11R, 2'S); (-)-mefloquine = '_s' =
(11S, 2'R)) follows a two-compartment disposition with first-order oral
absorption. Carboxymefloquine ('_cmq') is formed molar 1:1 from both
parents via the apparent parent clearance and follows a two-compartment
disposition; its first-order clearance is autoinduced by CMQ plasma
concentration via a two-stage RNA + enzyme-pool turnover model
(precursor1 = enzymatic-RNA precursor pool, precursor2 = metabolizing
enzyme pool; both kdeg-driven, both at unit steady state in the absence
of CMQ; CMQ clearance scales linearly with precursor2). A shared
body-weight allometric exponent acts on the central volume of each
parent enantiomer (reference 55 kg). The split-dose IPTp regimen
(REGIMEN_SPLIT = 1: 7.5 mg/kg on two consecutive days) carries a small
(+5%) bioavailability increment relative to the single-dose regimen
(REGIMEN_SPLIT = 0: 15 mg/kg on day 1). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Simpson_2013_mefloquine.html">Mefloquine
(Simpson 2013)</a> </td>
<td style="text-align:left;"> In vitro (P. falciparum). Sigmoid
Emax inhibition model of mefloquine effect on hypoxanthine uptake by
clinical Plasmodium falciparum isolates from the Thai-Myanmar border
(Shoklo Malaria Research Unit, 1993-2005), with pfmdr1 genotype
covariate effects on EC50. The 'subject' in the NLME framework is a
parasite isolate (n=460 isolates with mefloquine data).
STIM_MEFLOQUINE_NM is the per-well drug concentration in the in vitro
hypoxanthine-uptake-inhibition assay; the model has no PK and no time
evolution. E0 and Emax are fixed per Simpson 2013 Table 3 footnote.
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Nath_2007_melphalan.html">Melphalan
(Nath 2007)</a> </td>
<td style="text-align:left;"> Two-compartment IV population PK
model for melphalan in paediatric blood or marrow transplant recipients
(Nath 2007). Structural CL is a linear additive function of body weight,
prior-carboplatin therapy, and 99mTc-DTPA-tracer-measured GFR; central
volume Vc is a linear additive function of body weight;
intercompartmental rate constants k12 and k21 are estimated directly
(not as Q/Vc and Q/Vp). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Nath_2010_melphalan.html">Melphalan
total (Nath 2010)</a> </td>
<td style="text-align:left;"> Two-compartment IV-infusion
population PK model for total plasma melphalan in adults with multiple
myeloma undergoing high-dose therapy and autologous stem-cell transplant
(Nath 2010); additive non-renal + renal CL with hematocrit, fat-free
mass, and creatinine-clearance covariates. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Nath_2010_melphalan.html">Melphalan
unbound (Nath 2010)</a> </td>
<td style="text-align:left;"> Two-compartment IV-infusion
population PK model for unbound (ultrafiltrate) plasma melphalan in
adults with multiple myeloma undergoing high-dose therapy and autologous
stem-cell transplant (Nath 2010); additive non-renal + renal CL with
hematocrit, fat-free mass, and creatinine-clearance covariates.
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Cao_2013_mepolizumab.html">Mepolizumab
(Cao 2013)</a> </td>
<td style="text-align:left;"> Second-generation minimal
physiologically-based PK (mPBPK) model for mepolizumab in adults (Cao
2013 Model A; clearance from plasma) </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Gebhard_2023_leukemia_maintenance_therapy.html">Mercaptopurine
(Gebhard 2023)</a> </td>
<td style="text-align:left;"> Oral 6-mercaptopurine (6MP)
population PK during maintenance therapy for childhood acute
lymphoblastic leukemia, predicting the erythrocyte
6-thioguanine-nucleotide concentration E-TGN (Gebhard 2023, model
PK^6MP_{mm,pop}). The plasma layer is a FIXED one-compartment model with
first-order absorption and a fixed bioavailability of 0.12, all taken
from the literature (Supplementary Table S2). A third compartment
carries 6-thioguanine nucleotides -- the active metabolites of 6MP --
inside red blood cells, filled by SATURABLE Michaelis-Menten influx
driven by the plasma 6MP concentration and drained by a first-order
efflux rate constant. V_mm and K_eff were estimated with IIV on 452
children with 4624 E-TGN observations (Table 3); K_mm was estimated as a
population-only parameter with no IIV, which is what the 'pop' subscript
of the model name denotes. Because every patient's record begins
mid-maintenance-therapy, the red-cell compartment is initialised at the
patient's first observed E-TGN value (covariate BL_TGN_RBC) rather than
at zero. Volumes are per m^2 body-surface area and doses are supplied in
umol/m^2, so BSA cancels and no BSA covariate is needed. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Hawwa_2008_mercaptopurine.html">Mercaptopurine
(Hawwa 2008)</a> </td>
<td style="text-align:left;"> Population PK / pharmacogenetic
model for oral 6-mercaptopurine (6-MP) and its two active intracellular
metabolites 6-thioguanine nucleotides (6-TGNs) and
6-methylmercaptopurine nucleotides (6-mMPNs) measured in erythrocytes
(RBCs) of 19 paediatric patients (n = 75 samples; 150 concentrations)
with acute lymphoblastic leukaemia receiving maintenance chemotherapy at
a target oral dose of 75 mg/m^2/day. The structural model is a
one-compartment first-order absorption + first- order elimination model
for 6-MP whose plasma concentration is NOT observed; transformation of
bioavailable 6-MP into the two RBC metabolites occurs at a common
metabolic rate constant kme = 0.78 * k20 (78% of total 6-MP
elimination), with the fractional split between metabolites governed by
FM3 (the fractional metabolic transformation of 6-MP into 6-TGNs; the
complementary fraction 1 - FM3 goes to 6-mMPNs). The fixed structural
anchors ka = 1.3 1/h, F = 0.22, k20 = 0.53 1/h, and the kme : k20 ratio
of 0.78 are taken from the prior 6-MP literature (Hawwa 2008 cites Zimm
1983 and Lennard 1990; values listed in Methods page 4 of the British
Journal of Clinical Pharmacology article). The apparent distribution
volume of 6-MP central and of each metabolite compartment is not
identifiable from the RBC sampling design and is fixed to 1 L by the
ADVAN6 implementation convention used by Hawwa 2008 (analogous to Urien
2005 capecitabine; see vignette Errata for the dimensional-analysis
discussion). The only estimated structural parameters are FM3, CL_6TGNs,
and CL_6mMPNs; the only retained covariates are TPMT genotype (any
TPMT*3* mutation, pooled binary) on FM3 (theta = 2.56) and body surface
area (m^2) on the apparent clearance of 6-TGNs as a power-law (theta =
1.16, anchored to BSA = 1 m^2). IIV is estimated only on the two
metabolite clearances; no IIV on FM3 was estimable. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Gebhard_2023_leukemia_maintenance_therapy.html">Mercaptopurine
anc (Gebhard 2023)</a> </td>
<td style="text-align:left;"> Joint PK/PD model of oral
6-mercaptopurine (6MP) myelosuppression during maintenance therapy for
childhood acute lymphoblastic leukemia (Gebhard 2023, final model
PKPD^6MP_{lin,mm}). This is the paper's headline model. A FIXED
one-compartment plasma layer with first-order absorption feeds a
red-cell compartment holding 6-thioguanine nucleotides (E-TGN) via
SATURABLE Michaelis-Menten influx; the red-cell concentration then
drives a linear effect function Edrug = slope * E-TGN that suppresses
the proliferation rate of a Friberg-style myelosuppression chain
(proliferating pool, three transit compartments, circulating
neutrophils) with power-law rebound feedback (base / ANC)^gamma. Because
every patient's record begins mid-maintenance-therapy rather than at
drug-free baseline, the red-cell compartment is initialised at the
patient's first observed E-TGN (covariate BL_TGN_RBC) and the Friberg
chain is initialised at a treatment steady state scaled by an estimated
fraction-of-baseline parameter inieff. Estimated on 452 children with
4624 E-TGN and 9808 ANC observations (Table 5, whole-data-set column).
Two outputs: E-TGN (umol/L) and ANC (G/L). Volumes are per m^2
body-surface area and doses are supplied in umol/m^2, so BSA cancels and
no BSA covariate is needed. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Bergen_2017_meropenem.html">Meropenem
(Bergen 2017)</a> </td>
<td style="text-align:left;"> In vitro (hollow-fiber infection
model). Mechanism-based PK/PD (life-cycle growth) model of meropenem
bacterial killing and resistance against Pseudomonas aeruginosa 1280
(meropenem MIC 0.25 mg/L) across simulated critically ill patient
renal-function profiles (augmented renal clearance, normal, and
impaired). The bacterial population is split into three pre-existing
subpopulations of decreasing meropenem susceptibility (susceptible,
intermediate, resistant), each described by two states (state 1
preparing for replication, state 2 immediately before replication; six
bacterial compartments total). Meropenem acts via inhibition of
successful bacterial replication (a Hill-type Inh_Rep function per
subpopulation; no direct killing term). The intermediate and resistant
subpopulations have higher IC50_Rep and steeper or shallower Hill
coefficients than the susceptible subpopulation; the susceptible
subpopulation has Imax_Rep and Hill fixed to 1. Meropenem disposition in
the HFIM is a fixed-half-life first-order decline parameterised from the
upstream popPK model (Mattioli 2016, reference 20 in the source paper);
the default half-life is 1.1 h (normal renal function); 0.6 h (augmented
renal clearance) and 4.0 h (impaired renal function) are obtained by
overriding thalf_mem at simulation time. No patient covariates and no
random effects: this is the typical-value MBM fit (Bergen 2017 Table 3)
to the simultaneous P. aeruginosa 1280 HFIM data across the three
renal-function scenarios and four dosing regimens (2, 1, or 0.5 g q8h
plus 1 g q12h for impaired). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Fukumoto_2023_meropenem.html">Meropenem
(Fukumoto 2023)</a> </td>
<td style="text-align:left;"> Two-compartment IV population PK
model for meropenem in 31 adults with sepsis in a Japanese emergency
center / ICU (Fukumoto 2023). Clearance scales as a power function of
the BSA-normalized MEASURED creatinine clearance obtained from an 8-hour
timed urine collection, CL = 13.6 * (CRCL / 87.6)^0.66 L/h, centered on
the cohort-median 87.6 mL/min/1.73 m^2. The measured CCr was the single
retained covariate and outperformed Cockcroft-Gault CCr and eGFR, which
underestimate renal function in septic patients with normal or augmented
renal clearance. Interindividual variability was estimated on CL and V1
only; the random effects on Q and V2 were fixed at zero. Residual error
is proportional. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Germovsek_2018_meropenem.html">Meropenem
(Germovsek 2018)</a> </td>
<td style="text-align:left;"> One-compartment plasma + CSF
(two-state) IV population PK model for meropenem in neonates and young
infants (<=90 days) with late-onset sepsis and/or meningitis
(Germovsek 2018; NeoMero-1 and NeoMero-2 studies). Plasma CL and Vc are
allometrically scaled to body weight (fixed exponent 0.632 on CL, 1.0 on
Vc) with a fixed Rhodin-style postmenstrual-age maturation Hill function
on CL and a power covariate of (CREAT_REF / CREAT) on CL; an additional
CSF compartment with fixed Vcsf = 0.15 L/70 kg and estimated
inter-compartmental clearance CL_CSF carries a logit-scale CSF
penetration fraction (typical 8.4 %) modulated by CSF total protein
concentration. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Hanberg_2018_meropenem.html">Meropenem
(Hanberg 2018)</a> </td>
<td style="text-align:left;"> Two-compartment IV population PK
model for meropenem in critically ill adults receiving venovenous or
venoarterial extracorporeal membrane oxygenation (ECMO) treatment, with
simultaneous fitting of plasma concentrations (central compartment
Ac/Vc) and free subcutaneous adipose-tissue (SCT) concentrations sampled
by microdialysis (peripheral compartment Ap/Vp scaled by an estimated
fraction unbound in tissue f_u,tissue = 0.79). Elimination clearance is
a direct linear function of the patient's estimated creatinine clearance
(eCLCr, Cockcroft-Gault, raw mL/min) via CL_i = CLfrac * eCLCr_i with
CLfrac = 0.0460 L/h per (mL/min); 9 of 10 patients were also on
continuous renal replacement therapy so eCLCr partly reflects the CRRT
contribution (Hanberg 2018). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Kim_2024_meropenem.html">Meropenem
(Kim 2024)</a> </td>
<td style="text-align:left;"> Two-compartment intravenous
population PK model for meropenem in healthy Korean adults with normal
renal function (Kim 2024; n = 12, 84 plasma samples after a single 500
mg 30-min IV infusion). Total clearance depends on serum creatinine
through a power model centred at the cohort median 0.86 mg/dL: CL = 12.4
* (CREAT/0.86)^-0.392 L/h, so CL falls from 14.3 L/h at CREAT = 0.6
mg/dL to 11.7 L/h at CREAT = 1.0 mg/dL. Because the estimated
correlation between the random effects on CL and Vc was 0.99, the paper
codes a SINGLE eta shared by both parameters, with the Vc random effect
constructed as 1.53 * eta_CL (Table 2 'V1' row under interindividual
variability). Interindividual variability on Q and Vp is fixed, not
estimated. Residual error is proportional. The unbound concentration Cu
= fu * Cc (fu = 0.98) is the driver of the fT>MIC PK/PD targets (40%
fT>MIC, 40% fT>4MIC, 100% fT>MIC, 100% fT>4MIC) used in the
paper's Monte Carlo probability-of-target-attainment simulations for
intermittent, 3-h extended, and continuous infusion regimens.
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Padari_2012_meropenem.html">Meropenem
(Padari 2012)</a> </td>
<td style="text-align:left;"> One-compartment IV population PK
model for meropenem in very-low-birth-weight neonates (gestational age
<=32 weeks, birth weight <1,500 g; n=19; Padari 2012). Vss scales
linearly with current body weight; CL follows the Rhodin (2009) fixed
renal-maturation function (allometric exponent 0.75 on CL, Hill-type
postmenstrual-age maturation with TM50 = 47.7 weeks and Hill = 3.4);
serum creatinine, postnatal age, and gestational age were screened and
did not improve fit and are not retained. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Shekar_2014_meropenem.html">Meropenem
(Shekar 2014)</a> </td>
<td style="text-align:left;"> Two-compartment IV population PK
model for meropenem in critically ill adult patients on extracorporeal
membrane oxygenation (ECMO) and historical critically ill control
patients with sepsis, with a piecewise covariate on clearance that
switches between a fixed RRT-cohort CL and a Cockcroft-Gault-CrCL-driven
non-RRT CL (Shekar 2014) </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Ulldemolins_2015_meropenem.html">Meropenem
(Ulldemolins 2015)</a> </td>
<td style="text-align:left;"> One-compartment IV population PK
model for meropenem in 30 critically ill adults with septic shock and
continuous renal replacement therapy (Ulldemolins 2015). Clearance is
the sum of a constant CRRT-mediated baseline (3.68 L/h at zero residual
diuresis) and an additive linear contribution from 24-hour residual
diuresis (0.22 L/h per 100 mL/24h); central volume scales with body
weight by power exponent 2.07 around the population-median 73 kg. CRRT
intensity, blood flow, filter type, and serum albumin were tested but
not retained. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Wittau_2015_meropenem.html">Meropenem
(Wittau 2015)</a> </td>
<td style="text-align:left;"> Two-compartment intravenous
population PK model for meropenem in morbidly obese adults (Wittau
2015). Allometric scaling on fat-free mass with a reference FFM of 53
kg. Unbound meropenem concentrations in subcutaneous tissue and
peritoneal fluid are described as the plasma concentration multiplied by
the site-to-plasma AUC ratios FSC and FPF (the final model assumed very
rapid equilibration with plasma, so SC and PF are not carried as
separate ODE states). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Rees_2018_meropenem_ciprofloxacin.html">Meropenem
ciprofloxacin (Rees 2018)</a> </td>
<td style="text-align:left;"> In vitro (hollow-fiber infection
model). Mechanism-based PK/PD (life-cycle growth) model of bacterial
killing and resistance for meropenem plus ciprofloxacin against
hypermutable Pseudomonas aeruginosa CW44, with three pre-existing
subpopulations and subpopulation plus mechanistic synergy </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Yang_2024_meropenem_pbpk.html">Meropenem
pbpk (Yang 2024)</a> </td>
<td style="text-align:left;"> PBPK-derived reduced
one-compartment model for meropenem in critically ill (severe pneumonia
with or without sepsis) adult Asian ICU patients. The source paper built
an 18-tissue whole-body PBPK model in PK-Sim v11.2 for healthy adults
and extrapolated it to critically ill patients by scaling albumin,
alpha-1-acid glycoprotein, hematocrit and GFR; that whole-body structure
is a PK-Sim platform model whose ODEs, organ volumes, blood flows and
partition coefficients are NOT written out in the publication and are
therefore not reproduced here. What IS fully reported, and is what this
file encodes, is the reduced disposition model the authors carried out
of the PBPK and into their Monte Carlo target-attainment analysis: Vd
23.21 L, CL 12.07 L/h and unbound fraction 0.98 for Asian patients with
severe infection (Results, Monte Carlo simulations). Intravenous
infusion dosing; linear elimination; no covariates. The PK/PD index is
the fraction of the dosing interval during which the free concentration
exceeds the MIC (f%T>MIC), with 40%fT>MIC as the primary target
and 100%fT>MIC as a stricter alternative; f%T>MIC is computed from
the simulated profile rather than integrated as a model state, following
the Minichmayr_2024_ceftaroline precedent. Interindividual variability
was assumed lognormal on Vd and CL in the Monte Carlo but its magnitude
is not reported anywhere in the paper or its supplement, so both etas
are encoded as fixed(0); no residual error model was reported.
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/LopezArguello_2023_pbp_binding_pseudomonas.html">Meropenem
qsp (LopezArguello 2023)</a> </td>
<td style="text-align:left;"> QSP. In vitro (Pseudomonas
aeruginosa PAO1). Whole-cell penicillin-binding protein (PBP)
covalent-binding model for meropenem (carbapenem): seven coupled ODEs
for the rate of net influx of drug across the outer membrane into
periplasm and the competitive, mass-balanced acylation of six PBPs (1a,
1b, 2, 3, 4, 5/6) counted as molecules per bacterial cell. The intact
parameter switches between the intact whole-cell assay
(penetration-limited; drug enters periplasm at Rate_Influx/access) and
the lysed isolated-membrane assay (no outer membrane; a vast excess of
drug molecules is present at time 0). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Landersdorfer_2018_meropenem_tobramycin.html">Meropenem
tobramycin PAO1 (Landersdorfer 2018)</a> </td>
<td style="text-align:left;"> In vitro (Pseudomonas aeruginosa
PAO1 wild-type). Mechanism-based PK/PD (life-cycle growth) model of
bacterial killing and resistance for meropenem plus tobramycin, with
three pre-existing subpopulations (susceptible,
MEM-resistant/TOB-intermediate, MEM-intermediate/TOB-resistant) and
mechanistic synergy via tobramycin-induced outer-membrane
permeabilisation of meropenem </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Landersdorfer_2018_meropenem_tobramycin.html">Meropenem
tobramycin PAOmutS (Landersdorfer 2018)</a> </td>
<td style="text-align:left;"> In vitro (Pseudomonas aeruginosa
PAOdelta-mutS hypermutable strain). Mechanism-based PK/PD (life-cycle
growth) model of bacterial killing and resistance for meropenem plus
tobramycin, with three pre-existing subpopulations (susceptible,
MEM-resistant/TOB-intermediate, MEM-intermediate/TOB-resistant) and
mechanistic synergy via tobramycin-induced outer-membrane
permeabilisation of meropenem </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Chae_2012_metformin.html">Metformin
(Chae 2012)</a> </td>
<td style="text-align:left;"> One-compartment population PK
model with first-order absorption for oral metformin in healthy Korean
adults, coupled to a three-transit Sun-Jusko signal-transduction PD
model for the antihyperglycaemic effect (Chae 2012). Plasma drug
concentration in the central compartment drives a Hill-type stimulation
function DR = Emax * Cp^r / (EC50^r + Cp^r) that initiates a cascade of
three secondary-messenger transit compartments (M1 -> M2 -> M3)
with shared mean transit time tau. The third messenger M3 is the
measured percent change in plasma glucose from baseline relative to a
sugar-bolus control arm. Creatinine clearance enters CL/F as a power
covariate with reference 106.5 mL/min and exponent 0.782. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Choi_2018_metformin.html">Metformin
(Choi 2018)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model for oral metformin in 36 healthy adult Korean men from a phase I
single-dose 2-way crossover bioequivalence study comparing a
single-agent metformin tablet against a metformin-containing fixed-dose
combination (FDC) tablet (Choi 2018). The absorption process is parallel
mixed-input: fraction F1 of the dose is absorbed first-order from the
depot compartment (rate Ka), and fraction (1-F1) is absorbed zero-order
directly into the central compartment over duration D2 with lag time
ALAG2. Formulation enters as a binary covariate (FORM_FDC) with
multiplicative power-style effects on Ka (Ka_FDC = 0.83 *
Ka_single-agent) and on relative bioavailability F (F_FDC = 0.94 *
F_single-agent = 0.94). IIV on CL/F, Vc/F (correlated, rho 0.225), and
Ka; proportional residual error only. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/vanRongen_2018_metformin.html">Metformin
(vanRongen 2018)</a> </td>
<td style="text-align:left;"> One-compartment population PK
model for oral metformin in 22 overweight and obese Caucasian
adolescents (van Rongen 2018). First-order absorption into a single
central compartment with apparent oral clearance (CL/F) and apparent
oral volume of distribution (V/F). Total body weight (TBW) enters
linearly on CL/F with reference 75.8 kg (study median): CL/F = 1.17 * (1
+ 0.0138 * (TBW - 75.8)) L/min. Proportional residual error; IIV on
CL/F, V/F, and ka. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Yoon_2013_metformin.html">Metformin
(Yoon 2013)</a> </td>
<td style="text-align:left;"> One-compartment population
pharmacokinetic model with first-order oral absorption and an
absorption-lag time for a single 500 mg oral dose of metformin in
healthy Korean male adults (Yoon 2013). Body weight enters V/F as a
linear-in-deviation covariate; two organic-cation-transporter (OCT)
genetic polymorphisms enter CL/F as multiplicative fractional shifts,
OCT2 c.808G>T (SLC22A2, A270S, widely known as rs316019) and OCTN1
c.917C>T (SLC22A4, T306I). Variant carriers are pooled (heterozygotes
and homozygous variants together vs the homozygous wild-type reference)
per the source paper's dominant-model encoding. Slow first-order
absorption (ka = 0.248 1/h) relative to elimination (kel = cl/vc = 1.21
1/h) produces the apparent flip-flop kinetics reported for metformin.
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Gebhard_2023_leukemia_maintenance_therapy.html">Methotrexate
(Gebhard 2023)</a> </td>
<td style="text-align:left;"> Low-dose oral methotrexate (MTX)
population PK during maintenance therapy for childhood acute
lymphoblastic leukemia, predicting the erythrocyte methotrexate
concentration E-MTX (Gebhard 2023, model PK^MTX_{fix,bio,lin,peri}). The
plasma layer is a FIXED two-compartment model with first-order
absorption whose parameters were taken from the literature
(Supplementary Table S1) and a saturable dose-dependent bioavailability
F = 1 - 0.77 * D / (15.01 + D) with D the MTX dose in mg/m^2. A fourth
compartment carries methotrexate (predominantly methotrexate
polyglutamates) inside red blood cells, filled by LINEAR influx driven
by the PERIPHERAL plasma concentration and drained by a first-order
efflux rate constant; both red-cell rate constants were estimated on 452
children with 4192 E-MTX observations (Table 2) and carry IIV. Because
every patient's record begins mid-maintenance-therapy, the red-cell
compartment is initialised at the patient's first observed E-MTX value
(covariate BL_MTX_RBC) rather than at zero. Volumes are per m^2
body-surface area and doses are supplied in umol/m^2, so BSA cancels and
no BSA covariate is needed. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Joerger_2006_methotrexate.html">Methotrexate
(Joerger 2006)</a> </td>
<td style="text-align:left;"> Population PK model for
methotrexate (MTX) and its principal circulating metabolite
7-hydroxy-methotrexate (7-OH-MTX) in adult cancer patients receiving
high-dose intravenous MTX therapy (Joerger 2006). Joint parent +
metabolite model: linear 3-compartment MTX (central + two peripheral
compartments) with first-order elimination from the central compartment,
feeding a linear 2-compartment 7-OH-MTX disposition through a fixed
metabolic fraction of 10 percent. Additive-linear covariate effects of
baseline creatinine clearance (Cockcroft-Gault, raw mL/min, truncated at
140), concurrent benzimidazole-class proton-pump-inhibitor comedication,
and prior NSAID administration on both MTX and 7-OH-MTX total clearance.
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Olivo_2024_methotrexate.html">Methotrexate
(Olivo 2024)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model for high-dose intravenous methotrexate (12 g/m^2 over a 4 h
infusion) in Brazilian paediatric patients with osteosarcoma treated on
the Brazilian Osteosarcoma Treatment Group (BOTG) protocol (Olivo 2024;
n = 32 patients, 216 cycles, 563 therapeutic-drug-monitoring
concentrations). Linear first-order elimination from the central
compartment. Serum creatinine scales clearance as a power function
normalized to the cohort median 0.58 mg/dL (exponent -0.192), and body
surface area scales the central volume as a power function normalized to
the cohort median 1.45 m^2 (exponent 0.301). Correlated exponential
between-subject variability on CL and Vc (correlation 94%), exponential
between-occasion variability on CL shared across MTX cycles, and a
proportional residual error. Built to anticipate leucovorin (folinic
acid) rescue dose adjustments before the first monitored MTX
concentration. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Ruhs_2012_methotrexate.html">Methotrexate
(Ruhs 2012)</a> </td>
<td style="text-align:left;"> PK/PD model of methotrexate (MTX)
and homocysteine (HCY) after high-dose MTX treatment in children with
acute lymphoblastic leukemia (Ruhs 2012). Two-compartment IV PK for MTX
with linear BSA scaling on CL, V1, Q, V2 (theta values reported per m^2
BSA in the paper) and a power effect of the age- and gender-adjusted
serum creatinine ratio (CREAT_REF / CREAT) on CL (Eq. 1); coupled to a
single-compartment indirect response model for HCY where MTX inhibits
the HCY elimination rate kout via an inverse Emax function (Emax fixed
to 1) and the typical HCY baseline depends linearly on age. IOV reported
in the paper on CL (17.15% CV) and HCYBL (23.83% CV) across the window
and four consolidation HDMTX administrations is not encoded in the model
file (only between-subject IIV is carried). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Taylor_2020_methotrexate.html">Methotrexate
(Taylor 2020)</a> </td>
<td style="text-align:left;"> Three-compartment population PK
model for intravenous high-dose methotrexate (5 or 8 g/m^2 over 24 h IV
infusion) in pediatric NOPHO ALL2000 / ALL2008 patients with acute
lymphoblastic leukemia; BSA-normalized PK parameters (reference 1.73
m^2) and a time-varying serum creatinine power effect on clearance
(reference 29 umol/L) implemented as the default population PK model
behind the MTXPK.org clinical decision support tool (Taylor 2020)
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Saleh_2023_leicns_pk30_mouse_brain.html">Methotrexate
mouse pbpk (Saleh 2023)</a> </td>
<td style="text-align:left;"> PBPK (LeiCNS-PK3.0 CNS
physiologically-based model, mouse version). Preclinical (mouse, CD1
nude). Nine-compartment CNS PBPK model predicting unbound methotrexate
concentrations in brain extracellular fluid (brain ECF) after a single
1000 mg/kg intravenous dose. The CNS structure is the mouse
re-parameterisation of LeiCNS-PK3.0: brain microvasculature
(brain_vascular), brain ECF, a phospholipid brain-cell-membrane binding
compartment (brain_cell_membrane), brain intracellular fluid
(brain_icf), lysosomes (brain_lysosome), and the four CSF compartments
(lateral ventricles, third + fourth ventricles, cisterna magna,
subarachnoid space) draining in series back to plasma. Transport across
the BBB and BCSFB is the sum of a paracellular clearance (Qp, charged +
neutral drug) and a transcellular clearance (Qt, neutral drug only,
scaled by pH-dependent neutral fractions PHF and by asymmetry factors AF
that encode active transport). Every CNS parameter is fixed to mouse
physiology (Table III) or derived from the drug's physicochemical
properties (Table I); none was fitted here. The BBB asymmetry factors
are back-calculated from Kp,uu,BBB = 0.195 (estimated by the authors;
Table V). The plasma PK model is the empirical two-compartment model of
Table IV (in-house NONMEM fit) and acts purely as a forcing function:
brain uptake does not deplete plasma, exactly as published. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Billard_1995_methoxsalen.html">Methoxsalen
blood (Billard 1995)</a> </td>
<td style="text-align:left;"> Three-compartment intravenous
population PK model for 8-methoxypsoralen (8-MOP, methoxsalen) whole
blood concentrations in healthy adult volunteers receiving 5/10/15 mg
over 60 min (Billard 1995) </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Billard_1995_methoxsalen.html">Methoxsalen
plasma (Billard 1995)</a> </td>
<td style="text-align:left;"> Three-compartment intravenous
population PK model for 8-methoxypsoralen (8-MOP, methoxsalen) plasma
concentrations in healthy adult volunteers receiving 5/10/15 mg over 60
min (Billard 1995) </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Teuscher_2015_methylphenidate.html">Methylphenidate
(Teuscher 2015)</a> </td>
<td style="text-align:left;"> Pediatric population PK model for
methylphenidate hydrochloride extended-release multilayer beads
(MPH-MLR, Aptensio XR) after a single oral dose, parameterized as a
two-input, one-compartment, first-order-elimination structure: a
fast-release (IR) depot delivers a fraction F1 of dose with first-order
absorption rate Ka1, a slow-release (ER) depot delivers the remaining 1
- F1 with first-order rate Ka2 after an absorption lag tlag, and the
central compartment eliminates linearly via clearance CL and apparent
volume V. Body weight enters CL via a power covariate CL = CL_TV *
WT^theta (Eq 4). Between-individual variability is retained on CL and V;
IIV on Ka1, Ka2, F1, and tlag was not in the final pediatric fit (Table
1). The companion exposure-response analysis maps simulated Cmax to
change-from-baseline ADHD-RS-IV total score via the Emax model E = Emax
* Cmax / (EC50 + Cmax) with Emax = -34.96 and EC50 = 5.77 ng/mL (Table
2); the PD step lives outside the ODE system because the published
mapping uses a per-period Cmax, not the instantaneous central
concentration. The vignette reproduces the full PK simulation, NCA, and
Cmax-to-ADHD-RS-IV exposure-response. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Eugene_2016_metoprolol.html">Metoprolol
(Eugene 2016)</a> </td>
<td style="text-align:left;"> One-compartment population PK
model for oral metoprolol tartrate with first-order absorption and lag
time in elderly inpatients with multiple comorbidities; sex as the only
covariate on apparent clearance (Eugene 2016). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/CohenWolkowiez_2012_metronidazole.html">Metronidazole
(CohenWolkowiez 2012)</a> </td>
<td style="text-align:left;"> One-compartment IV population PK
model for metronidazole in preterm infants (Cohen-Wolkowiez 2012).
Clearance scales linearly with body weight (reference 1.5 kg) and as a
power function of postmenstrual age (reference 32 weeks); central volume
scales linearly with body weight. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Suyagh_2011_metronidazole.html">Metronidazole
(Suyagh 2011)</a> </td>
<td style="text-align:left;"> One-compartment population PK
model for intravenous metronidazole in 32 preterm neonates receiving
treatment of or prophylaxis against necrotising enterocolitis, with
dried-blood-spot HPLC sampling (Suyagh 2011). Clearance is described by
an allometric 3/4-power scaling on body weight (reference 1.0 kg) and a
linear postmenstrual- age maturation term centred at 30 weeks; volume of
distribution is proportional to body weight. The publication is open
access only at the abstract level, so inter-individual variability on CL
and V and the residual-error magnitude are FIXED at 0 here; users
running stochastic VPCs must supply their own variability terms (see the
validation vignette's Errata section). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Clinckers_2008_MHD_rat.html">MHD
rat (Clinckers 2008)</a> </td>
<td style="text-align:left;"> Preclinical (rat). Population PK
model for 10,11-dihydro-10-hydroxy- carbamazepine (MHD), the active
metabolite of oxcarbazepine, in male Wistar rat plasma and hippocampal
extracellular fluid (Clinckers 2008). One-compartment central
disposition (V2) with combined zero-order (fraction F1 of dose over
duration D2) and lagged first-order (1 - F1, ka with lag ALAG1)
absorption after intraperitoneal bolus, coupled to a biophase / effect
compartment (V3) reached via inter-compartmental rate constants k23 and
k32. Acute focal pilocarpine-induced seizure activity and local
intrahippocampal verapamil (efflux-transporter blockade) each shrink the
biophase volume (V3a -> V3b under seizure; V3a -> V3c under
verapamil); plasma kinetics are unaffected. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Zou_2012_MI_219.html">MI
219 (Zou 2012)</a> </td>
<td style="text-align:left;"> Predicted-human two-compartment
IV PK model for MI-219 (a small-molecule HDM2/p53 inhibitor) in adults,
with parameters projected from NONMEM-based interspecies allometric
scaling of single-dose IV plasma profiles in rats (5 mg/kg), beagle dogs
(2 mg/kg), and cynomolgus monkeys (10 mg/kg). Linear elimination from
the central compartment; mouse data were excluded from the joint NONMEM
fit because the mouse profile was not superimposable on the other
species under Wajima / Dedrick normalisation. The model file encodes the
predicted human typical values at a 70 kg reference body weight (Zou
2012 Table 5, NONMEM column). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Leroux_2018_fluconazole_micafungin.html">Micafungin
(Leroux 2018)</a> </td>
<td style="text-align:left;"> One-compartment population PK
model of intravenous micafungin in preterm and term neonates with
suspected or proven systemic candidiasis (Leroux 2018), with linear
current-weight scaling of CL and V. Typical-value structural model only:
the source paper and Data S1 supplement (goodness-of-fit plots only) do
not report inter-individual variability magnitudes, residual error
structure, or the functional form / coefficient of the
corrected-gestational-age effect on CL that the paper mentions, so IIV
and RUV are encoded as fixed(0) and the CGA covariate is omitted. See
vignette Errata. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Martial_2017_micafungin.html">Micafungin
(Martial 2017)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model for IV micafungin in adult intensive-care-unit patients with
suspected or proven fungal infection (Martial 2017). Body-weight
allometric scaling (fixed exponents 0.75 on CL and Q, 1 on V1 and V2; 70
kg reference), log-normal IIV on CL and V1 (encoded as diagonal; the
source reports a qualitative non-zero correlation but no numerical
covariance), and a proportional residual error. No covariates were
retained in the final model (only weight via the a-priori allometric
structure). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Beredaki_2023_micafungin.html">Micafungin
clsi (Beredaki 2023)</a> </td>
<td style="text-align:left;"> In vitro (Candida albicans
clinical isolates in RPMI-1640 with 10% pooled human serum;
two-compartment closed dialysis/diffusion PK/PD model). Micafungin in
vitro PK/PD model with the exposure-response relationship indexed on
CLSI M27 MICs. Beredaki 2023 simulated q24h micafungin exposures in the
internal compartment of a dialysis/diffusion model and described the
concentration decay with the one-compartment mono-exponential Ct = C0 *
exp(-k * t) (Methods, 'In vitro pharmacokinetics'), with an average
half-life of 14 h (range 9-15 h) in the presence of 10% pooled human
serum. The 72 h change in log10 CFU/mL relative to the starting inoculum
was then related to the PK/PD index fAUC0-24/MIC with the sigmoidal
variable-slope Emax model E = Emax * EI^n / (EI^n + EI50^n) (Methods,
'PK/PD analysis'), where E is the REDUCTION in log10 CFU/mL relative to
the drug-free control. Beredaki 2023 printed the equation but not its
coefficients, so e0, lemax, lec50 and lhill were recovered by digitising
the fitted curve in Figure 5(a) (CLSI panel, R^2 = 0.92); the recovered
coefficients reproduce the paper's own Table 2 CLSI stasis target (2.8
fAUC0-24/MIC) to +3% and its 1-log-kill target (9.2 fAUC0-24/MIC) to
-13%, equivalent to 0.10 log10 CFU/mL on the effect axis. The fungal
density bact (linear CFU/mL) is integrated as d/dt(bact) = ln(10) * ((e0
- kill72) / 72) * bact so that log10(bact) changes by exactly (e0 -
kill72) across the paper's 72 h observation window, reproducing the
endpoint model exactly at the time the paper actually fitted it. The
companion EUCAST parameterisation is Beredaki_2023_micafungin_eucast.
See the vignette for the reported no-serum targets, which are NOT
packaged because Beredaki 2023 published no exposure-response curve for
that condition. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Beredaki_2023_micafungin.html">Micafungin
eucast (Beredaki 2023)</a> </td>
<td style="text-align:left;"> In vitro (Candida albicans
clinical isolates in RPMI-1640 with 10% pooled human serum;
two-compartment closed dialysis/diffusion PK/PD model). Micafungin in
vitro PK/PD model with the exposure-response relationship indexed on
EUCAST E.Def 7.3 MICs. Beredaki 2023 simulated q24h micafungin exposures
in the internal compartment of a dialysis/diffusion model and described
the concentration decay with the one-compartment mono-exponential Ct =
C0 * exp(-k * t) (Methods, 'In vitro pharmacokinetics'), with an average
half-life of 14 h (range 9-15 h) in the presence of 10% pooled human
serum. The 72 h change in log10 CFU/mL relative to the starting inoculum
was then related to the PK/PD index fAUC0-24/MIC with the sigmoidal
variable-slope Emax model E = Emax * EI^n / (EI^n + EI50^n) (Methods,
'PK/PD analysis'), where E is the REDUCTION in log10 CFU/mL relative to
the drug-free control. Beredaki 2023 printed the equation but not its
coefficients, so e0, lemax, lec50 and lhill were recovered by digitising
the fitted curve in Figure 5(b) (EUCAST panel, R^2 = 0.87); the
recovered coefficients reproduce the paper's own Table 2 EUCAST stasis
target (2.8 fAUC0-24/MIC) to -1% and its 1-log-kill target (7.9
fAUC0-24/MIC) to -6%, equivalent to 0.05 log10 CFU/mL on the effect
axis. The fungal density bact (linear CFU/mL) is integrated as
d/dt(bact) = ln(10) * ((e0 - kill72) / 72) * bact so that log10(bact)
changes by exactly (e0 - kill72) across the paper's 72 h observation
window, reproducing the endpoint model exactly at the time the paper
actually fitted it. The companion CLSI parameterisation is
Beredaki_2023_micafungin_clsi. See the vignette for the reported
no-serum targets, which are NOT packaged because Beredaki 2023 published
no exposure-response curve for that condition. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Brill_2014_midazolam.html">Midazolam
(Brill 2014)</a> </td>
<td style="text-align:left;"> Three-compartment population PK
model for midazolam with two equalized peripheral volumes and a
three-transit-compartment first-order oral absorption chain (Ka = Ktr),
supporting oral and intravenous dosing, in 20 morbidly obese patients
(mean total body weight 144 kg, range 112-186; mean BMI 47, range 40-68)
and 12 non-obese healthy volunteers (mean total body weight 76 kg, mean
BMI 22). Total body weight enters as a linear covariate on central
volume (reference 127 kg) and a power covariate on peripheral volume
(reference 127 kg); morbid-obesity status (BMI > 40) shifts oral
bioavailability up and the transit absorption rate down. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Franken_2017_midazolam.html">Midazolam
(Franken 2017)</a> </td>
<td style="text-align:left;"> Joint parent-metabolite
population PK model for midazolam, its primary active metabolite
1-OH-midazolam (1-OH-M), and the secondary metabolite
1-OH-midazolam-glucuronide (1-OH-MG) in 45 terminally ill adult
palliative-care patients (Franken 2017). Midazolam: one-compartment
disposition with two parallel first-order absorption routes (oral and
subcutaneous bolus) using route-specific absorption rate constants fixed
from literature (Ka oral = 5.5 1/h, Ka SC = 10 1/h); oral
bioavailability F is estimated and SC F assumed = 1. 1-OH-M: one
compartment, central volume fixed equal to midazolam V, clearance
estimated. 1-OH-MG: one compartment, clearance and volume estimated. All
inter-compartment fluxes carry the parent / metabolite signal in
midazolam-equivalent mass units (concentrations were adjusted to
midazolam equivalents via molecular weight per Methods). Midazolam
clearance depends on serum albumin (power form, reference 25 g/L) and
1-OH-MG clearance depends on eGFR (standard four-variable MDRD, power
form, reference 104 mL/min/1.73 m^2). IIV on midazolam CL was correlated
with oral F (rho fixed to unity per Results); other IIVs are
independent. Residual variability is additive on log-transformed
concentrations (LTBS) for all three analytes; a cross-output residual
correlation noted in Methods is not encoded in this nlmixr2 port (see
vignette Assumptions and deviations). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Janssen_2017_cabazitaxel_phenotyping.html">Midazolam
(Janssen 2017)</a> </td>
<td style="text-align:left;"> One-compartment population PK
model for intravenous midazolam used as a CYP3A metabolic-phenotyping
probe in 10 men with metastatic castration-resistant prostate cancer
(Janssen 2017 Table 2A). Each patient received a single 2.5 mg IV
midazolam bolus 1-7 days before their scheduled cabazitaxel infusion;
the empirical Bayes estimates of individual midazolam clearance from
this fit are then used as covariate input to the companion Janssen 2017
cabazitaxel model (see modellib('Janssen_2017_cabazitaxel')).
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Swart_2004_lorazepam_midazolam.html">Midazolam
(Swart 2004)</a> </td>
<td style="text-align:left;"> Two-compartment IV population PK
model for midazolam by continuous infusion in mechanically ventilated
critically ill adult ICU patients. Clearance is selected by chronic
alcohol-abuse status and decreases linearly with age above 57 years;
intercompartmental clearance decreases linearly with APACHE II score
above 26. Fitted by NONMEM V in the Swart 2004 learning cohort (n = 21).
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/vanRongen_2015_midazolam.html">Midazolam
(vanRongen 2015)</a> </td>
<td style="text-align:left;"> Joint
parent-and-sequential-metabolites population PK model for intravenous
midazolam, its primary CYP3A oxidative metabolite 1'-hydroxymidazolam
(1-OH-midazolam), and the downstream phase-II 1'-hydroxymidazolam
glucuronide (1-OH-midazolam glucuronide) in 19 overweight and obese
adolescents (12.5-18.9 years, body weight 62-149.8 kg) undergoing
surgery (van Rongen 2015). Two-compartment disposition for midazolam
(central + peripheral) routes the entire elimination clearance CL1 to
1-OH-midazolam formation. 1-OH-midazolam is described by a
one-compartment model with apparent volume of distribution fixed at 0.9
times the midazolam central volume (Mandema 1992); the entire
1-OH-midazolam clearance CL3 is routed to 1-OH-midazolam glucuronide
formation. 1-OH-midazolam glucuronide is described by a two-compartment
model with renal elimination clearance CL4. Total body weight (TBW)
enters the peripheral volume of distribution of midazolam as a power
function with reference 104.7 kg (cohort median) and estimated exponent
X = 1.68; no other covariate effect was retained. Concentrations are
modeled in umol/L throughout (paper Methods), so dosing is in umol;
dose_umol = dose_mg * 1000 / MW_midazolam where MW_midazolam = 325.77
g/mol. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/vanRongen_2017_midazolam.html">Midazolam
(vanRongen 2017)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model for midazolam in 19 obese adolescents (12-18.9 years, total body
weight 62-149.8 kg, BMI 24.8-55 kg/m^2) and 20 morbidly obese adults
(26-57 years, total body weight 112.3-186.3 kg, BMI 39.9-67.6 kg/m^2),
with a five-transit-compartment first-order oral absorption chain (Ka =
Ktr) supporting oral and intravenous dosing (van Rongen 2017 Final
model, Table 2). Study population (adolescent vs morbidly obese adult)
separates clearance into two cohort-specific values (CL_104.7 kg in
adolescents with an estimated TBW power on top, CL fixed-across-WT in
morbidly obese adults). The same V_141.8 kg central value of the
peripheral compartment is shared between cohorts but TBW power scaling
applies only to morbidly obese adults. Central volume,
inter-compartmental clearance Q, transit-absorption rate Ka = Ktr, and
oral bioavailability F are shared across both cohorts. Oral data were
collected only in morbidly obese adults; adolescents received only IV
bolus doses. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Cella_2012_midazolam_paediatric_scaling.html">Midazolam
children adolescents (Cella 2012)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model for midazolam in children and adolescents (Cella 2012 Model 2), IV
bolus only, with per-kg linear scaling of the central volume and a
linear normalisation of the peripheral volume by age (months) at a
74-month reference. Cohort of 18 paediatric oncology patients (ages 3.2
to 16.2 years, body weights 12.6 to 60.1 kg) dosed at 0.12 mg/kg IV
before invasive procedures. Fitted with informative priors from De Wildt
2002 via the NONMEM PRIOR / Wishart subroutine. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Cella_2012_midazolam_paediatric_scaling.html">Midazolam
infants adults (Cella 2012)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model for midazolam in infants, toddlers, and adults (Cella 2012 Model
1), with first-order absorption supporting intravenous and oral dosing,
body-weight allometric scaling of clearance (exponent fixed to 0.75 at a
70 kg reference), per-kg linear scaling of the central volume, and a
constant peripheral volume. Pooled cohort of 23 infants and toddlers in
a paediatric surgical ICU and 34 healthy adult volunteers. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Brussee_2018_midazolam_pbpk.html">Midazolam
pbpk (Brussee 2018)</a> </td>
<td style="text-align:left;"> PBPK (semi-physiological;
well-stirred liver + Qgut gut wall) population PK model for midazolam
and its primary metabolite 1-OH-midazolam in 37 preterm neonates
(gestational age 26-34 weeks, body weight 0.770-2.030 kg at the time of
dosing). Distinguishes first-pass CYP3A-mediated metabolism in the gut
wall (Qgut model) and liver (well-stirred model) from systemic hepatic
elimination of the metabolite. Tissue volumes (V_h, V_pv, V_gw) and
hepatic blood flow Q_h are allometrically scaled from a term-neonate
reference (Bjorkman 2005) by body weight with fixed exponents (1 for
volumes, 0.75 for flow); intestinal length scales as 2.736 * WT[g]^0.512
cm (Struijs 2009) so the Qgut hybrid flow varies with body size.
Supports oral administration (depot, full first-pass through gut wall
and liver) and IV (dose directly to central; no first-pass). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Hajjar_2018_pompe_disease.html">Miglustat
(Hajjar 2018)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model for oral miglustat (AT2221; N-butyl-1-deoxynojirimycin)
administered as a pharmacological chaperone for cipaglucosidase alfa in
adult patients with Pompe disease (Hajjar 2018 ACCP poster, phase 1/2
study ATB200-02 / NCT02675465). Absorption is described by a sequential
zero-order release into the depot (duration D1 = 0.459 h) followed by
first-order absorption (Ka = 0.485 /h) into the central compartment.
Apparent disposition parameters (CL/F = 8.55 L/h, Vc/F = 36.3 L, Q/F =
3.16 L/h, Vp/F = 45.6 L) are reported at the 70 kg reference body weight
and allometrically scaled with exponents 0.75 fixed on clearances and 1
fixed on volumes. Bioavailability F is not estimable from oral-only data
and is anchored at 1 (apparent CL/F and V/F parameterisation). Residual
error is proportional (variance 0.0408, SD 0.202 on the linear-scale
concentration). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Dorlo_2008_miltefosine.html">Miltefosine
(Dorlo 2008)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model with first-order oral absorption and linear elimination for
miltefosine in 31 Dutch military personnel with Old World (Leishmania
major) cutaneous leishmaniasis contracted in Afghanistan (Dorlo 2008),
treated with oral miltefosine 50 mg three times daily (150 mg/day,
median 1.76 mg/kg/day) for 28 days with post-treatment follow-up to a
maximum of 202 days. CL/F, Vc/F, Q/F, and Vp/F are estimated apparent
parameters; relative bioavailability F is unidentifiable from oral-only
data and is structurally fixed at 1. Inter-individual variability is
log-normal on ka, CL/F, and Vc/F (diagonal in this implementation; see
Assumptions in the vignette for the unreported CL/Vc correlation noted
by the authors). IIV on Q/F and Vp/F was not estimable from the data.
Residual error is proportional (31.5% CV). No covariate effects were
retained in the final model. This is the structural model later re-used
as the base PK structure in Dorlo 2017 visceral-leishmaniasis
miltefosine work. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Dorlo_2017_miltefosine.html">Miltefosine
(Dorlo 2017)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model with first-order oral absorption for miltefosine in 95 Eastern
African adults and children (>=7 years) with visceral leishmaniasis
(Dorlo 2017), enrolled across three treatment centres in Kenya and Sudan
and randomised to either a 28-day monotherapy regimen of oral
miltefosine 2.5 mg/kg/day or a 10-day oral miltefosine 2.5 mg/kg/day arm
combined with a single 10 mg/kg liposomal amphotericin B IV dose on day
1. CL/F, Q/F, Vc/F, and Vp/F are allometrically scaled on fat-free mass
(exponents 0.75 and 1.0; reference FFM 53 kg). Relative bioavailability
is structurally fixed at 100% from the end of the initial reduced
absorption window onwards, and reduced by a typical 74.3% during the
window itself (0 < t <= 7 days for monotherapy, 0 < t <= 1
day for the combination arm); the duration is regimen-dependent via the
MIL_REGIMEN indicator. The combined-error residual model is proportional
(31.0%) with additive component fixed at 0.001 ug/mL. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Sahota_2015_miridesap.html">Miridesap
(Sahota 2015)</a> </td>
<td style="text-align:left;"> Target-mediated drug disposition
(TMDD) PK/PD model for CPHPC (miridesap, GSK2315698, Ro 63-8695) and
serum amyloid P (SAP) in healthy volunteers (study CPH113776) and
patients with systemic amyloidosis (study CPH114527). Two-compartment PK
for CPHPC (IV plus first-order subcutaneous depot); two-compartment
turnover model for SAP with first-order endogenous production and
elimination; bimolecular CPHPC + free SAP -> complex binding treated
as effectively irreversible (KOFF set to zero because the complex
internalisation rate is much faster than the dissociation rate).
Final-model covariates (Sahota 2015 Eq. 1 and Eq. 2): creatinine
clearance modifies CPHPC clearance below an 80 mL/min threshold; hepatic
amyloid involvement multiplies SAP intercompartmental clearance Q4;
whole-body amyloid load (categorical 0-3) multiplies SAP peripheral
volume V4 in two cumulative steps; biological sex multiplies baseline
plasma SAP. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Chua_2025_mirikizumab.html">Mirikizumab
(Chua 2025)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model for mirikizumab (anti-IL-23p19 IgG4 mAb) in patients with
moderately-to-severely active Crohn's disease (Chua 2025 VIVID-1 phase
3) </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Vorontsova_2022_misoprostol.html">Misoprostol
(Vorontsova 2022)</a> </td>
<td style="text-align:left;"> One-compartment population
pharmacokinetic model of misoprostol acid (MPA, the active metabolite)
following buccal or vaginal misoprostol tablet administration for
full-term labor induction, with mixed linear plus Michaelis-Menten
clearance. The absorption rate constant is estimated separately by route
(buccal vs vaginal) and dose level (25 vs 50 microgram); a relative
bioavailability multiplier captures the higher vaginal exposure, with
inter-occasion variability across the first two dose events. IIV is
estimated on apparent clearance, apparent central volume of
distribution, and the absorption rate constant. Development cohort: 47
women at term gestation (>=37 weeks) undergoing labor induction in
the IMPROVE trial (NCT02408315). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/An_2012_mitoxantrone_pbpk.html">Mitoxantrone
human pbpk (An 2012)</a> </td>
<td style="text-align:left;"> Human-scaled simulation.
Semi-mechanistic whole-body PBPK model 3 for mitoxantrone (Novantrone)
in adult cancer patients after a single 12 mg/m^2 IV bolus, projected
forward from the mouse fit in An_2012_mitoxantrone_mouse_pbpk (An and
Morris 2012, AAPS J). Same topology as the mouse model: seven
physiological tissue compartments (central plasma plus six
perfusion-limited well-stirred organs - lung, heart, spleen, liver,
kidney, brain) and a permeability-limited remainder compartment lumping
muscle, fat, bone, and skin and resolving into an interstitial
(is_remainder) and an intracellular (int_remainder) subspace coupled by
a permeability-surface area product. Plasma unbound fraction fu = 0.2,
DNA dissociation constant K_DNA = 0.0013 uM, protein-binding
dissociation constant K_macro = 1.44 uM, and per-organ T_macro are
carried over from the mouse fit as cross-mammalian constants (paper
Methods). Per-organ T_DNA values are replaced with the human DNA-content
literature values reported in Table III: lung and spleen DNA use the
literature rapidly- perfused-organ value (15 uM); brain T_DNA is the
mouse-derived value (0.10 uM); the remainder T_DNA uses the literature
slowly-perfused- organ value (4.5 uM). The remainder ISF/intracellular
split is assumed to follow the mouse proportion 33/67 (Table I) applied
to the human remainder volume V_other = 62 L. Hepatic and renal
intrinsic clearances are derived from clinical CL_H = 19 L/h/m^2 and
CL_R = 2.7 L/h/m^2 (Ehninger 1990 ref 6) via the well-stirred
rearrangement Clint = Q_H * CL / (fu * Q_H - fu * CL) yielding Clint_H =
250 L/h and Clint_R = 27 L/h. PS_remainder is allometrically scaled from
the mouse value PS = 1.44 mL/min via PS = A * M^0.75 (Kawai 1998 ref 28)
giving PS = 31.1 L/h. The model is a typical-value forward simulation;
there is no IIV and no residual error from the paper. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/An_2012_mitoxantrone_pbpk.html">Mitoxantrone
mouse pbpk (An 2012)</a> </td>
<td style="text-align:left;"> Preclinical (mouse).
Semi-mechanistic whole-body PBPK model 3 for mitoxantrone (Novantrone)
in male ND4 Swiss Webster mice (24-32 g) after a single 5 mg/kg
intravenous bolus (penile vein) (An and Morris 2012, AAPS J). Seven
physiological tissue compartments: central plasma plus six
perfusion-limited well-stirred organs (lung, heart, spleen, liver,
kidney, brain), with a permeability-limited remainder compartment that
lumps muscle, fat, bone, intestine, and skin and resolves into an
interstitial (is_remainder) and an intracellular (int_remainder)
subspace coupled by a permeability- surface area product PS. Hepatic and
renal elimination act on the unbound cellular concentration of liver and
kidney via well-stirred intrinsic clearances Clint_H and Clint_R.
Saturable tissue binding to DNA (capacity T_DNA, affinity K_DNA) and
macromolecular protein (capacity T_macro, affinity K_macro) is encoded
as a Cp-dependent effective tissue:plasma partition coefficient
Kp_eff(Cp) that varies instantaneously with plasma concentration (Eqs.
9-11 of the paper). Plasma unbound fraction is fixed to 0.2; tissue
binding affinities are shared across all organs. The model is intended
for typical- value simulation of mouse plasma and tissue
concentration-time profiles. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Honda_2006_mizoribine.html">Mizoribine
(Honda 2006)</a> </td>
<td style="text-align:left;"> One-compartment oral PK model for
mizoribine in healthy Caucasian male volunteers (Honda 2006);
first-order absorption with a fixed absorption-lag time, apparent volume
of distribution V/F linear in body weight, apparent oral clearance CL/F
linear in Cockcroft-Gault creatinine clearance (CLcr), and additive
residual error on the serum-concentration scale. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Peng_2014_MK3577.html">MK3577
(Peng 2014)</a> </td>
<td style="text-align:left;"> Semi-mechanistic PD model for the
glucagon receptor antagonist MK-3577 (Merck) in healthy male subjects
undergoing a glucagon challenge (Peng 2014). Glucose / glucagon /
insulin homeostasis is described with constant endogenous baselines Gss,
Iss, GNss; glucose has central + peripheral distribution plus an effect
compartment for delayed regulation of glucose production. MK-3577 drives
an inhibitory Imax model on the glucagon-stimulation of glucose
production (Imax,MK = 0.961, IC50,MK = 13.9 nM) and a stimulatory Emax
model on glucagon secretion (Emax,MK = 0.788 FIX, EC50,MK = 575 nM FIX)
for the prechallenge compensatory feedback. Sandostatin (octreotide) PK
is modeled with literature CL / V (0.121 L/kg/h, 0.194 L/kg) and
inhibits endogenous insulin (IC50,S2 = 0.921 ng/mL) and glucagon
(IC50,S1 = 5.50 ng/mL) secretion at a fixed Imax of 1. The MK-3577 PK
layer is NOT modeled here because the absorption rate ka, apparent
volume V/F, and molecular weight for the mg-to-nM conversion are not
reported in the on-disk paper or its tables; users supply the MK-3577
plasma concentration as a time-varying covariate column CP_MK3577_NM
(nM) per the standing operator decision (extract PD layer only; PK
supplied externally). See vignette Assumptions and deviations for the
gap. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Peng_2014_MK3577.html">MK3577
t2dm (Peng 2014)</a> </td>
<td style="text-align:left;"> T2DM-patient adaptation of the
Peng 2014 semi-mechanistic glucose / glucagon / insulin model with
MK-3577 as the glucagon receptor antagonist (Peng 2014 Fig. 1b and 'CTS
Method for T2DM Patients'). Three structural changes vs. the healthy
model: (1) GPRG1 = 0 (glucose self-regulation of GPROD is fully
compromised in T2DM, matching Silber 2007); (2) CL_GI is scaled to 11%
of the healthy value (lead- compound finding); (3) baseline glucose is
elevated by a fold factor theta with typical value fixed at 1 (i.e.,
baseline FPG is 2 x healthy G_SS) and IIV fixed at 51% CV based on
lead-compound data. The new T2DM baselines for insulin (I_SSP) and
glucagon (GN_SSP) are derived from theta via Peng 2014 Eqs. 7-10
(insulin: I_SSP = I_SS * (1+theta)^IPRG; glucagon: closed-form
rearrangement of Eqs. 9 and 10 conditioned on the T2DM-scaled CL_GI).
The effect compartment for glucose negative feedback is omitted because
GPRG1 = 0 makes its contribution vanish; the Sandostatin compartment is
also omitted because the T2DM phase IIa CTS used in Peng 2014 had no
glucagon challenge -- only endogenous homeostasis under multi-day
MK-3577 dosing. The MK-3577 PK layer is NOT modeled here for the same
reason as the healthy model (ka, V/F, MW not in the on-disk PDF); users
supply the time-varying MK-3577 plasma concentration via CP_MK3577_NM
(nM). See vignette Assumptions and deviations. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Wu_2012_modafinil.html">Modafinil
(Wu 2012)</a> </td>
<td style="text-align:left;"> Joint parent + metabolite
population pharmacokinetic model for oral modafinil and its principal
carboxylic-acid metabolite modafinil acid
(2-[(diphenylmethyl)sulfonyl]acetic acid) in 49 healthy volunteers from
five major ethnic groups of China (Han, Mongolian, Korean, Uygur, Hui)
under a single 200 mg oral dose (Wu 2012). Four-compartment NONMEM
ADVAN6 / L2 structure: GI depot with first-order absorption (ka),
two-compartment modafinil disposition (apparent CL/F, Vc/F, Q/F, Vp/F),
and a one-compartment modafinil acid disposition (apparent CL3/F1F2,
V3/F1F2). All modafinil elimination is treated as forming modafinil acid
at the apparent-parameter level because F2 (the absolute
modafinil-to-acid metabolic-conversion fraction) is not identifiable
from oral plasma data alone; F2 is absorbed into the apparent acid
parameters. Sex acts on CL/F, Q/F, and Vp/F of modafinil; ethnicity acts
on Vc/F of modafinil (Korean and Hui share a single composite
multiplier; Mongolian and Uygur each have their own) and on CL3/F1F2 of
modafinil acid (Han and Mongolian share the reference; Korean has its
own multiplier; Uygur and Hui share a composite multiplier). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Mukai_2019_mogamulizumab.html">Mogamulizumab
(Mukai 2019)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model for mogamulizumab in adults with cutaneous T-cell lymphoma or
adult T-cell lymphoma (Mukai 2019) </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Hwang_2023_monalizumab.html">Monalizumab
(Hwang 2023)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model for monalizumab (anti-CD94/NKG2A IgG4) in patients with advanced
solid tumors or squamous cell carcinoma of the head and neck (Hwang
2023) </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Abrantes_2017_moroctocog.html">Moroctocog
(Abrantes 2017)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model for factor VIII activity (IU/dL) following intravenous
administration of moroctocog alfa (B-domain-deleted recombinant FVIII,
marketed as ReFacto, ReFacto AF and Xyntha) in patients with moderate to
severe hemophilia A; pooled analysis of 754 patients across 13 clinical
trials over 20 years (Abrantes 2017). The exogenous-drug component is
added to a constant endogenous-baseline FVIII activity
(severe-subpopulation typical value, 0.474 IU/dL; the paper's full model
is a two-class mixture, see vignette deviations). Clearance and
inter-compartmental clearance scale allometrically with body weight at
theory-based exponent 0.75; central and peripheral volumes share an
estimated allometric exponent 0.812. Clearance has a piecewise-linear
age effect (increasing from birth to 1 year of age, then decreasing into
adulthood; centered at 20 years), a +166% inhibitor (ADA_POS) effect,
and a -34.7% study B1831090 effect. The peripheral volume is +88.4%
larger in Black subjects. Bioavailability F carries multiplicative
covariate effects for product (1.38x for Xyntha vs ReFacto), assay
(-39.0% for OSA central, -14.6% for OSA local laboratory) following
Abrantes 2017 Table 2 footnote g. Proportional residual error is 19.2%
(CSA reference) and switches to 26.9% (+40.3%) for OSA-assayed samples.
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/deHoogd_2017_morphine.html">Morphine
(deHoogd 2017)</a> </td>
<td style="text-align:left;"> Joint parent-metabolite
population PK model for morphine and its two glucuronide metabolites
(M3G, M6G) in 20 morbidly obese adults (post-gastric-bypass) and 20
healthy adult volunteers (de Hoogd 2017). Morphine: three-compartment IV
model with total body weight (TBW) covariate on the second peripheral
volume V5M. Non-glucuronide morphine clearance is structurally fixed at
35% of total morphine CL in a 70-kg healthy adult. M3G and M6G are each
one-compartment models fed by formation-delay transit chains (n = 5 for
M3G, n = 2 for M6G); VM3G = VM6G is a structural equality. TBW
covariates apply to CLF M6G, the M3G transit rate Ktr, M3G elimination
CL, and M6G elimination CL, all power-form normalised to a reference of
98.5 kg (population median). Proportional residual error is reported
separately for the healthy- volunteer cohort and the morbidly obese
cohort, selected via the binary indicator DIS_OBESE_MORBID. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Elkomy_2015_morphine.html">Morphine
(Elkomy 2015)</a> </td>
<td style="text-align:left;"> Joint parent-metabolite
population PK model for morphine and its two glucuronide metabolites M3G
and M6G in 20 infants and young children (3 days - 5.4 years; 3.1 - 18.5
kg) after congenital heart surgery (Elkomy 2015 AAPS J). Morphine:
linear two- compartment IV disposition with allometric body-weight
scaling (CL and CLD with exponent 0.75 FIXED; VC and VP with exponent
1.0 FIXED) normalised to a reference of 6 kg (study median). Each
metabolite is modeled as a morphine-driven intermediate effect
compartment (rate constant Kint chasing morphine plasma concentration
via dCint/dt = Kint * (Cc - Cint)) feeding an empirical Emax
transduction where metabolite concentration = Mmax * Cint / (Cint50 +
Cint). Estimated glomerular filtration rate (Schwartz formula) is a
covariate: Kint scales linearly with GFR/70 and Mmax scales as 70/GFR
(both exponents FIXED at +/-1 per the paper's covariate analysis).
Between-subject random effects on Kint, Mmax, and Cint50 are SHARED
across the M3G and M6G channels (one eta per group; Table II). Doses are
administered as nmol of morphine equivalents (one nmol of clinical
morphine sulfate yields two nmol of free morphine); concentrations are
output in nmol/L (nM) for morphine, M3G, and M6G. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Franken_2015_morphine.html">Morphine
(Franken 2015)</a> </td>
<td style="text-align:left;"> Joint parent-metabolite
population PK model for morphine and its two glucuronide metabolites
(M3G, M6G) in 47 terminally ill adult palliative care patients (Franken
2015). Morphine: two-compartment disposition with three parallel
first-order absorption routes (subcutaneous bolus, immediate-release
oral liquid, controlled-release oral tablet) using route-specific fixed
absorption rate constants; oral bioavailability F is estimated (SC F
assumed 1). M3G and M6G are each one-compartment models fed by
fixed-fraction transformation of morphine clearance (Fm1 = 0.55 for M3G,
Fm2 = 0.10 for M6G, both fixed from literature). Morphine clearance
decreases exponentially as time-to-death (TTD, days) approaches zero.
Metabolite clearance depends on estimated glomerular filtration rate
(eGFR, MDRD four-variable formula) and serum albumin via shared
power-form covariate exponents. Residual variability was reported as
additive error on the log-transformed observation (LTBS). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Pierre_2017_morphine.html">Morphine
(Pierre 2017)</a> </td>
<td style="text-align:left;"> Joint parent-metabolite
population PK model for IV morphine and its primary glucuronide
metabolite morphine-3-glucuronide (M3G) in 14 healthy adults and 7
patients with biopsy-confirmed nonalcoholic steatohepatitis (NASH)
following a single 5 mg morphine sulfate IV infusion (Pierre 2017).
Morphine is described by a three-compartment disposition (central + two
peripherals) with parallel renal (CL_M_R) and non-renal (CL_M_NR)
clearances; the entire non-renal clearance is assumed to lead to M3G
formation via a single liver transit compartment with first-order rate
constant k_trans. M3G is described by a one-compartment model with a
single total clearance (CL_M3G). Cumulative urinary morphine and M3G
amounts are tracked as elimination-amount compartments. Total body
weight enters all CL/Q and V parameters a priori with fixed allometric
exponents (0.75 and 1, respectively) referenced to 70 kg. The NASH
severity score (NASF; combined NAFLD activity score and fibrosis
staging, 0-12) is the only additional covariate retained in the final
model; it acts on M3G clearance through a linear effect on the natural
logarithm of (NASF / 4) for NASF >= 4 and is identically zero for
NASF < 4 so that healthy and benign-NAFLD subjects (NASF < 5)
recover the typical CL_M3G. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Colin_2014_moxifloxacin.html">Moxifloxacin
(Colin 2014)</a> </td>
<td style="text-align:left;"> Three-compartment population PK
model for moxifloxacin in post-bariatric (roux-en-y gastric bypass)
volunteers (Colin 2014): linear first-order absorption (no lag, no
transit) into a central compartment with two peripheral compartments,
allometric scaling on lean body mass (exponent 0.75 on all CL terms and
1 on all volumes, reference LBM 60 kg), and inter-individual variability
on ka, central volume, and clearance. Single 400 mg oral and 400 mg 1-h
IV infusion doses are fit simultaneously with an implicit
bioavailability of 1. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Hong_2015_moxifloxacin.html">Moxifloxacin
(Hong 2015)</a> </td>
<td style="text-align:left;"> Sequential population PK + PD
(QT-interval) model for single-dose oral moxifloxacin (400 mg or 800 mg,
Avelox tablets) in healthy adult Korean male volunteers (Hong 2015): a
two-compartment first-order absorption PK model with a lag time and a
dose-dependent absorption rate constant (different Ka for 400 mg vs 800
mg), followed by an individually corrected QT-interval PD model that
adds two mixed-effect cosine circadian components (24 h and 6 h), a
first-order-decaying placebo (water-intake) effect, and an Emax drug
effect on QT prolongation. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Landersdorfer_2009_moxifloxacin.html">Moxifloxacin
(Landersdorfer 2009)</a> </td>
<td style="text-align:left;"> Population PK model for oral
moxifloxacin bone penetration (Landersdorfer 2009): two-compartment
plasma disposition with first-order absorption from a gut depot, plus
two paper-mechanistic bone matrix compartments (cortical and cancellous
bone) connected to the central compartment by fixed transfer rate
constants. The bone tissue:serum equilibrium concentration ratio is
captured by the multiplicative scale terms fcortical and fcancellous on
the cortical and cancellous bone observations. Disposition parameters
were MAP-Bayesian estimated against Simon 1997 priors; bone-penetration
scale terms used noninformative priors. Single 400 mg oral dose in 24
adults undergoing total hip replacement; serum and femoral bone samples
(cortical + cancellous, head + neck) collected 2 to 7 hours post-dose.
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Morganroth_2015_moxifloxacin.html">Moxifloxacin
(Morganroth 2015)</a> </td>
<td style="text-align:left;"> Population pharmacodynamic linear
concentration-effect model for moxifloxacin-induced placebo- and
baseline-corrected QTcF interval prolongation (DDQTcF) in 40 healthy
adult male Japanese and 40 healthy adult male Caucasian volunteers
following a single 400 mg oral dose in a thorough QT study (Morganroth
2015). The linear mixed-effects PD model of Table 4 has form DDQTcF =
(alpha + rho * RACE_WHITE) + (beta + gamma * RACE_WHITE) * Cc, with
alpha = 1.71 ms, beta = 2.58 ms per ug/mL (Japanese reference), rho =
2.58 ms (additive intercept shift in Caucasian; USA site), gamma = -0.24
ms per ug/mL (concentration-by-country interaction; Caucasian slope =
2.34 ms per ug/mL). The source publication does not fit a popPK model;
the PK driver in this file is a typical-value 1-compartment oral
approximation with CL/F = 8.47 L/h, V/F = 132.6 L, and ka = 1.7 /h
derived from the pooled NCA summary statistics in Morganroth 2015 Table
1 (see vignette Errata). Per operator sidecar-001 (option C) the paper's
BVN(0, Sigma) subject random effects on the PD intercept and slope are
OMITTED because Sigma is not numerically reported in the paper, and a
small placeholder additive residual SD of 1 ms is used to satisfy
rxode2's residual-error requirement; downstream users who need VPC-style
simulation must add their own IIV. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Nielsen_2011_antibacterial_efficacy.html">Moxifloxacin
(Nielsen 2011)</a> </td>
<td style="text-align:left;"> In vitro (Streptococcus pyogenes
M12 NCTC P1800). Semimechanistic PKPD model of moxifloxacin time-kill
kinetics; two-stage bacterial life-cycle (proliferating drug-sensitive S
and non-growing drug-insensitive R) with sigmoidal Emax killing of S via
an effect compartment; first-order drug elimination (ke set per in vitro
kinetic-system flow rate); drug-specific degradation kdeg fixed at zero.
Parameter values are from the combined static and dynamic estimation in
Table 3. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Kaushal_2024_mRNA0184.html">MRNA0184
cyno (Kaushal 2024)</a> </td>
<td style="text-align:left;"> Preclinical (cynomolgus monkey).
Translational semi-mechanistic PK/PD model for mRNA-0184, a
lipid-nanoparticle-encapsulated mRNA encoding human relaxin-2 fused to a
variable light chain kappa domain (Rel2-vlk), for heart failure. PK:
3-compartment plasma1-tissue-plasma2 redistribution of Rel2-vlk mRNA
(both plasma compartments share V1; elimination is from the tissue
compartment) reproducing the delayed second concentration peak
characteristic of LNP modalities; observed mRNA concentration is the sum
of the two plasma compartments. PD: Rel2-vlk protein production linear
in the concentration of a hypothetical effect compartment equilibrating
with plasma mRNA, distributed in a 2-compartment (central/peripheral)
system with a single symmetric intercompartmental clearance and
first-order elimination from the central compartment. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Kaushal_2024_mRNA0184.html">MRNA0184
human (Kaushal 2024)</a> </td>
<td style="text-align:left;"> Human-scaled allometric
projection (NO human data were fitted). Translational semi-mechanistic
PK/PD model for mRNA-0184, a lipid-nanoparticle-encapsulated mRNA
encoding human relaxin-2 fused to a variable light chain kappa domain
(Rel2-vlk), for heart failure with reduced ejection fraction. This is
the cynomolgus-monkey model of Kaushal 2024 forward-projected to a 70 kg
adult by allometric scaling (exponent 1 on volumes, 0.75 on Rel2-vlk
mRNA clearances, 0.85 on Rel2-vlk protein clearances). PK: 3-compartment
plasma1-tissue-plasma2 redistribution of Rel2-vlk mRNA (both plasma
compartments share V1; elimination from the tissue compartment). PD:
Rel2-vlk protein production linear in a hypothetical effect-compartment
mRNA concentration, distributed in a 2-compartment system with a single
symmetric intercompartmental clearance and first-order central
elimination. Used to support the 0.025 mg/kg every-2-weeks
first-in-human starting dose for NCT05659264. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Attarwala_2023_mRNA3927.html">MRNA3927
(Attarwala 2023)</a> </td>
<td style="text-align:left;"> Preclinical (mouse, rat,
cynomolgus monkey; allometrically scalable to humans). Translational
semi-mechanistic PK and PK/PD model for mRNA-3927, an LNP-encapsulated
dual mRNA encoding propionyl-CoA carboxylase (PCC) subunits PCCA and
PCCB. PK: 3-compartment plasma1-tissue-plasma2 redistribution (V shared
between the two plasma compartments; V and V2 fixed at the mouse
reference and scaled allometrically) with body-weight allometric scaling
of clearances (mouse reference 0.025 kg; estimated exponents cla on
CL12/CL32 and clb on CL23/CL20). PD: liver PCC protein 2-compartment
indirect-response model driven by an effect compartment linked to plasma
mRNA, with synthesis linear in effect-compartment mRNA concentration and
first-order degradation. Three downstream biomarkers (2-methylcitrate,
3-hydroxypropionate, C3/C2 carnitine ratio) follow direct sigmoidal Imax
suppression by liver PCC protein with Imax fixed at 0.999. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Niloy_2026_MTMSATrp_mouse.html">MTMSATrp
mouse (Niloy 2026)</a> </td>
<td style="text-align:left;"> Preclinical (mouse).
One-compartment population PK model for MTMSA-Trp, a novel mithramycin
analogue investigated for Ewing sarcoma, in female athymic nu/nu mice
following single IV bolus doses of 0.3, 1, 3, 5, or 10 mg/kg.
First-order elimination from the central compartment with an empirical
power-function effect of dose on apparent clearance (CL decreases with
increasing dose; reference dose 3 mg/kg, exponent beta = -0.30).
Parameters are expressed in per-kg body-weight units (mL/h/kg for CL,
mL/kg for V) so the dose record carries the per-kg dose directly (mg/kg)
without an explicit body-weight covariate. Parameter values from Niloy
2026 Table 1 (final model). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Laffont_2025_opioid_overdose_reversal_simulation.html">Mu
receptor binding (Mann 2022)</a> </td>
<td style="text-align:left;"> QSP. Competitive mu-opioid
receptor binding kinetics layer of the Mann 2022 translational
opioid-overdose model. Tracks the fraction of receptors bound by an
opioid agonist (RL_op) and by an opioid antagonist (RL_antag) under
simultaneous exposure to both ligands. All 12 ligands characterised by
Mann 2022 Supplement 1 Table S2 are carried inline as fixed parameters
(Kon in pM^-n s^-1, Koff in s^-1, slope n unitless); the OPIOID_ID and
ANTAGONIST_ID integer covariates select which ligand occupies each
binding slot at simulation time, so the same compiled model can simulate
any agonist-antagonist pair from the Table-S2 panel without re-
instantiation. Ligand effect-site concentrations enter the model as the
time-varying covariate columns L_OPIOID_pM and L_ANTAGONIST_pM,
typically piped from the PK layer in a composed chain (e.g.,
Mann_2022_fentanyl_iv or Mann_2022_carfentanil_iv for the opioid slot;
Laffont_2024_naloxone or Laffont_2024_nalmefene for the antagonist
slot). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Barau_2012_mycophenolic_acid.html">Mycophenolic
acid (Barau 2012)</a> </td>
<td style="text-align:left;"> One-compartment population PK
model for mycophenolic acid (MPA, active moiety of mycophenolate mofetil
MMF) after oral MMF dosing in paediatric liver transplant recipients
(Barau 2012). First-order absorption and first-order elimination, with
diagonal (uncorrelated) inter-individual variability on ka, CL/F, and
V/F and proportional residual error. Two covariates are retained in the
final model: a linear-with-age effect on ka of the form ka_TV = 3.9 -
2.2 * (AGE / 8.65 years), so ka declines from 3.9 1/h at AGE = 0 to 1.7
1/h at the cohort median age of 8.65 years; and a power-on-binary effect
on V/F of the form V/F = 64.7 L * 2.3^POSTTX_EARLY, where POSTTX_EARLY =
1 within the first 6 months post-transplant (POD <= 180 days) and 0
thereafter, so V/F is 64.7 L in the stable post-transplant period and
148.8 L in the immediate post-transplant period (paper attributes the
volume increase to the higher unbound MPA fraction associated with low
serum albumin in the immediate post-transplant period). Apparent
clearance CL/F = 12.7 L/h carries no retained covariate effect in the
final model. Enterohepatic recirculation, the MPAG metabolite
compartment, and protein binding are not modelled here -- the paper
attributes the absence of secondary peaks to surgical removal of the
gallbladder in the liver-transplant recipients. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/deWinter_2009_mycophenolic_acid.html">Mycophenolic
acid (deWinter 2009)</a> </td>
<td style="text-align:left;"> Semi-mechanistic
competitive-protein-binding population PK model for mycophenolic acid
(MPA, the active moiety of mycophenolate mofetil MMF) and its
glucuronide metabolite MPAG in adult renal transplant recipients (de
Winter 2009). Free MPA (fMPA) follows a two-compartment disposition with
first-order oral absorption (lag-time TLAG; fixed ka = 4.00 1/h); free
MPAG (fMPAG) follows a one-compartment disposition. Both species bind
competitively to a saturable plasma protein binding pool with capacity
BMAX and species-specific association / dissociation rate constants k24
/ k42 (MPA) and k56 / k65 (MPAG). The fMPAG-to-gallbladder transport
rate constant k57 drives enterohepatic recirculation: fMPAG accumulates
in a gallbladder compartment and empties into the fMPA central
compartment during a fixed window (TGB to TGB+DGB post-dose) at rate
constant k72, completing the EHC loop. Three covariates: a power effect
of creatinine clearance (CRCL) on CL fMPAG (exponent 1.36; CRCL
reference 45 mL/min); a power effect of plasma albumin (ALB) on BMAX
(exponent 1.39; ALB reference 0.5 mmol/L); and a multiplicative
power-form effect of cyclosporine cotreatment (CONMED_CSA) on k57
(multiplier 0.002, reducing EHC by ~99.8% under cyclosporine vs the
tacrolimus reference). Total MPA (tMPA) and total MPAG (tMPAG) plasma
concentrations are reported as the sum of the unbound and bound
concentrations of each species. Dosing is BID by default (tau = 12 h
hardcoded in model() for the gallbladder-emptying window).
Concentrations are in molar units (umol/L) per the source paper's choice
to analyse MMF / MPA / MPAG on a molar basis (MMF MW 433.5; MPA MW
320.3; MPAG MW 496.5). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Dong_2014_mycophenolic_acid.html">Mycophenolic
acid (Dong 2014)</a> </td>
<td style="text-align:left;"> Population PK-PD model for oral
mycophenolic acid (MPA, the active moiety of mycophenolate mofetil MMF)
in paediatric renal transplant recipients in the early post-transplant
period (Dong 2014). Two-compartment disposition with a Savic 2007-style
8-transit-compartment absorption chain followed by a first-order
absorption step from depot to central; dose-dependent relative
bioavailability described by a power function of dose per body surface
area (DBSA) with reference 450 mg/m^2; estimated body-weight exponent of
0.31 on CL/F (not the canonical allometric 0.75). The PD layer links MPA
plasma concentration to inosine monophosphate dehydrogenase (IMPDH)
activity in peripheral blood mononuclear cells via a simplified
inhibitory Emax model with Emax fixed at 0 (i.e., complete inhibition
achievable in the limit of high MPA concentration). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Frymoyer_2013_mycophenolic_acid.html">Mycophenolic
acid (Frymoyer 2013)</a> </td>
<td style="text-align:left;"> Population PK model for unbound
mycophenolic acid (MPA, the active moiety of mycophenolate mofetil MMF)
in adult allogeneic haematopoietic cell transplantation (alloHCT)
recipients (Frymoyer 2013). Two-compartment disposition with first-order
absorption and linear elimination; oral bioavailability F = 0.560.
Absorption lag time follows a two-class mixture: Group 1 (no delay, ALAG
= 0, 91 % of subjects) and Group 2 (delayed absorption, ALAG = 1.96 h, 9
% of subjects), gated by the latent MIX_LAGGED_ABS class indicator.
Creatinine clearance (Cockcroft-Gault with ideal body weight, NOT
BSA-normalized) is the only retained covariate, entering CL as a power
scaling (CRCL / 86 mL/min)^0.207. Inter-individual variability is
log-normal on all structural parameters and on F; residual error is
proportional. Doses are MPA-equivalent (mg) -- MMF mass must be
converted externally via F_MW = 0.739 (oral) or 0.682 (IV) per Frymoyer
2013 Methods. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Jiao_2008_mycophenolic_acid.html">Mycophenolic
acid (Jiao 2008)</a> </td>
<td style="text-align:left;"> Population PK model with
enterohepatic circulation (EHC) for mycophenolic acid (MPA) and its
7-O-glucuronide metabolite (MPAG) in healthy Chinese male volunteers
after a single 500 mg oral dose of mycophenolate mofetil (MMF,
Cellcept). Five-compartment chain model (Figure 2 of Jiao 2008): a
gastrointestinal depot, a two-compartment MPA disposition (central +
peripheral), a one-compartment MPAG disposition (central_mpag), and a
gallbladder accumulation compartment (gallbladder_mpag). First-order
absorption with an absorption-lag time. Complete (fm = 1, fixed)
one-pass conversion of MPA to MPAG by glucuronidation; MPAG is renally
cleared in parallel with biliary excretion into the gallbladder. EHC is
encoded as time-gated bolus releases of the gallbladder pool back into
the GI depot at two postprandial meal times (4 and 10 h post-dose,
study-1 design), with rate constant k51 acting over a 0.01 h window; the
recycled MPAG is reabsorbed via the same first-order ka as the oral
dose. The fraction of MPAG biliary-routed at the branch is encoded as
EHCP = k45 / (k40 + k45). Body-weight scaling: paper Eq 5
(linear-proportional 'slope without intercept') with reference 65.5 kg
applied to CL_MPA/F, Q/F, and V_3/F via fixed allometric exponent 1.
Cross-parameter IIV linkage: eta(CL_MPAG/F) = psi_q_cl_mpag * eta(Q/F)
reproduces the paper's joint eta structure where psi_q_cl_mpag is the
paper's 'q' parameter. UGT1A9 polymorphisms were screened but not
retained in the final model (no significant effect). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Park_2023_mycophenolic_acid.html">Mycophenolic
acid (Park 2023)</a> </td>
<td style="text-align:left;"> Population PK model for total
mycophenolic acid (MPA, the active moiety of mycophenolate mofetil MMF)
in pediatric allogeneic haematopoietic stem cell transplantation (HSCT)
recipients receiving oral MMF for acute graft-versus-host disease
prophylaxis or treatment (Park 2023). One-compartment disposition with
first-order absorption and no lag time (NONMEM ADVAN2 TRANS2). Body
surface area is the only retained covariate, entering the apparent
volume of distribution as a centered-linear term Vd/F = 89.83 * (1 +
0.854 * (BSA - 1.11)). Inter-individual variability is log-normal on
CL/F and Vd/F; residual error is combined proportional plus additive.
Doses are MMF mass (mg) with no MMF-to-MPA molecular-weight conversion
-- CL/F and Vd/F are apparent parameters that absorb both the
molecular-weight ratio and oral bioavailability. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Sherwin_2012_mycophenolic_acid.html">Mycophenolic
acid (Sherwin 2012)</a> </td>
<td style="text-align:left;"> Pediatric / adolescent
enterohepatic-recirculation population PK model for mycophenolic acid
(MPA) and its main inactive metabolite 7-O-MPA-glucuronide (MPAG) in
patients with childhood-onset systemic lupus erythematosus (cSLE) on
oral mycophenolate mofetil (MMF) (Sherwin 2012; n = 19, age 10-28
years). Absorption uses a Savic 2007 transit-compartment chain (number
of compartments NN = 8.2 estimated, mean transit time MTT = 1.1 h
estimated) feeding the gut compartment, which delivers MPA into the
central compartment at a fixed first-order absorption rate constant Ka =
1.5 1/h. MPA follows two-compartment disposition (CL1/F, V3/F central;
CL2/F, V4/F peripheral). The fraction FM of total MPA elimination is
converted to MPAG (FM fixed at 0.85; the remaining 0.15 is metabolism to
AcMPAG, not contained in the model). MPAG follows one-compartment
disposition with V_MPAG fixed equal to V3 MPA and apparent renal
clearance CLM/F. Total MPAG elimination is partitioned into renal ((1 -
FMPAG) fraction) and biliary (FMPAG = 0.65 fraction, fixed). Biliary
MPAG enters a gallbladder compartment that empties to the gut during
fixed meal-time windows (1-2 h and 4-6 h post-dose); only a fraction EHC
= 0.35 (fixed) of the emptied gallbladder content is reabsorbed (the
rest is excreted in feces). Upon return to the gut compartment MPAG is
reconverted to MPA and re-enters the absorption pathway via Ka,
generating the characteristic secondary peak. The model() block
hardcodes the BID dose interval (tau = 12 h) so the meal-time windows
recur each interval; CL1/F, V3/F, CL2/F, V4/F, and CLM/F carry
exponential IIV (paper-reported CV%). Inter-individual variability and
residual error follow the source Table 3. No covariates entered the
final model: bodyweight, age, sex, race, ethnicity, and disease duration
were screened and rejected (see covariatesDataExcluded). Dose unit is
MPA-mass-equivalent mg (MMF mg x 0.739 by molecular-weight ratio MPA/MMF
= 320.3 / 433.5). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Yu_2017_mycophenolic_acid.html">Mycophenolic
acid (Yu 2017)</a> </td>
<td style="text-align:left;"> Two-compartment population
pharmacokinetic model with first-order oral absorption (no lag) for
mycophenolic acid (MPA, the active component of mycophenolate mofetil,
MMF) in Chinese adult renal transplant recipients (Yu 2017). Apparent
clearance CL/F follows a linear-additive covariate model in body weight
and serum creatinine (CL/F = 0.0916 * BW + 0.0417 * Scr + 7.98 L/h);
apparent central volume V1/F follows a linear-additive covariate model
in the UGT2B7 211G>T (rs7438135) genotype (V1/F = 14.7 + 7.72 *
UGT2B7 L) where the paper's ordinal genotype code maps 211GT to 1, 211GG
to 2, and 211TT to 3. Residual error is combined proportional plus
additive on plasma MPA. Interoccasion variability (13.7% CV on CL/F and
V1/F) reported by the paper is documented in the vignette but not
encoded in this typical-value model because Karlsson-Sheiner IOV
requires per-occasion etas and an OCC data column; the IIV-only encoding
remains usable for typical-value and IIV-only simulations. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Zeng_2010_mycophenolic_acid.html">Mycophenolic
acid (Zeng 2010)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model with first-order absorption for mycophenolic acid (MPA, the active
moiety of mycophenolate mofetil MMF) in children and young people
undergoing blood or marrow, kidney, and liver transplantation (Zeng
2010, Br J Clin Pharmacol). Both intravenous (2 h infusion to the
central compartment) and oral (depot with first-order absorption rate ka
and bioavailability F) routes were modelled jointly. Apparent clearance
CL/F (combined IV/oral typical value) varies linearly with body weight
via (1 + theta_WT * WT/27.9) where 27.9 kg is the cohort median, and
additively with concomitant calcineurin-inhibitor type via (1 +
theta_CYTA * CYTA): CYTA = 0 on ciclosporin (the reference; n = 23) and
CYTA = 1 on tacrolimus (n = 15) (Zeng 2010 Table 2 model 4). Ciclosporin
inhibits MRP2-mediated biliary efflux of MPAG and thus suppresses
enterohepatic recirculation of MPA, so paediatric MPA CL/F is
approximately 2.5x higher under ciclosporin (CYTA = 0; multiplier 1.0)
than under tacrolimus (CYTA = 1; multiplier 1 + (-0.60) = 0.40).
Inter-individual variability is diagonal on CL, ka, and F; residual
error is exponential (log-normal) with SD 0.48 on the log scale.
Inter-occasion variability of 5.8% CV on CL/F reported in Zeng 2010
Table 3 (with occasion defined as 7 days in patients on daily MMF) is
NOT encoded structurally here because the model-library use case does
not define an operational occasion column; downstream users who want to
simulate IOV can add an OCC indicator and a per-occasion eta in rxode2.
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Zhao_2010_mycophenolic_acid.html">Mycophenolic
acid (Zhao 2010)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model for mycophenolic acid (MPA, the active moiety delivered as oral
mycophenolate mofetil MMF) in children with idiopathic nephrotic
syndrome (Zhao 2010). First-order absorption (ka = 5.16 1/h) with
absorption lag time (tlag = 0.215 h) into a central compartment.
Apparent oral clearance CL/F (typical value 9.7 L/h at the cohort
medians WT = 23.5 kg, ALB = 38.6 g/L) is modeled with two covariates: a
power effect of body weight on CL/F with exponent 0.753 referenced to
23.5 kg (close to allometric but estimated, not fixed), and an unusual
linear-in-ratio effect of serum albumin in the form CL/F = q1 *
(WT/23.5)^q2 * [1 - q3 * (ALB/38.6)] with q1 = 22.5 L/h, q2 = 0.753, q3
= 0.570 (higher serum albumin reduces apparent CL/F, consistent with
stronger MPA-albumin binding in nephrotic patients with restored
albumin). Apparent central V1/F = 22.3 L; apparent peripheral V2/F was
fixed at 250 L (estimation between 100 and 600 L was non-identifiable;
the fixed value lies in the range reported for adult transplant
cohorts). Apparent inter-compartment clearance Q/F = 18.8 L/h.
Exponential inter-individual variability is estimated on lag time, V1/F,
Q/F, and CL/F (no IIV on ka or V2/F). A proportional residual error
(44.6%) on MPA plasma concentration completes the model. Dosing in this
packaged form is in mg of MMF; the MMF-to-MPA hydrolysis is implicit in
the apparent bioavailability F. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Chen_2014_nab_paclitaxel.html">Nab
paclitaxel (Chen 2014)</a> </td>
<td style="text-align:left;"> Three-compartment population PK
with saturable (Michaelis-Menten) distribution between the central and
first peripheral compartments and saturable elimination from the central
compartment, coupled with a Friberg-style 5-compartment semi-mechanistic
PD model for paclitaxel-induced neutropenia, fit to 150 adult patients
with advanced solid tumors who received nab-paclitaxel (Abraxane) 80-375
mg/m^2 as a 30-minute IV infusion (Chen 2014). The first peripheral
compartment exchanges with central via the saturable Vmtr / Kmtr
process; the second peripheral compartment exchanges via linear
intercompartmental clearance Q2. Baseline albumin lowers the maximal
elimination rate VMEL via a power-form covariate; advanced age (>= 65
years) potentiates the linear Slope of paclitaxel-driven inhibition of
the proliferating neutrophil precursor pool, and baseline albumin also
modifies the baseline ANC via a power-form covariate. PK observation is
plasma paclitaxel concentration (ug/L = ng/mL); PD observation is
absolute neutrophil count (10^9 cells/L). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Chen_2024_guhongInjection.html">NAcetylglutamine
rat (Chen 2024)</a> </td>
<td style="text-align:left;"> Preclinical (rat).
Two-compartment intravenous pharmacokinetic model for
N-acetyl-L-glutamine (NAG), one of eight constituents of guhong
injection (GHI) quantified in plasma, in male Sprague-Dawley rats
subjected to 30 min left-anterior-descending ligation followed by 1 h
reperfusion (myocardial ischemia/reperfusion, MI/R) (Chen 2024). GHI was
given as a single tail-vein injection of 2.5, 5 or 10 mL/kg; the
N-acetyl-L-glutamine dose is the GHI volume dose times its content in
GHI (30 mg/mL), i.e. 75 mg/kg, 150 mg/kg, 300 mg/kg. Disposition was
fitted separately in each dose group with Drug and Statistics (DAS)
v3.2.6, so V1, V2, CL1 and Q are selected from the covariate
DOSE_GHI_MLKG rather than through a dose-covariate function the authors
did not fit. Direct-effect sigmoid-Emax models link the
N-acetyl-L-glutamine plasma concentration to the GHI-minus-model-group
difference in creatine kinase-MB (CK-MB), ischemia-modified albumin
(IMA), cardiac troponin I (cTn I) and alpha-hydroxybutyrate
dehydrogenase (alpha-HBDH) (E = Emax * C^gamma / (ED50^gamma + C^gamma);
Tables 12, 13, 14, 15). Chen 2024 fitted a PK/PD model only for the
analyte/biomarker/dose combinations whose PLSR coefficient was negative,
so the effect of an unfitted combination is returned as zero rather than
extrapolated. No between-subject variability or residual error was
reported; every parameter is fixed at the published mean and the
residual SDs are fixed at zero. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Chen_2024_nadroparin.html">Nadroparin
(Chen 2024)</a> </td>
<td style="text-align:left;"> One-compartment population PK
model with first-order subcutaneous absorption and first-order
elimination for nadroparin (a low-molecular-weight heparin) in 40
preterm and term neonates and infants under 8 months of age treated for
arterial or venous thromboembolic disease (Chen 2024). The model is
fitted to plasma anti-Xa activity (IU/mL) rather than to a drug
concentration, so the disposition parameters are apparent anti-Xa
clearance (CL/F) and apparent anti-Xa volume of distribution (Vd/F). The
single retained covariate is Schwartz-formula creatinine clearance on
CL/F, entered as a median-normalised power model CL/F = 0.211 * (CRCL /
51.1)^0.238, consistent with nadroparin being cleared predominantly by
renal excretion. Inter-individual variability was retained on CL/F only;
the variances on Vd/F and ka approached zero during model building and
were fixed to zero. Body-weight allometric scaling with a fixed 0.75
exponent and a sigmoid Emax postmenstrual-age maturation function were
both tested but were not retained in the final model once creatinine
clearance was included. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Kyhl_2016_nalmefene.html">Nalmefene
(Kyhl 2016)</a> </td>
<td style="text-align:left;"> Population PK model for nalmefene
in healthy volunteers (Kyhl 2016): two-compartment model with
first-order absorption after oral dosing, separate absorption rates for
tablet and solution formulations, and a link to mu-opioid receptor
occupancy. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Laffont_2024_nalmefene.html">Nalmefene
(Laffont 2024)</a> </td>
<td style="text-align:left;"> Population PK model for
intranasal (IN) nalmefene HCl in healthy adult volunteers (Laffont
2024): two-compartment model with linear elimination, parallel
zero-order plus lagged first-order absorption, and allometric
body-weight scaling on apparent clearance. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Dowling_2008_naloxone.html">Naloxone
(Dowling 2008)</a> </td>
<td style="text-align:left;"> Three-compartment population PK
model for naloxone in six healthy male volunteers receiving 0.8 mg
intravenous, 0.8 mg intramuscular, 0.8 mg intranasal, 2 mg intravenous,
and 2 mg intranasal doses in an open-label crossover design (Dowling
2008). Intramuscular and intranasal absorption are modeled as
first-order via separate depot compartments (Ka_im 0.65 1/h, F_im 0.36;
Ka_in 1.52 1/h, F_in 0.038); intravenous doses go directly to the
central compartment (F 1, structural anchor). Fat-free mass
(Janmahasatian 2005 formula, called LBW2005 in the paper) is
allometrically scaled on clearance with fixed exponent 0.75, and body
weight is linearly scaled on central volume (exponent 1); both effects
use a 70 kg reference. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Laffont_2024_naloxone.html">Naloxone
(Laffont 2024)</a> </td>
<td style="text-align:left;"> Population PK model for
intranasal (IN) naloxone HCl in healthy adult volunteers (Laffont 2024):
two-compartment model with linear elimination and parallel zero-order
plus lagged first-order absorption; Q/F and Vp/F fixed to literature
values from Yassen 2007. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Sharma_2018_naltrexone_bupropion.html">Naltrexone
bupropion (Sharma 2018)</a> </td>
<td style="text-align:left;"> Dose- and time-dependent
population pharmacodynamic (DTPD) body-weight model for the
naltrexone/bupropion fixed-dose combination (Contrave) in obese and
overweight adults under lifestyle intervention, based on 4591 subjects
pooled from six Contrave clinical trials (placebo and active-treatment
arms). Indirect-response body-weight model with linear NHANES-derived
disease progression, inverse-Bateman lifestyle-intervention stimulation
of body-weight loss (kout), and a combined Emax dose- and time-dependent
inhibitory drug effect; diabetes (T2DM) and race covariates on key
parameters. Does not include the linked Markov dropout layer (Tr10,
Tr01, Tr12, Tr02) of Table 3, and does not include the PPPD
concentration-driven variant (whose underlying naltrexone/bupropion
PopPK model is an unpublished internal Takeda report). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Bjornsson_2011_naproxcinod.html">Naproxcinod
(Bjornsson 2011)</a> </td>
<td style="text-align:left;"> Joint population PK / pain
intensity (PI) / informative-dropout model for naproxen following oral
administration of naproxcinod (a naproxen nitrate ester prodrug),
naproxen, or placebo after wisdom-tooth extraction (Bjornsson 2011, 242
patients with moderate-to-severe post-surgical dental pain). PK:
one-compartment disposition of unbound naproxen with parallel Savic
transit-compartment absorption chains for naproxcinod (MTT 1.77 h, NN
3.58) and naproxen (MTT 0.500 h, NN 4.23) feeding a shared central
compartment. Total naproxen is computed from unbound via a saturable
albumin-binding equation Ctot = Cu + Bmax * Cu / (Km + Cu) (Bmax = 643
umol/L, Km = 0.549 umol/L). Relative bioavailability of naproxen via
naproxcinod vs naproxen is 59.7%. PD: pain intensity on a 100-mm visual
analogue scale modeled as PI(t) = PI_baseline * (1 - placebo(t)) * (1 -
drug(t)), where placebo(t) = Pmax * (1 - exp(-kpl * t)) (Pmax 20.2%, kpl
0.237 /h; additive IIV on Pmax allows individual PI to either decrease
or increase from baseline) and drug(t) is a sigmoid Emax function of
unbound naproxen with Emax fixed at 1, EC50 0.135 umol/L, and Hill
exponent 1.61. TTE: rescue-medication request modeled as a Weibull
hazard (lambda 0.00999, alpha 0.729) with log-linear covariate effects
of PI(t) and (PI_baseline - 55) on the slope of PI(t); the hazard is set
to zero for t < 1.5 h to reflect the protocol's rescue-medication
abstention window. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Boucher_2018_naproxen_mbma.html">Naproxen
mbma (Boucher 2018)</a> </td>
<td style="text-align:left;"> MBMA. Model-based meta-analysis
longitudinal time-course Emax model for the Western Ontario and McMaster
Universities (WOMAC) pain score (0-10 scale) in adults with
osteoarthritis, fitted to study-arm-mean data from 18 randomized
double-blind placebo-controlled trials of naproxen vs placebo (12 flare
designs, 6 non-flare). The WOMAC pain response over time follows a
three-parameter Emax model in time: pain = E0 + Emax * time / (ET50 +
time), where ET50 is the time to half-maximal effect. Flare design
shifts both baseline E0 and Emax; naproxen treatment shifts Emax and
shortens ET50 (faster onset: ET50 0.21 week vs placebo 0.69 week).
Between-study variability is carried as study-arm-level random effects
on E0 (SD 0.62) and Emax (SD 0.74); the residual describes
study-arm-mean variability weighted by each arm's observed standard
error (sigma fixed to 1). Suitable simulation scope is study-arm-mean
WOMAC pain time-course, NOT individual-patient pain scores. Parameter
values are the NONMEM column of Table 2 (the same model was fit in
NONMEM, BUGS, and R with closely agreeing estimates). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Long_2017_necitumumab.html">Necitumumab
(Long 2017)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model for necitumumab in cancer patients (Long 2017), with IV infusion
input and parallel linear plus Michaelis-Menten (target-mediated)
elimination from the central compartment and allometric weight scaling
on CL, Q, V1, and V2. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Djerada_2014_nefopam.html">Nefopam
(Djerada 2014)</a> </td>
<td style="text-align:left;"> Joint parent + metabolite
population PK model for nefopam (2-compartment; IV zero-order infusion
into central) and its N-demethyl metabolite desmethyl-nefopam
(1-compartment; fed by an apparent metabolic clearance K13 from the
nefopam central compartment) in 48 elderly patients (65-99 years) with
normal, moderate, or severe renal impairment after a single 20 mg 30 min
IV nefopam infusion for postoperative analgesia (hip-fracture repair).
Fit in Monolix v4.1 with SAEM. No covariates were retained in the final
model despite an extensive screen (age, sex, weight, height, BMI, LBW,
FFM, IBW, BSA, iohexol-clearance GFR, MDRD GFR, and Cockroft-Gault GFR);
severe renal impairment (GFR <= 30 mL/min) correlated post-hoc with
reduced nefopam clearance and higher AUC0-infinity by Spearman test but
did not meet the model-building inclusion criteria. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Hirt_2006_nelfinavir.html">Nelfinavir
(Hirt 2006)</a> </td>
<td style="text-align:left;"> Population PK model for oral
nelfinavir and its active metabolite M8 (hydroxy-tert-butylamide) in 182
pediatric HIV-1 infected children aged 3 days to 17 years (Hirt 2006).
One-compartment model for nelfinavir (depot + central) with first-order
absorption (Ka) and linear elimination via apparent total clearance
CL_T/F; the active metabolite M8 is described by a single compartment
(central_m8) with apparent volume FIXED to 1 L (not identifiable). Only
the fraction F_MT (~2.5%) of nelfinavir's total clearance enters M8; the
remainder is lost to non-M8 elimination pathways. Body-weight scaling is
linear (per-kg parameterisation of V/F and CL/F); both V/F and CL/F
decrease with age via a shared power exponent of -0.29 relative to the
median age 8.2 years. M8 elimination rate KM0 is increased ~1.9-fold by
concomitant administration of an enzyme-inducing NNRTI (efavirenz or
nevirapine, pooled under the indicator CONMED_NNRTI_IND consistent with
the paper's finding that the two drugs' inducer effects on KM0 were not
significantly different and the two were never administered
simultaneously). Inter-individual variability on V/F, CL/F, and KM0;
correlation 0.45 between IIVs on CL/F and KM0; additive residual error
in mg/L for each output. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Hirt_2007_nelfinavir.html">Nelfinavir
(Hirt 2007)</a> </td>
<td style="text-align:left;"> Six-compartment population
pharmacokinetic model for nelfinavir and its M8 metabolite describing
placental transfer from maternal plasma into umbilical (cord) plasma and
amniotic fluid (Hirt 2007). Oral nelfinavir is absorbed first-order with
a lag time into the maternal central compartment. Nelfinavir is then (i)
eliminated, (ii) converted to M8 in a maternal M8 compartment, and (iii)
transferred to a cord nelfinavir compartment. M8 is eliminated from the
mother and transferred to a cord M8 compartment. Both nelfinavir and M8
transfer from cord to amniotic fluid and are eliminated from amniotic
fluid by first-order rate constants. The distribution volume of M8 in
the mother and the volumes of all cord and amniotic-fluid compartments
were not estimable and are fixed at 1 L per the paper. Covariate
effects: day-of-delivery indicator increases maternal nelfinavir CL and
V each by 92 percent and gates a body-weight effect on CL within the
delivery cohort only (reference 73 kg, exponent 2.81); pregnancy
increases M8 elimination by 67 percent; body weight scales M8
elimination on the full database (reference 63 kg, exponent 1.41);
concomitant NNRTI use increases M8 elimination by 148 percent.
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Chen_2023_nemonoxacin.html">Nemonoxacin
(Chen 2023)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model for oral nemonoxacin capsules in Chinese adults, pooled across
phase I to III trials (Chen 2023; n = 161 subjects / 195 cases; 2007
plasma concentrations). First-order absorption with a lag time and
estimated relative bioavailability. Clearance is an additive linear
function of Cockcroft-Gault creatinine clearance (10.3 L/h intercept +
0.026 L/h per mL/min), and allometric body-weight scaling is fixed at
0.75 on CL / Q and 1 on Vc / Vp with a 70 kg reference. Covariate
effects: female sex lowers Vc by 11%; community-acquired pneumonia
raises Vp by 23%; food slows absorption (ka x 0.44), lengthens the lag
time (T_lag x 1.6), and lowers bioavailability (F x 0.88).
Inter-occasion variability on CL distinguishes the single-dose occasion
from steady state (72 h after the first of multiple doses). The paper's
companion PK/PD analysis is an exposure-response logistic regression on
AUC0-24/MIC, Cmax/MIC and %T > MIC; its regression coefficients are
not reported, so only the population PK layer is encoded here (the
published PK/PD targets are reproduced in the validation vignette).
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Kemal_2026_nemtabrutinib.html">Nemtabrutinib
(Kemal 2026)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model for nemtabrutinib (oral BTK inhibitor) in adults with hematologic
malignancies including CLL/SLL (Kemal 2026, full covariate model)
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Bienczak_2016_nevirapine.html">Nevirapine
(Bienczak 2016)</a> </td>
<td style="text-align:left;"> One-compartment population PK
model for oral nevirapine in African children (Bienczak 2016) with
three-transit-compartment absorption, semi-mechanistic well-stirred
hepatic extraction (Gordi-style) splitting oral bioavailability into a
pre-hepatic component FpreH (age-driven exponential maturation toward an
older-child reference fixed to 1) and a hepatic component FH derived
algebraically from intrinsic clearance CLint via FH = QH / (QH + fu *
CLint), allometric scaling of CLint and Vc to median weight 14.5 kg and
of hepatic plasma flow QH to a 70 kg reference, CYP2B6 516G>T |
983T>C metabolizer-status (EM / IM / SM / USM) effects on CLint, and
a 29% diurnal-variation cosine on CLint with zenith at noon. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Schipani_2011_nevirapine.html">Nevirapine
(Schipani 2011)</a> </td>
<td style="text-align:left;"> One-compartment population PK
model for oral nevirapine in HIV-infected adults (Schipani 2011), with
CYP2B6 516G>T (rs3745274) and 983T>C (rs28399499) genotype and
body-weight covariate effects on CL/F. Covariate effects are additive on
linear-scale CL/F per the published equation. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Svensson_2012_nevirapine.html">Nevirapine
(Svensson 2012)</a> </td>
<td style="text-align:left;"> One-compartment population PK
model for oral nevirapine in HIV-infected South African adults (Svensson
2012, the multi-source 'mega-model' integration paper) with first-order
absorption through two transit compartments (Savic 2007
parameterisation, ktr = (NTRANS+1)/MTT shared across all transit-rate
steps), a two-population mixture on apparent oral clearance CL/F (fast
eliminators 3.12 L/h at 82.7% probability vs slow eliminators 1.45 L/h
at 17.3% probability, the slow class associated by the paper Discussion
with CYP2B6 516TT homozygotes), Anderson-Holford allometric scaling
(fat-free mass at exponent 0.75 for CL/F with reference FFM 42 kg
corresponding to a 70 kg / 1.6 m woman, body weight at exponent 1 for
V/F with reference WT 70 kg, both exponents fixed), a fed/fasted binary
covariate on absorption mean transit time MTT (2.46 h fed vs 0.596 h
fasted, a 4.1-fold slowing of absorption with food) and a concomitant
tuberculosis-treatment (rifampicin + isoniazid +/- ethambutol) effect on
bioavailability F (39% decrease; F = 0.613 when on TB treatment vs F =
1.0 reference, with an additional 34.1% between-subject variability
specific to the TB-treatment effect). Residual error is proportional
(8.41% CV). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Iida_2008_nicorandil.html">Nicorandil
(Iida 2008)</a> </td>
<td style="text-align:left;"> Two-compartment IV PK plus
inhibitory Emax PD plus asymptotic- exponential disease-progression
population PKPD model for nicorandil in acute heart failure (AHF)
patients with pulmonary artery wedge pressure (PAWP, mmHg) as the
haemodynamic biomarker (Iida 2008 model 10). Five clinical studies
pooled: 11 healthy volunteer subjects (concentration only) and 94 AHF
patients (concentration plus PAWP), 618 nicorandil and 559 PAWP
observations. Allometric size scaling with a 70 kg reference (exponent
0.75 on CL and Q per paper Equation 5; canonical exponent 1.0 on V1 and
V2 per Holford 1996). AHF-vs-healthy disease cohort modifies all four PK
parameters multiplicatively (FCL = 1.94, FV1 = 1.39, FQ = 0.519, FV2 =
4.06; paper Table 2). PD layer: inhibitory Emax model on plasma
concentration (no effect compartment, paper Results paragraph
'Pharmacodynamic analysis'), summed with an asymptotic-exponential
disease- progression term that decreases PAWP from a baseline S0 to a
steady-state Sss with half-life Tprog. Inhibitory maximum Emax = -11.7
mmHg, EC50 = 423 ng/mL, S0 = 25.6 mmHg, Sss = 19.5 mmHg, Tprog = 5.83 h.
Bootstrap median final estimates. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Ahlstrom_2010_nicotinicAcid_rat.html">NicotinicAcid
rat (Ahlstrom 2010)</a> </td>
<td style="text-align:left;"> Preclinical (rat). PK/PD feedback
model for nicotinic acid (NiAc) and non-esterified fatty acids (NEFA) in
male Sprague-Dawley rats following IV infusions. NiAc disposition is a
two-compartment model with two parallel capacity-limited
(Michaelis-Menten) elimination processes (likely glycine conjugation and
amidation) plus endogenous synthesis. NEFA turnover is described by an
inhibitory drug-mechanism function (Hill-Imax, with Imax fixed at 1)
acting on the formation of NEFA, coupled to a moderator feedback chain
of 8 transit compartments (precursor1..precursor8): the first
compartment inhibits NEFA formation amplified by exponent p and the last
compartment stimulates NEFA loss. A NiAc-independent capillary release
rate kcap sets the lower physiological limit of NEFA in plasma. All
structural parameters are body-weight-normalized (per kg). Parameter
values from Ahlstrom 2010 Tables 1 (NiAc PK) and 2 (NEFA PD).
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Castro-Surez_2020_nimotuzumab.html">Nimotuzumab
(Castro-Surez 2020)</a> </td>
<td style="text-align:left;"> Semi-mechanistic two-compartment
QSS TMDD population PK model for nimotuzumab (anti-EGFR humanized IgG1)
in adults with autosomal dominant polycystic kidney disease
(Castro-Suarez 2020); EGFR binding represented in both central (Rtot)
and peripheral (Rtotp) compartments under quasi-steady-state, plus a
turnover mediator that stimulates non-specific clearance via a sigmoid
Emax of free central nimotuzumab. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Schmid_2017_nintedanib.html">Nintedanib
(Schmid 2017)</a> </td>
<td style="text-align:left;"> Population pharmacokinetic model
of nintedanib and its main hydrolytic metabolite BIBF 1202 (Schmid
2017): a one-compartment first-order absorption + lag parent
(nintedanib) jointly fit with a one-compartment first-order absorption +
lag metabolite (BIBF 1202) coupled to the parent via a fixed fractional
formation-during-elimination term (kmet = CL/V2 * ffM) and a fixed V3/V2
volume ratio inherited from rat IV data. The 1191-patient pooled data
set spans four trials in NSCLC (Reck 2011 NSCLC phase II, LUME-Lung 1,
LUME-Lung 2) and IPF (TOMORROW). Covariates include allometric body
weight on CL, linear age on F1, smoking-status on F1, ethnic-origin
composite (Indian/Chinese/Taiwanese vs Korean vs reference) on F1,
study-group effects on F1 and ka, and on the metabolite side body weight
on F2 with ethnic-origin (Indian alone, non-Indian Asian) on F2, ECOG
status, LDH (hockey-stick), study-group effect on ka2, and NSCLC
histology on ka2. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Valenzuela_2025_nipocalimab.html">Nipocalimab
(Valenzuela 2025)</a> </td>
<td style="text-align:left;"> Integrated PK/RO/IgG/MG-ADL QSS
TMDD model for nipocalimab in healthy adults and generalized myasthenia
gravis (Valenzuela 2025) </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Chan_2023_nirmatrelvir.html">Nirmatrelvir
(Chan 2023)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model with first-order absorption for nirmatrelvir coadministered with
ritonavir 100 mg (PAXLOVID) in adults with and without COVID-19 (Chan
2023; pooled analysis of 8 phase I and phase II/III studies, N = 1237).
Allometric baseline body weight on clearances (fixed 0.75) and volumes
(fixed 1) referenced to 70 kg; a breakpoint power model for
BSA-normalized creatinine clearance on CL (CL scales with nCLCR below
the estimated 70.1 mL/min/1.73 m2 breakpoint and is independent of nCLCR
at or above it); fractional carbamazepine, itraconazole and COVID-19
effects on CL; a power effect of age on central volume referenced to 45
years; and a relative-bioavailability model combining a dose power
function (referenced to 300 mg) with a fractional 150-mg-tablet
formulation effect. Combined additive plus proportional residual error
with separate proportional magnitudes for the phase I and phase II/III
data. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Clegg_2024_nirsevimab.html">Nirsevimab
(Clegg 2024)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model for nirsevimab in preterm and term infants (Clegg 2024)
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Landersdorfer_2013_nisin_amikacin_linezolid.html">Nisin
amikacin (Landersdorfer 2013)</a> </td>
<td style="text-align:left;"> In vitro (methicillin-resistant
Staphylococcus aureus USA300). Mechanism-based pharmacodynamic model for
nisin plus amikacin in a 48-h static-concentration time-kill assay
(S-ADAPT and NONMEM analyses; subpopulation synergy concept). Six
pre-existing bacterial populations crossing nisin (susceptible Nis-S,
intermediate Nis-I, resistant Nis-R) with amikacin (susceptible Ami-S,
resistant Ami-R) susceptibility, each following a Bulitta two-state
life-cycle growth model (state 1 -> state 2 -> 2*state 1 with
replication rate k21 fixed). Nisin kills with a second-order function
(k2*Cnis) and amikacin with a saturating Hill function; a saturating
carrying-capacity replication factor (REP = 2*CFUmax/(CFUmax + CFUall))
caps the population. Nisin- and amikacin-cross-resistant populations
carry reduced biofitness (multiplicative growth-rate factor fk12). Nisin
and amikacin concentrations are external time-varying inputs (covariates
Cnis and Cami); the model contains no human PK component. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Landersdorfer_2013_nisin_amikacin_linezolid.html">Nisin
linezolid (Landersdorfer 2013)</a> </td>
<td style="text-align:left;"> In vitro (methicillin-resistant
Staphylococcus aureus USA300). Mechanism-based pharmacodynamic model for
nisin plus linezolid in a 48-h static-concentration time-kill assay
(S-ADAPT and NONMEM analyses; subpopulation synergy concept). Three
pre-existing bacterial populations (Nis-S/Lin-S, Nis-I/Lin-S,
Nis-R/Lin-I), each following a Bulitta two-state life-cycle growth
model. Nisin kills with a second-order function (k2*Cnis); linezolid
inhibits protein synthesis (turnover of a protein pool P), which (i)
raises Inh_Rep = 1 - P and therefore reduces successful replication for
the Lin-S populations and (ii) inhibits the slow state 1 -> state 2
growth-rate transition via a steep Hill function (Inh_k12) in all three
populations. The Nis-R/Lin-I population has no Inh_Rep effect (only
Inh_k12). A saturating carrying-capacity replication factor (REP =
2*CFUmax/(CFUmax + CFUall)) caps the population. Nisin and linezolid
concentrations are external time-varying inputs (covariates Cnis and
Clin); the model contains no human PK component. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Sharma_2023_nitrofurantoin.html">Nitrofurantoin
human pbpk (Sharma 2023)</a> </td>
<td style="text-align:left;"> PBPK (whole-body, GNU MCSim 6.1,
age-dependent physiology). Nitrofurantoin (NFT) disposition in human
adults -- Sharma 2023 'Model V5a' extrapolated across species WITHOUT
further calibration, the paper's final human model. Same thirteen
mass-balance amount states and same structure as the rabbit and rat
siblings (perfusion-rate-limited distribution, glomerular filtration +
saturable active tubular secretion - first-order tubular reabsorption,
Michaelis-Menten hepatic metabolism, saturable hepatobiliary efflux with
enterohepatic recirculation). Three things are human-specific. (1)
Physiology is not a fixed reference adult: height, body weight, cardiac
output, liver / kidney / fat / plasma volumes and liver / kidney / fat
blood flows are all AGE- and SEX-dependent polynomials, so AGE and SEXF
are genuine covariates that reshape the whole body. (2) Renal and
metabolic parameters are allometrically scaled from the RABBIT fit and
the enterohepatic-recirculation and gut-absorption parameters from the
RAT fit, each as parameter * (BW_species / BW_human)^0.25. (3) Renal
function is an explicit input: CRCL carries the subject's absolute
glomerular filtration rate in mL/min, which lets the model reproduce the
paper's renal-insufficiency analysis (Figure 7) showing that a fall from
normal to severely compromised GFR raises plasma Cmax ~1.3-fold, trough
~2-fold and AUC ~1.3-fold while substantially cutting urinary NFT
delivery -- simultaneously raising hepatic exposure (a DILI risk) and
undercutting efficacy at the bladder. Between-subject variability is a
lognormal geometric SD of 1.17 (~16% CV) applied to all 18 drug-specific
parameters, as in the paper's Monte-Carlo simulations; the model has no
human-fitted parameters at all, so every human prediction is a genuine
extrapolation. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Sharma_2023_nitrofurantoin.html">Nitrofurantoin
rabbit pbpk (Sharma 2023)</a> </td>
<td style="text-align:left;"> Preclinical (rabbit). PBPK
(whole-body, GNU MCSim 6.1, Bayesian MCMC). Nitrofurantoin (NFT)
disposition in rabbits -- Sharma 2023 'Model V5a', the paper's final
structure. Thirteen mass-balance amount states: gut lumen, gut tissue,
liver, cumulative hepatic metabolism, bile, cumulative faeces, kidney,
renal tubular filtrate, pre-void urine storage, fat, lumped rest of
body, plasma, cumulative urine. Perfusion-rate-limited tissue
distribution with a single combined plasma pool (no arterial/venous
split); only unbound drug (fu/Kbp, divided by each tissue:plasma
partition coefficient) distributes. Renal handling is deliberately
non-linear: passive glomerular filtration plus SATURABLE active tubular
secretion out of the kidney into the tubules, minus first-order tubular
reabsorption from the tubules back into the kidney -- the combination
the paper shows is required to reproduce the observed fall in fractional
urinary recovery from ~60% to ~10% over a 30-fold IV dose increase.
Hepatic elimination is Michaelis-Menten metabolism plus a second
saturable hepatobiliary efflux into bile, which returns to the gut lumen
at a first-order rate (enterohepatic recirculation, EHR). Renal
parameters were calibrated on rabbit IV plasma and urine data (model
V4); the EHR parameters are the rabbit arm of a hierarchical rat+rabbit
fit (model V5a), and are small in rabbits (biliary excretion < 1% of
dose), so EHR mainly adds late-phase biphasic plasma behaviour rather
than changing urinary recovery. Deterministic typical-value simulator:
the MCMC posterior describes PARAMETER UNCERTAINTY, not between-subject
variability, so no IIV is encoded (see the vignette Errata). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Sharma_2023_nitrofurantoin.html">Nitrofurantoin
rat pbpk (Sharma 2023)</a> </td>
<td style="text-align:left;"> Preclinical (rat). PBPK
(whole-body, GNU MCSim 6.1, Bayesian MCMC). Nitrofurantoin (NFT)
disposition in rats -- Sharma 2023 'Model V5a', the paper's final
structure. Structurally IDENTICAL to the rabbit sibling (see
modellib('Sharma_2023_nitrofurantoin_rabbit_pbpk')): thirteen
mass-balance amount states with perfusion-rate-limited distribution,
non-linear renal handling (glomerular filtration + saturable active
tubular secretion - first-order tubular reabsorption), Michaelis-Menten
hepatic metabolism, and saturable hepatobiliary efflux feeding an
enterohepatic recirculation loop. What differs is (a) rat physiology and
(b) the rat arm of the hierarchical enterohepatic-recirculation fit. The
renal and metabolic parameters were NOT refitted to rat data -- they are
the rabbit model V4 estimates carried over unchanged and rescaled by rat
body weight, which is what makes the rat plasma and urine predictions a
genuine cross-species test rather than a fit (Results 3.3: 'the fact
that the model was extrapolated from rabbits by adapting to known rat
physiology and that biochemical parameters were scaled just based on rat
body weight provides strong confidence'). The rat is the species that
supplied the biliary-excretion data, so its hepatobiliary efflux
capacity is ~24-fold higher than the rabbit's and enterohepatic
recirculation is a real feature of the rat plasma profile (visible
late-phase biphasic kinetics). The rat EHR estimates are also the ones
the human model inherits by allometric scaling. Deterministic
typical-value simulator: the MCMC posterior describes PARAMETER
UNCERTAINTY, not between-subject variability, so no IIV is encoded (see
the vignette Errata). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Bajaj_2017_nivolumab.html">Nivolumab
(Bajaj 2017)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model for nivolumab (anti-PD-1 IgG4) with time-varying clearance
(sigmoid Emax) in patients with advanced solid tumors (Bajaj 2017)
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Zhang_2019_nivolumab.html">Nivolumab
(Zhang 2019)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model with time-varying clearance for intravenous nivolumab (anti-PD-1
IgG4) in adults with advanced solid tumors, alone or in combination with
ipilimumab or chemotherapy (Zhang 2019) </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Oualha_2014_norepinephrine.html">Norepinephrine
(Oualha 2014)</a> </td>
<td style="text-align:left;"> Population PK/PD model for
continuous IV norepinephrine in hypotensive critically ill children
(Oualha 2014). One-compartment open PK with first-order elimination plus
an endogenous zero-order production rate q0 and
circulating-volume-anchored Vc = 0.08 * WT; allometric scaling of CL and
q0 on body weight (exponents fixed to 3/4). Emax PD sub-model on mean
arterial pressure (MAP) with a power-of-postmenstrual-age effect on
basal MAP0 and a categorical organ-dysfunction-count effect on the
maximal drug-induced MAP increase dMAP (32 mmHg for <=3 dysfunctions
vs 12 mmHg for >=4). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Chen_2024_noscapine.html">Noscapine
(Chen 2024)</a> </td>
<td style="text-align:left;"> Semi-mechanistic population PK
model for oral noscapine in healthy adults (Chen 2024) with zero-order
release into a four-compartment transit chain, an explicit liver
compartment that carries the profound hepatic first-pass extraction
(apparent clearance CL/F leaves the liver, not the plasma), and
three-compartment systemic disposition. Liver plasma flow Qh (55 L/h)
and liver volume Vh (1.5 L) are held fixed at physiologic values.
Apparent clearance carries a CYP2C9 genotype-predicted-phenotype effect
on three levels keyed to the CPIC activity score (extensive metabolizer
reference 958 L/h; intermediate metabolizer with activity score 1.5, 531
L/h; poor and intermediate metabolizers with activity score 1.0, 343
L/h) plus a total-body-weight power term (exponent 1.34, 77.3 kg
reference); inter-compartmental clearance to the first peripheral
compartment carries an age power term (exponent 0.348, 29 year
reference). Relative bioavailability of the reformulated test suspension
is 82.8% of the reference suspension. Correlated inter-individual
variability on absorption duration, CL/F, Vc/F and F1; inter-occasion
variability on the transit rate and on Qp1/F across the two crossover
periods; exponential residual error. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Biliouris_2018_nusinersen.html">Nusinersen
(Biliouris 2018)</a> </td>
<td style="text-align:left;"> Semimechanistic nine-compartment
population PK model of nusinersen (antisense oligonucleotide, Biogen
ISIS 396443) intended for extrapolation of nonhuman-primate (cynomolgus
monkey) fits to paediatric patients with spinal muscular atrophy,
following intrathecal lumbar-puncture bolus administration. Structure
(Biliouris 2018): CSF is the sampled dosing site, coupled
bidirectionally to three anatomically distinct spinal-cord segments
(cervical, thoracic, lumbar), to the brain (with a deeper brain-tissue
redistribution compartment), and to the pons; CSF also drains one-way
into the plasma / central compartment, which has its own peripheral
distribution and first-order elimination. Volumes scale linearly with
body weight relative to a 2.8 kg reference; rate constants scale as
(WT/2.8)^(-0.08); the CSF physiological volume V_CSF is overridden by a
stepwise paediatric-age function (120, 130, 135, 140 mL for age classes
<0.25, 0.25-0.5, 0.5-1, 1-2 years) rather than by WT. Residual error
is proportional per observed matrix; twelve exponential-IIV terms are
carried on the elimination and transfer rate constants and on the CSF /
plasma volumes. All THETA / OMEGA / SIGMA values are held FIXED from the
paper's final NONMEM simulation control stream on file. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Luu_2017_nusinersen.html">Nusinersen
(Luu 2017)</a> </td>
<td style="text-align:left;"> Four-compartment population PK
model for nusinersen (antisense oligonucleotide) following intrathecal
administration in pediatric patients with spinal muscular atrophy (Luu
2017): a CSF + CNS-tissue subsystem (intrathecal bolus enters the CSF)
coupled by a unidirectional CSF-to-plasma transport to a plasma +
systemic-tissue subsystem, with baseline body weight as a power
covariate on CL_p and V_CSF and a linear covariate on V_p. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Zhang_2011_nutlin3a.html">Nutlin3a
(Zhang 2011)</a> </td>
<td style="text-align:left;"> Preclinical (mouse). Whole-body
PBPK model for nutlin-3a (MDM2 inhibitor) in adult C57BL/6 mice after
intravenous and oral administration (Zhang et al. 2011, DMD). Thirteen
physiological tissue compartments (adipose, adrenal gland, bone marrow,
brain, intestine + lumen, liver, lung, muscle, retina, spleen, vitreous,
residual diffusion-limited tissue + residual vascular space) with
arterial and venous blood pools (75/25 split of total blood volume).
Perfusion-limited tissues use a partition coefficient K_i; the eye is
modelled as retina + vitreous coupled by a permeability-surface-area
product PA_VIT; the residual compartment is diffusion-limited (5%
vascular space, 95% tissue, coupled by PA_RES). Elimination is combined
linear (hepatic, k_e) and saturable Michaelis-Menten (arterial,
V_max/K_m). Oral absorption is first-order from an intestinal lumen
depot. Plasma protein binding is reported (B_max = 286 uM, K_A = 0.085
1/uM, Langmuir form) but is only used for an unbound-concentration
derivation that the paper applies to tissue exposure / IC50 comparisons,
not to the elimination ODEs; the ODE system operates on total
concentrations. The model is intended for typical-value simulation.
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Nagy_2017_obiltoxaximab.html">Obiltoxaximab
(Nagy 2017)</a> </td>
<td style="text-align:left;"> Preclinical and clinical (NZW
rabbit, cynomolgus macaque, human). Joint two-compartment population PK
model for obiltoxaximab, the anti-protective-antigen chimeric
IgG1(kappa) monoclonal antibody approved for inhalational anthrax under
the US FDA Animal Rule. One file carries the three species-specific
parameter sets used for animal-to-human dose translation (Nagy 2017
Supplementary Table S1), selected by the SPECIES_RABBIT /
SPECIES_MACAQUE indicators with human as the reference species. Animals
additionally have first-order intramuscular absorption (Ka, F1), and
anthrax-infected subjects carry a parallel Michaelis-Menten elimination
arm that approximates protective-antigen target-mediated drug
disposition. For infected humans the macaque nonlinear-clearance
component is carried over and allometrically scaled to human body size,
exactly as the paper does to project infected-human exposures.
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Nagy_2017_obiltoxaximab.html">Obiltoxaximab
survival (Nagy 2017)</a> </td>
<td style="text-align:left;"> Preclinical (NZW rabbit +
cynomolgus macaque). Weibull cure-rate (mixture) survival model for
obiltoxaximab treatment of inhalational anthrax, fit simultaneously to
infected rabbit and macaque survival data and used to justify the 16
mg/kg human dose under the US FDA Animal Rule. The cure fraction psurv
(probability of surviving to the Day-28 end of study) follows an Emax
dose-response on the logit scale with an exponentiated log10
prior-to-treatment (PTT) bacteremia term; the Weibull death-rate lambda
for the non-cured fraction is log-linear in log10 PTT bacteremia.
Species was investigated as a covariate but is not retained in the final
model. The model is algebraic and deterministic (no ODE state, no IIV,
no residual error): it returns the survivor function directly.
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Gibiansky_2014_obinutuzumab.html">Obinutuzumab
(Gibiansky 2014)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model of obinutuzumab (GA101, glycoengineered type II anti-CD20 mAb) in
adults with chronic lymphocytic leukemia (CLL) or non-Hodgkin lymphoma
(NHL); clearance is the sum of a time-independent component CL_inf and a
mono-exponentially decaying time-dependent component
CL_T*exp(-cl_exp_kdes*time), with histology (CLL / BCL / DLBCL / MCL),
baseline tumor size, body weight, and sex as covariates (Gibiansky
2014). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Yu_2022_ofatumumab.html">Ofatumumab
(Yu 2022)</a> </td>
<td style="text-align:left;"> Population PK / B-cell-count
model for subcutaneous ofatumumab in adults with relapsing multiple
sclerosis (Yu 2022) </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Chigutsa_2012_ofloxacin.html">Ofloxacin
(Chigutsa 2012)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model for oral ofloxacin in South African adults with
multidrug-resistant tuberculosis (MDR-TB) (Chigutsa 2012; n = 65; pooled
Cape Town and Durban cohorts). Savic 2007 transit-compartment absorption
chain (number of transit compartments NN = 6 estimated). Total apparent
oral clearance is an additive sum of two routes: a glomerular-filtration
component scaling linearly with creatinine clearance (CrCl computed by a
lean-body-weight modification of the Cockcroft-Gault equation; reference
68 mL/min), and an extraglomerular component (active tubular secretion +
minor biliary excretion) allometrically scaled to total body weight
(exponent 0.75 fixed, reference 70 kg). Central volume is allometrically
scaled to lean body mass (exponent 1 fixed, reference 46 kg LBM);
peripheral volume to total body weight (exponent 1, reference 70 kg);
intercompartmental clearance to total body weight (exponent 0.75,
reference 70 kg). Mean transit time is 2.4-fold longer when ofloxacin is
administered after a meal (Cape Town cohort, FED = 1) than fasted
(Durban cohort, FED = 0). F is fixed at 1; residual error is combined
additive (0.6 mg/L) and proportional (9.6%). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/PillaReddy_2013_panss_subscales.html">Olanzapine
panss subscales (PillaReddy 2013)</a> </td>
<td style="text-align:left;"> Population PK/PD model for
olanzapine against the three PANSS subscales (positive, negative,
general) in adults with schizophrenia from Pilla Reddy 2013 Part II. The
PK sub-model is the one-compartment olanzapine structural model from
Part I (PMID 23473810) Table 2: first-order absorption ka = 0.30 1/h,
apparent oral clearance CL/F = 21.8 L/h, apparent central volume of
distribution Vc/F = 700 L. The PD sub-model has three outputs that share
the Weibull placebo time- course form Pplacebo = Pmax * (1 -
exp(-(t/TD)^POW)) but each subscale carries its own placebo Pmax, TD,
POW (Part II Table 1) and olanzapine's own Emax / EC50 / KT triplet per
subscale (Part II Table 2). The KT for olanzapine PANSS positive and
general (0.048 and 0.035 1/day) is the
common-across-atypical-antipsychotic value (Part II Methods); the KT for
the negative subscale (0.028 1/day) was estimated separately per drug.
Olanzapine was numerically superior to the other SGAs for the negative
subscale (Emax = 0.33 vs 0.14-0.17 for the other SGAs; Part II Results),
making this a clinically meaningful subscale- specific comparison. The
exponential time-to-event dropout sub-model from Part II Table 4 is
documented in population$dropout_model but is not encoded in this
model body.
|
|
Olanzapine
rat (Johnson 2011)
|
Preclinical (rat). Mechanism-based hybrid physiology-based population
PK-PD model for olanzapine and striatal dopamine D2 receptor occupancy
(D2RO) in rats (Johnson 2011). Plasma PK is a 2-compartment model fitted
across IP, SC, and IV routes in Wistar / Sprague-Dawley rats (single
dose 0.01-40 mg/kg, pooled from 12 studies, n = 283); the absorption
rate constant was not estimable, so all routes deposit drug directly
into the central compartment, and the intraperitoneal bioavailability
FIP is estimated (about 64%) with an 87% CV log-normal IIV. SC and IV
bioavailability are fixed at 1. The brain submodel adds a brain-vascular
compartment (Vbv, fed by cerebral blood flow CLbv from systemic central)
and a brain- extravascular compartment (Vbev, fed across the BBB by an
estimated clearance CLbev applied to the unbound concentration on each
side via fixed fu_plasma and fu_brain). D2 receptor occupancy in
striatum is the reduced model published by the authors (Bmax dropped per
their sensitivity analysis): dRO/dt = kon * Cfree_bev * (1 - RO) - koff
* RO, with kon = koff/Kd and Cfree_bev = fu_brain * (Cbev in nM), so the
binding kinetics are driven by the free brain-extravascular
concentration converted to nM via the olanzapine molecular weight
(312.43 g/mol). All structural parameters are body-weight-normalised
(per kg).
|
|
Olaratumab
(Mo 2018)
|
Two-compartment population PK model with linear clearance for olaratumab
in patients with advanced or metastatic cancer (Mo 2018)
|
|
Olodaterol
(Borghardt 2016)
|
Population PK model for inhaled and intravenous olodaterol (long-acting
beta-2-adrenergic receptor agonist) in 148 healthy adult volunteers from
three Phase I trials (Borghardt 2016). Four-compartment systemic
disposition (central + 3 peripheral) fitted to IV plasma + urine data,
with two parallel first-order elimination processes from the central
compartment: renal (cl_renal) and nonrenal (cl_nonren). For inhaled
administration via the Respimat inhaler, three parallel first-order
absorption depots (slow, intermediate, fast) feed the central
compartment, with absorption half-lives of 21.8 h, 2.00 h, and 0.268 h
respectively. The pulmonary bioavailable fraction (49.4% of the nominal
ex-mouthpiece dose) is split across the three depots by two
logit-transformed proportionality parameters. Smoking is a covariate on
the slow and fast absorption rate constants (active smokers vs
ex-smokers and never-smokers pooled). Systemic disposition parameters
were estimated from IV data and fixed when fitting the inhalation data.
|
|
Olokizumab
(Kretsos 2014)
|
Two-compartment population PK with linear elimination and SC first-order
absorption (depot, central, peripheral1) plus effect-compartment
fractional sigmoid Imax PD model for C-reactive protein (CRP)
suppression in mild-to-moderate rheumatoid arthritis patients receiving
single-dose IV or SC olokizumab (anti-IL-6 monoclonal antibody, IgG4,
CDP6038). Final-analysis estimates from Kretsos et al. 2014 Table 1
(Final column), pooling first-in-human (healthy volunteers, Hickling
2011) and first-in-patient (Cohorts 1+2, n=27 active-treatment subjects)
data. The PK observation model adds a per-subject endogenous anti-IL-6
baseline (‘endo’) as an additive offset on the observed OKZ
concentration. Body weight was reported as a significant covariate on CL
and central volume (paper Discussion) but its functional form /
exponents were not reported in main text or supplement; the body-weight
covariate effect is omitted here – see vignette Assumptions.
|
|
Olprinone
(Kunisawa 2014)
|
Two-compartment intravenous population PK model for olprinone (a
phosphodiesterase III inhibitor) in healthy adult Japanese male
volunteers with body-weight normalization on CL, Vc, Q and Vp (Kunisawa
2014)
|
|
Omalizumab
(Hayashi 2007)
|
Mechanism-based binding population PK/PD model for omalizumab and IgE in
Japanese atopic-asthma patients (Hayashi 2007). Three serum entities
(free omalizumab, free IgE, and the omalizumab-IgE complex) each carry
their own clearance and volume of distribution and are coupled through
instantaneous-equilibrium binding (law of mass action) with a
concentration-dependent dissociation constant. Body weight modifies
omalizumab CL and Vd; baseline IgE modifies IgE CL and IgE production
rate. Subcutaneous absorption is first-order. Disposition parameters are
reported as apparent (divided by SC bioavailability f). Three observed
quantities: total omalizumab (ug/mL), total IgE (ng/mL), and free IgE
(ng/mL).
|
|
Omalizumab
(Lowe 2009)
|
Mechanism-based binding population PK/PD model for omalizumab and free /
total IgE in 1928 patients (1781 with severe persistent allergic asthma
across four Phase III studies plus 152 healthy atopic volunteers in a
single-dose bioequivalence study; Lowe 2009). Three serum entities (free
omalizumab, free IgE, and the omalizumab-IgE complex) each carry their
own clearance and apparent volume of distribution and are coupled
through instantaneous-equilibrium binding (law of mass action) with a
baseline-IgE-dependent dissociation constant that further varies with
the instantaneous total-omalizumab-to-total-IgE molar ratio. Body weight
modifies all clearances, all volumes, and the IgE production rate via
allometric power covariates centred at 70 kg; baseline IgE modifies CL
of free IgE, IgE production rate, and Kd via power covariates centred at
365 ng/mL. Subcutaneous absorption is first-order. Disposition
parameters are reported as apparent (divided by SC bioavailability f).
Extends Hayashi 2007 (modellib(‘Hayashi_2007_omalizumab’)) with (i) IIV
on Kd, (ii) baseline IgE as a covariate on Kd, and (iii) bodyweight
covariates on the IgE production and clearance parameters. Three
observed quantities: total omalizumab, total IgE, and free IgE (all in
ng/mL).
|
|
Omalizumab
(Marcantonio 2022)
|
QSP. One-compartment monospecific anti-ligand mechanistic PKPD model of
omalizumab-IgE binding in adults with moderate-to-severe allergic asthma
(Marcantonio 2022 Early Feasibility Assessment, Case Study 3).
Omalizumab binds soluble IgE; model treats IgE as the ligand and
FcepsilonRI (high-affinity IgE receptor on basophils and mast cells) as
the cognate receptor. Bivalent binding (crystallography suggests 2:1
stoichiometry with some 2:2 and 3:3 populations per Davies 2017).
Parameters FIXED from paper Table S6; the receptor half-life used is the
Assess default of 15 min rather than the Table S6 alternative of 2 hr
(paper explicitly tests both).
|
|
Omalizumab
pediatric (Zhu 2023)
|
Population pharmacodynamic indirect-response (IDR Type IV) model for
forced expiratory volume in 1 second (FEV1, percent predicted on a 0-1
fractional scale) driven by serum free IgE in pediatric patients (6-11
years) with moderate to severe persistent inadequately controlled
allergic asthma treated with omalizumab (Zhu 2023). PD-only – free IgE
concentration enters as the exogenous time-varying covariate IGE_FREE
(per-FEV1-observation interpolated value, ng/mL). Adapted from the
adult/adolescent IgE-FEV1 model (Lowe et al. 2009) with simplifications
for the sparser pediatric data: observed baseline FEV1 per subject,
common IIV magnitude on Imax and FEV1max, and Hill coefficient gamma
fixed at 9. The estimated IC50 in pediatrics (39.4 ng/mL) is higher than
in adults/adolescents (19.8 ng/mL); the model still supports the 25
ng/mL free IgE target underpinning the Xolair dosing table.
|
|
Ombitasvir
(Mensing 2017)
|
One-compartment population PK model for oral ombitasvir in HCV
genotype-1 infected adults receiving the 3D (paritaprevir/ritonavir +
ombitasvir + dasabuvir) +/- ribavirin regimen (Mensing 2017).
First-order absorption, linear elimination, combined proportional +
additive residual error, IIV on CL/F only. The author’s final model
retained cirrhosis, gender, age, and body weight as significant
covariates on CL/F (and age, body weight on Vc/F), but the paper does
not publish point estimates for these covariate coefficients (only
graphical exposure-ratio forest plots in Figure 2); the implemented
model is the structural typical-value model with covariate coefficients
omitted (documented in covariatesDataExcluded).
|
|
Omega3PUFA
(Wang 2024)
|
One-compartment population PK model with first-order oral absorption for
omega-3 polyunsaturated fatty acids (PUFA) in community-dwelling adults
with type 2 diabetes, with an HDL-cholesterol power covariate on Ka, V
and CL, coupled to a direct-effect inhibitory Imax model for
glycosylated hemoglobin (HbA1c) (Wang 2024)
|
|
Omeprazole
(Solana 2014)
|
Two-compartment intravenous-infusion population PK model for omeprazole
in 40 critically ill children (Solana 2014), with fixed Anderson-Holford
allometric body-weight scaling on all four disposition parameters
(exponents 0.75 on CL and Q, 1.00 on Vc and Vp; reference 70 kg).
Between-patient variability was retained on CL only; residual error is
proportional.
|
|
Omeprazole
(Zhao 2018)
|
Population PK-pharmacogenetic model for oral omeprazole and its two
metabolites 5-hydroxy-omeprazole and omeprazole sulfone in Caucasian
neonates and young infants (Zhao 2018). One-compartment parent
disposition with first-order absorption (Ka modulated by ABCB1 C3435T
genotype) is followed by parallel formation into two one-compartment
metabolites with apparent volume V_M/F fixed to 1 L; the
omeprazole-to-5-hydroxy-omeprazole formation clearance (CLOMZ-M1) is
modulated by CYP2C19 metabolizer phenotype (poor / intermediate /
extensive-or-ultrarapid) and a postnatal-age power function, while the
omeprazole-to-omeprazole-sulfone formation clearance (CLOMZ-M2) and the
metabolite apparent eliminations carry no covariates. Linear omeprazole
elimination was estimated as negligible (< 0.0001 L/h) and is
therefore not included in the final structural model.
|
|
Ondansetron
(deAlwis 1998)
|
Two-compartment population PK model with zero-order intravenous-infusion
input for ondansetron in pooled paediatric, young-adult, elderly, and
aged subjects (de Alwis 1998). The paper uses an empirical additive
linear-regression covariate model in the 1990s NONMEM tradition (Maitre
1991 three-step approach): clearance CL and inter-compartmental
clearance CLd are sex-stratified with separate male and female
intercepts and slopes; the central volume V1 has a body-weight slope
only; the steady-state volume Vss has body-weight and age slopes; the
peripheral volume Vp is derived as Vss - V1. Inter-individual
variability is diagonal log-normal on CL, V1, Vss, and CLd. Proportional
residual error is stratified across five paper-defined study
sub-populations (young healthy volunteers 18-41 y, elderly healthy
volunteers 61-75 y, aged healthy volunteers >= 75 y, paediatric
cancer patients receiving chemotherapy, paediatric patients receiving
general anaesthesia), switched at runtime via the canonical AGE /
DIS_HEALTHY / DIS_CANCER_PED covariates.
|
|
Ontamalimab
(Wang 2020)
|
Two-compartment population PK model for ontamalimab (SHP647), a fully
human IgG2 anti-MAdCAM-1 monoclonal antibody, in adults with
moderate-to-severe ulcerative colitis or Crohn’s disease (Wang 2020),
with first-order SC absorption, absorption lag time, parallel linear and
Michaelis-Menten elimination from the central compartment, and
allometric weight scaling on CL, Vc, Q, Vp, and Vmax.
|
|
Orin1001
(Li 2024)
|
Two-compartment population PK model with first-order absorption and a
lag time for oral ORIN1001 in Chinese patients with advanced solid
tumors
|
|
Ormutivimab
(Zhang 2022)
|
Time-dependent population pharmacodynamic emax model for rabies virus
neutralizing antibody (RVNA) activity after rabies vaccination in
healthy Chinese adults, with a categorical drug-product covariate that
contrasts Ormutivimab (rHRIG, a recombinant human anti-rabies IgG1
monoclonal antibody) against plasma-derived human rabies immunoglobulin
(HRIG) (Zhang 2022). Output Cc is neutralizing antibody activity in
IU/mL measured by the rapid fluorescent focus inhibition test (RFFIT).
The published Y1 two-compartment PK overlay for the passive-antibody
component of the combined drug+vaccine groups (E = Y1 + Y2) is NOT
included here because the seven structural PK constants (Ka, V1, V2,
K10, K12, K21, C0) are not reported anywhere on disk; see the vignette’s
Assumptions and deviations section for the omitted-component audit
trail.
|
|
Ornidazole
(Li 2023)
|
One-compartment intravenous population PK of ornidazole in breastfeeding
women after caesarean section, with breast-milk concentration linked to
plasma by an estimated milk-to-plasma concentration ratio that rises as
a power of time postpartum. Apparent clearance decreases with total
bilirubin.
|
|
Oseltamivir
(Chairat 2016)
|
Joint population pharmacokinetic model for oral oseltamivir (parent) and
its active antiviral metabolite oseltamivir carboxylate in 12 obese (BMI
>= 30 kg/m^2) and 12 non-obese (BMI < 30 kg/m^2) healthy Thai
adult volunteers (Chairat 2016 BJCP). First-order absorption (ka) into a
one-compartment parent (OS) disposition, an intermediate metabolism
compartment delaying carboxylate appearance (rate km), and a
one-compartment oseltamivir carboxylate (OC) disposition. Relative oral
bioavailability F is fixed to unity with interindividual variability on
F absorbing absorption differences. Creatinine clearance computed using
Janmahasatian fat-free mass (CLCR(FFM); raw Cockcroft-Gault with FFM
substituted for total body weight) is a linear covariate on CL/FOC,
centred at the population median CLCR(FFM) of 73 mL/min (3.84% increase
per 10 mL/min increase). Obesity itself was not a retained covariate in
the formal model. Residual error is additive on log-transformed
concentrations of OS and OC (encoded here as a log-normal residual on Cc
and Cc_oselcarb).
|
|
Oseltamivir
(Kamal 2013)
|
Joint parent-metabolite population PK model for oral oseltamivir
(prodrug, OP) and its active metabolite oseltamivir carboxylate (OC) in
390 subjects aged 1 to 78 years pooled from 13 clinical trials (healthy
adults, influenza-inoculated and naturally infected adults, healthy
geriatric subjects, renally impaired adults, and healthy and infected
pediatric subjects 1 to 18 years). Oseltamivir is described by a
two-compartment model with first-order absorption and first-order
conversion to OC (CLp/F treated as the OP-to-OC conversion clearance
under the assumption of complete metabolism; <5% of prodrug is
excreted unchanged renally). OC is described by a one-compartment model
with first-order elimination. All clearance and volume terms are
apparent (conditioned on oral bioavailability F; OC terms additionally
on the fraction metabolized fm, assumed 1). Covariates: body weight as a
power function on OP CLp/F, OC CLm/F, and OC Vcm/F (allometric-style
exponents estimated, not fixed); creatinine clearance (BSA-normalized to
1.73 m^2) as a power function on OC CLm/F; and age as a linear
(additive) term on OC Vcm/F. Inter-individual variability is exponential
on all seven structural parameters, with two off-diagonal covariances
(CLp/F with CLm/F, and Vp/F with Vcm/F). Residual error is proportional
only for oseltamivir (40.5% CV reduced CCV model) and combined additive
plus proportional for OC (14.0% CV proportional + 17.9 ng/mL additive
SD).
|
|
Oseltamivir
(Kamal 2015)
|
Mechanistic drug-disease (viral-dynamics) model of influenza-virus
progression and oseltamivir antiviral effect in adults with experimental
and naturally-acquired influenza A (H1N1) virus infection (Kamal 2015).
Builds on the Baccam et al. (2006) target-cell-limited viral-dynamics
framework: uninfected target respiratory epithelial cells (target_cells)
are infected by free virus (virus) at second-order rate beta_inf;
infected cells (infected_cells) produce virus at rate p_prod per cell
per day and die at rate delta_clr; free virus is cleared at rate c_clr.
Oseltamivir inhibits viral production through an inhibitory Hill
function acting on log10(p) (Equation 4 of Kamal 2015), parameterised so
Emax is the maximum log10-fold reduction of p and ED50 is the dose
producing a 2-fold (50%) reduction of p on the linear scale. Dose enters
via the per-record DOSE covariate (mg per administered oseltamivir dose;
0 during placebo or outside the treatment window); no oseltamivir
pharmacokinetics are modelled. Initial conditions are fixed per Baccam
et al. (2006): target_cells(0) = 4e8 epithelial cells (from a 160 cm^2
upper-respiratory-tract surface area and 2e-11 to 4e-11 m^2 per
epithelial cell), infected_cells(0) = 0, and virus(0) = 10^0.25
TCID50/mL (the viral-titer lower limit of quantification, used as the
inoculation viral titer). The viral load viralLoad (TCID50/mL of nasal
wash, canonical PD-output name) is the single observed output with
proportional residual error, equivalent to the paper’s log10-transformed
additive-error model. The three viral-dynamics compartments are declared
paper-specific (see paper_specific_compartments).
|
|
Oseltamivir
(Standing 2012)
|
Population PK model for oral oseltamivir and its active metabolite
oseltamivir carboxylate in preterm and term neonates and infants
(Standing 2012). One-compartment parent + one-compartment metabolite
with first-order absorption, an empirical transit compartment delaying
first-pass metabolite appearance, well-stirred-model hepatic first-pass
conversion (FM derived from CLI / liver-blood-flow FQ), and
physiologically scaled clearances combining (WT/70)^0.75 allometry with
a Rhodin 2009 renal-maturation Hill sigmoid on CLU/CLM and a fitted HCE1
Hill sigmoid (PM50 86.1 wk, Hill 3.17) on intrinsic clearance CLI.
Volumes (VD, VDM) and liver blood flow (FQ) fixed from external
references.
|
|
Oseltamivir
pbpk (Luo 2024)
|
PBPK (semi-mechanistic, custom WinNonlin 8.1 implementation). Joint
oseltamivir + oseltamivir carboxylate disposition in healthy adults and
in liver cirrhosis (Child-Pugh A/B/C). Oseltamivir is an inactive ester
prodrug hydrolysed by hepatic CES1 to the antivirally active oseltamivir
carboxylate, which is eliminated renally by combined glomerular
filtration and tubular secretion (both CLint,K values exceed GFR,
Section 3.1.6). The semi-PBPK circuit is stomach, three small-intestinal
lumen segments (duodenum / jejunum / ileum), the matching three gut-wall
segments, portal vein, liver, kidney and a one-compartment systemic
compartment. Cirrhosis is applied by switching the Child-Pugh-specific
physiology of Table 1 (organ blood flows, functional liver volume, GI
transit rates, GFR, plasma-binding protein concentrations, hepatic CES1
content) and rescaling CLint, CLint,K, Peff and Vsys through Eq 1-6.
Deterministic: the paper’s virtual populations are uniform 80-120% draws
on the drug parameters, not lognormal random effects, so no IIV is
encoded.
|
|
Oseltamivircarboxylate
pbpk (Granda 2024)
|
PBPK (mechanistic kidney, 35 states). Individualised prediction of
oseltamivir carboxylate renal clearance from per-subject biomarker
measurements of kidney blood flow and OAT1/3-mediated tubular secretory
capacity, on top of tracer-measured GFR (Granda 2024, Clin Transl Sci).
The kidney is resolved into 11 longitudinal subsegments (proximal tubule
S1-S3, descending and ascending loop of Henle, distal tubule, and five
collecting-duct subsegments), each with a tubular lumen, a tubular
epithelial cell and a peritubular blood subspace (33 states), plus a
systemic blood compartment and a bladder. Mechanisms: unbound glomerular
filtration, OAT1/3-mediated active secretion in the proximal tubule
only, pH-dependent bidirectional passive diffusion along the whole
nephron, and CKD tubular-flow adaptation. The structural equations,
segment volumes, surface areas, tubular pH profile and adaptive flow
factors are the Huang & Isoherranen 2018 / 2020 framework; Granda
2024 replaces the framework population defaults for kidney blood flow
and secretory clearance with per-subject measured / fitted values.
Predicts each subject’s oseltamivir carboxylate renal clearance from
their measured GFR and kidney blood flow plus the kynurenic-acid-derived
secretory capacity, scaled by 0.038. Reproduces the Predicted OC CLr
column of Table 4. Deterministic typical-value model: the paper reports
no IIV and no residual error.
|
|
Osimertinib
(Brown 2017)
|
Joint two-compartment population PK model for osimertinib (AZD9291) and
its active metabolite AZ5104 in advanced non-small cell lung cancer
(NSCLC) patients pooled with healthy volunteers (Brown 2017).
First-order oral absorption into a parent (osimertinib) compartment is
followed by a second compartment (AZ5104) in series; the fraction of
parent eliminated as AZ5104 is fixed at 0.25 per the publication. Body
weight (allometric on parent CL/F and Vc/F and on AZ5104 CL/F), serum
albumin (power on parent Vc/F), healthy-volunteer disease state (linear
factor on both parent and AZ5104 CL/F), and ethnicity (Chinese,
Japanese, Asian-other, and non-Asian non-Caucasian linear factors on
AZ5104 CL/F) were retained as significant covariates.
|
|
Osimertinib
qsp (Liang 2024)
|
QSP. EGFRm+ target-engagement (receptor-occupancy) model for osimertinib
(OSI, AZD9291) in NSCLC, describing irreversible covalent binding of OSI
to the two EGFR mutants studied by Liang 2024 – T790M and L858R – with
target turnover. Two independent free-target / drug-target-complex pairs
share a single osimertinib concentration driver, reproducing the pair of
mutant inhibition curves in Liang 2024 Figure 1. The osimertinib
concentration is NOT fitted here: Liang 2024 generated it with a
whole-body PK-Sim 10.0 PBPK model that is a platform port (no ODEs, no
organ volumes and no blood flows are published, and no .pksim5 project
was deposited), so that layer is not reproducible from the on-disk
sources and is deliberately NOT extracted. The total osimertinib
concentration is instead supplied per record as the canonical
time-varying covariate CEFFECT and multiplied by the fraction unbound fu
inside model(), exactly as in the authors’ own supplementary code
listing. Deterministic mechanism model: Liang 2024 simulated ten virtual
subjects per scenario from PK-Sim population physiology rather than
fitting IIV or residual error, so no etas and no error model are
encoded. IMPORTANT DEVIATION – the complex ODE carries an inferred ‘-
kdeg * complex’ elimination term that is absent from the paper’s printed
Eq 5 and from the supplementary listing. As printed, the complex has no
elimination at all and (with koff = 0) occupancy rises monotonically to
100% under any sustained exposure, which provably contradicts the flat
sawtooth plateau of the paper’s own Figure 1. Restoring the term
conserves total target at rbase and yields the steady-state occupancy
konCfree / (konCfree + kdeg); it uses only published values
(kdeg = 0.025 /h is declared in the supplement and used on the
free-target line), but it is an inferred correction rather than a
transcription. Extraction performed under operator sidecar decision
oare_PMC10946252 request-001 = option B (answered 2026-08-05). See the
vignette ‘Assumptions and deviations’ section for this and for the
residual ~400-fold kon / concentration scale discrepancy against Figure
1’s plasma band.
|
|
Oxaliplatin
(Valenzuela 2011)
|
Population PK/PD model for hyperthermic intraperitoneal oxaliplatin
(HIO) and induced neutropenia in 30 adults with peritoneal
carcinomatosis after cytoreductive surgery (Valenzuela 2011). PK:
peritoneum-as-depot first-order absorption (parameterized in the paper
as peritoneum-to-plasma clearance Qa and peritoneum volume Va = vd, with
ka = Qa/Va as a secondary parameter) feeding an open two-compartment
plasma disposition; bioavailability F was fixed to 1 so Cl/F, Vc/F,
Q2/F, Vp/F are apparent. PD: Friberg semi-mechanistic myelosuppression
chain (one proliferating compartment plus three transit compartments
feeding circulating ANC) with a linear drug effect Edrug = alpha * Cc on
the proliferation rate and a (Circ0/Circ)^gamma feedback amplification;
MTT was fixed at 118 h and the circulating-cell elimination rate
constant kCirc was fixed at 0.07 per h (both from Friberg 2002). No
subject covariates were retained in the final model; ten demographic and
biochemistry covariates were screened graphically and showed no
correlation with PK/PD parameters.
|
|
Oxaliplatin
(Zhu 2023)
|
Two-compartment population PK model for ultrafilterable platinum in
plasma after intravenous oxaliplatin in adults with metastatic
colorectal cancer, estimated from human concentration-time profiles
digitised from the literature. Zhu 2023 uses the central-compartment
concentration as the driver of an in vitro-derived tumour-killing model;
that in vivo tumour-growth layer is NOT included here because its growth
equation and limiting parameter are not reported anywhere in the paper -
see the vignette Errata. The in vitro drug-effect half is available as
modellib(‘Zhu_2023_oxaliplatin_organoid’).
|
|
Oxaliplatin
organoid (Zhu 2023)
|
In vitro (patient-derived colorectal-cancer tumour organoids, PDTOs).
Exponential organoid-growth model with a sigmoidal Emax (Hill) killing
term describing the 96 h concentration-viability relationship of
oxaliplatin. A vehicle-control organoid and a treated organoid grow in
parallel; the reported readout is cell viability, the ratio of treated
to control organoid volume. This is the in vitro half of the Zhu 2023 in
vitro-to-in vivo translation: the same Emax / EC50 / Hill parameters are
carried into the human oxaliplatin PK/PD model, see
modellib(‘Zhu_2023_oxaliplatin’).
|
|
Oxcarbazepine
(Rodrigues 2017)
|
Parent-metabolite population PK model for oral oxcarbazepine (OXC) and
its active monohydroxy derivative (MHD) in epileptic children aged 2-12
years (Rodrigues 2017). Two-compartment OXC + one-compartment MHD with
first-order absorption, complete metabolic conversion (Fm fixed to 1),
reversible MHD-to-OXC back-transformation (KBT), empirical allometric
weight scaling on CL_OXC/F, Vc_OXC/F, CL_MHD/F, and Vc_MHD/F (no scaling
on Q_OXC/F or Vp_OXC/F), and a 29.3% increase in MHD clearance under
concomitant enzyme-inducing antiepileptic drugs.
|
|
Oxyfluorfen
human (Decrane 2023)
|
QSP (PBPK + thyroid-hormone kinetics). Human cross-species extrapolation
of the rat oxyfluorfen model of Decrane et al. 2023 (Curr Res Toxicol
5:100138), used by the authors to forecast the drop in serum T4 and T3
from long-term oral exposure to the herbicide oxyfluorfen in drinking
water. Structurally identical to the rat companion model (13
flow-limited chemical compartments including a diffusion-limited thyroid
split into thyroid blood and thyroid tissue, plus five thyroid-hormone
states carrying the HPT feedback loop), but with human physiology (Table
2), an age-dependent cardiac output, a hepatic clearance derived from
human in-vitro hepatocyte data rather than fitted, human basal
thyroid-hormone levels, non-allometric human hormone production and
transfer rates, and a DIFFERENT empirical sodium-iodide-symporter (NIS)
inhibition function fitted to human hNIS-HEK293T-EPA in-vitro data.
There is no human in-vivo calibration data for oxyfluorfen, so the
authors caution that the predictions ‘should be considered with
caution’. Deterministic typical-value (no IIV, no residual error).
Companion model: Decrane_2023_oxyfluorfen_rat.
|
|
Oxyfluorfen
rat (Decrane 2023)
|
QSP (PBPK + thyroid-hormone kinetics). Preclinical (rat,
Sprague-Dawley). Whole-body PBPK model for the diphenyl-ether herbicide
oxyfluorfen coupled to a hypothalamic-pituitary-thyroid (HPT) axis
thyroid-hormone kinetics sub-model (Decrane et al. 2023, Curr Res
Toxicol 5:100138). Oxyfluorfen is distributed across 13 flow-limited
compartments (gut lumen, GI tissue, liver, kidney, muscle, skin, fat,
brain, slowly perfused, rapidly perfused, a diffusion-limited thyroid
split into thyroid blood and thyroid tissue, and a single well-mixed
blood pool) with hepatic metabolic clearance and GFR-driven renal
excretion. The predicted oxyfluorfen concentration in thyroid blood
drives an empirical in-vitro-derived sodium-iodide-symporter (NIS)
inhibition function that scales thyroidal T4 and T3 synthesis (the
paper’s CBthy; see the model file and vignette Errata for the evidence
that CBthy is the thyroid blood rather than the thyroid tissue
concentration, a reading that reproduces both species’ published points
of departure); five thyroid-hormone states (T4 and T3 in thyroid tissue,
T4, T3 and TSH in serum) carry the HPT feedback loop in which TSH
stimulates T4 synthesis (stim) and serum T4 regulates TSH production and
turnover (feed1, feed2). The model is deterministic typical-value (no
IIV, no residual error) – the paper reports point estimates only, with
no parameter uncertainty, no between-animal variability and no
measurement-error model. Companion model:
Decrane_2023_oxyfluorfen_human.
|
|
Oxypurinol
(Stocker 2012)
|
One-compartment population PK model for oxypurinol (the active
metabolite of allopurinol) in adults with gout (Stocker 2012).
First-order formation from allopurinol (Kfm taken as the apparent
first-order absorption rate into the central compartment),
one-compartment distribution, and first-order elimination. Apparent
clearance (CL/Fm) is modified by raw Cockcroft-Gault creatinine
clearance based on lean body weight (CRCL), concomitant any-class
diuretic use (CONMED_DIURETIC; thiazide / furosemide / spironolactone
pooled), and concomitant probenecid use (CONMED_PROBENECID), each via a
linear-deviation multiplicative factor. Apparent volume (V/Fm) is
allometrically scaled on lean body weight (LBW) with the volume exponent
held fixed at the theoretical value of 1.0. The dose entered into the
model is the oxypurinol-equivalent dose, taken as 0.9 x allopurinol dose
per the paper’s prior published assumption.
|
|
Ozanezumab
(Berges 2015)
|
Two-compartment IV population PK plus effect-compartment sigmoid Emax
PKPD model for the proportion of skeletal-muscle membrane Nogo-A
co-localized with ozanezumab in adults with amyotrophic lateral
sclerosis (ALS), based on the GlaxoSmithKline first-in-human study
NCT00875446 (Berges 2015, Table 2)
|
|
Ozoralizumab
(Takeuchi 2023)
|
One-compartment population PK model with first-order absorption for
subcutaneous ozoralizumab (anti-TNF VHH NANOBODY) in Japanese patients
with rheumatoid arthritis (Takeuchi 2023)
|
|
Paclitaxel
(deJonge 2005)
|
Semi-mechanistic population pharmacokinetic model for orally
administered paclitaxel formulated in Cremophor EL (CrEL) and
coadministered with cyclosporin A in adult cancer patients. Free
paclitaxel in the gastrointestinal tract (depot) absorbs first-order
(kabs) into a two-compartment plasma disposition (central + peripheral1;
linear elimination CL/F, volume V/F, intercompartmental clearance Q
derived from the paper’s k23 = Q/Vc and k32 = Q/Vp). A second GI-tract
paclitaxel pool (bound) holds drug encapsulated in CrEL
micelles; the depot <-> bound equilibrium is governed by a single
rate constant keq whose forward binding rate scales with the GI-tract
CrEL amount (cremophor), which itself decays first-order
with rate kcrem. Bioavailability F1 is fixed at 1 with log-normal
between-subject variability; the paper found no dose-dependence in F.
Inter-occasion variability on CL collapses to between-subject
variability in this packaged form because the source dataset’s occasion
column is not encoded – see vignette Assumptions and deviations.
|
|
Paclitaxel
(Janssen 2023)
|
Semi-physiological enriched three-compartment population PK model for
intravenous paclitaxel with saturable elimination and saturable
distribution in pregnant cancer patients, applying gestational changes
in albumin binding, glomerular filtration, hepatic plasma flow, CYP3A4
activity and body fluid volumes to the non-pregnant Crombag 2019 base
model
|
|
Paclitaxel
myelosuppression (Wahlby 2004)
|
Semi-mechanistic Friberg-Karlsson myelosuppression PD model for
paclitaxel-induced neutropenia in 45 cancer patients, demonstrating
Wahlby 2004’s extended covariate-model formulation. Final-model adds a
time-varying bilirubin (TBILI) effect on mean transit time and a
per-occasion delta-from-baseline-bilirubin effect on the linear
drug-effect Slope, with inter-individual variability in the
delta-bilirubin-Slope coefficient (Wahlby 2004 Eq 3 demonstrated).
Paclitaxel PK is supplied via per-subject empirical-Bayes columns
(CL_INDIV, VC_INDIV, VP_INDIV) following the Friberg 2002 paclitaxel
convention; users can also pair this PD model with the
Friberg_2002_paclitaxel PK structure directly via the modellib registry.
|
|
Pacmilimab
qsp (Ippolito 2024)
|
QSP. Quantitative systems pharmacology model of immuno-oncology (QSP-IO)
describing the antitumour immune response to pacmilimab, a conditionally
activated (Probody) anti-PD-L1 antibody, in triple-negative breast
cancer. Four physiological compartments (central, peripheral, tumour,
tumour-draining lymph node) plus APC endosomal and surface compartments,
three immunological-synapse compartments (T cell-cancer cell, T
cell-APC, macrophage-cancer cell) and four out-of-synapse compartments
introduced by this paper (cancer cell, T cell, macrophage, APC). Covers
Gompertzian tumour growth with explicit tumour vasculature, naive and
activated CD4+/CD8+ T cell trafficking and proliferation, self- and
neo-antigen release, uptake, endosomal processing and MHC-I
presentation, TCR-mediated activation, PD-1/PD-L1/PD-L2 and
CTLA-4/CD28/CD80/CD86 checkpoint binding, MDSC recruitment with
arginase-I and nitric-oxide suppression, M1/M2 tumour-associated
macrophages with CD47/SIRP-alpha phagocytosis control, and IL-2 / IL-10
/ IL-12 / IFN-gamma / TGF-beta / CCL2 dynamics. The Probody module
carries six free states per compartment (masked, open and cleaved
combinations of the two active sites) with reversible unmasking and
irreversible protease cleavage, plus nine mono- and bivalently bound
states at each of nine PD-L1 bearing sites. Dosing the fully masked
state P_mm gives pacmilimab; dosing the fully cleaved state P_cc gives
the unmasked anti-PD-L1 antibody (equivalent to atezolizumab
monotherapy), which is how the paper simulates its reference arm.
Deterministic mechanism model: the authors generated virtual patients by
Latin hypercube sampling of the distributions in Supplementary Table S1
rather than by fitting IIV or residual error, so no etas and no error
model are encoded.
|
|
Paliperidone
panss subscales (PillaReddy 2013)
|
Population PK/PD model for paliperidone extended release against the
three PANSS subscales (positive, negative, general) in adults with
schizophrenia from Pilla Reddy 2013 Part II. The PK sub-model is the
one-compartment paliperidone structural model from Part I (PMID
23473810) Table 2 with the sequential zero-order plus first-order
absorption simplified to first-order only (the ER absorption profile is
approximately steady at steady state because the OROS-extended- release
tablet is dosed once daily): first-order absorption ka = 0.57 1/h,
apparent oral clearance CL/F = 14.1 L/h, apparent central volume of
distribution Vc/F = 475 L. The PD sub-model has three outputs that share
the Weibull placebo time-course form Pplacebo = Pmax * (1 -
exp(-(t/TD)^POW)) but each subscale carries its own placebo Pmax, TD,
POW (Part II Table 1) and paliperidone’s own Emax / EC50 / KT triplet
per subscale (Part II Table 2). The KT for paliperidone PANSS positive
and general (0.048 and 0.035 1/day) is the common-across-atypical-
antipsychotic value; the KT for the negative subscale (0.13 1/day) was
estimated separately per drug. The lag time ALAG1 = 0.67 h and the
zero-order absorption duration DUR = 23.6 h reported in Part I Table 2
for paliperidone ER are not encoded here because the Css used by the PD
model is approximately invariant to within-dose absorption details at
steady state. The exponential time-to-event dropout sub-model from Part
II Table 4 is documented in population$dropout_model but not encoded in the model body.
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Robbie_2012_palivizumab.html">Palivizumab
(Robbie 2012)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model for palivizumab (anti-RSV humanized IgG1 kappa mAb) with
first-order IM absorption in adults and children (Robbie 2012)
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Cao_2013_PAmAb.html">PAmAb
(Cao 2013)</a> </td>
<td style="text-align:left;"> Second-generation minimal
physiologically-based PK (mPBPK) model for PAmAb in adults (Cao 2013
Model A; clearance from plasma) </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Marcantonio_2022_efa.html">Panitumumab
(Marcantonio 2022)</a> </td>
<td style="text-align:left;"> QSP. Two-compartment monospecific
anti-receptor mechanistic PKPD model of panitumumab-EGFR binding in
adults with metastatic colorectal cancer (Marcantonio 2022 Early
Feasibility Assessment, Case Study 2). Drug administered IV as a
bivalent (valency = 2) antibody that binds membrane EGFR (in central and
peripheral compartments). Soluble EGFR is not modelled (JSON shed_css =
0). All species eliminate first-order; drug bound to membrane receptor
eliminates at the receptor's rate. Structure identical to the
Marcantonio 2022 trastuzumab anti-receptor model; differs only in the
drug-specific parameters. Parameters FIXED from paper Tables 3 (target)
and 4 (drug) and the Assess run file JSON. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Pettersen_2009_pantoprazole.html">Pantoprazole
(Pettersen 2009)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model for intravenous pantoprazole in 20 paediatric intensive-care
patients aged 10 days to 16.4 years (Pettersen 2009). Pantoprazole is
given as a zero-order infusion (15-30 min) into the central compartment
with first-order elimination. Body-weight allometric scaling is fixed
(0.75 on CL/Q, 1 on Vc/V2, reference 20 kg). Clearance is further
modified by age (power on AGE/5 years), and three binary clinical
covariates retained at the forward-selection / backward-elimination
step: systemic inflammatory response syndrome (DIS_SIRS), concomitant
CYP2C19-inhibitor coadministration (CONMED_CYP2C19_INH, pooling
fluconazole, voriconazole, and isoniazid), and clinically defined
hepatic dysfunction (HEPIMP, paediatric criterion TBILI >= 4 mg/dL OR
ALT > 2x ULN for age). Each of the three indicators reduces
pantoprazole CL by 62.3%, 65.8%, and 50.5% respectively when present
alone. The reference subject is a 20 kg / 5-year-old paediatric ICU
patient without SIRS, hepatic dysfunction, or CYP2C19 inhibitor
coadministration. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Anderson_1998_paracetamol.html">Paracetamol
(Anderson 1998)</a> </td>
<td style="text-align:left;"> One-compartment oral PK model for
paracetamol (acetaminophen) with an explicit cerebrospinal-fluid (CSF)
equilibration compartment in nine ventilator-dependent children (5
months to 12 years) with indwelling ventricular drains for raised
intracranial pressure (Anderson 1998 NONMEM fit, Table 3). First-order
absorption, single nasogastric dose of 40 mg/kg paracetamol elixir,
plasma + CSF sampled hourly for 4 h and 2-hourly through 10 h. CSF
concentration follows the plasma concentration with first-order
equilibration rate keq = ln(2)/teq and steady-state ratio PC = Ccsf/Cc.
Parameters are standardized to a 70 kg adult using fixed allometric
exponents (0.75 on CL, 1 on V, 0.25 on the equilibration half-time teq;
keq therefore scales with exponent -0.25). The published equation 2 for
residual error var = SF^2 * (C^PWR + V) is unconventional and the NONMEM
PWR and V terms are not reported; placeholder additive residual SDs are
used so the model simulates plausibly (see vignette Errata). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Krekels_2015_paracetamol.html">Paracetamol
(Krekels 2015)</a> </td>
<td style="text-align:left;"> Parent-and-metabolites population
PK model for intravenous paracetamol (administered as the prodrug
propacetamol; doses expressed as paracetamol equivalents) and its
glucuronide and sulphate phase-II conjugates in 54 preterm and term
neonates and infants (Krekels 2015). One-compartment plasma disposition
for paracetamol with three parallel elimination pathways from the
central compartment: glucuronide formation (CL_gluc), sulphate formation
(CL_sulf), and unchanged renal excretion (CL_renal). Each metabolite
distributes into a one-compartment plasma space whose volume is fixed at
18% of the parent volume (Vc_gluc = Vc_sulf = 0.18 * Vc, based on the
previously reported adult paracetamol model in Allegaert et al. and
adult literature). The two metabolites share a common urinary excretion
rate constant kE_met = mf * kE_renal, where kE_renal = CL_renal / Vc is
the parent unchanged-renal rate constant and mf (multiplication factor)
is estimated to be 11.3. Cumulative urinary amounts of parent
paracetamol and the two metabolites are tracked as elimination-amount
compartments and exposed as additive-error observations. Bodyweight
enters linearly on Vc (and so on the metabolite volumes by inheritance),
on the glucuronide formation clearance (CL_gluc), and on the unchanged
renal clearance (CL_renal); the sulphate formation clearance (CL_sulf)
scales with bodyweight as a power with an estimated exponent of 1.40. No
postnatal age, postmenstrual age, sex, term-vs-preterm, or
study-protocol covariate was retained in the final model, and no
time-varying (up-regulation) component was detected on the
glucuronidation pathway. Parameter values reported throughout
(mL/min/kg, L/kg) are per-kg quantities; individual structural
parameters are obtained in model() by multiplying by body weight in kg
(linear) or body weight in kg raised to n (power). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Wattanakul_2016_paracetamol.html">Paracetamol
(Wattanakul 2016)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model for paracetamol (acetaminophen) administered as a single 600 mg
dose by either intramuscular injection (zero-order absorption over
DUR_IM) or oral syrup (first-order absorption with rate constant ka) in
21 adult Thai patients with uncomplicated Plasmodium falciparum malaria
and fever > 38 C (Wattanakul 2016). Intramuscular bioavailability is
fixed to F_IM = 1; the relative oral bioavailability is F_PO = 0.844
(95% CI 0.682-0.951). The depot compartment carries oral doses (f(depot)
= F_PO) while intramuscular doses target central with rate = -2 to
invoke the modeled dur(central) = DUR_IM. No covariates were retained:
allometric scaling on body weight did not improve the fit and a stepwise
covariate search (age, AST, ALT, bilirubin, BUN, creatinine, sex,
hemoglobin, parasitaemia, systolic BP, temperature) found no significant
effect at p < 0.05. Inter-individual variability for V_C and DUR_IM
was estimated below 1% CV and fixed to zero in the source paper without
changing the OFV; this model omits the corresponding etas accordingly.
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Wu_2025_paracetamol.html">Paracetamol
(Wu 2025)</a> </td>
<td style="text-align:left;"> Parent-and-three-metabolites
population PK model for intravenous and rectal paracetamol (PCM) and its
glucuronide (PCM-GLU), sulfate (PCM-SULF), and combined oxidative
metabolites (PCM-cysteine + PCM-mercapturate, PCM-OXI, denoted with the
canonical cysmer suffix) from preterm and term neonates through infants,
children, and adults (Wu 2025). Two-compartment plasma disposition for
parent PCM with three parallel formation clearances and parallel renal
elimination of unchanged parent; one-compartment plasma disposition for
each metabolite with renal elimination expressed as a fraction of
glomerular filtration rate (GFR). The preterm-and-term-neonate-to-adult
(PTNA) maturation equation (Wu 2024) is applied to each formation
clearance and to a separate PCM-SULF renal-secretion clearance; an
additional adult-only correction factor scales the renal clearance of
PCM-GLU in subjects >= 18 years. Rectal absorption parameters (Ka,
Tlag, F) are fixed from Wang 2014. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Mensing_2017_3D_HCV_regimen.html">Paritaprevir
(Mensing 2017)</a> </td>
<td style="text-align:left;"> One-compartment population PK
model for oral paritaprevir (co-dosed with ritonavir) in HCV genotype-1
infected adults receiving the 3D regimen (Mensing 2017). First-order
absorption with a fixed absorption lag time, linear elimination,
additive residual error on log-transformed concentrations (encoded as
log-normal Cc ~ lnorm(expSd)), IIV on CL/F only. The author's final
model retained cirrhosis, gender, age, opioid use, and
antidiabetic-agent use as significant covariates on CL/F (and age, body
weight on Vc/F), but the paper does not publish point estimates for
these covariate coefficients (only graphical exposure-ratio forest plots
in Figure 2); the implemented model is the structural typical-value
model with covariate coefficients omitted (documented in
covariatesDataExcluded). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Kim_2015_paroxetine.html">Paroxetine
(Kim 2015)</a> </td>
<td style="text-align:left;"> One-compartment population PK
model with first-order absorption for paroxetine (SSRI antidepressant)
in Korean adults with major depressive disorder or anxiety disorder
receiving therapeutic drug monitoring (Kim 2015). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Lee_2023_patritumab.html">Patritumab
(Lee 2023)</a> </td>
<td style="text-align:left;"> Integrated population PK model
for the conjugated (anti-HER3-ac-DXd) and unconjugated payload (DXd) of
patritumab deruxtecan (HER3-DXd, U3-1402, anti-HER3 antibody-drug
conjugate) in adult cancer patients (Lee 2023 ACoP poster).
anti-HER3-ac-DXd disposition is a two-compartment model with three
parallel elimination pathways from the central compartment: a transient
time-decaying linear clearance CL_t(time) = CL_T * exp(-Kdes * time), a
non-specific time-dependent linear clearance CL_ns(time) that declines
sigmoidally from CL_ss * (1 + Emax) at time = 0 to CL_ss at infinity via
a Hill function CL_ns(time) = CL_ss * (1 + Emax * T50^hill / (T50^hill +
time^hill)), and a Michaelis-Menten saturable clearance CL_mm = Vmax /
(Km + Cc). DXd is a one-compartment model with parallel linear and
Michaelis-Menten elimination; its formation rate equals the sum of the
three anti-HER3-ac-DXd elimination rates each scaled by a dimensionless
fractional-conversion factor Frac_ns / Frac_t / Frac_mm (Frac_ns fixed
at 1 as the identifiability anchor). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Lu_2022_patritumab.html">Patritumab
(Lu 2022)</a> </td>
<td style="text-align:left;"> Joint two-analyte population PK
model for patritumab deruxtecan (HER3-DXd, an anti-HER3 antibody-drug
conjugate) in adults with HER3-expressing solid tumors (Lu 2022).
DXd-conjugated antibody (intact ADC) is described by a 2-compartment
model with parallel linear and Michaelis-Menten clearance. Released
unconjugated DXd (MAAA-1181a, exatecan-derivative payload) is described
by a 1-compartment model with linear clearance and a first-order,
time-dependent release rate driven by the level of DXd-conjugated
antibody in the central compartment, scaled by the molecular-weight
ratio MW_DXd/MW_DXdAb and a payload-to-intact-drug ratio PIR modulated
by a cycle-1-vs-later (factor1) and a within-cycle exponential (factor2)
modifier. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Ouerdani_2015_pazopanib.html">Pazopanib
(Ouerdani 2015)</a> </td>
<td style="text-align:left;"> Semi-mechanistic tumour growth
and angiogenesis-inhibition (TGI) model for pazopanib in renal-cell
carcinoma patients (Ouerdani 2015 clinical fit): logistic tumour growth
(state tumor_size) limited by a separately tracked
vasculature-determined carrying capacity (state carrying_capacity), with
antiangiogenic and cytotoxic drug effects parameterised as power
functions of per-period mean AUC_PAZO and an exponentially declining
resistance on the cytotoxic effect. The empirical exponent on capacity
growth (n) is fixed at 0.5 for the clinical fit (vs 1 in the paired
mouse model) to better describe the tumour-regrowth and
long-term-antiangiogenic phases observed in patients. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Ouerdani_2015_pazopanib_mouse.html">Pazopanib
mouse (Ouerdani 2015)</a> </td>
<td style="text-align:left;"> Preclinical (mouse, CB-17 SCID
with CAKI-2 renal-cell carcinoma xenografts). Semi-mechanistic tumour
growth and angiogenesis-inhibition (TGI) model for pazopanib (Ouerdani
2015): logistic tumour growth (state tumor_size) limited by a separately
tracked vasculature-determined carrying capacity (state
carrying_capacity), with an antiangiogenic drug effect on
carrying-capacity loss (power form in AUC_PAZO) and a putative cytotoxic
drug effect on tumour decay (exponentially declining resistance, no AUC
effect after the cytotoxic exponent was fixed to 0). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Chen_2024_guhongInjection.html">PCoumaricAcid
rat (Chen 2024)</a> </td>
<td style="text-align:left;"> Preclinical (rat).
Two-compartment intravenous pharmacokinetic model for p-coumaric acid
(pCA), one of eight constituents of guhong injection (GHI) quantified in
plasma, in male Sprague-Dawley rats subjected to 30 min
left-anterior-descending ligation followed by 1 h reperfusion
(myocardial ischemia/reperfusion, MI/R) (Chen 2024). GHI was given as a
single tail-vein injection of 2.5, 5 or 10 mL/kg; the p-coumaric acid
dose is the GHI volume dose times its content in GHI (78.3 ug/mL), i.e.
195.75 ug/kg, 391.5 ug/kg, 783 ug/kg. Disposition was fitted separately
in each dose group with Drug and Statistics (DAS) v3.2.6, so V1, V2, CL1
and Q are selected from the covariate DOSE_GHI_MLKG rather than through
a dose-covariate function the authors did not fit. Direct-effect
sigmoid-Emax models link the p-coumaric acid plasma concentration to the
GHI-minus-model-group difference in creatine kinase-MB (CK-MB),
ischemia-modified albumin (IMA), cardiac troponin I (cTn I) and
alpha-hydroxybutyrate dehydrogenase (alpha-HBDH) (E = Emax * C^gamma /
(ED50^gamma + C^gamma); Tables 12, 13, 14, 15). Chen 2024 fitted a PK/PD
model only for the analyte/biomarker/dose combinations whose PLSR
coefficient was negative, so the effect of an unfitted combination is
returned as zero rather than extrapolated. No between-subject
variability or residual error was reported; every parameter is fixed at
the published mean and the residual SDs are fixed at zero. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Wahlby_2004_time_varying_covariates.html">Pefloxacin
(Wahlby 2004)</a> </td>
<td style="text-align:left;"> One-compartment population PK
model for intravenous 1-hour pefloxacin infusions in 74 critically ill
adults, demonstrating Wahlby 2004's extended covariate-model
formulation. Final-model clearance carries time-varying CRCL (with
inter-individual variability in the CRCL effect coefficient, Eq 3),
per-subject baseline total bilirubin BIL_BASE (replaces BIL), age,
centre indicator, and per-subject baseline weight WT_BASE (replaces WT,
with a saturating 'up to median weight' qualifier per Methods). Central
volume retains the upstream Karlsson 1993 (ref [10]) WT/CRCL/BIL effects
unchanged. Underlying structural PK comes from Karlsson MO, Sheiner LB.
The importance of modeling interoccasion variability in population
pharmacokinetic analyses. J Pharmacokin Biopharm 1993;21(6):735-750 (not
on disk in this worktree). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Kloos_2021_pegasparaginase.html">Pegasparaginase
(Kloos 2021)</a> </td>
<td style="text-align:left;"> One-compartment population PK
model with time-dependent (split-point) clearance for intravenous
PEGasparaginase in pediatric acute lymphoblastic leukemia patients
treated on the Dutch Childhood Oncology Group ALL-11 protocol (Kloos
2021). Clearance and volume of distribution are normalized to body
surface area; clearance is constant for the first 12.7 days after a dose
and then increases linearly with time after dose as the polyethylene
glycol moiety is hydrolyzed. Clearance is 38 percent higher during an
active infection and 11-19 percent lower outside induction, encoded as
multiplicative treatment-phase factors with protocol 1A as the
reference. Inter-individual variability on clearance is shared with the
volume of distribution through a scaled eta; inter-occasion variability
on clearance uses one occasion per administered dose. Combined
proportional and additive residual error. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Brekkan_2018_pegfilgrastim.html">Pegfilgrastim
(Brekkan 2018)</a> </td>
<td style="text-align:left;"> Bidirectional population PK/PD
model for pegfilgrastim (PG) in healthy volunteers after single 6 mg
subcutaneous doses. PK is one-compartment with sequential zero- and
first-order absorption (zero-order input rate R1 into depot followed by
first-order Ka into central), and parallel elimination via a linear
ANC-dependent pathway (cl_anc * ANC) and a saturable non-specific
Michaelis-Menten pathway (Vmax / Km). PD is a Friberg/Quartino-style
maturation cascade (4 transit compartments + circulating compartment)
with the production rate set by baseline ANC and a fixed 7-hour
circulating neutrophil half-life, plus three Emax drug effects:
proliferation (scaling production), maturation (scaling transit rate
ktr), and a margination effect on circulating-pool clearance kcirc that
is parameterised by scaled Emax,prol and EC50 (Emax,Scale = 0.0622,
EC50,Scale = 0.477). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Naik_2013_peginesatide.html">Peginesatide
(Naik 2013)</a> </td>
<td style="text-align:left;"> Two-compartment population PK/PD
model for peginesatide in adult chronic kidney disease (CKD) patients
(Naik 2013). PK: first-order subcutaneous absorption with saturable
Michaelis-Menten elimination and fixed inter-compartmental clearance.
PD: modified precursor-dependent lifespan indirect-response (LIDR) model
of hemoglobin (1 progenitor compartment + 7 red-blood-cell aging
compartments) with a peginesatide Emax stimulation on progenitor
production and an empirical exponential downward-drift factor on the
progenitor-to-RBC transit. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Bi_2017_peginterferon_alfa_2a.html">Peginterferon
alfa 2a (Bi 2017)</a> </td>
<td style="text-align:left;"> One-compartment population PK
model with first-order absorption for peginterferon alfa-2a in adult
patients with chronic hepatitis B (Bi 2017). Creatinine clearance
(Cockcroft-Gault, mL/min, not BSA-normalized) modifies clearance via a
power form, and body mass index modifies central volume via a power
form. Exponential IIV on CL, V, and Ka; combined proportional + additive
residual error on plasma concentration. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Gupta_2006_peginterferon_alfa_2b.html">Peginterferon
alfa 2b (Gupta 2006)</a> </td>
<td style="text-align:left;"> One-compartment population PK
model with first-order subcutaneous absorption for peginterferon alfa-2b
(PEG-Intron) in adult patients with chronic myelogenous leukaemia (Gupta
2006). Apparent clearance declines over treatment time via an Emax-type
function CL(t) = CL0 / (1 + (t / T50)^beta) with beta fixed to 1 in the
final model, so CL(t) = CL0 / (1 + t / T50). Cockcroft-Gault creatinine
clearance modifies baseline clearance via a power form. Exponential IIV
on CL0, T50, and V; proportional residual error on plasma concentration.
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Hu_2017_peginterferon_beta_1a.html">Peginterferon
beta 1a (Hu 2017)</a> </td>
<td style="text-align:left;"> One-compartment population PK
model for peginterferon beta-1a in adults with relapsing multiple
sclerosis (Hu 2017). First-order SC absorption with the absorption rate
constrained above the elimination rate to avoid flip-flop kinetics. BMI
is a covariate on both clearance and volume of distribution. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Ahamadi_2017_pembrolizumab.html">Pembrolizumab
(Ahamadi 2017)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model for pembrolizumab (humanized anti-PD-1 IgG4 monoclonal antibody)
with allometric scaling and covariate effects of sex, albumin, tumor
type, ECOG performance status, prior ipilimumab status, eGFR, and
baseline tumor burden, in adults with advanced solid tumors (Ahamadi
2017, KEYNOTE-001/-002/-006) </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Elassaiss-Schaap_2017_pembrolizumab.html">Pembrolizumab
(Elassaiss-Schaap 2017)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model with parallel linear and Michaelis-Menten clearance plus a
direct-response Imax PK/PD model on the ex vivo IL-2 stimulation ratio
(PD-1 target engagement) for IV pembrolizumab (anti-PD-1 IgG4 mAb) in
adults with advanced solid tumors (Elassaiss-Schaap 2017, KEYNOTE-001
parts A, A1, A2). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Lindauer_2017_pembrolizumab.html">Pembrolizumab
(Lindauer 2017)</a> </td>
<td style="text-align:left;"> QSP / mini-PBPK. Translational
semi-mechanistic PK/PD/TGI model for the anti-PD-1 monoclonal antibody
pembrolizumab in advanced melanoma. Couples a two-compartment plasma PK
(parallel linear + Michaelis-Menten clearance, human PK substituted from
Elassaiss-Schaap 2017 KEYNOTE-001) to a Shah-Betts (2012) physiologic
tumor tissue compartment (vascular, endosomal, interstitial sub-spaces
with FcRn recycling), mechanistic pembrolizumab-PD-1 binding in both
blood and tumor, an indirect-response positive feedback that upregulates
tumor PD-1 expression when the complex forms, and a Simeoni-type
tumor-growth model in which the antitumor effect is a power function of
the tumor receptor occupancy. Mouse-derived parameter estimates plus
three human melanoma growth-rate scenarios (slow/medium/fast) and two
kill-rate scaling options (allometric / growth-proportional) are
tabulated in Lindauer 2017 Table 1 and Table S3; the default human
parameterisation here is medium growth with allometric kill-rate scaling
(the central reference scenario). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Gong_2023_pemigatinib.html">Pemigatinib
(Gong 2023)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model for oral pemigatinib (a selective fibroblast growth factor
receptor [FGFR] 1-3 inhibitor) in healthy participants and patients with
advanced solid tumors including cholangiocarcinoma (CCA) and
myeloid/lymphoid neoplasms with FGFR1 rearrangement (Gong 2023; N = 467
across seven FIGHT studies, 4552 concentration records). Disposition is
a two-compartment model with sequential zero-order and first-order oral
absorption (dose enters the depot over a zero-order window of duration
D1 = 0.810 h, then is absorbed first-order at ka = 3.67 h^-1) and linear
elimination (CL/F = 10.7 L/h, Vc/F = 118 L, Vp/F = 95.0 L, Q/F = 25.2
L/h). Covariate effects retained after stepwise forward addition and
backward elimination: concomitant phosphate-binding agent use reduces
CL/F by 15.5%; male sex increases CL/F by 26.2% and reduces ka by 58.3%
(female is the reference); concomitant proton-pump inhibitor use reduces
ka by 62.0%; concomitant histamine-2 receptor antagonist use reduces D1
by 33.4%; and baseline body weight scales Vc/F and Vp/F as power
functions of (WT / 73.9 kg) with exponents 0.842 and 1.13 respectively.
The paper reports all of these covariate effects as statistically
significant but not clinically significant on steady-state exposure.
Inter-individual variability is a correlated CL/F-Vc/F block (log-scale
variances 0.201 and 0.191, covariance 0.129, correlation 0.659) plus
independent terms on ka (1.69) and D1 (0.371); IIV on Q/F and Vp/F was
fixed to zero in the final model. Residual error is additive on the log
scale (approximately proportional in linear space) at 32.3%.
Concentrations are expressed in nM using the pemigatinib molecular
weight of 487.5 g/mol, matching the h*nM exposure units used throughout
the paper's exposure-response analyses. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Gong_2023_pemigatinib.html">Pemigatinib
creatinine (Gong 2023)</a> </td>
<td style="text-align:left;"> Exposure-response Emax model
relating steady-state pemigatinib exposure to the percentage change from
baseline in serum creatinine concentration, in 300 patients receiving
pemigatinib monotherapy across FIGHT-101, FIGHT-102, and FIGHT-202 (Gong
2023). Pemigatinib inhibits the renal transporters OCT2 (IC50 0.075 uM)
and MATE1 (IC50 1.1 uM), which mediate active tubular secretion of
creatinine; the resulting rise in serum creatinine is exposure-dependent
and reversible rather than a marker of renal injury. The model is a
direct-effect Emax function of the per-subject steady-state AUC over the
24 h dosing interval: pct change = Emax * AUC_PEMI / (EC50 + AUC_PEMI),
with Emax = 43.4% and EC50 = 2595 h*nM. It carries no ODE state -- the
exposure metric AUC_PEMI is supplied as a static covariate derived from
the companion population PK model (see
modellib('Gong_2023_pemigatinib')), mirroring the authors' workflow of
simulating a dense steady-state post hoc profile in NONMEM, deriving
AUCss noncompartmentally, and regressing the biomarker on it in SAS.
Evaluating the model at the paper's own mean steady-state AUC of 2850
h*nM for 13.5 mg once daily, and dose-scaling that value, reproduces the
four published predictions of 14.2%, 18.3%, 22.7%, and 26.9% at 6, 9,
13.5, and 20 mg to three significant figures. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Gong_2023_pemigatinib.html">Pemigatinib
phosphate (Gong 2023)</a> </td>
<td style="text-align:left;"> Exposure-response Emax model
relating steady-state pemigatinib exposure to the mean change from
baseline in serum phosphate concentration at cycle 1 day 8 and cycle 1
day 15, in 300 patients receiving pemigatinib monotherapy across
FIGHT-101, FIGHT-102, and FIGHT-202 (Gong 2023). Pemigatinib inhibits
FGFR1-3; FGFR1 blockade attenuates FGF23 signalling in the renal
proximal tubule, reducing urinary phosphate excretion, so the
exposure-dependent rise in serum phosphate is an on-target class effect
that the authors use as a pharmacodynamic surrogate for pemigatinib
exposure. The model is the paper's three-parameter direct-effect Emax
function of the per-subject steady-state AUC over the 24 h dosing
interval, with baseline serum phosphate entering as an additive
covariate: change = Emax * AUC_PEMI / (EC50 + AUC_PEMI) + coef *
baseline, with Emax = 5.51 mg/dL, EC50 = 1665 h*nM, and coef = -0.185
per mg/dL (carried as -0.5730 per mmol/L against the SI-canonical PHOS
column). It carries no ODE state -- the exposure metric AUC_PEMI is
supplied as a static covariate derived from the companion population PK
model (see modellib('Gong_2023_pemigatinib')), mirroring the authors'
workflow of simulating a dense steady-state post hoc profile in NONMEM,
deriving AUCss noncompartmentally, and regressing the biomarker on it in
SAS. The endpoint is reported in the paper's mg/dL. The fitted EC50 of
1665 h*nM approximates the mean AUC0-24h at 8 mg once daily, which is
the basis of the paper's claim that serum phosphate can serve as an
exposure surrogate. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Ogungbenro_2009_penciclovir.html">Penciclovir
(Ogungbenro 2009)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model with first-order absorption and lag time for penciclovir in pooled
adults and children (Ogungbenro 2009). Famciclovir is the oral prodrug
of penciclovir; both oral famciclovir and intravenous penciclovir doses
are described jointly (six clinical studies, 69 subjects of whom 23 are
children, 160 occasions, 1676 plasma penciclovir observations).
Allometric body-weight scaling with reference 70 kg (exponent 0.75
shared on CL and Q, exponent 1.0 shared on V1 and V2), an empirical
piecewise age effect on CL with separate K parameters for AGE < 40
years (rising-with-youth limb) and AGE >= 40 years
(declining-with-elderly limb), and a power function of creatinine
clearance on CL with reference 100 mL/min (Cockcroft-Gault, raw mL/min).
Inter-individual variability on ka, CL, V1 (fixed at omega^2 = 0.003),
V2, and Q; combined proportional plus additive residual error (additive
variance fixed at 0.01 mg^2/L^2). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Muller_2007_penicillin_G.html">Penicillin
G (Muller 2007)</a> </td>
<td style="text-align:left;"> Two-compartment IV bolus
population PK model for penicillin G (benzylpenicillin) in 20 very
preterm neonates with gestational age less than 32 weeks studied on day
3 of life (Muller 2007). Clearance is linearly scaled to current body
weight with reference 1.195 kg (cohort mean); central volume, peripheral
volume, and intercompartmental clearance are not weight-scaled in the
final model. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Padari_2018_penicillin_G.html">Penicillin
G (Padari 2018)</a> </td>
<td style="text-align:left;"> Two-compartment IV population PK
model for penicillin G (benzylpenicillin) in preterm and term neonates
(Padari 2018; pooled with Metsvaht 2007 GA <=28 wk cohort). CL and Q
are allometrically scaled to body weight (fixed exponent 0.75) with a
fixed Rhodin-style postmenstrual-age (PMA) sigmoidal renal-maturation
function on CL; Vc and Vp are allometrically scaled (fixed exponent
1.0). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Li_2014_penicillinG.html">PenicillinG
cattle (Li 2014)</a> </td>
<td style="text-align:left;"> Preclinical (cattle).
Three-compartment population pharmacokinetic model for penicillin G in
cattle, with four parallel first-order absorption depots covering
intramuscular penicillin sodium, intramuscular procaine penicillin,
subcutaneous procaine penicillin, and oral procaine penicillin (the oral
depot feeds the liver compartment directly), plus separate liver and
kidney tissue compartments connected to the central compartment by
inter-compartmental clearance; pooled meta-analysis of 100 cattle from
30 published studies and FARAD records (Li 2014). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Li_2014_penicillinG.html">PenicillinG
swine (Li 2014)</a> </td>
<td style="text-align:left;"> Preclinical (swine).
Three-compartment population pharmacokinetic model for penicillin G in
swine, with two parallel first-order absorption depots covering
intramuscular penicillin potassium and intramuscular procaine
penicillin, plus separate kidney and muscle tissue compartments
connected to the central compartment by inter-compartmental clearance;
pooled meta-analysis of 89 pigs from 13 published studies and one
unpublished FDA dataset (Li 2014). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Silva_2023_perampanel.html">Perampanel
(Silva 2023)</a> </td>
<td style="text-align:left;"> One-compartment popPK model of
perampanel in Portuguese adults with refractory epilepsy on chronic
therapeutic drug monitoring (Silva 2023). NONMEM FOCE-I fit of 72
steady-state plasma concentrations from 44 patients; concentrations were
obtained during the elimination phase only (9.7-24 h post-dose) so
first-order absorption could not be estimated, and dosing was modelled
as an IV bolus into the central compartment (perampanel oral
bioavailability is ~100% per the summary of product characteristics).
Concomitant enzyme-inducing antiepileptic drugs (carbamazepine,
oxcarbazepine, phenobarbital, or phenytoin) increase apparent clearance
2.76-fold; body-mass index enters the volume of distribution as a power
function centred at the sample median BMI of 25.1 kg/m^2. Inter-patient
variability is exponential on clearance only; residual error is
proportional. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Luo_2024_CES1_cirrhosis.html">Perindopril
pbpk (Luo 2024)</a> </td>
<td style="text-align:left;"> PBPK (semi-mechanistic, custom
WinNonlin 8.1 implementation). Joint perindopril + perindoprilat
disposition in healthy adults and in liver cirrhosis (Child-Pugh A/B/C).
Perindopril is an inactive ester prodrug hydrolysed by hepatic CES1 to
the active diacid perindoprilat, which is eliminated renally.
Perindopril has a second, parallel hepatic pathway (UGT glucuronidation)
that does NOT form perindoprilat; because the responsible UGT isoenzyme
is unidentified, its cirrhosis scaling uses the metoprolol AUC0-inf
change rate of 0.62 (Section 3.1.4). The semi-PBPK circuit is stomach,
three small-intestinal lumen segments (duodenum / jejunum / ileum), the
matching three gut-wall segments, portal vein, liver, kidney and a
two-compartment systemic compartment. Cirrhosis is applied by switching
the Child-Pugh-specific physiology of Table 1 (organ blood flows,
functional liver volume, GI transit rates, GFR, plasma-binding protein
concentrations, hepatic CES1 content) and rescaling CLint, CLint,K, Peff
and Vsys through Eq 1-6. Deterministic: the paper's virtual populations
are uniform 80-120% draws on the drug parameters, not lognormal random
effects, so no IIV is encoded. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Gaohua_2023_permeabilityLimited_pbpk.html">PermeabilityLimited
pbpk (Gaohua 2023)</a> </td>
<td style="text-align:left;"> PBPK (whole-body,
permeability-limited, 55 ODEs; bespoke MATLAB/SimBiology 2022a model).
Theoretical what-if investigation of how passive permeability,
metabolism, active transporters and dosing route determine the dynamics
of the tissue/plasma partition coefficient Kp(t) and the volume of
distribution Vd(t). Twelve tissues (adipose, bone, brain, heart, kidney,
muscle, skin, liver, pancreas, spleen, gut, lung) each carry four
subcompartments - residual blood cells (_bc), residual plasma (_plasma),
extracellular water (_ew) and intracellular water (_iw) - and the three
blood compartments (venous, arterial, portal vein) carry the blood-cell
and plasma subcompartments only, giving 12*4 + 3*2 = 54 disposition
states plus a gut-lumen depot. Passive permeation runs between adjacent
subcompartments (Eqs 8-10), active uptake and efflux transporters sit on
the cell membrane between _ew and _iw (Eqs 11-12), and metabolism may
occur in any subcompartment (Eqs 13-16). There is no drug: the compound
is a generic small molecule with fu = fi = 1 everywhere, so a
perfusion-limited model would give Kp = 1 in every tissue and Vdss = 1
L/kg exactly; any departure from those values measures the
permeability-limited model's divergence from the perfusion-limited one.
Every permeability, metabolic clearance and transporter clearance is
parameterised as a fold-multiple of that tissue's plasma flow (the
fold_* parameters), which is exactly how the paper drives its what-if
scenarios - each scenario in Tables 1-4 is a one-parameter change.
Deterministic typical-value simulation model: the paper reports no IIV
and no residual-error model. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Garg_2014_pertuzumab.html">Pertuzumab
(Garg 2014)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model with first-order linear elimination from the central compartment
for intravenous pertuzumab (PERJETA) in patients with a variety of
HER2-targeted solid tumors (Garg 2014) </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Wang_2021_pertuzumab.html">Pertuzumab
(Wang 2021)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model with first-order subcutaneous absorption and bioavailability for
pertuzumab (Perjeta) administered either intravenously or as the
fixed-dose combination subcutaneous formulation with trastuzumab (PH FDC
SC) in patients with HER2-positive early breast cancer in the FeDeriCa
study (Wang 2021) </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Yin_2020_pexidartinib.html">Pexidartinib
(Yin 2020)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model for oral pexidartinib (CSF1R/KIT/FLT3 inhibitor) in healthy
subjects and adult patients with tenosynovial giant cell tumour (TGCT)
or other advanced solid tumours (Yin 2020). Absorption is sequential
zero-order deposition into a depot (duration D1, lag time ALAG1)
followed by first-order absorption (KA) into the central compartment,
with linear elimination from central. Apparent clearance CL/F scales
allometrically on (WT/80)^0.75 and is additionally modified by piecewise
power effects of CRCL (active only when CRCL < 90 mL/min), AST
(active only when AST > 80 U/L), and total bilirubin (active only
when TBILI > 20.5 umol/L), plus multiplicative effects for Asian race
(1.27x), healthy-participant cohort (1.26x; the Phase 1 healthy-subject
studies), and female sex (0.869x). Apparent central and peripheral
volumes Vc/F and Vp/F scale on (WT/80)^1; apparent inter-compartmental
clearance Q/F scales on (WT/80)^0.75. Relative bioavailability of the
Phase 1 formulation is fixed at 0.855 vs the Phase 3 / commercial
reference formulation. Inter-individual variability is a 3x3 block on
log(CL,Vc,Vp), independent diagonals on log(KA) and log(Q), and a
Phase-1-formulation-specific IIV on the F1 bioavailability anchor. The
published inter-occasion variability (5 occasions on KA, 10 occasions on
F1) is not encoded structurally here (following the Andrews 2017 /
Brooks 2021 tacrolimus precedent for the model-library use case where no
operational occasion column is defined). Residual error is proportional
with separate magnitudes for patient samples (29.7% CV) and
healthy-subject samples (19.6% CV), switched per-subject by the
DIS_HEALTHY indicator. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Yin_2021_pexidartinib.html">Pexidartinib
(Yin 2021)</a> </td>
<td style="text-align:left;"> Semi-mechanistic longitudinal
tumor-size (RECIST) exposure-response PD model for pexidartinib in adult
patients with tenosynovial giant cell tumor (TGCT), driven by
pre-computed running average pexidartinib concentration Cavg (mg/L).
Tumor size Y(t) declines from an individual baseline Y0 through a
saturable drug effect gated by an onset first-order process: Y(t) = Y0 *
(1 - Emax * (1 - exp(-kdrug * Cavg)) * (1 - exp(-konset * TAFD))) +
growth * time, with Emax fixed at 0.999 and natural tumor growth fixed
at 0 (Yin 2021 Results: the placebo-cohort growth rate estimate 0.227
cm/yr had a 95% CI that included zero and was fixed). Baseline Y0,
drug-effect rate constant kdrug, and onset rate constant konset each
carry three multiplicative covariate effects: joint extremity (upper vs
lower reference), joint size (small vs large reference), and age
centered at 44 years. Individual variability is a 3x3 log-normal block
on baseline, kdrug, and konset. Residual error is a power-of-prediction
form SD(Y) = 0.365 * Ypred^0.550. The pexidartinib PK backbone (Cavg
input) is a separately extracted model,
`modellib('Yin_2020_pexidartinib')`, corresponding to the same authors'
Yin 2020 J Clin Pharmacol popPK publication (reference 5 in Yin 2021).
This PD model does NOT carry the ORR proportional-odds logistic
regression (Table S3) or the piecewise-exponential TTE hepatic-AE models
(Table S5) that appear as parallel endpoints in Yin 2021; those are
non-ODE statistical / survival regressions and are documented in the
paired vignette narrative but not encoded here as separate model files.
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Betts_2019_pf_06671008.html">Pf
06671008 qsp (Betts 2019)</a> </td>
<td style="text-align:left;"> QSP. Preclinical (mouse).
Translational quantitative systems pharmacology model for the CD3 x
P-cadherin LP DART bispecific PF-06671008, fit to HCT-116 xenografts in
NSG mice with human PBMC engraftment. Couples bispecific PK (2-cpt
linear), permeability-diffusion tumor drug disposition, trimer
(drug-CD3-Pcad) formation in the TME, and tumor growth via a
4-compartment transduction (Simeoni-based) model (Betts 2019 AAPS J).
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Guo_2022_PF_06939999.html">PF
06939999 (Guo 2022)</a> </td>
<td style="text-align:left;"> Population PK/PD model for
PF-06939999 (a small-molecule PRMT5 inhibitor) in 28 adults with
advanced solid tumors enrolled in the dose-escalation part of
NCT03854227. PK is a two-compartment model with first-order absorption
(CL/F, V1/F, Q/F, V2/F, Ka). Plasma SDMA (the PD biomarker for PRMT5
inhibition) is modelled by an indirect-response model with saturable
Imax inhibition on zero-order SDMA production (Kin/Kout), the
log-transformed SDMA observation taking an additive (log-normal)
residual error. Platelet count is described by the Friberg
semi-mechanistic myelosuppression model (proliferating cells plus three
transit compartments feeding a circulating compartment) with a linear
drug effect Slope*Cc on the proliferation rate and feedback
(Circ0/circ)^gamma. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Langdon_2010_PF00821385.html">PF00821385
dog (Langdon 2010)</a> </td>
<td style="text-align:left;"> Preclinical (beagle dog).
Translational popPK-PD model for PF-00821385, a Pfizer HIV-1 gp120
cell-fusion inhibitor candidate (molecular weight 440.49 g/mol) studied
in conscious freely-moving Beagle dogs. PK is a one-compartment
disposition model with first-order oral absorption; PD describes heart
rate as the sum of (a) a typical-value baseline HR with log-normal
inter-subject variability, (b) a 24-h cosine circadian rhythm with
typical-value amplitude and a log-normal inter-subject variable peak
time, and (c) a linear drug effect on free plasma concentration with no
IIV. The PD-slope SLOPE = 1.76 bpm per micromolar free drug is from
Langdon 2010 Table 1; plasma unbound fraction fu = 0.64 is FIXED via
back-calculation from the published unbound vs total Cmax ratio at 20
mg/kg oral (paper Introduction); see vignette Errata. PK and PD were fit
sequentially in NONMEM VI using FOCE INTER with individual Bayesian post
hoc PK estimates serving as input to the PD model. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Langdon_2010_PF00821385.html">PF00821385
human (Langdon 2010)</a> </td>
<td style="text-align:left;"> First-in-human popPK-PD model for
PF-00821385, a Pfizer HIV-1 gp120 cell-fusion inhibitor candidate
(molecular weight 440.49 g/mol), developed in 24 healthy male volunteers
from a single-ascending-dose study (Langdon 2010 Tables 2 and Figure 3).
PK is a two-compartment model with first-order oral absorption and an
additive residual error on the log-transformed plasma concentrations
(i.e., a log-normal residual). PD describes supine pulse rate as the sum
of (a) a typical- value baseline rate with log-normal inter-subject
variability, (b) a 24-h cosine circadian rhythm with typical-value
amplitude and log- normal inter-subject variable peak time, and (c) a
linear drug effect on free plasma concentration with no IIV. The
PD-slope SLOPE = 0.76 bpm per micromolar free drug is from Langdon 2010
Table 2; plasma unbound fraction fu = 0.64 is FIXED via back-calculation
from the canine toxicology Cmax data (see vignette Errata). The PD layer
was fit sequentially to individual Bayesian post hoc PK estimates from
the population PK fit (NONMEM VI with FOCE INTER; 500-iteration
nonparametric bootstrap for SE / CI). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Li_2018_PF04236921.html">PF04236921
(Li 2018)</a> </td>
<td style="text-align:left;"> Integrated population PK and
indirect-response PK/PD model for the anti-interleukin-6 monoclonal
antibody PF-04236921 in healthy volunteers and adults with rheumatoid
arthritis, Crohn's disease, or systemic lupus erythematosus (Li 2018).
Two-compartment IV/SC PK with first-order absorption and linear
elimination from the central compartment; disease-stratified linear
clearance and PD parameters; PF-04236921 inhibits the zero-order CRP
synthesis rate of an indirect-response model. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Chang_2011_PF04455242_prolactin.html">PF04455242
human (Chang 2011)</a> </td>
<td style="text-align:left;"> Two-compartment population PK and
reduced direct-response PD model for PF-04455242 (kappa opioid receptor
antagonist) in healthy adult volunteers (Chang 2011). PK is fit with
zero-order oral absorption (duration D1) and lag time (ALAG1) into the
central compartment; residual error uses the log-transform-both-sides
(lognormal) form. PD is the reduced antagonism model (Eq. 11/12) that
replaces the spiradoline PK with a deterministic Weibull-scaled placebo
prolactin profile and predicts the time-matched prolactin response under
PF-04455242 antagonism. Simulation time t = 0 must be aligned with the
IM spiradoline challenge dose; PF-04455242 is dosed earlier (typically t
= -1 h in the proof-of-mechanism study). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Chang_2011_PF04455242_prolactin.html">PF04455242
rat (Chang 2011)</a> </td>
<td style="text-align:left;"> Preclinical (Sprague-Dawley rat).
Competitive antagonism PK-PD model of PF-04455242 (kappa opioid receptor
antagonist) on spiradoline-induced plasma prolactin elevation.
One-compartment first-order absorption PK for both spiradoline (KOR
agonist challenge) and PF-04455242, with a dose-dependent absorption
rate constant for PF-04455242 (1.64 /h at 3.2 mg/kg SC, 0.385 /h at 10
mg/kg SC). Direct-response sigmoid Emax PD: prolactin = baseline + Emax
* Csp^gamma / ((EC50 * (1 + Cpf/Ki))^gamma + Csp^gamma) with competitive
antagonism of the spiradoline-induced rise by PF-04455242. Spiradoline
plasma compartments are declared via paper_specific_compartments rather
than registering a new sibling-drug suffix; see Errata in the vignette
for the rationale. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Benson_2014_PF04457845_qsp.html">PF04457845
qsp (Benson 2014)</a> </td>
<td style="text-align:left;"> QSP. Whole-body
four-physiological-compartment (brain, plasma, rest-of-body ROB,
blood-brain-barrier microvascular endothelial cells MEC)
systems-pharmacology model for the irreversible FAAH-1 inhibitor
PF-04457845 and five fatty acid ethanolamide substrates (anandamide AEA,
N-oleoyl-ethanolamide OEA, N-palmitoyl-ethanolamide PEA,
N-linoleoyl-ethanolamide LEA, N-stearoyl-ethanolamide SEA). 39 ODE
states coupling: PF-04457845 pharmacokinetics (first-order absorption,
saturable Michaelis-Menten plus linear elimination, plasma-ROB tissue
distribution); irreversible PF-04457845 inhibition of FAAH with FAAH
protein turnover; NAPE-phospholipase-D-mediated ethanolamide synthesis
from the N-acyl phosphatidylethanolamine precursors with competitive
substrate inhibition among the five ethanolamides; FAAH-independent
clearance via N-acylethanolamine-hydrolyzing acid amidase (NAAA);
bidirectional AEA-transporter and passive diffusion transport of
ethanolamides between ROB, MEC and plasma; blood-brain-barrier flux of
ethanolamides between brain and MEC; and Emax cannabinoid receptor CB1
occupancy in brain by AEA. All 110+ structural, physiologic,
enzyme-kinetic, receptor-binding, and PK parameters are fixed from the
paper's supplement Table S1 and Model S1 SBML export: Peters and Hultin
2008 PBPK physiology for the average 70-kg-adult tissue volumes;
literature in vitro enzyme-kinetic measurements for FAAH kcat/Km,
NAPE-PLD forward/reverse rates and substrate Ki, and NAAA affinities;
McPartland 2007 CB1 in vitro K_d; and Pfizer Phase I data (Li 2012) for
FAAH turnover, drug PK, and the fitted NAT relative activities. No IIV,
no residual variability -- the model is deterministic and describes mean
biomarker profiles. 2-arachidonoyl-glycerol (2-AG) is not included
(fixed at zero) per the paper's stated scope. Model was originally
implemented in DBSolve Optimum and Matlab/SimBiology. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Jones_2011_PF04878691_HCV.html">PF04878691
(Jones 2011)</a> </td>
<td style="text-align:left;"> Two-compartment population
pharmacokinetic model with first-order oral absorption and time-varying
clearance for the toll-like-receptor-7 (TLR7) agonist PF-04878691 in
healthy male and female adult volunteers (Jones 2011 BJCP, Phase 1
multiple-dose escalation study, twice-weekly oral doses of 3, 6, or 9 mg
over 2 weeks). Observed plasma exposure increased over the dosing period
inconsistently with the 12-16 h terminal half-life; a standard linear
time-invariant two-compartment model over-estimated Cmax on day 1 and
under-estimated exposure on day 11. The clearance was therefore
parameterised with an exponentially decaying time-dependent component
superimposed on a steady-state arm: CL(t) = CL_SS + CL_TIME *
exp(-cl_exp_kdes * TAFD), where TAFD is the time after first dose.
Reparameterised from the paper's CLF (final = CL_SS) and CL0 (initial =
CL_SS + CL_TIME). The hypothesised mechanism for the time-varying
clearance is IFN-mediated CYP1A2 inhibition by the TLR7-induced
interferon response (Discussion). All disposition parameters are
reported per kilogram body weight (paper: doses were
body-weight-normalised so estimated PK parameters carry per-kg units);
WT is therefore a required covariate. No other covariates retained.
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Jones_2011_PF04878691_HCV.html">PF04878691
lymphocyte (Jones 2011)</a> </td>
<td style="text-align:left;"> Coupled PK + indirect-response
pharmacodynamic model for absolute lymphocyte count during oral
PF-04878691 (TLR7 agonist) administration in healthy adult volunteers
(Jones 2011 BJCP). PK is the two-compartment time-varying clearance
model from the companion file Jones_2011_PF04878691.R (Table 1; all PK
structural parameters and IIVs fixed at the published Table 1 values so
the PK forcing function is the published popPK profile). Drug stimulates
the re-distribution (loss) of lymphocytes through a power function on
kout: dLYMPH/dt = kin - kout * (1 + slope * Cc^gamma) * LYMPH, with
baseline lymphocyte count rbase = kin / kout so that kin = rbase * kout
(Jones 2011 Methods / Table 3 lymphocyte model). The typical Emax
indirect-response model could not adequately identify the parameters
given the limited number of dose levels studied, so the Emax * Cc^gamma
/ (EC50^gamma + Cc^gamma) drug effect was replaced with the power
function slope * Cc^gamma (Methods 'Population PK-OAS and PK-lymphocyte
models'). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Jones_2011_PF04878691_HCV.html">PF04878691
oas (Jones 2011)</a> </td>
<td style="text-align:left;"> Coupled PK + indirect-response
pharmacodynamic model for the 2',5'-oligoadenylate synthetase (OAS)
gene-expression fold change during oral PF-04878691 (TLR7 agonist)
administration in healthy adult volunteers (Jones 2011 BJCP). PK is the
two-compartment time-varying clearance model inherited from the
companion file Jones_2011_PF04878691.R (Table 1; all PK structural
parameters and IIVs fixed at the published Table 1 values so the PK
forcing function is the published popPK profile). Drug stimulates the
production of OAS through a power function: dOAS/dt = kin * (1 + slope *
Cc^gamma) - kout * OAS, with baseline OAS fold change rbase = kin / kout
so that kin = rbase * kout (Jones 2011 Methods / Tables 2 OAS model).
The typical Emax indirect-response model could not adequately identify
the parameters given the limited number of dose levels studied, so the
Emax * Cc^gamma / (EC50^gamma + Cc^gamma) drug effect was replaced with
the power function slope * Cc^gamma (Methods 'Population PK-OAS and
PK-lymphocyte models'). The OAS observation is unitless (fold change
from baseline). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Jones_2011_PF04878691_HCV.html">PF04878691
viralLoad (Jones 2011)</a> </td>
<td style="text-align:left;"> Combined PK + OAS + HCV viral RNA
pharmacodynamic chain for oral PF-04878691 (TLR7 agonist) used to
predict the antiviral efficacy of PF-04878691 in chronic hepatitis C
(HCV) patients (Jones 2011 BJCP Figure 10 simulation). PK is the
two-compartment time-varying clearance model from
Jones_2011_PF04878691.R (Table 1; all PK structural parameters fixed at
the published Table 1 values plus the IIVs on CL_SS and ka). The
PF-04878691 OAS indirect-response sub-model is the same as
Jones_2011_PF04878691_oas.R (Table 2; OAS in fold-change units, baseline
rbase_oas = 0.96, drug stimulates production through slope * Cc^gamma).
The OAS-viral-load relationship was fit on TLR9-agonist (CPG-10101) data
in HCV patients (Jones 2011 Table 4) and is assumed transferable to
PF-04878691 under the paper's explicit translation assumption that 'both
TLR7 and TLR9 work through the same pathway'. The viral-load model is an
inhibitory sigmoid Imax driven by the change in OAS from baseline
expressed as a fold change oas_fc_above = oas(t) / rbase_oas - 1, so at
the OAS baseline the viral-load deviation from BASE is zero. The viral
RNA observation (vload) is in log10 copies/mL. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Grasela_1985_phenobarbital.html">Phenobarbital
(Grasela 1985)</a> </td>
<td style="text-align:left;"> One-compartment population PK
model for phenobarbital in preterm neonates (Grasela & Donn 1985),
derived from routine clinical data via NONMEM. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Saleh_2023_leicns_pk30_mouse_brain.html">Phenobarbital
mouse pbpk (Saleh 2023)</a> </td>
<td style="text-align:left;"> PBPK (LeiCNS-PK3.0 CNS
physiologically-based model, mouse version). Preclinical (mouse, ICR).
Nine-compartment CNS PBPK model predicting unbound phenobarbital
concentrations in brain extracellular fluid (brain ECF) after a single
10 mg/kg intraperitoneal dose. The CNS structure is the mouse
re-parameterisation of LeiCNS-PK3.0: brain microvasculature
(brain_vascular), brain ECF, a phospholipid brain-cell-membrane binding
compartment (brain_cell_membrane), brain intracellular fluid
(brain_icf), lysosomes (brain_lysosome), and the four CSF compartments
(lateral ventricles, third + fourth ventricles, cisterna magna,
subarachnoid space) draining in series back to plasma. Transport across
the BBB and BCSFB is the sum of a paracellular clearance (Qp, charged +
neutral drug) and a transcellular clearance (Qt, neutral drug only,
scaled by pH-dependent neutral fractions PHF and by asymmetry factors AF
that encode active transport). Every CNS parameter is fixed to mouse
physiology (Table III) or derived from the drug's physicochemical
properties (Table I); none was fitted here. The BBB asymmetry factors
are back-calculated from Kp,uu,BBB = 0.0121 (estimated by the authors;
Table V). The plasma PK model is the empirical one-compartment model of
Table IV (in-house NONMEM fit) and acts purely as a forcing function:
brain uptake does not deplete plasma, exactly as published. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Hennig_2015_phenytoin.html">Phenytoin
(Hennig 2015)</a> </td>
<td style="text-align:left;"> One-compartment population PK
model for phenytoin in critically ill children with a linear partition
coefficient describing protein binding to albumin (Hennig 2015).
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Tanaka_2012_phenytoin.html">Phenytoin
(Tanaka 2012)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model for phenytoin after IV fosphenytoin sodium administration in
Japanese healthy volunteers and adult / pediatric patients (Tanaka
2012). The fosphenytoin compartment converts first-order (K12) to the
phenytoin central compartment; phenytoin is cleared from central and
exchanges with a peripheral compartment via Q. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Yukawa_1990_phenytoin.html">Phenytoin
(Yukawa 1990)</a> </td>
<td style="text-align:left;"> Steady-state Michaelis-Menten
population PK model for phenytoin in 334 Japanese epilepsy outpatients
on chronic oral phenytoin (Yukawa 1990 Model 2). Covariate effects on
Vmax (allometric body weight, co-anticonvulsants) and Km (age <15 yr,
co-anticonvulsants); dose-dependent powder bioavailability. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Boer-Perez_2026_piperacillin.html">Piperacillin
(Boer-Perez 2026)</a> </td>
<td style="text-align:left;"> One-compartment population PK
model for piperacillin in preterm and term neonates with severe
infections (Boer-Perez 2026); body-weight allometric scaling, sigmoidal
postmenstrual-age maturation on CL fixed from Rhodin 2009, and a power
effect of serum creatinine on CL. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Bulitta_2007_piperacillin.html">Piperacillin
(Bulitta 2007)</a> </td>
<td style="text-align:left;"> Two-compartment first-order IV
population PK model for piperacillin in 8 adult cystic-fibrosis patients
and 26 adult healthy volunteers receiving 4 g piperacillin as a 5-min
intravenous infusion (Bulitta 2007). Lean body mass (LBM) is the size
descriptor with allometric scaling (exponents 0.75 on CL and Q, 1.0 on
V1 and V2; LBM_STD = 53 kg). A cystic-fibrosis disease-state indicator
multiplicatively scales V1 and V2 via fcyf_vss^DIS_CF (fcyf_vss =
0.926), with fcyf_cl^DIS_CF retained on CL at its boundary estimate of
1.00 for model-form traceability. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Bulitta_2010_piperacillin.html">Piperacillin
(Bulitta 2010)</a> </td>
<td style="text-align:left;"> Three-compartment population PK
model for piperacillin in healthy adult volunteers after a single
intravenous infusion, with first-order non-renal clearance and parallel
first-order plus mixed-order (Michaelis-Menten) renal elimination,
allometrically scaled to 70 kg; a urine compartment accumulates the
renally excreted amount (Bulitta 2010 Model 3, final model, NONMEM
estimates) </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/CohenWolkowiez_2014_piperacillin_tazobactam.html">Piperacillin
(CohenWolkowiez 2014)</a> </td>
<td style="text-align:left;"> One-compartment population PK
model for piperacillin in premature and term infants under 61 days
postnatal age (Cohen-Wolkowiez 2014); linear body-weight scaling on CL
and V (fixed exponent = 1) and a power effect of postmenstrual age on
CL. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Jeon_2014_piperacillin.html">Piperacillin
(Jeon 2014)</a> </td>
<td style="text-align:left;"> Two-compartment IV population PK
model for piperacillin in 50 Korean adult burn-ICU patients receiving
piperacillin-tazobactam 4.5 g (4 g piperacillin + 0.5 g tazobactam)
every 8 h as a 30-min infusion (Jeon 2014) </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Landersdorfer_2012_piperacillin.html">Piperacillin
(Landersdorfer 2012)</a> </td>
<td style="text-align:left;"> Three-compartment population PK
model for piperacillin in healthy adult volunteers after intravenous
infusion, with parallel first-order plus mixed-order (Michaelis-Menten)
renal clearance and first-order non-renal clearance; a urine compartment
accumulates the renally excreted amount (Landersdorfer 2012 Model 3, the
final model) </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Nichols_2016_piperacillin_tazobactam.html">Piperacillin
(Nichols 2016)</a> </td>
<td style="text-align:left;"> One-compartment population PK
model for piperacillin in critically ill children (1-9 years) receiving
extended-infusion piperacillin-tazobactam (Nichols 2016); IV zero-order
input, first-order elimination, and a linear-additive effect of body
weight on CL centered at the cohort median 18 kg. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/ObrinkHansen_2015_piperacillin.html">Piperacillin
(ObrinkHansen 2015)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model for piperacillin in critically ill adults with septic shock
(Obrink-Hansen 2015); linear first-order elimination with an additive
linear effect of plasma creatinine on clearance, IIV on CL and central
volume, and a proportional residual error. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/LopezArguello_2023_pbp_binding_pseudomonas.html">Piperacillin
qsp (LopezArguello 2023)</a> </td>
<td style="text-align:left;"> QSP. In vitro (Pseudomonas
aeruginosa PAO1). Whole-cell penicillin-binding protein (PBP)
covalent-binding model for piperacillin (penicillin): seven coupled ODEs
for the rate of net influx of drug across the outer membrane into
periplasm and the competitive, mass-balanced acylation of six PBPs (1a,
1b, 2, 3, 4, 5/6) counted as molecules per bacterial cell. The intact
parameter switches between the intact whole-cell assay
(penetration-limited; drug enters periplasm at Rate_Influx/access) and
the lysed isolated-membrane assay (no outer membrane; a vast excess of
drug molecules is present at time 0). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Wenker_2024_piperacillin_tazobactam.html">Piperacillin
tazobactam (Wenker 2024)</a> </td>
<td style="text-align:left;"> In vitro (hollow-fibre infection
model, HFIM; six Gram-negative strains). Sigmoidal Emax PK/PD-index
model for piperacillin/tazobactam in its clinical 8:1 ratio. Wenker 2024
ran a 21-experiment dose-fractionation study (7 growth controls plus 14
treated arms) in an HFIM and fit, by non-linear least squares on the 24
h timepoint, the change in bacterial density over 24 h as a function of
each candidate PK/PD index. fT>MIC (the percentage of the dosing
interval during which the free piperacillin/tazobactam concentration
exceeds the isolate MIC) was the best-fitting index (AIC 94.1, R^2
0.691) versus fCmax/MIC (AIC 102, R^2 0.526) and fAUC/MIC (AIC 96.9, R^2
0.62). The packaged model is the fT>MIC model of Wenker 2024 Figure
1: effect = e0 - emax * FTMIC_TZP^hill / (ec50^hill + FTMIC_TZP^hill),
where effect is the change in log10(CFU/mL) accrued over the 24 h
experiment (positive = net growth, negative = net kill), e0 = 4.155
(FIXED) is the change in the untreated growth controls, emax = 8.851
(FIXED) is the maximum achievable reduction of that change, ec50 = 51.01
%fT>MIC is the index value giving half-maximal effect (the paper
calls it EI50), and hill = 2.11 is the sigmoidicity coefficient (the
paper calls it gam). There is NO pharmacokinetic component: exposure
enters solely through the externally supplied per-experiment PK/PD index
FTMIC_TZP, and the model has no ODE states because Wenker 2024 fit only
the 24 h endpoint and never reported the starting inoculum numerically.
The corresponding PK/PD targets recovered from these coefficients are
48% fT>MIC for bacteriostasis, 60% fT>MIC for 1 log10 kill and 75%
fT>MIC for 2 log10 kill; the paper reports 48%, 60% and 77%
respectively (see the vignette Errata for the 2 log10 discrepancy).
Neither between-experiment variability nor a residual error magnitude
was reported, so no eta parameters are present and addSd is FIXED at 0;
the model is intended for typical-value and target-derivation
simulation. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Hoglund_2012_piperaquine.html">Piperaquine
(Hoglund 2012)</a> </td>
<td style="text-align:left;"> Population PK model for oral
piperaquine in pregnant and non-pregnant Sudanese women with
uncomplicated Plasmodium falciparum malaria (Hoglund 2012).
Three-transit-compartment absorption (ka = ktr) into a three-compartment
disposition model. Body weight is the only retained covariate, applied
as an allometric function on all clearances (fixed exponent 0.75) and
volumes (fixed exponent 1.0). Relative bioavailability F is fixed at 1.
The final model retains BSV on CL and F, treats MTT between-occasion
variability as forward-simulation IIV, and uses an additive residual on
the log-transformed observation (proportional in linear concentration
space). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Hoglund_2017_piperaquine.html">Piperaquine
(Hoglund 2017)</a> </td>
<td style="text-align:left;"> Population PK model for oral
piperaquine in adults, children, and healthy volunteers across 11 pooled
clinical studies (Hoglund 2017; individual-participant-data
meta-analysis, n = 728). Two-transit- compartment absorption with kA =
kTR feeding a three-compartment disposition model. Allometric body
weight scaling on all clearances (fixed exponent 0.75) and volumes
(fixed exponent 1.0) with reference weight 54 kg. Enzyme maturation
function on elimination clearance (Hill-type sigmoid with MF50 = 0.575
y, Hill = 5.51). Dose-occasion effect adds 23.7% to relative
bioavailability per consecutive dose. Bioavailability anchored at 1 with
IIV. Predictions are venous plasma piperaquine base concentrations
(ng/mL); a separately estimated capillary-to-venous scale of 106% is
documented but not applied because only venous output is simulated.
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Tarning_2008_piperaquine.html">Piperaquine
(Tarning 2008)</a> </td>
<td style="text-align:left;"> Population PK model for oral
piperaquine in Burmese and Karen adults and children with uncomplicated
Plasmodium falciparum malaria (Tarning 2008). Two-compartment
disposition with first-order absorption (no lag) and elimination from
the central compartment. Body weight is the only retained covariate: a
linear (1 + theta * (WT - 48)) effect on apparent oral clearance CL/F
and on apparent central volume of distribution Vc/F, centred on the
cohort median of 48 kg. The combined three-dose and four-dose Artekin
regimens were pooled; no treatment-regimen effect was retained.
Exponential IIV on all five disposition / absorption parameters.
Residual error is proportional in linear concentration space (the source
paper fit an additive error on natural-log-transformed concentrations).
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Tarning_2012_dihydroartemisinin_piperaquine.html">Piperaquine
(Tarning 2012)</a> </td>
<td style="text-align:left;"> Three-compartment population PK
model for oral piperaquine in 24 pregnant (second / third trimester) and
24 matched non-pregnant women with uncomplicated malaria treated with
the fixed-dose oral dihydroartemisinin-piperaquine combination once
daily for 3 days (Tarning 2012 AAC). Transit-compartment absorption with
5 fixed transit compartments (ktr = (n+1)/MTT with n=5); the
drug-transit rate is set equal to the absorption rate from the last
transit to central (single estimated ktr). F fixed at 1; CL/F and F
carry proportional pregnancy effects (+45.0% on CL/F and +46.8% on F).
IIV on CL/F (21.5% CV) and Vc/F (39.5% CV); between-occasion variability
(BOV across 3 dose occasions) on MTT (45.8% CV) and F (56.3% CV)
multiplexed by the OCC indicator. Additive residual on natural-log
concentrations (sigma = 0.285), encoded as proportional residual on the
linear-concentration scale per Kloprogge 2018 lumefantrine precedent.
Companion file Tarning_2012_dihydroartemisinin.R models the
co-administered dihydroartemisinin arm. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Tarning_2014_piperaquine.html">Piperaquine
(Tarning 2014)</a> </td>
<td style="text-align:left;"> Population PK model for oral
piperaquine in adults with uncomplicated Plasmodium falciparum malaria
in Thailand (Tarning 2014; n = 30, fed vs fasting parallel design).
Three-transit-compartment absorption (ka = ktr) feeding a
three-compartment disposition model. Allometric body-weight scaling on
all clearances (fixed exponent 0.75) and volumes (fixed exponent 1.0);
70 kg reference. Linear dose-occasion effect on relative bioavailability
(+25.3% per consecutive dose, OCC = 1, 2, 3). Linear age effect on the
first peripheral volume of distribution (+4.10% per year of age).
Relative bioavailability anchored at 1 with between-dose-occasion
variability (no BSV in the final model). Concomitant low-fat food was
tested as a covariate but was not retained in the final model.
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Kakara_2014_statins_LDLC.html">Pitavastatin
(Kakara 2014)</a> </td>
<td style="text-align:left;"> PD-only indirect-response Imax
model for LDL-cholesterol lowering by pitavastatin (Kakara 2014). One
LDL-C compartment with zero-order synthesis Kin inhibited by Imax * DOSE
/ (ID50 + DOSE), where DOSE is the current daily pitavastatin dose
(mg/day) supplied as a time-varying covariate column. An additive 0.109
contribution to the inhibition fraction is applied when ezetimibe is
coadministered (CONMED_EZE = 1). The LDL-C synthesis-elimination loop is
set up at steady state by enforcing Kin = Baseline * Kout (Kout derived
inside model() as Kin / Baseline). Baseline LDL-C is age-scaled as 152 *
(AGE/62)^(-0.240). Imax (0.567), Kin (32.8 mg/dL/day), Baseline (152
mg/dL), the age power exponent (-0.240), the ezetimibe INH contribution
(0.109), and the IIV magnitudes are shared with Kakara_2014_atorvastatin
and Kakara_2014_rosuvastatin (one joint NONMEM 7.2 FOCE-INTER fit across
378 patients). Pitavastatin ID50 = 0.860 mg per Kakara 2014 Table 2.
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Lu_2019_polatuzumab.html">Polatuzumab
(Lu 2019)</a> </td>
<td style="text-align:left;"> Integrated two-analyte population
PK model of polatuzumab vedotin (anti-CD79b vc-MMAE antibody-drug
conjugate) in adults with non-Hodgkin lymphoma (Lu 2019). The
antibody-conjugated MMAE (acMMAE) is described by a two-compartment
model with three parallel elimination pathways from the central
compartment: a slowly-time-decaying nonspecific linear clearance (CL_NS,
sigmoidal Hill decline with cycle), a rapidly-decaying linear clearance
(CL_t, mono-exponential decline), and a saturable Michaelis-Menten
clearance (CL_MM). All three acMMAE pathways feed unconjugated MMAE
formation in the central MMAE compartment with relative conversion
fractions FRAC_NS, FRAC_NS x FRAC_CLT, and FRAC_NS x FRAC_MM, modulated
by a time-dependent multiplier (1 + FRAC_T x exp(-alpha x t)) on FRAC_NS
that captures the cycle-over-cycle decline in MMAE formation.
Unconjugated MMAE is described by an apparent two-compartment model with
parallel linear (CL_MMAE) and Michaelis-Menten (Vmax_MMAE / KSS)
elimination from its central compartment. Modeled in MMAE-equivalent
micrograms (pola dose in ug/kg x weight in kg x 3.65 x 718 / 145001
-> MMAE-equivalent ug administered to the acMMAE central
compartment), with concentrations in ng/mL = ug/L. The Asian-race
indicator on acMMAE Vc (e_asian_vc = 0.929, i.e., 7.1% lower V1 in Asian
patients) is retained from the Lu 2019 final model and was subsequently
re-quoted and assessed as not clinically meaningful in the Shi 2020
ethnicity-sensitivity analysis (PMID 32770353) of the same upstream
popPK model. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Lu_2017_polatuzumab_neuropathy.html">Polatuzumab
neuropathy (Lu 2017)</a> </td>
<td style="text-align:left;"> Time-to-event hazard model for
the onset of grade >= 2 peripheral neuropathy (PN) during polatuzumab
vedotin treatment in adults with relapsed/refractory B-cell non-Hodgkin
lymphoma (Lu 2017). The PN hazard is driven by a hypothetical effect
compartment receiving plasma antibody-conjugated MMAE (acMMAE) with
first-order distribution k1e in and ke0 = k1e out, modulated by a
Weibull time function on the drug-effect potency (alpha drug-effect,
beta shape) and by twelve baseline-covariate proportional-hazard terms
(age, body weight, sex, active grade 1 PN at baseline, prior
radiotherapy, prior vinca alkaloid, prior platinum-based chemotherapy,
rituximab combination, tumor histology DLBCL vs other-non-FL, baseline
tumor sum of products of perpendicular diameters, baseline serum
albumin). The acMMAE plasma driver is inlined from the published Lu 2019
integrated two-analyte popPK (acMMAE side only; see
Lu_2019_polatuzumab.R) per the standing policy of reusing a published
same-drug PK when the originally-used PK source (Lu 2015 ASCPT poster,
unpublished) is not on disk. Both the instantaneous hazard and the
cumulative hazard / survival outputs are exposed for direct VPC
simulation of the Kaplan-Meier curve. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Cheah_2016_polymyxin_Abaumannii_dynamics.html">Polymyxin
AB3070294 (Cheah 2016)</a> </td>
<td style="text-align:left;"> In vitro (Acinetobacter baumannii
AB307-0294; clinical heteroresistant isolate). Mechanism-based PK/PD
model for polymyxin B and colistin against A. baumannii in a dynamic
one-compartment in vitro infection model (IVM). Identical structural
model to Cheah_2016_polymyxin_ATCC19606 (three bacterial subpopulations
bact_s/bact_r/bact_d with logistic carrying capacity, Bulitta 2010
lipid-A receptor-occupancy submodel, Hill-function killing,
single-compartment adaptive-resistance turnover, IVM one-compartment
PK); strain-specific parameter values from Cheah 2016 Table 1 column
AB307-0294. Fitness cost G_inhib_max was not estimated for this strain
(Table 1 'NE') so f_cost is held at 0. SC50 is inherited as a FIXED
proxy from Bulitta 2015 (Cheah 2016 does not report it); see vignette
Errata for the full inheritance list. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Cheah_2016_polymyxin_Abaumannii_dynamics.html">Polymyxin
ATCC19606 (Cheah 2016)</a> </td>
<td style="text-align:left;"> In vitro (Acinetobacter baumannii
ATCC 19606; heteroresistant reference strain). Mechanism-based PK/PD
model for polymyxin B and colistin against A. baumannii in a dynamic
one-compartment in vitro infection model (IVM). The bacterial system is
partitioned into three subpopulations -- polymyxin-susceptible (bact_s,
CFU_S in the paper), constitutively polymyxin-resistant (bact_r, CFU_R;
killing rate fixed at zero), and dormant or extremely slowly replicating
cells (bact_d, Pop_D; nonobservable on viable-count plates) -- with a
logistic carrying capacity CFU_max constraining the total observable
population and a first-order bidirectional transition between
susceptible and dormant states (k_SD, k_DS). Polymyxin in the IVM
reservoir (central compartment) follows one-compartment first-order
kinetics (CL_IVM, V_IVM) with simulated elimination half-life 11.6 h.
Polymyxin target-site binding follows the Bulitta 2010 lipid-A LPS
receptor-occupancy model: competitive displacement of bound divalent
cations (Ca2+ and Mg2+) by polymyxin gives F_bound_cations (Eq 4), and a
Hill function of the unoccupied fraction (Hill_binding, EC50) gives
F_polymyxin_eff (Eq 5). The effective polymyxin concentration
C_polymyxin_eff is the F_polymyxin_eff-weighted reservoir concentration
divided by (1 + R_adaptive) to encode adaptive resistance attenuation
(Eq 6). Bacterial killing is a Hill function of C_polymyxin_eff (Eq 7;
Kill_max fixed at 100/h, Hill_killing, KillC50). Adaptive resistance
R_adaptive is a single-compartment turnover whose driver Stim is a
Hill-1 of raw reservoir polymyxin concentration (Eq 8; S_max fixed at
300, SC50 inherited from Bulitta 2015 since Cheah 2016 does not report
it), with rate constant k_adapt (Eq 9). For ATCC 19606 the fitness cost
G_inhib_max was not estimated by the authors (Table 1 'NE') so f_cost is
held at 0. Observation is the log10 of the drug-free agar viable count
CFU_S + CFU_R (Eq 11). The model has no inter-experiment IIV
(typical-value fit per strain) and the residual error is set to a tiny
fixed value because Cheah 2016 does not report it -- see vignette Errata
for the full inheritance / approximation list. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Cheah_2016_polymyxin_Abaumannii_dynamics.html">Polymyxin
FADDIAB008 (Cheah 2016)</a> </td>
<td style="text-align:left;"> In vitro (Acinetobacter baumannii
FADDI-AB008; clinical heteroresistant isolate; loss-of-LPS resistance
mechanism). Mechanism-based PK/PD model for polymyxin B and colistin
against A. baumannii in a dynamic one-compartment in vitro infection
model (IVM). Identical structural model to
Cheah_2016_polymyxin_ATCC19606 (three bacterial subpopulations
bact_s/bact_r/bact_d with logistic carrying capacity, Bulitta 2010
lipid-A receptor-occupancy submodel, Hill-function killing,
single-compartment adaptive-resistance turnover, IVM one-compartment
PK); strain-specific parameter values from Cheah 2016 Table 1 column
FADDI-AB008. For this strain the experimental data supported inclusion
of a fitness cost f_cost on susceptible replication (Eq 10): G_inhib_max
= 0.994 (Table 1). SC50 is inherited as a FIXED proxy from Bulitta 2015
(Cheah 2016 does not report it); see vignette Errata. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Cheah_2016_polymyxin_Abaumannii_dynamics.html">Polymyxin
FADDIAB030 (Cheah 2016)</a> </td>
<td style="text-align:left;"> In vitro (Acinetobacter baumannii
FADDI-AB030; clinical polymyxin-susceptible isolate without
heteroresistance). Mechanism-based PK/PD model for polymyxin B and
colistin against A. baumannii in a dynamic one-compartment in vitro
infection model (IVM). Identical structural model to
Cheah_2016_polymyxin_ATCC19606 (three bacterial subpopulations
bact_s/bact_r/bact_d with logistic carrying capacity, Bulitta 2010
lipid-A receptor-occupancy submodel, Hill-function killing,
single-compartment adaptive-resistance turnover, IVM one-compartment
PK); strain-specific parameter values from Cheah 2016 Table 1 column
FADDI-AB030. For this strain the experimental data supported inclusion
of a fitness cost f_cost on susceptible replication (Eq 10): G_inhib_max
= 0.991 (Table 1). Also notable for this strain: a very steep
Hill_killing of 19.5 (Table 1), reflecting near-switchlike polymyxin
killing once C_eff approaches KillC50. SC50 is inherited as a FIXED
proxy from Bulitta 2015 (Cheah 2016 does not report it); see vignette
Errata. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Liang_2023_polymyxinB.html">PolymyxinB
(Liang 2023)</a> </td>
<td style="text-align:left;"> Two-compartment intravenous
population PK model for polymyxin B in critically ill adults not
receiving CRRT or ECMO (Liang 2023). Fitted by nonparametric adaptive
grid (NPAG) in Pmetrics. Serum albumin is a power covariate on CL and
age is a power covariate on Vc, both normalized to the cohort median
(ALB 31.45 g/L, age 68 years) with exponents fixed at -0.95 and +0.95
respectively. Combined additive plus proportional residual error derived
from the Pmetrics assay-error polynomial scaled by the final gamma.
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Nicholas_2009_ponezumab.html">Ponezumab
(Nicholas 2009)</a> </td>
<td style="text-align:left;"> Two-compartment intravenous
population PK model for PF-04360365 (ponezumab), a humanized
anti-amyloid IgG2 delta-a monoclonal antibody, in adults with
mild-to-moderate Alzheimer's disease; allometric body-weight scaling
with estimated exponents on every disposition parameter and a full 4x4
inter-individual block on (CL, V1, V2, Q) (Nicholas 2009 preliminary
popPK) </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Dvorackova_2023_posaconazole.html">Posaconazole
(Dvorackova 2023)</a> </td>
<td style="text-align:left;"> Population PK model for oral
posaconazole tablets in adult lung-transplant recipients (Dvorackova
2023). One-compartment disposition with first-order absorption and
first-order elimination, parameterised on the apparent (oral) scale as
CL/F and Vd/F because bioavailability was not identifiable from the
oral-only therapeutic-drug-monitoring data. The absorption rate constant
Ka was fixed to 0.8 1/h (back-calculated from the tmax and half-life
reported in the posaconazole SmPC) because all concentrations were
sampled in the elimination phase; inter-individual variability on Ka was
nevertheless estimated and is very large, reflecting that absorption is
essentially unidentifiable from these data. Age is the only covariate
retained in the final model, entering log-linearly (exponentially) on
apparent clearance so that CL/F declines by about 0.9 percent per year
of age. Residual variability is proportional. The model was used for
Monte Carlo dose optimisation against the EUCAST trough targets of 0.7
mg/L for prophylaxis and 1.25 mg/L for therapy. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Kohl_2010_posaconazole.html">Posaconazole
(Kohl 2010)</a> </td>
<td style="text-align:left;"> One-compartment population PK
model for prophylactic oral posaconazole in adult allogeneic stem cell
transplant recipients with hematological malignancies (Kohl 2010); ka
fixed, age and concurrent diarrhea as covariates. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Shu_2024_posaconazole.html">Posaconazole
(Shu 2024)</a> </td>
<td style="text-align:left;"> Population PK model for
posaconazole oral suspension (Noxafil) in Chinese hematopoietic stem
cell transplantation (HSCT) recipients (Shu 2024). One-compartment
disposition with first-order absorption and first-order elimination,
parameterised on the apparent (oral) scale as CL/F and V/F because the
therapeutic-drug-monitoring data were oral-only and bioavailability was
not identifiable. The absorption rate constant Ka was fixed to 0.4 1/h
from earlier posaconazole-suspension popPK studies, because almost every
sample was a pre-dose trough and the absorption phase could not support
an estimate. Creatinine clearance enters apparent clearance as a power
function centred on the cohort median 103.81 mL/min; body weight enters
apparent volume as a power function centred on the cohort median 45.85
kg; and concomitant proton-pump-inhibitor use multiplies apparent volume
by 3.83. Inter-individual variability is exponential on CL/F and V/F and
is very large (omega 1.118 and 0.826 on the log scale). Residual
variability is proportional. The model was used for Monte Carlo dose
optimisation of weight-banded BID and TID regimens against steady-state
trough targets of 0.7 ug/mL for prophylaxis and 1.0 ug/mL for treatment
of invasive fungal disease. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/vanIersel_2018_posaconazole.html">Posaconazole
(vanIersel 2018)</a> </td>
<td style="text-align:left;"> Population PK model for the
delayed-release solid oral tablet formulation of posaconazole in adult
healthy volunteers and patients at high risk for invasive fungal disease
(van Iersel 2018). One-compartment disposition with sequential
zero-order then first-order absorption: each oral dose loads into the
depot compartment as a zero-order infusion of duration D1, after which
depot drains to central with first-order rate constant ka and central
eliminates with first-order rate constant CL/V. The random effect on D1
is the same as the random effect on ka multiplied by a correlation
factor (cor_kad1 = -0.586). Covariates retained in the final model are
body weight on relative bioavailability (allometric power exponent),
tablet formulation A/B versus C/D on bioavailability, AML/MDS disease
state on bioavailability, fed status on absorption rate, and
single-dose-versus-multiple-dose record indicator on clearance. Residual
variability is log-additive with separate magnitudes for phase 1 versus
phase 3 studies. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/PerezRuixo_2025_posdinemab.html">Posdinemab
(PerezRuixo 2025)</a> </td>
<td style="text-align:left;"> Mechanism-based population PK-PD
model with full TMDD for the anti-tau monoclonal antibody posdinemab in
serum, CSF, and ISF (Perez-Ruixo 2025): two-compartment serum
disposition with linear elimination, distribution into a CSF compartment
and a downstream ISF compartment, explicit second-order binding of free
posdinemab to free p217+tau in CSF and to tau seeds in ISF,
internalization of free target and drug-target complex, and
Alzheimer's-disease-vs-healthy effect on baseline p217+tau. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Lin_2024_pozelimab.html">Pozelimab
(Lin 2024)</a> </td>
<td style="text-align:left;"> Two-compartment two-binding-site
TMDD-QE population PK model of total pozelimab and total C5 in healthy
volunteers, adults with paroxysmal nocturnal hemoglobinuria, and
pediatric and adult patients with CHAPLE disease (Lin 2024) </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Ide_2009_pravastatin.html">Pravastatin
(Ide 2009)</a> </td>
<td style="text-align:left;"> Population PK model for orally
administered pravastatin with enterohepatic circulation (Ide 2009) in
healthy Japanese male volunteers. Absorption is described by an Erlang
chain of 8 transit compartments (N_depot = 8); disposition is
one-compartment central with a gallbladder recirculation compartment
whose release is gated by the gallbladder-emptying time tg (continuous
filling from central via k12 for t < tg, gated release to central via
k21 for t >= tg) producing the characteristic second-peak phenomenon.
SLCO1B1 *15 haplotype carrier status (paired heterozygote / homozygote
indicators) increases relative oral bioavailability Frel
multiplicatively (1.50x and 1.95x respectively). Gastric conversion of
pravastatin to its inactive 3'alpha-isopravastatin (RMS-416) is highly
variable; the source paper corrected for this by using an apparent dose
(actual dose x Fa, where Fa = AUCpra / (AUCpra + AUCrms)) as the model
input, so the packaged model fixes the depot bioavailability anchor at
the population-mean Fa = 0.571 derived from Table II mean AUC values.
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Shoji_2011_pregabalin.html">Pregabalin
(Shoji 2011)</a> </td>
<td style="text-align:left;"> One-compartment population PK
model for pregabalin in adults (Shoji 2011 BJCP; pooled healthy
volunteers, subjects with impaired renal function, and patients with
post-herpetic neuralgia or diabetic peripheral neuropathy from 14
clinical trials). CL/F is proportional to Cockcroft-Gault creatinine
clearance (capped at an estimated break point) with an additional
ideal-body-weight power effect. V/F depends on ideal body weight, body
mass index, age, and sex. Absorption rate and lag-time are reduced by a
high-fat meal at the time of dosing. Combined proportional + additive
residual error is stratified by healthy-vs-patient status. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Bender_2009_pregabalin_rat.html">Pregabalin
rat binary (Bender 2009)</a> </td>
<td style="text-align:left;"> Preclinical (rat).
Two-compartment population PK model for pregabalin in male
Sprague-Dawley rats following a 2 h intravenous infusion (4 or 10
mg/kg/h) in a chronic- constriction-injury (CCI) neuropathic-pain model,
with the concomitant administration of sildenafil encoded as a BINARY
presence indicator (CONMED_SILDENAFIL). Sildenafil presence reduces
pregabalin clearance by a fixed fraction (theta_SLD = 0.302, i.e. 30.2%
reduction) per the paper's discrete-covariate parameterisation; the
alternative continuous saturable-metabolite parameterisation is encoded
in the companion file Bender_2009_pregabalin_rat_smetab.R. Crossover
design with two occasions per rat (Day 1 / Day 4 with a washout) carries
between-occasion variability on CL and Vc multiplexed by the OCC
indicator. Parameter values from Bender 2009 Table IV (Binary Sildenafil
Covariate column). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Bender_2009_pregabalin_rat.html">Pregabalin
rat smetab (Bender 2009)</a> </td>
<td style="text-align:left;"> Preclinical (rat).
Two-compartment population PK model for pregabalin in male
Sprague-Dawley rats following a 2 h intravenous infusion (4 or 10
mg/kg/h) in a chronic- constriction-injury (CCI) neuropathic-pain model,
with the concomitant administration of sildenafil encoded as a
CONTINUOUS saturable inhibition driven by the time-varying plasma
concentration of sildenafil's active N-methyl metabolite (SLDM).
Effective CL = theta_CL * (1 - SLDM / (theta_SLD + SLDM)) with theta_SLD
= 1350 ng/mL acting as the IC50 of metabolite-driven inhibition.
Statistically the preferred parameterisation in the paper (delta-OFV =
-42.6 vs the no-covariate base; the simpler binary form is in the
companion file Bender_2009_pregabalin_rat_binary.R with delta-OFV =
-8.5). Crossover design with two occasions per rat (Day 1 / Day 4 with a
washout) carries between-occasion variability on CL and Vc multiplexed
by the OCC indicator. Parameter values from Bender 2009 Table IV
(Continuous Sildenafil Metabolite Covariate column). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Gaohua_2012_pregnancy_pbpk.html">Pregnancy
pbpk caffeine (Gaohua 2012)</a> </td>
<td style="text-align:left;"> PBPK (whole-body, 14-compartment
pregnancy p-PBPK adapted from the Simcyp Simulator version 11 full-PBPK
platform). Caffeine (CYP1A2 substrate) disposition in healthy Caucasian
women aged 20-40 years, with gestational-age-dependent maternal
physiology and hepatic CYP1A2 activity. The 14 ODE compartments are
arterial blood, venous blood, lung, adipose, bone, brain, heart, kidney,
gut, liver, muscle, skin, spleen, and a lumped fetoplacental unit (fetus
+ placenta + amniotic fluid + membranes + umbilical cord) per Gaohua
2012 Figure 1; the uterus and mammary glands are merged into the muscle
compartment, so muscle volume and flow are computed as the residual that
balances total body weight and cardiac output during pregnancy.
Time-varying physiology (cardiac output, body weight, plasma / RBC
volumes, hematocrit, serum albumin, skin / adipose / renal /
fetoplacental blood flows, and CYP1A2 / CYP2D6 / CYP3A4 enzyme
activities) follows the polynomial formula X = X0 * (a0 + a1*GA +
a2*GA^2 + a3*GA^3) in Table 2; the fetoplacental volume follows the
Gompertz curve in Eq. 1. Drug-specific values for fa, Fg, ka, fu, B:P,
basal CL_int,H, the CYP fractional contributions A_1A2 / A_2D6 / A_3A4,
and the 12 tissue:plasma partition coefficients (Rodgers and Rowland)
are from Tables 3-4. Set covariate GA = 0 to simulate the non-pregnant
reference woman; values 0 < GA < 40 simulate any gestational
stage. The model is a perfusion-limited typical-value PBPK forward
simulation; the paper added no IIV or residual-error model. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Gaohua_2012_pregnancy_pbpk.html">Pregnancy
pbpk metoprolol (Gaohua 2012)</a> </td>
<td style="text-align:left;"> PBPK (whole-body, 14-compartment
pregnancy p-PBPK adapted from the Simcyp Simulator version 11 full-PBPK
platform). Metoprolol (predominantly CYP2D6 substrate; minor CYP3A4
contribution) disposition in healthy Caucasian women aged 20-40 years,
with gestational-age-dependent maternal physiology and hepatic CYP2D6 /
CYP3A4 activity. The 14 ODE compartments are arterial blood, venous
blood, lung, adipose, bone, brain, heart, kidney, gut, liver, muscle,
skin, spleen, and a lumped fetoplacental unit (fetus + placenta +
amniotic fluid + membranes + umbilical cord) per Gaohua 2012 Figure 1;
the uterus and mammary glands are merged into the muscle compartment, so
muscle volume and flow are computed as the residual that balances total
body weight and cardiac output during pregnancy. Time-varying physiology
(cardiac output, body weight, plasma / RBC volumes, hematocrit, serum
albumin, skin / adipose / renal / fetoplacental blood flows, and CYP1A2
/ CYP2D6 / CYP3A4 enzyme activities) follows the polynomial formula X =
X0 * (a0 + a1*GA + a2*GA^2 + a3*GA^3) in Table 2; the fetoplacental
volume follows the Gompertz curve in Eq. 1. Drug-specific values for fa,
Fg, ka, fu, B:P, basal CL_int,H, the CYP fractional contributions A_1A2
/ A_2D6 / A_3A4, and the 12 tissue:plasma partition coefficients
(Rodgers and Rowland) are from Tables 3-4. Set covariate GA = 0 to
simulate the non-pregnant reference woman; values 0 < GA < 40
simulate any gestational stage. The model is a perfusion-limited
typical-value PBPK forward simulation; the paper added no IIV or
residual-error model. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Gaohua_2012_pregnancy_pbpk.html">Pregnancy
pbpk midazolam (Gaohua 2012)</a> </td>
<td style="text-align:left;"> PBPK (whole-body, 14-compartment
pregnancy p-PBPK adapted from the Simcyp Simulator version 11 full-PBPK
platform). Midazolam (CYP3A4 substrate) disposition in healthy Caucasian
women aged 20-40 years, with gestational-age-dependent maternal
physiology and hepatic CYP3A4 activity. The 14 ODE compartments are
arterial blood, venous blood, lung, adipose, bone, brain, heart, kidney,
gut, liver, muscle, skin, spleen, and a lumped fetoplacental unit (fetus
+ placenta + amniotic fluid + membranes + umbilical cord) per Gaohua
2012 Figure 1; the uterus and mammary glands are merged into the muscle
compartment, so muscle volume and flow are computed as the residual that
balances total body weight and cardiac output during pregnancy.
Time-varying physiology (cardiac output, body weight, plasma / RBC
volumes, hematocrit, serum albumin, skin / adipose / renal /
fetoplacental blood flows, and CYP1A2 / CYP2D6 / CYP3A4 enzyme
activities) follows the polynomial formula X = X0 * (a0 + a1*GA +
a2*GA^2 + a3*GA^3) in Table 2; the fetoplacental volume follows the
Gompertz curve in Eq. 1. Drug-specific values for fa, Fg, ka, fu, B:P,
basal CL_int,H, the CYP fractional contributions A_1A2 / A_2D6 / A_3A4,
and the 12 tissue:plasma partition coefficients (Rodgers and Rowland)
are from Tables 3-4. Set covariate GA = 0 to simulate the non-pregnant
reference woman; values 0 < GA < 40 simulate any gestational
stage. The model is a perfusion-limited typical-value PBPK forward
simulation; the paper added no IIV or residual-error model. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Mehta_2023_tb_lesion_mpbpk.html">Pretomanid
mpbpk (Mehta 2023)</a> </td>
<td style="text-align:left;"> mPBPK (minimal physiologically
based, translational mouse-to-human). Pretomanid in pulmonary
tuberculosis patients, with explicit cavitary lung-lesion and
uninvolved-lung site-of-action compartments. First-order oral absorption
with saturable, dose-dependent bioavailability F = 1 / (1 + DOSE/ED50),
linear clearance from blood, two lumped peripheral tissue pools that
split cardiac output and residual body volume by a fixed fraction, and
perfusion-limited lesion / uninvolved-lung compartments driven by
penetration ratios. Physiological volumes and flows are computed from
body weight (Brown 1997); clearance is allometrically scaled from the
mouse fit with an exponent of 0.75. The lesion and uninvolved-lung
states hold concentrations (mg/L), not amounts. Intended for
typical-value and population simulation of site-of-action target
attainment. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Saleh_2023_leicns_pk30_mouse_brain.html">Prexasertib
mouse pbpk (Saleh 2023)</a> </td>
<td style="text-align:left;"> PBPK (LeiCNS-PK3.0 CNS
physiologically-based model, mouse version). Preclinical (mouse, CD1
nude). Nine-compartment CNS PBPK model predicting unbound prexasertib
concentrations in brain extracellular fluid (brain ECF) after a single
10 mg/kg subcutaneous dose. The CNS structure is the mouse
re-parameterisation of LeiCNS-PK3.0: brain microvasculature
(brain_vascular), brain ECF, a phospholipid brain-cell-membrane binding
compartment (brain_cell_membrane), brain intracellular fluid
(brain_icf), lysosomes (brain_lysosome), and the four CSF compartments
(lateral ventricles, third + fourth ventricles, cisterna magna,
subarachnoid space) draining in series back to plasma. Transport across
the BBB and BCSFB is the sum of a paracellular clearance (Qp, charged +
neutral drug) and a transcellular clearance (Qt, neutral drug only,
scaled by pH-dependent neutral fractions PHF and by asymmetry factors AF
that encode active transport). Every CNS parameter is fixed to mouse
physiology (Table III) or derived from the drug's physicochemical
properties (Table I); none was fitted here. The BBB asymmetry factors
are back-calculated from Kp,uu,BBB = 0.09 (estimated by the authors;
Table V). The plasma PK model is the empirical two-compartment model of
Table IV (ref [22]) and acts purely as a forcing function: brain uptake
does not deplete plasma, exactly as published. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Wattanakul_2024_primaquine_lactation.html">Primaquine
(Wattanakul 2024)</a> </td>
<td style="text-align:left;"> Mechanistic joint
parent-metabolite population PK model for oral primaquine and its
carboxyprimaquine metabolite in lactating women with Plasmodium vivax
infection, fitted simultaneously to maternal venous plasma, capillary
plasma, and breast-milk concentrations. Four-transit absorption (NN = 4,
ka set equal to ktr) into a one-compartment primaquine disposition model
whose entire systemic clearance is a formation clearance into a
one-compartment carboxyprimaquine disposition model, plus first-pass
conversion of a fraction FM of the absorbed dose directly into
carboxyprimaquine. Each central compartment exchanges with its own
breast-milk compartment through a shared apparent inter-compartmental
clearance and an analyte-specific milk:plasma partition coefficient; the
exchange is gated by a square-wave breastfeeding function (10 feeds/day,
24-minute feeding window in a 2.4-hour cycle). Separate capillary:venous
conversion factors are estimated for each analyte. Allometric
body-weight scaling on clearance (0.75) and volume (1) referenced at WT
= 51 kg; inter-occasion variability on bioavailability and mean transit
time across four sampling occasions. All amounts are molar (nmol)
because the primaquine to carboxyprimaquine conversion is 1:1 molar.
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Wattanakul_2024_primaquine_lactation.html">Primaquine
motherinfant (Wattanakul 2024)</a> </td>
<td style="text-align:left;"> Mechanistic mother-to-infant
transfer model for primaquine and carboxyprimaquine, extending the
maternal population PK model of Wattanakul 2024 (see
modellib('Wattanakul_2024_primaquine')) with a breastfed-infant
compartment chain so that infant exposure can be predicted from maternal
dosing. The maternal side is unchanged apart from the milk compartments
now being drained by breastfeeding. During each feeding window a
square-wave gate transfers the entire breast-milk content of each
analyte into the infant's dose compartment; between feeds the gate
closes and the milk compartments re-equilibrate with maternal plasma.
The infant absorbs through a two-transit chain with mean transit time
fixed to a paediatric literature value, and has no first-pass
metabolism. Infant clearances and volumes are scaled from the mother's
individual estimates by infant body weight (allometric exponents 0.75
and 1), with monoamine-oxidase-A maturation applied to primaquine
clearance only. No random effects are placed on the infant parameters:
all predicted infant variability is inherited from the mother.
Simulation model -- no infant pharmacokinetic parameter was estimated,
because all but one infant primaquine sample was below the limit of
quantification. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Cao_2013_PRO95780.html">PRO95780
(Cao 2013)</a> </td>
<td style="text-align:left;"> Second-generation minimal
physiologically-based PK (mPBPK) model for PRO95780 (drozitumab) in
adults (Cao 2013 Model A; clearance from plasma) </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Mohamed_2013_procainamide.html">Procainamide
(Mohamed 2013)</a> </td>
<td style="text-align:left;"> Joint parent-metabolite
two-compartment popPK model for procainamide and its major active
N-acetyl metabolite N-acetylprocainamide (NAPA) in a single 40-year-old
male with chronic kidney disease stage 5 receiving continuous renal
replacement therapy (CRRT) after aortic valve replacement (Mohamed
2013). Structural model (paper equations 1-3): procainamide central and
peripheral compartments with linear distribution clearance (Cld) and two
parallel first-order elimination arms from the central compartment -
Cl_other combining all non- metabolism procainamide clearance pathways
(CRRT, residual renal, and any additional non-NAPA-forming metabolic
routes) and Cl_f,napa the formation clearance of NAPA from procainamide;
the metabolite NAPA is described as a single central compartment fed by
the Cl_f,napa flux out of the procainamide central compartment and
eliminated linearly with total clearance Cl_napa (CRRT plus residual
renal). The NAPA apparent volume of distribution (Vc)_N was FIXED at 100
L, derived as the patient's body weight (70 kg) times a literature Vd of
1.5 L/kg for NAPA in functionally anephric patients on hemodialysis
(paper ref 9), because the fraction of procainamide elimination going
through NAPA formation could not be identified independently from the
concentration data. All other structural parameters were successfully
estimated by first-order conditional estimation in NONMEM VII. RUV was
described by a proportional error model (paper equation 4) on both
procainamide and NAPA concentrations; the estimated residual- error
magnitude is not reported in Mohamed 2013 Table 1, so this library
implementation encodes a nominal 15 percent CV proportional SD on each
output and documents the omission in the vignette Errata. Because the
source is a single-subject case report, no between- subject variability
is identifiable and no eta parameters are encoded; the model is a
typical-value description tied to this specific patient's disposition on
CRRT. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Chi_2018_propofol.html">Propofol
(Chi 2018)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model for propofol target-controlled IV infusion in Chinese adults with
hepatic insufficiency undergoing elective liver transplantation, with
additive body-weight effect on clearance and power Child-Turcotte-Pugh
score effect on peripheral volume (Chi 2018 final regression model).
Typical-value-only model: the source paper reports the six final-model
THETAs but provides no OMEGA (IIV), no SIGMA (residual error), and no
GOF / VPC, so all etas are fixed at zero and no residual error term is
included. See vignette Assumptions and deviations for the resulting
limitations on VPC-style validation and the recommendation to consult
the modellib('Ye_2012_propofol') companion (when extracted) for a
fully-reported 3-compartment propofol popPK fit in a larger
Chinese-multicenter cohort that shares the Chi 2018 first author.
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Diepstraten_2013_propofol.html">Propofol
(Diepstraten 2013)</a> </td>
<td style="text-align:left;"> Three-compartment intravenous
population PK model for propofol in morbidly obese and nonobese adults,
adolescents, and children (Diepstraten 2013 meta-analysis of five
previously published studies; N = 94 patients, TBW 37-184 kg, age 9-79
years). Final model E in Table 3: total body weight scales clearance
allometrically with an estimated exponent and scales the slow
inter-compartmental clearance Q3 linearly; age modifies clearance via a
bilinear function centered at 41 years with separate slopes below and
above the breakpoint. Inter-individual variability on CL, V1, V3, and Q3
(log-normal) and proportional intra-individual error on log-transformed
concentrations. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Koo_2012_propofol.html">Propofol
(Koo 2012)</a> </td>
<td style="text-align:left;"> Pharmacodynamic sigmoid Emax
model for the probability of recovery of consciousness (ROC) versus
propofol effect-site concentration (Ce, ug/mL) during emergence from
propofol-remifentanil target-controlled-infusion (TCI) general
anesthesia in 94 ASA I-II adult patients undergoing elective minor eye
or ENT surgery (Koo 2012). Age modulates both the effect-site
concentration at 50% probability of ROC (Ce50) and the Hill exponent
lambda via linear-additive age-centred forms Ce50 = 1.15 - 0.0128 * (AGE
- 43) and lambda = 9.69 - 0.141 * (AGE - 43). Inter-individual
variability is log-normal on Ce50 (CV 26.0%); IIV on lambda was dropped
from the final model. Propofol PK is not fit in the source paper -- the
per-record effect-site propofol concentration is supplied as the
time-varying covariate CEFFECT (driven by the Schnider 1998/1999 TCI
controller in the source study; Keo = 0.459 /min). NONMEM Bernoulli
LAPLACE likelihood in the source paper; this implementation exposes the
typical-value probability of ROC with a placeholder additive residual
error (see vignette Assumptions and deviations), following the
Shin_2014_sevoflurane.R precedent from the same Yonsei research group.
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Przybylowski_2015_propofol.html">Propofol
(Przybylowski 2015)</a> </td>
<td style="text-align:left;"> Three-compartment IV population
PK plus effect-compartment sigmoidal Emax PD model for propofol in adult
ASA III cancer patients undergoing major lung surgery under
propofol-fentanyl total intravenous anesthesia (Przybylowski 2015; N =
23). The PD response is the AAI (A-line ARX-Index)
auditory-evoked-potential depth-of-anesthesia index with the maximum
effect fixed to 1 and the pretreatment baseline fixed to 87 from a prior
study. Inter-individual variability was estimated on Vc, CL, and the
deep-compartment intercompartmental clearance Q2 for PK and on Ce50,
gamma (Hill), and ke0 for PD; IIV on Vt1, Q1, Vt2 was fixed to 0 (data
uninformative). No demographic, biochemical, or hemodynamic covariates
were retained in the final model (Results). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Wahlquist_2024_propofol.html">Propofol
(Wahlquist 2024)</a> </td>
<td style="text-align:left;"> Three-compartment population PK
model for propofol with a symbolic-regression (neural-network) derived
covariate model on all four inter-compartmental rate constants, the
elimination rate constant and the central volume; trained on the pooled
Eleveld 30-study dataset spanning neonates to the elderly </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Wang_2012_propofol.html">Propofol
(Wang 2012)</a> </td>
<td style="text-align:left;"> Three-compartment intravenous
population PK model for propofol across the human life-span (Wang 2012;
174 subjects pooled across seven previously published studies covering
preterm and term neonates, infants, toddlers, children, adolescents, and
adults; body weight 0.68-122.7 kg, age 1 day-81 years). Final
'bodyweight-dependent exponent (BDE)' model (Model IV / Final PK model,
Table IV): clearance is scaled by total body weight via a power function
whose exponent k changes sigmoidally with body weight from k0 = 1.34 at
a theoretical 0 kg to k0 - kmax = 0.55 at large body weights, with k50 =
3.78 kg and a Hill coefficient gamma = 5.24 governing the steepness of
the decline. The slow inter-compartmental clearance Q3 and the second
peripheral volume V3 scale linearly with body weight (BW/70); the first
peripheral volume V2 scales as (BW/70)^0.55; the fast
inter-compartmental clearance Q2 is independent of body weight. The
central volume V1 = 7.58 L is constant for subjects with postnatal age
>= 100 days and scales linearly as V1 * (BW/70) for younger subjects.
Inter-individual variability (log-normal) was retained on CL, V1, V2,
V3, and Q3; no IIV on Q2. Additive residual error on log-transformed
concentrations was used, equivalent to a proportional error on the
linear concentration scale. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Knibbe_2005_propofol.html">Propofol
human (Knibbe 2005)</a> </td>
<td style="text-align:left;"> Two-compartment intravenous
population PK model for propofol in a 70 kg adult human, projected from
male Wistar rat (0.25 kg) parameters via the allometric power model with
literature exponents 0.75 for clearances and 1 for volumes. Parameter
values are taken from Knibbe 2005 Table 3 (column 'Scaled for humans (70
kg)'); inter- and intra-individual variability are inherited from the
rat fit (Table 3, column 'Observed in the rat (250 g)') per the Methods
text 'these human scaled pharmacokinetic parameters, together with ...
intra- and interindividual variabilities estimated in the rat were used
to simulate propofol concentrations'. The companion file
Knibbe_2005_propofol_rat.R carries the rat-side parameters used as the
scaling anchor. Knibbe 2005 demonstrated that concentrations simulated
from this scaled-human model agreed (r^2 = 0.83, P < 0.0001) with
concentrations observed in long-term-sedated critically ill patients
(Figure 2). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Levitt_2005_propofol_pbpk.html">Propofol
pbpk (Levitt 2005)</a> </td>
<td style="text-align:left;"> PBPK (whole-body). Human
physiologically based pharmacokinetic model for propofol (Levitt and
Schnider 2005 BMC Anesthesiology) fitted to the individual arterial
plasma data of 24 adult volunteers in three age groups (18-34, 35-65,
>65 years) from Schnider et al. 1998 Anesthesiology. Each subject
received an initial ~20-second IV bolus (2 mg/kg for subjects <65; 1
mg/kg for subjects >65) followed 60 minutes later by a 60-minute
constant infusion at 25, 50, 100, or 200 microg/kg/min. Twelve
well-stirred flow-limited tissue compartments (liver, intestine [paper's
'portal'], muscle, kidney, brain, heart, lung, skin, adipose, bone,
other [paper's 'other' + 'tendon' connective tissue lumped], plus venous
and arterial blood) use the PKQuest standard-human physiology (organ
weights, blood flows, and fraction lipid from Table 1 for a 70-kg
reference); propofol-specific tissue/blood partition coefficients are
hard-coded from the paper text at the standard freepl = 0.022 (adipose
84, brain 1.87, liver 2.12, intestine 1.7, other tissues 1.45). Lean
tissue weights and blood flows scale by lean body mass; adipose scales
with body fat percent (Gallagher 1996 regression internally derives body
fat from WT, HT, AGE, SEXF, RACE_ASIAN). Hepatic elimination is a single
well-stirred apparent-clearance approximation (CL_liver = 0.76 *
(Q_hepatic artery + Q_portal)) calibrated to the paper's Table 4
age-averaged fractional liver clearance of 0.76; this replaces the
paper's Roberts-Rowland dispersion-model liver (dispersion number 0.3)
with an ODE-compatible well-mixed compartment. Optional pulmonary
sequestration compartment (paper-specific 'lung_seq') receives a bolus
fraction frdose = max(0, 0.548 - 0.00891 * AGE) and releases it
exponentially with time constant T = 80 min (paper's average parameter
set for Figs 9-11); the user allocates the sequestered bolus fraction
via a second dose row on cmt = 'lung_seq'. No IIV or formal
residual-error variance was reported (individual fits; 15 percent
average absolute weighted residual). All parameters are FIXED at the
paper's average values. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Knibbe_2005_propofol.html">Propofol
rat (Knibbe 2005)</a> </td>
<td style="text-align:left;"> Preclinical (rat).
Two-compartment intravenous population PK model for propofol in male
Wistar rats following a single 30 mg/kg bolus delivered over 5 min, as
reported in Table 3 (column 'Observed in the rat (250 g)') of Knibbe
2005. The underlying NONMEM fit was performed by Knibbe et al.
(reference 11 of the paper) on 19 whole-blood samples from each of 22
chronically instrumented rats; Knibbe 2005 reproduces those rat point
estimates and uses them as the species anchor for an allometric scaling
to humans (see the companion model file Knibbe_2005_propofol_human.R,
which carries the human-projected parameters from Table 3 column 'Scaled
for humans (70 kg)'). Log-normal inter-individual variability on CL, V1,
Q, V2 and a constant-CV proportional intra-individual residual error
model. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Ngamprasertwong_2016_propofol_sheep.html">Propofol
sheep (Ngamprasertwong 2016)</a> </td>
<td style="text-align:left;"> Preclinical (sheep).
Maternal-fetal population PK model of propofol in mid-gestational
pregnant Dorset ewes (Ngamprasertwong 2016; N = 8 ewe-fetus pairs at
110-125 days gestation; term ~147-150 days). Two-compartment maternal
disposition (central + peripheral1) linked to a single fetal compartment
via a reversible inter-compartmental clearance QM-F; fetal clearance was
tested but estimated near zero (<0.001 L/min, RSE >100%) and set
to zero in the final model. Maternal clearance scales with heart rate
via the normalised power model CL = theta1 * (HR/158)^theta2; no other
covariate (gestational age, body weight, blood pressure, uterine blood
flow) reached statistical significance. Inter-individual variability was
estimated on CL and QM-F; IIV on Vc, Q, Vp, and VFetus was fixed to zero
in the source and is omitted here. Residual error is purely
proportional, with separate variances for maternal-ewe and fetal
observations. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/DelFrari_2018_propranolol.html">Propranolol
(DelFrari 2018)</a> </td>
<td style="text-align:left;"> One-compartment population PK
model for oral propranolol in infants (aged 50-243 days, 3.6-9.7 kg)
with proliferative Infantile Hemangiomas (Del Frari 2018). First-order
absorption and first-order elimination; apparent oral clearance CL/F
scales with body weight using a fixed allometric exponent of 0.75 and a
reference weight of 6.3 kg (the median weight pooled across visits
D1-D84). Apparent volume V/F has no covariate effect (the paper tested
but did not retain weight on V/F). Between-subject variability is
retained on CL/F and Ka only; BSV on V/F was dropped from the final
model (large 95% CI including 0 and 62.3% eta-shrinkage). Residual error
is proportional. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Takechi_2018_propranolol.html">Propranolol
(Takechi 2018)</a> </td>
<td style="text-align:left;"> One-compartment first-order
absorption population PK model for oral propranolol in Japanese infants
with infantile hemangioma (35-150 days postnatal age), with fixed
allometric body-weight scaling and a power effect of postnatal age on
apparent oral clearance; the companion logistic-regression PD model
relating exposure (AUC), treatment duration, and gestational age to
treatment-success probability is reproduced in the validation vignette.
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Pardridge_2023_brain_plasma_protein_binding.html">Propranolol
pbpk (Pardridge 2023)</a> </td>
<td style="text-align:left;"> PBPK (brain, semi-mechanistic).
Pardridge 2023 Pharmaceutical Research partly-flow /
partly-compartmental model of propranolol delivery to brain that
resolves plasma-protein binding as an explicit kinetic process inside
the brain capillary. Seven brain states carry albumin-bound,
alpha-1-acid-glycoprotein (AGP)-bound and free drug in the brain
capillary, free AGP in the capillary, free drug in brain, and free /
drug-occupied brain cytoplasmic binding protein. Drug crosses the
blood-brain barrier by bi-directional first-order permeation and may be
metabolised in brain. The model quantifies plasma-protein-mediated
uptake (PMU): because propranolol dissociates from AGP far faster in
vivo in the capillary (KG in vivo 19 uM) than in vitro (KG in vitro 3.3
uM), the free drug in brain is roughly twofold higher than equilibrium
dialysis of plasma predicts. Arterial input is either a constant total
plasma concentration (steady-state IV-infusion model, c_plasma_ss, Table
II LT0 = 100 nM) or a one-compartment first-order oral profile
(non-steady-state model, Eq 13; dose the depot compartment and set
c_plasma_ss to 0). All parameters are FIXED at the paper's
literature-sourced values; the paper reports no IIV and no residual
error because it is a deterministic simulation study rather than a fit
to individual data. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/DeCock_2012_propyleneGlycol.html">PropyleneGlycol
(DeCock 2012)</a> </td>
<td style="text-align:left;"> One-compartment population PK
model for intravenous propylene glycol (PG) excipient exposure in
preterm and term neonates receiving paracetamol-PG or phenobarbital-PG
(De Cock 2012). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Alsultan_2017_pyrazinamide.html">Pyrazinamide
(Alsultan 2017)</a> </td>
<td style="text-align:left;"> One-compartment population
pharmacokinetic model with first-order absorption and first-order
elimination for oral pyrazinamide in adults with drug-susceptible
pulmonary tuberculosis (Alsultan 2017); body weight is an allometric
covariate on CL/F and V/F (fixed exponents 0.75 and 1) and biological
sex is an exponential covariate on V/F </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Chirehwa_2017_pyrazinamide.html">Pyrazinamide
(Chirehwa 2017)</a> </td>
<td style="text-align:left;"> One-compartment population PK
model with Savic-style transit-compartment absorption (NN = 28) for oral
pyrazinamide in HIV/TB-coinfected adults on the WHO four-drug fixed-dose
combination (Chirehwa 2017); fat-free mass (Janmahasatian formula)
drives fixed allometric scaling of CL/F (exponent 0.75) and V/F
(exponent 1.0) referenced to a 42 kg subject, and CL/F increases
linearly by 14.3% from day 1 to day 29 of treatment, attributed to
rifampin-mediated enzyme induction. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Horita_2018_pyrazinamide.html">Pyrazinamide
(Horita 2018)</a> </td>
<td style="text-align:left;"> One-compartment population
pharmacokinetic model with three-compartment transit absorption followed
by first-order absorption and first-order elimination for oral
pyrazinamide in Ghanaian children with active tuberculosis (Horita
2018); allometric weight scaling on V/F (estimated exponent 0.677) and
CL/F (estimated exponent 0.735) normalised to the cohort median 14.3 kg.
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Kim_2023_pyrazinamide.html">Pyrazinamide
(Kim 2023)</a> </td>
<td style="text-align:left;"> One-compartment population
pharmacokinetic model with first-order absorption and first-order
elimination for oral pyrazinamide in Korean adults with drug-susceptible
tuberculosis (Kim 2023); lean body mass is an allometric covariate on
CL/F and V/F (fixed exponents 0.75 and 1) and geriatric diabetes
mellitus (age >= 70 years with diabetes mellitus) increases CL/F by
32% </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Mehta_2023_tb_lesion_mpbpk.html">Pyrazinamide
mpbpk (Mehta 2023)</a> </td>
<td style="text-align:left;"> mPBPK (minimal physiologically
based, translational mouse-to-human). Pyrazinamide in pulmonary
tuberculosis patients, with explicit cavitary lung-lesion and
uninvolved-lung site-of-action compartments. This is the
framework-qualification model of Mehta 2023: first-order oral
absorption, first-order elimination from a blood compartment and
perfusion-limited lesion / uninvolved-lung compartments driven by
penetration ratios. No lumped peripheral tissue compartment -- the paper
reports that adding one did not improve the fit. It is the only one of
the paper's three models whose lesion and uninvolved-lung predictions
could be checked against observed human site-of-action data.
Physiological volumes and flows are computed from body weight (Brown
1997). The lesion and uninvolved-lung states hold concentrations (mg/L),
not amounts. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Ramachandran_2023_tuberculosis_eptb_pbpk.html">Pyrazinamide
pbpk (Ramachandran 2023)</a> </td>
<td style="text-align:left;"> PBPK (whole-body, 18 ODEs, MATLAB
ode15s). Oral pyrazinamide disposition at extrapulmonary tuberculosis
(EPTB) sites in a 70-kg reference adult male (Ramachandran and Gadgil
2023, CPT Pharmacometrics Syst Pharmacol). Seventeen perfusion-limited
well-stirred tissue compartments connected by blood and lymph flow, plus
a gut-lumen state for enterohepatic recycling. The model's two novel
states are a pleural-fluid compartment (a filtrate of the lung that
drains via lymphatics) and a consolidated lymph-node compartment that
collects afferent lymph from every organ except bone and spleen and
returns it to venous blood - the two most common EPTB sites.
Physiological volumes, blood flows, and lymph flows are fixed literature
fractions of body weight, cardiac output (5200 mL/min), and afferent
lymph flow (8 L/day) respectively (Appendix S1 Tables S2 and S3).
Tissue:plasma partition coefficients were computed by the Rodgers and
Rowland method from the drug physicochemistry in Table S4 and are
tabulated in Table S5. Only the first-order oral absorption rate ka and
total systemic clearance CL were estimated, by weighted least squares
against reported plasma concentrations after a 2000 mg oral dose
(Appendix S1 Table S7). Clearance is split into a renal component fR *
CL driven by arterial concentration and a hepatic component (1 - fR) *
CL driven by the hepatic inlet concentration; the hepatic output enters
the gut lumen, which for pyrazinamide is a terminal sink cleared only by
faecal transit at kF = 0.252 /h (the paper assigns a non-zero gut
reabsorption rate only to rifampicin). The model is a deterministic
typical-value simulation: the paper reports no interindividual
variability and no residual error model, so propSd is fixed at 0.
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Karunajeewa_2009_sulfadoxinePyrimethamine.html">Pyrimethamine
(Karunajeewa 2009)</a> </td>
<td style="text-align:left;"> Population PK model for
pyrimethamine (PYR) in 60 Papua New Guinean women (30 pregnant, second
or third trimester; 30 age-matched nonpregnant controls) given a single
oral 1,500 mg sulfadoxine / 75 mg pyrimethamine dose for intermittent
presumptive treatment of malaria in pregnancy (Karunajeewa 2009).
Two-compartment disposition with first-order absorption and no lag, fit
as a separate NONMEM dataset from the parent SDOX/NASDOX dataset.
Allometric scaling at reference WT = 70 kg is applied to all apparent
volumes (exponent 1) and all apparent clearances (exponent 0.75).
Pregnancy is the only retained covariate; it enters as additive terms on
apparent CL/F (+0.439 L/h/70 kg), Vc/F (+76 L/70 kg) and Vp/F (+98 L/70
kg). Between-subject variability on CL/F, Vc/F and Vp/F is correlated
(3x3 block, correlations 0.797 / 0.756 / 0.731 from Table 4); BSV on Q/F
and ka is independent. The companion model for the co-administered
sulfadoxine plus its NASDOX metabolite is shipped as
'Karunajeewa_2009_sulfadoxine' (separate NONMEM dataset, fit
independently in the source publication). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Ayyoub_2016_pyronaridine.html">Pyronaridine
(Ayyoub 2016)</a> </td>
<td style="text-align:left;"> Pooled population PK model of
oral pyronaridine in 349 pediatric malaria patients (0.51-15 years,
6.8-56.2 kg) from one phase II and five phase III studies of the
pyronaridine-artesunate fixed-dose combination (Pyramax).
Two-compartment disposition with first-order absorption and first-order
elimination from the central compartment. Body weight enters as fixed
allometric scaling (exponent 0.75 on CL/F and Q/F, 1.00 on V2/F and
V3/F, centred on a 20 kg reference). Age enters as a power covariate on
the peripheral volume V3/F (exponent 0.624, centred on a 7 yr
reference). Formulation (1 = pediatric granule sachet, 0 = tablet)
increases the absorption rate Ka by 1.63-fold over the tablet baseline.
Residual error is additive on the natural-log concentration scale
(equivalent to proportional in linear space). Dose is encoded as
pyronaridine base in mg (paper Methods: pyronaridine tetraphosphate
doses are multiplied by 0.57 prior to modeling). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Kang_2023_pyronaridine_artesunate_hamster_pbpk.html">Pyronaridine
hamster pbpk (Kang 2023)</a> </td>
<td style="text-align:left;"> Preclinical (golden hamster).
PBPK (minimal, five-compartment; WinNonlin 8.3). Oral pyronaridine
disposition with the antiviral target tissues -- lung and trachea --
carried as explicit perfusion-rate-limited organ compartments and all
nontarget tissues lumped into a rest-of-body compartment (Kang et al.
2023, Pharmaceutics 15:838). Whole blood is the sampling matrix because
pyronaridine partitions strongly into erythrocytes (reported
blood-to-plasma ratio 4.9-17.8), so no blood-to-plasma conversion is
applied. Tissue uptake follows the well-stirred perfusion-limited form
Q_tissue * (C_blood - C_tissue / K_tissue), and a first-order
bidirectional exchange (k_tl, k_lt) links lung and trachea directly.
Physiological volumes and blood flows (Table 1) are fixed; the seven
biochemical parameters (Table 2) were fitted to 343 pooled pyronaridine
measurements by naive pooled-data analysis, so the model carries no
between-subject variability and is intended for typical-value simulation
of blood, lung and trachea profiles after single or daily oral dosing.
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Zhu_2024_pyrotinib.html">Pyrotinib
(Zhu 2024)</a> </td>
<td style="text-align:left;"> One-compartment population PK
model with first-order absorption and elimination for oral pyrotinib in
Chinese patients with HER2-positive breast cancer, with a serum total
protein effect on apparent clearance (Zhu 2024) </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Dias_2024_quetiapine_rat.html">Quetiapine
rat (Dias 2024)</a> </td>
<td style="text-align:left;"> Preclinical (rat, Wistar).
Semimechanistic pharmacodynamic (PD-only) precursor-pool model for
medial prefrontal cortex (mPFC) extracellular dopamine after a single 5
mg/kg intravenous dose of quetiapine given either as a solution (FQ) or
as lipid core nanocapsules (QLNC), in naive rats and in poly(i:c)
schizophrenia phenotyped rats (SPR). Dopamine precursors are synthesised
into a pool at a zero-order rate and released into the extracellular
dopamine compartment by a first-order rate constant that quetiapine
stimulates linearly; dopamine is removed by a reuptake process that a
negative-feedback modulator exacerbates, giving the fast return to
baseline. Quetiapine acts through a Sheiner effect compartment driven by
the unbound brain concentration, and co-administered nanoparticles
competitively blunt the drug effect while decaying first-order. Disease
severity enters as the continuous prepulse-inhibition score on both the
dopamine baseline and the drug-effect slope. This model has NO PK layer:
the unbound quetiapine brain concentration must be supplied by the user
as the time-varying covariate CU_QTP_BRAIN, generated from the companion
semimechanistic popPK model (Carreno et al. 2020,
doi:10.1124/jpet.120.000109). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Fattinger_1991_quinidine.html">Quinidine
(Fattinger 1991)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model for oral quinidine in adults treated for supraventricular or
ventricular arrhythmias (Fattinger 1991). Zero-order absorption from the
gastrointestinal tract with formulation-specific absorption duration:
immediate-release quinidine sulphate (Chinidin sulfuricum) with a
typical absorption duration of 1.37 h, and slow-release quinidine
bisulphate (Kinidin duriles) with a typical absorption duration of 6.0 h
and a 1.36-fold higher relative bioavailability versus quinidine
sulphate. Apparent total clearance is the sum of a renal arm
proportional to creatinine clearance (proportionality 0.0566 L/h per
mL/min) and a non-renal arm of 12.6 L/h that is halved to 6.8 L/h in
patients with severe heart failure or severe liver failure. Apparent
central volume is 161 L. Inter-compartmental clearance Q is 12.6 L/h and
peripheral volume V2 is 66.7 L. Inter-individual variability is assigned
to total clearance (40.2% CV), central volume (75.6% CV), and the
quinidine sulphate absorption duration (49.4% CV); residual variability
is proportional (22% CV). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Westerhout_2013_quinidine.html">Quinidine
(Westerhout 2013)</a> </td>
<td style="text-align:left;"> Preclinical (rat, male Wistar
WU). Systems-based pharmacokinetic (SBPK) model for quinidine
intra-brain distribution following IV infusion, fit jointly to unbound
plasma, brain parenchymal extracellular fluid (brain ECF), CSF in the
lateral ventricle (CSF_LV) and cisterna magna (CSF_CM), and
end-of-experiment total (deep) brain concentrations, with simultaneous
mechanistic state compartments for CSF in the combined third + fourth
ventricles (CSF_TFV) and the subarachnoid space (CSF_SAS) carrying the
ventricular CSF flow from LV through SAS back to systemic plasma at the
fixed physiological rate Q_CSF = 2.2 uL/min, plus a brain-ECF-to-CSF_LV
flow at Q_ECF = 0.2 uL/min (Westerhout 2013, J Pharmacokinet
Pharmacodyn). Two systemic peripheral compartments (V_PER1, V_PER2) with
inter-compartmental clearances Q_PL-PER1, Q_PL-PER2 carry the
multi-exponential plasma decline. P-glycoprotein (P-gp) activity (binary
indicator CONMED_TARIQUIDAR = 0 control / 1 tariquidar-inhibited)
modulates the systemic elimination CL_E (1.9-fold increase when P-gp is
active per Table 4) and every transfer clearance between plasma and the
brain compartments: passive influx into each brain compartment is
reduced when P-gp is active (influx hindrance, subtractive) and passive
efflux is increased (efflux enhancement, additive). At the BCSFB level,
P-gp acts as an efflux transporter at the LV (CL_LV-PL,P-gp estimated to
0 in the combined model, with the P-gp-mediated component carried by
CL_PL-LV,P-gp) and is absent at the CM (both P-gp components fixed to 0
in the combined model). The plasma-to-TFV transfer clearance is
structurally assumed equal to plasma-to-LV (no TFV microdialysis
sampling). Parameter values are the paper's preferred 'efflux
enhancement + influx hindrance' (combined) SBPK model from Table 4,
column 3 (OFV = 17,969); the two alternative P-gp mechanism variants
(efflux-enhancement-only, OFV = 18,105; influx-hindrance-only, OFV =
18,030) and the simpler preliminary compartmental model (Table 3) are
discussed in the validation vignette but not extracted as separate model
files. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Saleh_2023_leicns_pk30_mouse_brain.html">Quinidine
mouse pbpk (Saleh 2023)</a> </td>
<td style="text-align:left;"> PBPK (LeiCNS-PK3.0 CNS
physiologically-based model, mouse version). Preclinical (mouse, NMRI).
Nine-compartment CNS PBPK model predicting unbound quinidine
concentrations in brain extracellular fluid (brain ECF) after a single
40 mg/kg intraperitoneal dose. The CNS structure is the mouse
re-parameterisation of LeiCNS-PK3.0: brain microvasculature
(brain_vascular), brain ECF, a phospholipid brain-cell-membrane binding
compartment (brain_cell_membrane), brain intracellular fluid
(brain_icf), lysosomes (brain_lysosome), and the four CSF compartments
(lateral ventricles, third + fourth ventricles, cisterna magna,
subarachnoid space) draining in series back to plasma. Transport across
the BBB and BCSFB is the sum of a paracellular clearance (Qp, charged +
neutral drug) and a transcellular clearance (Qt, neutral drug only,
scaled by pH-dependent neutral fractions PHF and by asymmetry factors AF
that encode active transport). Every CNS parameter is fixed to mouse
physiology (Table III) or derived from the drug's physicochemical
properties (Table I); none was fitted here. The BBB asymmetry factors
are back-calculated from Kp,uu,BBB = 0.2185 (taken from ref [56]; Table
V). The plasma PK model is the empirical one-compartment model of Table
IV (in-house NONMEM fit) and acts purely as a forcing function: brain
uptake does not deplete plasma, exactly as published. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Shin_2006_quinidine_QT.html">Quinidine
QT (Shin 2006)</a> </td>
<td style="text-align:left;"> Population pharmacodynamic Emax
model for quinidine-induced QTc prolongation in 24 healthy Korean (12 M
/ 12 F) and 13 healthy Caucasian (7 M / 6 F) adults following a single
20 min IV infusion of quinidine gluconate 4 mg/kg (base). The Emax form
is QTc(t) = E0 + DeltaEmax * Cc / (EC50 + Cc) with E0 modulated by sex
(additive +34 ms in females; reference category = male) and DeltaEmax
modulated by ethnicity (multiplicative x1.26 in Caucasians; reference
category = Korean) plus an additive +106 ms interaction in Caucasian
females only. EC50 = 3.13 uM (= 1.0155 mg/L using quinidine MW 324.42
g/mol). Source publication does not fit a popPK model; the PK driver in
this file is a typical-value 1-compartment IV approximation with CL =
0.3 L/h/kg and Vc = Vss = 2.5 L/kg derived from the pooled NCA summary
statistics in Shin 2006 Table 2 (see vignette Errata). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Kervezee_2014_quinidine_rat.html">Quinidine
rat (Kervezee 2014)</a> </td>
<td style="text-align:left;"> PBPK (semi-mechanistic
brain-distribution, unbound-only). Preclinical (rat). Nine-compartment
brain-distribution model for i.v. quinidine in male Wistar rats
(Kervezee 2014), fitted to unbound plasma, brain extracellular fluid
(ECF), cerebrospinal fluid at the lateral ventricle (CSF-LV) and
cisterna magna (CSF-CM), and total deep-brain tissue. Topology from
Westerhout 2013: plasma (central), two peripheral tissue compartments
(peripheral1, peripheral2), one deep-brain intracellular compartment
(brain_deep), one brain ECF compartment (brain_ecf), and four sequential
CSF sub-compartments (csf_lv, csf_tfv, csf_cm, csf_sas) draining back
into plasma via CSF bulk flow. P-glycoprotein-mediated transport enters
as an additional clearance component at the BBB (subtracted from
PL-to-brain influx, added to brain-to-PL efflux) and on plasma
elimination. Kervezee 2014 introduces the diurnal-period covariate
PERIOD_ACTIVE (0 = resting / lights-on, 1 = active / lights- off) that
acts on five parameters: the P-gp components of CL_DBR-PL, CL_PL-ECF,
CL_ECF-PL, and CL_PL-LV, plus CSF bulk flow Q_CSF. Brain compartment
volumes and Q_ECF are fixed to physiological values from Westerhout 2013
refs 38-47; plasma volume V_PL is fixed to the rat plasma volume;
peripheral volumes are estimated. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Syvanen_2012_quinidine_rat.html">Quinidine
rat (Syvanen 2012)</a> </td>
<td style="text-align:left;"> Preclinical (rat, male
Sprague-Dawley). Two-compartment plasma + brain extracellular fluid
(ECF) population PK model for quinidine in rats with hippocampal
microdialysis sampling, fit jointly to plasma, brain ECF, and
end-of-experiment total brain concentrations (Syvanen 2012). The plasma
2-cmt system (central V1 / peripheral V2) couples to a brain ECF
compartment V_Br via asymmetric BBB clearances (Q_in = f1 * Q_out into
brain, Q_out out of brain, Q_out FIXED at 10.8 mL/min from the paper's
bootstrap-stability analysis). A third observed output, total brain
tissue concentration Cbrain_deep, is modelled as an algebraic
equilibrium multiple of brain ECF (Cbrain_deep = f2 * Cbrain_csf)
because the paper could not estimate separate rate constants for the
deep brain compartment. Two binary covariates: CONMED_TARIQUIDAR (15
mg/kg IP tariquidar pre-administered 30 min before quinidine, a
selective P-glycoprotein inhibitor) modifies CL, Q_out, Q_in, and f2;
DIS_POSTSE_KAINATE (1 week post-kainate-induced status epilepticus, rat
temporal-lobe-epilepsy paradigm) modifies CL, V2, and V_Br. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Kloprogge_2014_quinine.html">Quinine
(Kloprogge 2014)</a> </td>
<td style="text-align:left;"> Population PK model for oral
quinine in pregnant women with uncomplicated Plasmodium falciparum
malaria in Uganda (Kloprogge 2014). First-order absorption into a
two-compartment disposition model with allometric body-weight scaling on
clearance and intercompartmental clearance (power 2/3) and on apparent
volumes (power 1), centered at the cohort typical weight of 56 kg.
Relative bioavailability F is fixed at 1 with log-normal IIV; a linear
covariate effect of time-varying parasitaemia (per log10 parasites/uL,
last-observation-carried-forward) increases F by 38.9% per log10
parasitaemia, and an exponential effect of admission body temperature
decreases elimination clearance by ~21.6% per degC (centered at the
cohort median 37.2 degC). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/LeJouan_2005_quinine.html">Quinine
(LeJouan 2005)</a> </td>
<td style="text-align:left;"> Population PK model for oral
quinine in Cameroonian children (aged 0.55-6.7 years) with uncomplicated
Plasmodium falciparum malaria (Le Jouan 2005). One-compartment with
first-order absorption, time-varying free fraction fu = 0.15 + 0.001*(t
- 36) anchored at the literature value fu(t=36 h) = 0.15 (Babalola 1989)
and clamped to its t = 72 h value beyond the studied window, and
linear-in-body-weight apparent clearance CL/F = fu * 0.53 * WT and
apparent volume V/F = fu * (57 + 3.8 * WT). Doses are oral quinine base
in mg. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Sheng_2016_quinine_rat.html">Quinine
rat (Sheng 2016)</a> </td>
<td style="text-align:left;"> Preclinical (rat). Two
generalized Poisson (2GP) mixture PD model for bimodal lick-count data
from rodent brief-access taste aversion (BATA) experiments with quinine
hydrochloride dihydrate; the drug effect enters via a sigmoid emax on a
logistic-transformed mixing probability between a low-count and a
right-truncated high-count generalized-Poisson distribution. The fitted
compound is quinine HCl dihydrate used as a model bitter stimulus.
STIM_QUININE_MM is the applied sipper-tube concentration (mM); there is
no PK ODE and no time evolution (each record is an 8-second
presentation). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Aruldhas_2021_methadone.html">R
methadone (Aruldhas 2021)</a> </td>
<td style="text-align:left;"> Population pharmacokinetic model
for R-methadone and its R-EDDP metabolite in post-operative paediatric
surgical patients (Aruldhas 2021; 61 children aged 11-17 years given 0.1
mg/kg IV racemic methadone intra-operatively followed by 0.1 mg/kg oral
racemic methadone every 12 h as either a tablet or an oral suspension).
R-methadone disposition is a two-compartment model with first-order
absorption (separate tablet and suspension Ka values), an estimated
absolute bioavailability F common to both oral formulations, and a
one-compartment R-EDDP metabolite whose central volume is set equal to
the R-methadone central volume (scaling factor VF fixed to 1 due to
metabolite unidentifiability). Total R-methadone clearance CL scales
allometrically with body weight (fixed exponent 0.75, reference 70 kg).
The fractional R-methadone clearance to R-EDDP (CLF) is a linear
function of the CYP2B6 activity score and the number of active alleles
of the intronic CYP3A4 SNP rs2246709. The R-methadone central volume V2
is a linear function of the plasma alpha-1 acid glycoprotein (AAG)
concentration and the number of active alleles of the ORM1 SNP rs17650.
Between-subject variability is estimated on CL, V2, peripheral volume,
CLF, and R-EDDP clearance; residual error is proportional for both
R-methadone and R-EDDP. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Darpo_2014_racSotalol.html">RacSotalol
QTcF (Darpo 2014)</a> </td>
<td style="text-align:left;"> Concentration-QTcF linear
mixed-effects PD model for oral rac-sotalol in 39 healthy adults (28
men, 11 women) following a single 160 mg oral dose on day 1, with day-0
ECGs serving as the time-matched baseline. The endpoint is change from
baseline in the Fridericia- corrected QT interval (DeltaQTcF = QT /
RR^(1/3); ms). The full model is: DeltaQTcF = e0 + e_sexf_e0 * SEXF +
(slope + e_sexf_slope * SEXF) * CP_RACSOTALOL_UGML + e_qtc_bl_e0 *
(QTC_BL - 390), with male and median-baseline (QTC_BL = 390 ms)
reference. Reference parameter values (male, median-baseline subject):
e0 = -2.5 ms, slope = 24 ms per ug/mL, female increments +10.6 ms on the
intercept and +7 ms per ug/mL on the slope, centred-baseline-QTcF
coefficient -0.70 ms/ms. PD-only model: rac-sotalol plasma concentration
is supplied as a time-varying covariate CP_RACSOTALOL_UGML (ug/mL). The
source publication does not fit a population PK model -- the
pharmacokinetic profile was characterised by NCA only (Cmax 1.4 ug/mL
men, 1.8 ug/mL women; AUC_inf 14.6 men, 17.1 women); users wishing to
drive the PD model from a simulated PK source must supply their own
concentration trajectory (no rac-sotalol popPK model exists in the
nlmixr2lib registry). Companion model file Darpo_2014_racSotalol_QTcI.R
reports the same structure for the individually-corrected QT interval.
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Darpo_2014_racSotalol.html">RacSotalol
QTcI (Darpo 2014)</a> </td>
<td style="text-align:left;"> Concentration-QTcI linear
mixed-effects PD model for oral rac-sotalol in 39 healthy adults (28
men, 11 women) following a single 160 mg oral dose on day 1, with day-0
ECGs serving as the time-matched baseline. The endpoint is change from
baseline in the individually- corrected QT interval (DeltaQTcI, ms). The
full model is: DeltaQTcI = e0 + e_sexf_e0 * SEXF + (slope + e_sexf_slope
* SEXF) * CP_RACSOTALOL_UGML + e_qtc_bl_e0 * (QTC_BL - 390), with male
and median-baseline (QTC_BL = 390 ms) reference. Reference parameter
values (male, median-baseline subject): e0 = -3.2 ms, slope = 23 ms per
ug/mL, female increments +11.1 ms on the intercept and +7 ms per ug/mL
on the slope, centred-baseline-QTcI coefficient -0.70 ms/ms. PD-only
model: rac-sotalol plasma concentration is supplied as a time-varying
covariate CP_RACSOTALOL_UGML (ug/mL). The source publication does not
fit a population PK model -- the pharmacokinetic profile was
characterised by NCA only (Cmax 1.4 ug/mL men, 1.8 ug/mL women; AUC_inf
14.6 men, 17.1 women); users wishing to drive the PD model from a
simulated PK source must supply their own concentration trajectory (no
rac-sotalol popPK model exists in the nlmixr2lib registry). Companion
model file Darpo_2014_racSotalol_QTcF.R reports the same structure for
the Fridericia-corrected QT interval. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Ai_2024_ractopamine_goat_pbpk.html">Ractopamine
goat pbpk (Ai 2024)</a> </td>
<td style="text-align:left;"> PBPK (whole-body, hybrid flow-
and membrane-limited; goat). Eleven-tissue physiologically based
pharmacokinetic model for the beta-adrenoceptor agonist ractopamine in
Liaoning cashmere goats after repeated oral gavage, comprising gastric
contents, intestinal contents, liver, spleen, kidney, heart, lung,
muscle, fat, brain, a lumped rest-of-body compartment, arterial plasma,
venous plasma and a urinary-excretion sink. Liver, spleen, kidney, heart
and lung are perfusion (flow) limited; muscle, fat, brain and the rest
of the body are membrane (permeability) limited and each carry a
vascular plasma sub-compartment plus a tissue sub-compartment separated
by a permeability-area product. Absorption is first-order gastric
emptying (Kst) into the gut lumen followed by first-order uptake (Ka)
into the liver in competition with first-order fecal loss of unabsorbed
drug (Kgut); elimination is hepatic (Clhe) plus renal (Clre), both
acting on the unbound fraction. Built to predict edible-tissue residues
and withdrawal times against Codex Alimentarius maximum residue limits
(Ai 2024). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Cardilin_2018_radiation_radiosensitizer_mouse.html">Radiation
radiosensitizer mouse (Cardilin 2018)</a> </td>
<td style="text-align:left;"> Preclinical (mouse, FaDu
head-and-neck xenograft). Tumor growth inhibition model for combination
therapy with ionizing radiation and a radiosensitizer (linear-quadratic
radiation kill with a damage-compartment transit chain, driven by a
one-compartment radiosensitizer PK). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/ArabAlameddine_2012_raltegravir.html">Raltegravir
(ArabAlameddine 2012)</a> </td>
<td style="text-align:left;"> Two-compartment
first-order-absorption population PK model for oral raltegravir (RAL) in
145 HIV-positive adults and 19 healthy volunteers, with two
HIV-status-specific absorption rate constants (ka HIV+ slower than
HIV-), HIV-status-specific proportional residual error, a fixed
reference bioavailability F=1 for healthy volunteers, and an estimated
relative bioavailability for HIV+ subjects modified linearly by sex
(female +55%), atazanavir coadministration (+39%), and total bilirubin
centered at 30 umol/L (+36% per doubling), plus a -59% race effect on
the central volume of distribution for Caucasian relative to
non-Caucasian subjects (Arab-Alameddine 2012). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Bukkems_2021_raltegravir.html">Raltegravir
(Bukkems 2021)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model for oral raltegravir in a pooled cohort of 221 adults (healthy
volunteers, non-pregnant adults living with HIV, and pregnant women
living with HIV) across the 400 mg BID, 800 mg QD, and 1200 mg QD (two
600 mg tablets) regimens (Bukkems 2021). Absorption is modelled as a
chain of four sequential first-order compartments: depot -> transit1
-> transit2 -> transit3 -> central, with the first three
transitions governed by a shared rate constant ktr = 3 / mat (paper's
mean transit time MAT parameter) and the final transit3 -> central
transition governed by a separate first-order absorption rate constant
ka. Disposition is a two-compartment linear model with apparent central
and peripheral volumes and apparent clearance and inter-compartmental
clearance. Body weight enters as allometric scaling with fixed exponents
0.75 on CL and Q and 1.0 on Vc and Vp, referenced to 70 kg. Six
covariate-parameter relationships are retained in the final model: FED
on MAT (+160% with any food), CONMED_ATAZANAVIR on CL (-17%),
FORM_RAL_600 on F (+21%), FED_LOWFAT on F (-46%), PREG on F (-49%), and
CONMED_EFV on F (-17%). Inter-individual variability is a diagonal eta
on Vc plus a correlated 3-parameter block on CL, Q, and Vp with the
CL-Vp off-diagonal fixed to zero. Residual error is a proportional model
with a time-varying magnitude that switches at 3 h after dose (43.5% CV
before, 29.0% CV after, tracking the paper's empirical time-varying
residual). The paper's inter-occasion variability on F and MAT and its
additional eta on the residual magnitude are omitted from this packaged
model; see the validation vignette Assumptions and deviations section.
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Lee_2016_raltegravir.html">Raltegravir
(Lee 2016)</a> </td>
<td style="text-align:left;"> Population PK model for oral
raltegravir (a UGT1A1 phenotyping probe) and its glucuronide metabolite
in 24 East Asian patients with advanced solid tumours receiving FOLFIRI
chemotherapy (Lee 2016). Raltegravir absorption is described with a
depot, a single transit compartment (the paper estimates a non-integer
NN = 1.07 in the Savic 2007 transit-chain framework; the packaged model
approximates this with one explicit transit compartment), and a
one-compartment central compartment with first-order elimination (CL/F,
V/F). Raltegravir glucuronide is described by a one-compartment
metabolite compartment (central_gluc) with V_GLU fixed at 1 L (a
structural identifiability anchor) and a first-order metabolite
clearance CL_GLU. The formation rate constant kmet maps to the source
paper's FMET, which the authors define as the formation rate of
glucuronide divided by V_GLU; with V_GLU fixed at 1 L, kmet has units
1/h and drives dA_gluc / dt = kmet * V_GLU * C_RAL_central - CL_GLU *
C_gluc. Bioavailability F is fixed at 1 (single oral dose; absolute F
not identifiable). IIV is reported on CL/F, MTT, F, V/F, kmet (FMET),
and CL_GLU with a single off-diagonal covariance between CL/F and V/F
(correlation 0.567). The residual error was reported as additive on
log-transformed observations for both raltegravir and glucuronide, which
maps to a proportional residual on the linear-concentration scale. No
baseline covariates (age, sex, weight, body surface area, serum albumin
/ creatinine / bilirubin / liver enzymes, ethnicity, or UGT1A1 * 6 / *
28 / * 60 and CYP3A5 * 3 genotypes) were retained in the final model.
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Lommerse_2019_raltegravir.html">Raltegravir
(Lommerse 2019)</a> </td>
<td style="text-align:left;"> Integrated maternal-neonatal
two-compartment first-order-absorption population PK model of oral
raltegravir, coupling the maternal and fetal central compartments via a
very fast intercompartmental clearance (1000 L/h) during pregnancy to
enforce instantaneous placental equilibrium, and decoupling at birth
(time t=0 in the model). Neonatal apparent clearance rises from nil at
birth to CL_max (9.44 L/h at 25 kg) with a first-order maturation rate
constant CL_tau (11.3 1/year, 90% mature by ~11 weeks); neonatal
absorption rate constant rises from KA_base (0.0915 1/h) to KA_max (0.43
1/h) with a first-order maturation rate constant KA_tau (63.2 1/year,
90% mature by ~12 days). Neonate CL, Q, and volumes are allometrically
scaled with fixed exponents 0.75 and 1.0 to a reference weight of 25 kg.
Maternal disposition parameters (V2 3.52 L, V3 27 L, CL 9.73 L/h, Q
0.866 L/h; all at 25 kg reference) are fixed from the Rizk 2015
pediatric popPK (ref [12]); maternal KA (0.175 1/h) and bioavailability
(F 0.517) are estimated. IIV is on neonate CL and KA and maternal F;
residual error is combined additive (11.9 nM) and proportional (54%)
(Lommerse 2019). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Wang_2011_raltegravir.html">Raltegravir
(Wang 2011)</a> </td>
<td style="text-align:left;"> Population PK model for plasma
and intracellular (PBMC) raltegravir after a single 400 mg oral dose in
six healthy male Singaporean volunteers (Wang 2011). Plasma PK is
described by a one-compartment model with first-order elimination
preceded by a chain of two transit compartments between depot and
central (Kappelhoff 2005 transit-absorption parameterisation: MAT = (n +
1) / ktr with n = 2 transit compartments). Bioavailability F is implicit
in the apparent CL/F and V/F. Intracellular (PBMC) raltegravir is
described as an empirical partition of the predicted plasma
concentration via the paper's accumulation ratio ACR (point estimate
11.2%) with its own inter-individual variability and exponential
residual error (Wang 2011 Eq.: C_IC,obs = ACR * C_plasma,pred *
exp(eps_IC)). The packaged model maps ACR to the canonical paper-named
bare parameter `frac` and its log-transformed primary `lfrac`. No
baseline covariates were retained in the final model. Note that the
paper's term 'accumulation ratio' is a misnomer in the conventional
sense -- ACR < 1 means raltegravir does NOT accumulate
intracellularly, consistent with simple diffusion of unbound drug into
PBMCs (the authors' Conclusions). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Blair_2004_raltitrexed.html">Raltitrexed
(Blair 2004)</a> </td>
<td style="text-align:left;"> Three-compartment population PK
model for intravenous raltitrexed (Tomudex) in adult patients with
advanced solid tumours, with linear-additive covariate effects of
Cockcroft-Gault creatinine clearance on CL and of body weight and serum
albumin on central volume (Blair 2004) </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/HuttonSmith_2018_ranibizumab.html">Ranibizumab
(HuttonSmith 2018)</a> </td>
<td style="text-align:left;"> QSP. Three-compartment (retina,
vitreous, aqueous) ocular PK/PD model of intravitreal ranibizumab and
free VEGF suppression in wet AMD, with bivalent VEGF-ranibizumab binding
(V, R, VR, RVR species per compartment; 12 ODEs). Retina-vitreous
transfer uses hydrodynamic-radius-dependent ILM and RPE permeabilities
(Hutton-Smith 2017 rabbit-PK power laws); vitreous-aqueous elimination
k_el is derived from the ranibizumab ocular half-life via the
mass-balance of Section S2. Parameters K_D = 19000 pM and log-normal
population distributions of ocular half-life and VEGF production rate
were re-estimated on 31 wet-AMD patients from Saunders 2015. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Mulyukov_2018_ranibizumab.html">Ranibizumab
(Mulyukov 2018)</a> </td>
<td style="text-align:left;"> Indirect-response PK/PD model of
intravitreal ranibizumab on best-corrected visual acuity (SCORE_BCVA,
ETDRS letters) in anti-VEGF-naive adults with neovascular age-related
macular degeneration (Mulyukov 2018). SCORE_BCVA is driven by an
indirect-response ODE in which drug concentration stimulates the
SCORE_BCVA production rate (kin) through a Michaelis-Menten-like term
with a time-dependent maximum effect emax(t) = emax_ss + demax_0 *
exp(-kemax * t). The PK is a fixed first-order vitreous-elimination
placeholder (kel = 0.077/day, vitreous volume = 4 mL, no IIV) borrowed
from a previous population PK analysis (reference 20 of the paper)
because vitreous PK data were not collected in the development studies.
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Xu_2013_ranibizumab.html">Ranibizumab
(Xu 2013)</a> </td>
<td style="text-align:left;"> One-compartment population PK
model for total ranibizumab in serum following intravitreal injection in
adults with neovascular age-related macular degeneration (Xu et al.
2013, IOVS). Vitreous humor acts as a slow-release depot with
first-order absorption Ka into a systemic central compartment with
first-order clearance CL/F; a small parallel fraction of each
intravitreal dose reaches the central compartment via a rapid
needle-track shunt bypassing the vitreous. Covariates: Cockcroft-Gault
creatinine clearance on CL/F (power) and concomitant verteporfin PDT on
Ka (multiplicative). Serum ranibizumab was measured; vitreous
concentration is computed algebraically from vitreous amount over an
assumed 4 mL vitreous humor volume for downstream simulation and is not
observed. Data pooled from two Phase 1, two Phase 1/2, and one Phase 3
trial (MARINA / FOCUS). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Hawwa_2013_ranitidine.html">Ranitidine
(Hawwa 2013)</a> </td>
<td style="text-align:left;"> One-compartment population PK
model for ranitidine in critically ill children (n = 78, age 15 days to
15.5 years, weight 1.3 to 47 kg) receiving oral and/or intravenous bolus
doses for stress-ulcer or GORD prophylaxis. First-order absorption with
allometric scaling of clearance (fixed exponent 0.75) and central volume
(fixed exponent 1.0) to a 70 kg adult. Cardiac failure or cardiac
surgery (pooled binary indicator) multiplicatively reduces clearance by
53.7%. IIVs on absorption rate constant and bioavailability were dropped
during model building so the model could minimize; only CL and V carry
IIV. Proportional residual error (Hawwa 2013). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Ivaturi_2017_RBP_7000.html">RBP
7000 (Ivaturi 2017)</a> </td>
<td style="text-align:left;"> Integrated population
pharmacokinetic / PANSS pharmacodynamic model for the once-monthly
long-acting subcutaneous Atrigel formulation of risperidone (RBP-7000,
Indivior) in 337 adults with acute schizophrenia treated with two SC
injections (90 mg or 120 mg) 28 days apart in a Phase 3 registration
trial (NCT02109562). The PK sub-model is the empirical dual-absorption
structure inherited from the upstream RBP-7000 SAD and MAD studies
(Gomeni 2013; Laffont 2014, 2015): a fast first-order absorption rate
ka1 from the SC depot to the risperidone central compartment captures
the rapid release from the injection site, while a 5-compartment transit
chain with rate constant ktr feeds a slow first-order absorption rate
ka2 from the terminal transit compartment into central, mimicking the
slow sustained release from the solidified ATRIGEL implant. Systemically
available risperidone is distributed to a single peripheral compartment
(rate constants krrp and krpr), eliminated by non-metabolite routes
(krel), and partly converted to its equipotent 9-hydroxyrisperidone
metabolite at rate kr9; the metabolite is described by a one-compartment
model with first-order elimination (k9el) and an apparent volume of
distribution constrained equal to the central volume of the parent V
because VM was not identifiable. CYP2D6 intermediate and poor
metabolizers (vs the extensive / inconclusive reference) have 76 and 94
percent lower metabolite formation rate, respectively. Plasma
concentrations of risperidone and 9-OH-risperidone are converted to
total active moiety in risperidone-equivalent units by AM =
[risperidone] + [9-OH-risperidone] * 410/426 (molecular-weight
correction). The PANSS PD sub-model combines a Weibull-shaped placebo
response (PMAX, TPROG, POW), an additive linear-drift term (DRIFT) that
captures the improvement-then-worsening pattern observed in some
individuals, and an Emax model relating total active moiety to relative
PANSS decrease, with drug and placebo effects entering additively per
Predicted PANSS = BSL * (1 - PMAX * (1 - exp(-(T/TPROG)^POW)) - Emax *
AM / (EC50 + AM)) + DRIFT * T (T in weeks). The proportional-odds CGI-S
sub-model of Table 4 is documented in the vignette but not implemented
here because rxode2's additive residual / d/dt() ODE pipeline does not
natively express ordinal-logistic observation likelihoods; see the
vignette Assumptions and deviations. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/LopezArguello_2023_pbp_binding_pseudomonas.html">Relebactam
qsp (LopezArguello 2023)</a> </td>
<td style="text-align:left;"> QSP. In vitro (Pseudomonas
aeruginosa PAO1). Whole-cell penicillin-binding protein (PBP)
covalent-binding model for relebactam (diazabicyclooctane beta-lactamase
inhibitor): seven coupled ODEs for the rate of net influx of drug across
the outer membrane into periplasm and the competitive, mass-balanced
acylation of six PBPs (1a, 1b, 2, 3, 4, 5/6) counted as molecules per
bacterial cell. The intact parameter switches between the intact
whole-cell assay (penetration-limited; drug enters periplasm at
Rate_Influx/access) and the lysed isolated-membrane assay (no outer
membrane; a vast excess of drug molecules is present at time 0).
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Choi_2011_remifentanil.html">Remifentanil
(Choi 2011)</a> </td>
<td style="text-align:left;"> Combined effect-and-tolerance
pharmacodynamic model for the central-nervous-system effect of
remifentanil on EEG-derived temporal linear mode complexity (TLMC) in
healthy volunteers (Choi 2011). The PD model captures both depression of
CNS activity during infusion and rebound during recovery via a sigmoid
Emax driver from an effect compartment plus an opposing sigmoid term
driven by a slow tolerance compartment. The TLMC observation is
baseline-normalised so the readout is dimensionless with baseline E0 = 1
by construction. The 3-compartment IV remifentanil PK underneath is
fixed from the upstream Kang 2007 BJCP popPK (Kang 2007 Table 2;
rate-constant parameterisation; AGE and BSA additive covariate effects
on the elimination rate constant k10). Choi 2011 itself did not
re-estimate PK -- it read per-subject individual PK estimates from the
Kang 2007 fit as input data columns. Reported model-selection metrics
across the three competing PD models in Choi 2011 (combined
effect-and-tolerance, feedback, sigmoid Emax) identified the combined
model implemented here as the best by AIC (-6966) and positive
predictive value of rebound (100%); the feedback and sigmoid Emax models
did not capture rebound (Table 3). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Yang_2017_remifentanil.html">Remifentanil
(Yang 2017)</a> </td>
<td style="text-align:left;"> One-compartment population PK
model for continuous intravenous remifentanil infusion in critically ill
adults receiving venoarterial extracorporeal membrane oxygenation
(VA-ECMO), with sex and centrifugal-pump rotational speed as covariates
on clearance (Yang 2017). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Chen_2024_remimazolam.html">Remimazolam
(Chen 2024)</a> </td>
<td style="text-align:left;"> Joint population PK/PD model for
remimazolam, its inactive metabolite CNS 7054, and the bispectral index
(BIS) in healthy Chinese adult volunteers (Chen 2024). Remimazolam is
described by a three-compartment model with first-order elimination; the
whole of parent clearance feeds a single transit compartment that delays
the appearance of CNS 7054, which is itself described by a
two-compartment model. Sedation is described by an effect compartment
equilibrating with remimazolam plasma concentration and driving an
inhibitory sigmoid Imax model on BIS. Body weight enters every clearance
and volume term by allometric scaling with fixed exponents (0.75 and 1)
and a 60 kg reference weight; no other covariate was retained on either
the PK or the PD. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Luo_2024_CES1_cirrhosis.html">Remimazolam
pbpk (Luo 2024)</a> </td>
<td style="text-align:left;"> PBPK (semi-mechanistic, custom
WinNonlin 8.1 implementation). remimazolam disposition in healthy adults
and in liver cirrhosis (Child-Pugh A/B/C). Remimazolam is a
direct-acting ultrashort-acting sedative that CES1 INACTIVATES to a
carboxylic-acid metabolite, so no active metabolite is tracked. It is
administered intravenously only, and Table 2 reports no CLint,K, so the
kidney compartment carries distribution but no elimination. The
semi-PBPK circuit is three gut-wall segments, portal vein, liver, kidney
and a three-compartment systemic compartment. Cirrhosis is applied by
switching the Child-Pugh-specific physiology of Table 1 (organ blood
flows, functional liver volume, GI transit rates, GFR, plasma-binding
protein concentrations, hepatic CES1 content) and rescaling CLint,
CLint,K, Peff and Vsys through Eq 1-6. Deterministic: the paper's
virtual populations are uniform 80-120% draws on the drug parameters,
not lognormal random effects, so no IIV is encoded. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Laffont_2025_opioid_overdose_reversal_simulation.html">Respiratory
physiology (Mann 2022)</a> </td>
<td style="text-align:left;"> QSP. Magosso / Ursino respiratory
and cerebrovascular physiology with Mann 2022 extensions for
opioid-induced ventilatory depression and cardiovascular-collapse /
cardiac-arrest dynamics. Encodes the 11-state physiological submodel
from the FDA delaymymod.c implementation, plus the cardiac-arrest event
rule (PaO2 below 15 mm Hg sustained 220 s -> cardiac output decays
toward 0.01 L/min). The CAR (fraction of opioid receptors bound by an
agonist) input drives reductions in wakefulness drive (W - Wmax *
CAR^P3) and chemoreflex drives (factor 1 - CAR^P1). The Spencer
dissociation algebra for blood gas exchange is carried inline. The
original FDA implementation uses delay- differential equations for
peripheral and central chemoreflex filtering with delays of roughly
K_Dp/(Qb+Qt) ~ 7 s and K_Dc/(Qb+Qt) ~ 11 s; this model deploys the limit
of zero delay (Plag_X = X, Clag_X = X), which preserves the steady-state
structure and longer-time-scale overdose dynamics but does not reproduce
the second-scale delay artefacts of the original. Composes downstream of
Mann_2022_mu_receptor_binding (CAR_OPIOID input). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Roepcke_2023_rezafungin.html">Rezafungin
(Roepcke 2023)</a> </td>
<td style="text-align:left;"> Three-compartment population PK
model for rezafungin after weekly IV infusion in healthy subjects,
hepatically impaired subjects, and patients with candidemia and/or
invasive candidiasis (Roepcke 2023), with body-surface-area scaling on
CL, V1, and the shared peripheral volume V23, a serum-albumin effect on
V23, and a healthy-vs-diseased disease-state shift on CL and V1.
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Diao_2014_rFIXFc.html">RFIXFc
(Diao 2014)</a> </td>
<td style="text-align:left;"> Three-compartment population PK
model for recombinant factor IX Fc fusion protein (rFIXFc, eftrenonacog
alfa) in patients with severe to moderate haemophilia B aged 12-77 years
(Diao 2014). Disposition is described by linear three-compartment
kinetics with intravenous input and first-order elimination from the
central compartment; body weight is the only retained covariate, scaling
CL and V1 with estimated power exponents (not the canonical 0.75 / 1)
and a reference weight of 73 kg. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/VargasChristensen_2019_rfviii_rat.html">Rfviii
rat (VargasChristensen 2019)</a> </td>
<td style="text-align:left;"> Preclinical (rat).
Two-compartment quasi-steady-state target-mediated drug disposition
(QSS-TMDD) population PK model of recombinant Factor VIII (rFVIII) and
its carrier protein von Willebrand factor (VWF) in hemophilia A rats
(Vargas Christensen 2019). Jointly describes total rFVIII plasma
concentration, total VWF plasma concentration, and the rFVIII:VWF
complex luminescent oxygen channeling immunoassay (LOCI) signal in cps
following single IV bolus rFVIII over a 285-fold dose range (17.5 to
5000 IU/kg). Unbound rFVIII distributes to a peripheral compartment via
first-order rate constants k12 / k21 and is eliminated by linear
clearance CL of unbound rFVIII. VWF follows zero-order synthesis (ksyn =
kdeg * R0 at steady state) and first-order degradation of the unbound
species (kdeg). The rFVIII:VWF complex is eliminated with a
Michaelis-Menten-shape apparent rate constant driven by the unbound
rFVIII concentration (k_e,comp = Vmax,comp * Cfree / (KM,comp + Cfree));
at Cfree = 0 the complex has no direct elimination and its effective
half-life reduces to that of free VWF (ln(2)/kdeg = ~22 h; Figure 2 of
the paper). The rFVIII:VWF complex plasma concentration maps to the
observed LOCI signal via a 4-parametric logistic (base_cps + (max_cps -
base_cps) * complex^gamma / (cps50^gamma + complex^gamma)). CL scales
allometrically with body weight at fixed exponent 0.75 (reference weight
0.3 kg = the cohort median; the paper reports no explicit reference
weight). No covariate on V. Gender and age were tested by the paper but
not retained in the final model. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Dodds_2005_rfxiii_cyno.html">Rfxiii
cyno (Dodds 2005)</a> </td>
<td style="text-align:left;"> Preclinical (cynomolgus monkey).
Three-state mechanistic population PK model for recombinant Factor XIII
A2 dimer (rA2) administered IV bolus, with endogenous constant-influx
production of A2 dimer and B monomer, mass-action association A2 + 2 B
-> A2B2 heterotetramer following the 1A2 + 2B -> 1A2B2
stoichiometry, first-order elimination of each species, and three ELISA
assay outputs (total A2 = A2 + A2B2; A2B2 tetramer; free B) with
proportional + proportional + additive residual error. Parameters are
weight-normalised throughout (mass / kg). Estimated in NONMEM V (Dodds
2005). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Budha_2015_rg7652.html">Rg7652
(Budha 2015)</a> </td>
<td style="text-align:left;"> Population PK/PD model for RG7652
(an anti-PCSK9 monoclonal antibody) in healthy hypercholesterolemic
subjects (Budha 2015): one-compartment PK with first-order SC absorption
and combined linear plus Michaelis-Menten elimination from the central
compartment, linked to a Type 3 indirect-response model for serum
low-density lipoprotein cholesterol (LDL-C) in which RG7652 stimulates
LDL-C degradation through an Emax function. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Mensing_2017_3D_HCV_regimen.html">Ribavirin
(Mensing 2017)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model for oral ribavirin in HCV genotype-1 infected adults receiving the
3D + ribavirin regimen (Mensing 2017). First-order absorption, linear
elimination, combined proportional + additive residual error, IIV on
CL/F and a shared IIV on Vc/F + Vp/F. The author's final model retained
cirrhosis, gender, and creatinine clearance as significant covariates on
CL/F (and gender on Vc/F and Vp/F), but the paper does not publish point
estimates for these covariate coefficients (only graphical
exposure-ratio forest plots in Figure 2); the implemented model is the
structural typical-value model with covariate coefficients omitted
(documented in covariatesDataExcluded). Mensing 2017 reports correlated
IIV on CL/F and Vc/Vp; the correlation coefficient is not given in Table
3, so this implementation encodes the random effects as independent (a
documented deviation; see vignette Errata). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Mulder_2025_ribavirin.html">Ribavirin
(Mulder 2025)</a> </td>
<td style="text-align:left;"> Integrated population PK/PD model
for oral ribavirin (RBV) in solid organ transplant (SOT) recipients with
chronic hepatitis E virus (HEV) infection (Mulder 2025). PK:
two-compartment model with first- order absorption; ka, Vc, Q, and Vp
fixed at the Wu 2015 (HCV- patient) starting-model estimates and CL
re-estimated. Covariates carried over from Wu 2015: allometric weight on
Vc (exponent 1.29) and Vp (exponent 0.725) with reference weight 79 kg,
and a female- factor 0.732 on Vp. New covariate estimated on CL: MDRD
eGFR with a capped power effect (exponent 1.32) above an estimated
threshold of 57 mL/min/1.73 m^2. Haemoglobin: indirect-response
(kin/kout) on an endogenous Hb pool, with RBV producing a linear
concentration- proportional acceleration of the haemoglobin loss rate (1
+ slope * Cc) so that haemoglobin declines with increasing RBV exposure;
kin is set per subject from the baseline-Hb covariate HGB_BL so the Hb
state is at steady state pre-treatment. Viral load: target-cell- limited
(Baccam / Dahari) model with three paper-specific compartments (healthy
hepatocytes, infected hepatocytes, virions); RBV inhibits viral
replication via an Imax/IC50 sigmoidal Emax form (Imax = 0.999, IC50 =
1000 ng/L) so production of virions from infected cells is essentially
fully suppressed throughout the observed RBV concentration range;
healthy hepatocyte half-life and the infected:healthy hepatocyte
decay-rate ratio are fixed to the literature values (Dahari 2007) and
the viral elimination rate is estimated. Initial conditions for the
viral compartments are computed at baseline steady state: H(0) = 1
(arbitrary unit), I(0) = rho = 0.001 (fixed), V(0) = HEV_VLOAD per
subject; the synthesis rates ksyn (healthy), beta (infection), and p
(virion production) are derived inside model() from these initial
conditions and the rate constants so that all three viral compartments
start at baseline steady state. Hb and the three viral compartments are
declared paper_specific_compartments. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Saleh_2023_leicns_pk30_mouse_brain.html">Ribociclib
mouse pbpk (Saleh 2023)</a> </td>
<td style="text-align:left;"> PBPK (LeiCNS-PK3.0 CNS
physiologically-based model, mouse version). Preclinical (mouse, CD1
nude). Nine-compartment CNS PBPK model predicting unbound ribociclib
concentrations in brain extracellular fluid (brain ECF) after a single
100 mg/kg oral dose. The CNS structure is the mouse re-parameterisation
of LeiCNS-PK3.0: brain microvasculature (brain_vascular), brain ECF, a
phospholipid brain-cell-membrane binding compartment
(brain_cell_membrane), brain intracellular fluid (brain_icf), lysosomes
(brain_lysosome), and the four CSF compartments (lateral ventricles,
third + fourth ventricles, cisterna magna, subarachnoid space) draining
in series back to plasma. Transport across the BBB and BCSFB is the sum
of a paracellular clearance (Qp, charged + neutral drug) and a
transcellular clearance (Qt, neutral drug only, scaled by pH-dependent
neutral fractions PHF and by asymmetry factors AF that encode active
transport). Every CNS parameter is fixed to mouse physiology (Table III)
or derived from the drug's physicochemical properties (Table I); none
was fitted here. The BBB asymmetry factors are back-calculated from
Kp,uu,BBB = 0.0693 (taken from ref [9]; Table V). The plasma PK model is
the empirical one-compartment model of Table IV (ref [9]) and acts
purely as a forcing function: brain uptake does not deplete plasma,
exactly as published. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Hennig_2015_rifabutin.html">Rifabutin
(Hennig 2015)</a> </td>
<td style="text-align:left;"> Two-compartment population
pharmacokinetic model for rifabutin with simultaneous two-compartment
metabolite (25-O-desacetyl rifabutin) modelling in 44 African
HIV-infected adults with pulmonary tuberculosis on 300 mg daily oral
rifabutin (Hennig 2015). Body weight allometrically scaled (a priori; CL
exponent 0.75, V exponent 1) on all rifabutin apparent clearances and
apparent volumes; sex effect on rifabutin V/F (males 1.84-fold higher
than females); SLCO1B1 rs11045819 heterozygous-AC genotype increases
rifabutin bioavailability F by 30.4 percent relative to homozygous-CC
reference. Des-rifabutin parameters are apparent (with respect to
rifabutin F and metabolite-formation fraction) and were estimated
without allometric scaling, with metabolite Q and peripheral V fixed.
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Barnett_2018_rifampicin.html">Rifampicin
(Barnett 2018)</a> </td>
<td style="text-align:left;"> One-compartment population PK
model with Wilkins/Savic transit-compartment absorption for a single 600
mg oral dose of rifampicin in healthy adult males (Barnett 2018), refit
from the Wilkins 2008 structural form. The rifampicin model is one of
three popPK models developed jointly in Barnett 2018 to support OATP1B
drug-drug-interaction modeling with coproporphyrin I and rosuvastatin;
the rifampicin compartmental output is the time-varying CRIF input that
drives the competitive OATP1B inhibition term in the sibling
coproporphyrin I and rosuvastatin models. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Chigutsa_2011_rifampicin.html">Rifampicin
(Chigutsa 2011)</a> </td>
<td style="text-align:left;"> Population pharmacokinetic model
for oral rifampicin in adults with sputum-positive pulmonary
tuberculosis in South Africa (Cape Town). One-compartment disposition
with a fixed-length Erlang transit-absorption chain (NN = 19 fixed)
feeding the central compartment via first-order ka. Allometric scaling
of CL/F and V/F to a 70 kg reference body weight with canonical Anderson
and Holford (2008) exponents (0.75 on CL, 1.0 on V; cited as Chigutsa
2011 Methods reference 3 for the allometric model). Covariate effects:
female sex on V/F (-30%) and on the mean transit time MTT (+30% per
Results body text page 4124 -- women have a 30% LONGER absorption delay
than men; Table 2 Final-model row prints -30% with a CI bit-identical to
the V/F row immediately above, which is the canonical signature of a
typesetting row-duplication error; per the operator sidecar request-001
directive the body text +30% is the source of truth); high-dose-band
effect on MTT (-27% for daily doses >= 600 mg vs the 450 mg
reference); SLCO1B1 rs4149032 genotype-dependent oral bioavailability F
(heterozygous carriers -18%; homozygous variant carriers -28%; relative
to the homozygous-common-allele wild-type reference). Between-subject
variability (BSV) is carried on F, CL, and MTT with the CL-MTT
correlation block 0.86 from Table 2; within-subject (WSV / IOV)
variability reported in Table 2 is NOT carried (forward-simulation users
do not need the second-occasion IOV layer; see vignette Errata).
Combined additive + proportional residual error. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Clewe_2015_rifampicin.html">Rifampicin
(Clewe 2015)</a> </td>
<td style="text-align:left;"> Pharmacometric pulmonary
distribution model for rifampicin in adults without tuberculosis: a
one-compartment plasma PK model with single-transit oral absorption
coupled to a Smythe 2012 enzyme-pool autoinduction structure (MTT, N,
EMAX, EC50, kENZ all fixed from the upstream Smythe 2012 model) plus two
effect compartments capturing distribution from plasma to epithelial
lining fluid (ELF) and alveolar cells (AC); CL/F and Vc/F are
FFM-allometrically scaled to 70 kg, the ELF and AC equilibration rate
constants kELF and kAC are fixed to an equivalent 1-min half-life
(instantaneous distribution at the single 4-h post-dose BAL sampling
time), and only the unbound steady-state ELF/plasma and AC/plasma
concentration ratios are estimated (1.28 and 5.5 after correction for
the 20% rifampicin plasma free fraction). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Horita_2018_rifampicin.html">Rifampicin
(Horita 2018)</a> </td>
<td style="text-align:left;"> One-compartment population
pharmacokinetic model with sequential zero-order then first-order
absorption and first-order elimination for oral rifampin (rifampicin) in
Ghanaian children with active tuberculosis (Horita 2018); allometric
weight scaling on CL/F (fixed 0.75) and V/F (fixed 1.0) normalised to
the cohort median 14.3 kg. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Marsot_2017_rifampicin.html">Rifampicin
(Marsot 2017)</a> </td>
<td style="text-align:left;"> One-compartment population
pharmacokinetic model for oral rifampicin in adult patients with
staphylococcal osteoarticular infections (Marsot 2017; 62 patients, 103
steady-state plasma concentrations from routine therapeutic drug
monitoring at 300 mg three times daily). Absorption uses a
single-transit compartment chain (depot -> transit1 -> central)
with a fixed first-order absorption rate constant ka = 1.15 1/h;
first-order elimination from the central compartment. Coadministration
of oral fusidic acid (500 mg three times daily in 16 % of the cohort)
was retained as the sole significant covariate and reduces both apparent
oral clearance and apparent central volume of distribution: typical CL/F
is 5.1 L/h (with fusidic acid) vs 13.7 L/h (without) and typical V/F is
23.8 L (with) vs 61.1 L (without), an interaction attributed to CYP3A4
inhibition and altered plasma protein binding by fusidic acid.
Inter-individual variability is reported on CL/F (72.9 % CV) and V/F
(59.1 % CV); residual variability is additive with standard deviation
2.256 mg/L. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Schipani_2016_rifampicin.html">Rifampicin
(Schipani 2016)</a> </td>
<td style="text-align:left;"> Simultaneous population
pharmacokinetic model for oral rifampicin in a mixed Malawian cohort of
adults (n=115) and children (n=50) with tuberculosis. One-compartment
disposition with first-order absorption (depot to central). Allometric
scaling of CL/F and V/F to a 70 kg reference body weight with canonical
Anderson and Holford (2008) exponents (0.75 on CL, 1.0 on V; both
fixed). Estimated power-form effect of age on CL/F (exponent 0.517)
centered at AGE_median. Children (defined as body weight 5-29 kg, age
< 15 y per Schipani 2016 Results) carry a relative bioavailability
factor F = 0.517 vs adults (F fixed at 1). Inter-individual variability
is carried on CL/F (46.6% approx CV) and V/F (87.4% approx CV); ka and F
have no estimated IIV. Proportional residual error 48%. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Sloan_2017_rifampicin.html">Rifampicin
(Sloan 2017)</a> </td>
<td style="text-align:left;"> One-compartment population PK
model for oral rifampin in Malawian adults with smear-positive pulmonary
tuberculosis (Sloan 2017), developed using a two-stage NONMEM workflow:
stage 1 fit a one-compartment + Savic 2007 transit-compartment
absorption chain (NN, MTT, Ka) to 47 intensively-sampled patients, then
stage 2 fit CL/F and V/F (plus IIVs and a multiplicative sex effect on
CL) to 174 sparsely-sampled patients with absorption parameters fixed at
the stage 1 estimates; F is fixed at 1, between-subject variability is
on CL/F, V/F, and (fixed from stage 1) MTT, and an allometric weight
model with fixed exponents 0.75 / 1.0 is referenced to 70 kg.
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Smythe_2012_rifampicin.html">Rifampicin
(Smythe 2012)</a> </td>
<td style="text-align:left;"> Semimechanistic population PK /
enzyme-turnover autoinduction model for oral rifampicin in adult
tuberculosis patients (Smythe 2012). One-compartment disposition with
single-transit absorption (N = 1 FIX) feeds the central compartment;
rifampicin plasma concentration drives a nonlinear Emax production-rate
increase on a unitary-baseline enzyme pool, which in turn multiplies
apparent oral clearance. CL/F and V/F are Anderson-Holford
normal-fat-mass (NFM) allometrically scaled to a 70-kg patient with
separate estimated Ffat contributions on CL/F and V/F. HIV-positive
status increases V/F by 29.6%. IIV is on CL/F (correlated with V/F at
91.1%), V/F, and EC50; interoccasion variability is on MTT and
bioavailability F. Residual error is combined additive + proportional.
The same one-compartment + single-transit + autoinduction structural
backbone (and the autoinduction parameters MTT, N, Emax, EC50, kENZ) is
inherited verbatim by Clewe 2015 and Svensson 2016 -- see
modellib('Clewe_2015_rifampicin') and
modellib('Svensson_2016_rifampicin'). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Svensson_2016_rifampicin.html">Rifampicin
(Svensson 2016)</a> </td>
<td style="text-align:left;"> Combined population PK/PD model
for rifampicin in adults with drug-susceptible pulmonary tuberculosis: a
one-compartment, single-transit, oral PK model with first-order
plasma-concentration-driven autoinduction of clearance via an
enzyme-pool turnover (structure from Smythe 2012) linked to the
Multistate Tuberculosis Pharmacometric (MTP) three-state bacterial
disease model (fast-, slow-, and nonmultiplying Mycobacterium
tuberculosis states; structure from Clewe 2016) with rifampicin drug
effects as fixed-at-100% on/off inhibition of fast-multiplying bacterial
growth plus second-order plasma-concentration-driven death of slow- and
nonmultiplying bacteria; all PK parameters and all MTP transfer/growth
rates are fixed to the upstream-paper estimates, while the system
carrying capacity Bmax (with 152% CV IIV) and the two second-order death
rates SDk and NDk are re-estimated against 19 patients from a 1966-1977
Kenyan rifampicin monotherapy trial. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Vinnard_2017_rifampicin.html">Rifampicin
(Vinnard 2017)</a> </td>
<td style="text-align:left;"> One-compartment population PK
model for oral rifampicin in HIV/TB patients in Botswana (Vinnard 2017),
with a Savic 2007 analytical transit-compartment absorption chain
feeding a virtual depot, oral bioavailability fixed at 1,
between-subject variability on CL, F, MTT, and the (non-integer) number
of transit compartments NN, and inter-occasion variability on F across
two sampling visits (pre-ART vs after approximately 4 weeks of ART).
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Wicha_2018_rifampicin.html">Rifampicin
(Wicha 2018)</a> </td>
<td style="text-align:left;"> Preclinical-to-clinical
translational Multistate Tuberculosis Pharmacometric (MTP) framework for
high-dose oral rifampicin in adults with pulmonary tuberculosis. The
Svensson 2018 HIGHRIF1 plasma PK model (Erlang transit absorption +
Michaelis-Menten clearance + enzyme-pool autoinduction + dose-dependent
bioavailability anchored at 450 mg) is coupled via the Clewe 2015
epithelial lining fluid (ELF) effect compartment to a new
post-antibiotic-effect (PAE) compartment with saturable Michaelis-Menten
elimination, driving the Clewe 2016 three-state MTP model (fast-, slow-,
and nonmultiplying Mycobacterium tuberculosis substates) at
human-specific carrying capacity Bmax = 2.42e8/mL and fast-multiplying
growth rate kG = 0.206/day. Time unit is days; all PK rates from
Svensson 2018 (reported in 1/h) and the ELF kELF from Clewe 2015 are
multiplied by 24 to bring to days. All structural parameters are fixed
at the Wicha 2018 Table 1 typical values; only the Svensson 2018 IIV is
carried (IOV is omitted because the EBA forward simulation models a
single 14-day monotherapy course). The model predicts early bactericidal
activity (EBA0-2 / EBA0-5 / EBA0-14) for clinical rifampicin doses
2.5-50 mg/kg without re-estimating any parameter from clinical EBA data.
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Ramachandran_2023_tuberculosis_eptb_pbpk.html">Rifampicin
pbpk (Ramachandran 2023)</a> </td>
<td style="text-align:left;"> PBPK (whole-body, 18 ODEs, MATLAB
ode15s). Oral rifampicin disposition at extrapulmonary tuberculosis
(EPTB) sites in a 70-kg reference adult male (Ramachandran and Gadgil
2023, CPT Pharmacometrics Syst Pharmacol). Seventeen perfusion-limited
well-stirred tissue compartments connected by blood and lymph flow, plus
a gut-lumen state for enterohepatic recycling. The model's two novel
states are a pleural-fluid compartment (a filtrate of the lung that
drains via lymphatics) and a consolidated lymph-node compartment that
collects afferent lymph from every organ except bone and spleen and
returns it to venous blood - the two most common EPTB sites.
Physiological volumes, blood flows, and lymph flows are fixed literature
fractions of body weight, cardiac output (5200 mL/min), and afferent
lymph flow (8 L/day) respectively (Appendix S1 Tables S2 and S3).
Tissue:plasma partition coefficients were computed by the Rodgers and
Rowland method from the drug physicochemistry in Table S4 and are
tabulated in Table S5. Only the first-order oral absorption rate ka and
total systemic clearance CL were estimated, by weighted least squares
against reported plasma concentrations after a 450 mg oral dose
(Appendix S1 Table S7). Clearance is split into a renal component fR *
CL driven by arterial concentration and a hepatic component (1 - fR) *
CL driven by the hepatic inlet concentration; the hepatic output enters
the gut lumen, from which rifampicin is reabsorbed at kr = 0.17 /h
(enterohepatic circulation) or lost by faecal transit at kF = 0.252 /h.
The model is a deterministic typical-value simulation: the paper reports
no interindividual variability and no residual error model, so propSd is
fixed at 0. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Zvada_2010_rifapentine.html">Rifapentine
(Zvada 2010)</a> </td>
<td style="text-align:left;"> Parent-metabolite population
pharmacokinetic model for single-dose 900 mg oral rifapentine (RFP) and
its primary active metabolite 25-O-desacetyl rifapentine (25-DRFP) in 34
healthy adult male volunteers, with characterization of food effect on
bioavailability for four meal types (high-fat English breakfast A,
low-fat bulky maize porridge B, high-fat bulky maize porridge with lard
C, and low-fat high-fluid chicken noodle soup D) relative to fasted
reference (meal E). Parent RFP is described by a one-compartment model
with Savic transit absorption (NN = 10.9, MTT = 1.45 h) and a
step-function autoinduction of apparent clearance at MTIME = 43 h (CL1/F
= 2.14 to CL2/F = 3.22 L/h). All RFP is assumed to convert to 25-DRFP;
metabolite disposition is two-compartment with its own step-function
clearance switch at MTIME_M = 46.8 h (CLM1/F = 1.81 to CLM2/F = 4.63
L/h). Meal effects multiply the typical bioavailability via TVF = 1 * (1
+ sum of per-meal fractional changes). Inter-individual variability is a
3x3 block on CL/F, MTT, and F (correlations rho_F_MTT = 0.65 and
rho_CL_MTT = -0.56; cov(CL, F) assumed 0 since not reported); a single
shared eta on CL/F applies to both CL1 and CL2. Inter-occasion
variability (Table 2 IOV columns) is omitted because nlmixr2lib does not
standardize an OCC encoding; the cross-over IOV magnitudes are noted in
the vignette Errata. Residual variability is combined additive +
proportional on plasma RFP (additive 0.206 mg/L, proportional 10.6%) and
on plasma 25-DRFP (additive 0.211 mg/L, proportional 19.1%). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Zhang_2016_rilotumumab.html">Rilotumumab
(Zhang 2016)</a> </td>
<td style="text-align:left;"> Two-compartment IV population PK
model for rilotumumab (fully human anti-HGF IgG2 monoclonal antibody) in
patients with MET-positive gastric or gastroesophageal-junction
adenocarcinoma receiving rilotumumab in combination with epirubicin /
cisplatin / capecitabine (ECX). The structural model and parameter
values were inherited from the previously developed population PK
analysis of rilotumumab (Zhu et al. 2014, J Pharm Sci 103:328-336);
Zhang 2016 reports the typical-value point estimates and IIV %CV from
that prior model and uses it as the reference for an external visual
predictive check assessing whether ECX co-administration alters
rilotumumab PK. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Aouri_2017_rilpivirine.html">Rilpivirine
(Aouri 2017)</a> </td>
<td style="text-align:left;"> One-compartment population PK
model for oral rilpivirine in HIV-1-infected adults (Aouri 2017), with
zero-order absorption from the gastrointestinal tract directly into the
central compartment (duration D1 = 4 h; derived mean absorption time
D1/2 = 2 h), apparent clearance CL/F = 11.7 L/h, apparent volume of
distribution V/F = 401 L, combined proportional plus additive residual
error (21.6% and 9.8 ng/mL), and inter-individual variability on CL/F
only (33% CV). No demographic, clinical, or genetic covariates (sex,
body weight, height, age, race, AST, ALT, HCV, HBV, comedications,
CYP3A4*22, CYP3A5*3, CYP2C19*2, CYP2C19*17, UGT1A1*28, UGT1A4*2) were
retained in the final covariate model. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Marcantonio_2022_efa.html">Risankizumab
(Marcantonio 2022)</a> </td>
<td style="text-align:left;"> QSP. One-compartment monospecific
anti-ligand mechanistic PKPD model of risankizumab-p19 binding in adults
with plaque psoriasis (Marcantonio 2022 Early Feasibility Assessment,
Case Study 3). Risankizumab binds the p19 subunit of IL-23 (specific to
IL-23; distinguished from ustekinumab which binds the shared p40).
Bivalent binding (assumed valency = 2 as a monoclonal antibody).
Structure identical to the Marcantonio 2022 anti-ligand family;
parameters FIXED from paper Table S4. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Suleiman_2018_risankizumab.html">Risankizumab
(Suleiman 2018)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model of risankizumab (anti-IL-23 mAb) with first-order SC absorption in
subjects with moderate-to-severe plaque psoriasis and moderate-to-severe
Crohn's disease (Suleiman 2018 phase I-II) </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Suleiman_2019_risankizumab.html">Risankizumab
(Suleiman 2019)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model of risankizumab (anti-IL-23 mAb) with first-order SC absorption in
healthy subjects and patients with moderate-to-severe plaque psoriasis
(Suleiman 2019) </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Thakre_2022_risankizumab.html">Risankizumab
(Thakre 2022)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model of risankizumab (anti-IL-23 mAb) with first-order SC absorption in
patients with active psoriatic arthritis (Thakre 2022) </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Cleary_2023_risdiplam.html">Risdiplam
(Cleary 2023)</a> </td>
<td style="text-align:left;"> Population PK model for risdiplam
(Evrysdi) in healthy adults and patients with spinal muscular atrophy
aged 2 months to 61 years (Cleary 2023 Clin Pharmacokinet Table 2, final
PPK model). Three transit absorption compartments feed a linear
two-compartment disposition model. Apparent clearance and
intercompartmental clearance scale allometrically with time-varying body
weight (estimated exponent 0.276, reference 33 kg); apparent volumes use
a separate estimated exponent (0.860). Sigmoidal maturation functions of
time-varying postnatal age act on CL/F (Age50 0.877 y) and Vc/F (Age50
0.322 y), and healthy adults carry a higher CL/F than patients with SMA.
The proportional residual error switches between venous and capillary
blood samples. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Feng_2008_risperidone.html">Risperidone
(Feng 2008)</a> </td>
<td style="text-align:left;"> Adult one-compartment
parent-plus-metabolite population PK model for oral risperidone and its
active metabolite 9-OH-risperidone in 490 subjects pooled across the
CATIE-AD (n = 110, behavioural symptoms of Alzheimer disease, mean age
78.3 years) and CATIE-SZ (n = 380, schizophrenia, mean age 40.6 years)
trials (Feng 2008). First-order absorption with Ka fixed at 1.7 1/h into
a single central compartment with first-order elimination; the fraction
of risperidone metabolized to 9-OH-risperidone (KF) feeds a single
metabolite compartment whose apparent volume of distribution is set
equal to the parent apparent volume per the paper's identifiability
constraint. A mixture model with three CYP2D6 metabolizer subpopulations
(poor PM, intermediate IM, extensive EM) yields subpopulation-specific
apparent oral clearances (CL/F) and metabolite formation fractions (KF);
CL/F in IM (36 L/h) and KF in IM (1) are fixed per Table 3 to stabilize
the mixture estimation. Age is the only retained subject-level
covariate, acting on 9-OH-risperidone apparent clearance (CLM/F) via a
power model with exponent -0.378 referenced at a nominal median age of
45 years. Inter-individual variability is reported separately for CL/F
in PM and EM (no IIV is reported for CL/F in IM or for CLM/F), for Ka
(despite a fixed typical value), and for the shared Vd/F; combined
additive-plus-proportional residual error is reported separately for
risperidone and 9-OH-risperidone plasma concentrations. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Sherwin_2012_risperidone.html">Risperidone
(Sherwin 2012)</a> </td>
<td style="text-align:left;"> One-compartment
parent-plus-metabolite population PK model for oral risperidone and its
active metabolite (+/-)-9-hydroxyrisperidone in 45 children and
adolescents (aged 3-18.3 years, 16.8-110 kg) with neuropsychiatric
disorders treated with maintenance oral risperidone (Sherwin 2012).
First-order absorption (Ka fixed) into a single central compartment with
first-order elimination; the fraction of risperidone metabolized to
(+/-)-9-hydroxyrisperidone (KF) feeds a single metabolite compartment
whose apparent volume of distribution is set equal to the parent
apparent volume per Table 2 footnote (a). A mixture model with three
CYP2D6 metabolizer subpopulations (poor PM, intermediate IM, extensive
EM) yields subpopulation-specific apparent oral clearances and
metabolite formation fractions; KF in IM subjects is fixed at 1 to
stabilize the model per the paper's Mixture Model section. Allometric
scaling (exponent 0.75 for CL/F and CLM/F, exponent 1 for Vd/F,
reference 70 kg) is applied to all three subpopulations' clearance
estimates and to the shared apparent volume. Inter-individual
variability is reported separately for each subpopulation's CL/F (PM,
IM, EM), for the metabolite CLM/F, and for the shared Vd/F; a combined
additive-plus-proportional residual error is reported separately for
risperidone and (+/-)-9-hydroxyrisperidone plasma concentrations.
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Wang_2024_risperidone_lai_switching.html">Risperidone
consta (Wang 2024)</a> </td>
<td style="text-align:left;"> Population PK model for the
risperidone active moiety (risperidone + 9-OH-risperidone) after
intramuscular gluteal injection of RISPERDAL CONSTA, the reference
biweekly long-acting injectable risperidone formulation, in adults with
schizophrenia or schizoaffective disorder (Wang 2024). Same structure as
the companion Rykindo model: one-compartment disposition fed by three
parallel release pathways out of the injection site, namely an immediate
zero-order release of fraction F2 into the central compartment over
duration D2, a middle release of fraction F3 = 1 - F1 - F2 entering a
second depot as a zero-order input of duration D3 after lag ALAG3 and
then absorbed first-order with rate K32, and a main first-order release
of fraction F1 beginning ALAG1 = 27 days after injection. The long
main-release lag reproduces the well-known 3-week delay that obliges 3
weeks of oral risperidone supplementation when Consta is started.
Because the active moiety displays flip-flop kinetics, the elimination
rate constant K was set equal to KA, so the apparent central volume is
derived as V = CL/KA. Apparent clearance is a single value across trials
and sexes; only the main-release absorption rate constant differs
between the two trials. The companion Rykindo model is
modellib('Wang_2024_risperidone_rykindo'). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/PillaReddy_2013_panss_subscales.html">Risperidone
panss subscales (PillaReddy 2013)</a> </td>
<td style="text-align:left;"> Population PK/PD model for
risperidone against the three PANSS subscales (positive, negative,
general) in adults with schizophrenia from Pilla Reddy 2013 Part II. The
driving exposure variable is the active moiety (parent risperidone + the
equipotent metabolite 9-hydroxy-risperidone), following the Part I (PMID
23473810) and Vermeulen 2007 (Eur J Clin Pharmacol 63:1063-1077)
methodology. The PK sub-model is a simplified one-compartment
representation of the active moiety: the published Part I model for
risperidone is a two-compartment parent-plus-metabolite system with a
lag-time and a consecutive zero-then-first-order absorption process, and
clearance stratified by CYP2D6 phenotype (poor / medium / fast
metabolizers). This nlmixr2lib representation uses a single CL/F that
maps a typical oral risperidone dose to the active-moiety steady-state
concentration Css consumed by the PD model: CL_AM/F = 6.3 L/h (derived
from Part II Table 3 effective-dose / effective-Css pair 0.8 mg/day /
5.3 ng/mL at 30% PANSS reduction, CL/F = Dose / (Css * tau)), Vc = 144 L
(parent central volume from Part I Table 2; approximate active-moiety
value), and Ka = 2.37 1/h (parent first- order rate from Part I Table
2). The zero-order absorption duration DUR = 0.47 h and lag time ALAG1 =
0.16 h are omitted in this Part-II simplification (Css is approximately
invariant to short-window absorption details at steady state). The PD
sub-model has three outputs that share the Weibull placebo time-course
form Pplacebo = Pmax * (1 - exp(-(t/TD)^POW)) but each subscale carries
its own placebo Pmax, TD, POW (Part II Table 1) and risperidone's own
Emax / EC50 / KT triplet per subscale (Part II Table 2). The KT for
risperidone PANSS positive and general subscales (0.048 / 0.035 1/day)
was estimated as a common value across all atypical antipsychotic drugs
(Part II Methods, 'A common model ... was developed for PANSS positive
and general scales'); the KT for the negative subscale (0.16 1/day) was
estimated separately per drug because the cross-drug pooled fit did not
converge. The exponential time-to-event dropout sub-model from Part II
Table 4 is documented in population$dropout_model but is not
encoded in this model body.
|
|
Risperidone
rykindo (Wang 2024)
|
Population PK model for the risperidone active moiety (risperidone +
9-OH-risperidone) after intramuscular gluteal injection of RYKINDO
(LY03004), a biweekly long-acting injectable risperidone formulation, in
adults with schizophrenia or schizoaffective disorder (Wang 2024).
One-compartment disposition fed by three parallel release pathways out
of the injection site: (1) an immediate zero-order release of fraction
F2 directly into the central compartment over duration D2, (2) a middle
release of fraction F3 = 1 - F1 - F2 delivered as a zero-order input of
duration D3 into a second depot beginning ALAG3 after injection and then
absorbed first-order with rate K32, and (3) a main first-order release
of fraction F1 from the primary depot beginning ALAG1 after injection
with absorption rate constant KA. Because the active moiety displays
flip-flop kinetics, the elimination rate constant K was set equal to KA,
so the apparent central volume is derived as V = CL/KA. Apparent
clearance carries a sex effect (females about 18 percent lower) and a
between-study effect (0.675-fold in the two US relative-bioavailability
trials relative to the single-ascending-dose trial); KA is higher in the
multiple-dose trial. The companion RISPERDAL CONSTA model from the same
paper is modellib(‘Wang_2024_risperidone_consta’).
|
|
Ritlecitinib
base (Wojciechowski 2023)
|
Base model (iteration 1 of 3) for oral ritlecitinib: two-compartment
disposition with first-order absorption and a direct-response
non-stationary (autoinhibitory) Imax effect of the
peripheral-compartment concentration on both apparent clearance and
bioavailability. Fitted to intensively sampled healthy participants plus
sparsely sampled rheumatoid arthritis and alopecia areata patients (186
individuals, 2174 concentrations). Carries rheumatoid arthritis and
alopecia areata effects on CL/F, high-fat-meal and 800 mg dose effects
on ka, and inflammatory-disease scaling of the IIV and proportional
residual error magnitudes. Allometric weight scaling with fixed
exponents 0.75 on clearances and 1 on volumes referenced to 70 kg.
|
|
Ritlecitinib
final (Wojciechowski 2023)
|
Final model (iteration 3 of 3) for oral ritlecitinib: two-compartment
disposition with first-order absorption and a direct-response
non-stationary (autoinhibitory) Imax effect of the
peripheral-compartment concentration on both apparent clearance and
bioavailability. Parameters were re-estimated with the NONMEM PRIOR
(NWPRI) frequentist-prior subroutine, using the updated model as the
prior, on an evaluation dataset dominated by sparsely sampled phase
IIb/III alopecia areata patients plus healthy participants and severe
renal impairment participants (601 individuals, 2944 concentrations).
Carries an alopecia areata effect on CL/F, a severe renal impairment
effect on F, and inflammatory-disease scaling of the IIV and
proportional residual error magnitudes. Allometric weight scaling with
fixed exponents 0.75 on clearances and 1 on volumes referenced to 70 kg.
This is the iteration that underwrote the approved Litfulo
(ritlecitinib) product label.
|
|
Ritlecitinib
updated (Wojciechowski 2023)
|
Updated model (iteration 2 of 3) for oral ritlecitinib: two-compartment
disposition with first-order absorption and a direct-response
non-stationary (autoinhibitory) Imax effect of the
peripheral-compartment concentration on both apparent clearance and
bioavailability. Base-model parameters were re-estimated on the pooled
healthy participant, rheumatoid arthritis, ulcerative colitis, alopecia
areata, vitiligo and moderate hepatic impairment data (668 individuals,
5187 concentrations) and a stepwise covariate analysis was run. Carries
rheumatoid arthritis, ulcerative colitis, alopecia areata and vitiligo
effects on CL/F; ulcerative colitis and moderate hepatic impairment
effects on F; high-fat-meal, 800 mg dose and capsule effects on ka; an
over-encapsulated-capsule effect on loss from the depot; and
inflammatory-disease scaling of the IIV and proportional residual error
magnitudes. Allometric weight scaling with fixed exponents 0.75 on
clearances and 1 on volumes referenced to 70 kg.
|
|
Ritonavir
(Kappelhoff 2005)
|
One-compartment population PK model with first-order absorption, an
absorption lag time, and first-order elimination for oral ritonavir in
HIV-1-infected adults (186 patients, 1228 plasma concentrations;
Kappelhoff 2005). Concomitant lopinavir is the only retained covariate
and multiplies apparent oral clearance by 2.72-fold (power form: CL/F =
exp(lcl) * 2.72^CONMED_LPV). Inter-individual variability on apparent
CL/F, V/F, and ka, with correlated etas for V and ka (rho = 0.868).
Residual error has a single 15.4% proportional component and a
mixture-model additive component (subpopulation P1, 64.8% of subjects:
0.0600 mg/L; subpopulation P2, 35.2%: 0.199 mg/L), gated by the binary
covariate MIX_LARGE_RUV. Interoccasion variability on apparent
bioavailability (59.1% in the source) is not propagated – see the
validation vignette Assumptions and deviations section.
|
|
Ritonavir
(Mensing 2017)
|
One-compartment population PK model for oral ritonavir (co-dosed with
paritaprevir as a CYP3A4 pharmacokinetic enhancer) in HCV genotype-1
infected adults receiving the 3D regimen (Mensing 2017). First-order
absorption, linear elimination, combined proportional + additive
residual error, IIV on CL/F only. The author’s final model retained
gender, creatinine clearance, and HCV genotype (1a vs 1b) as significant
covariates on CL/F, but the paper does not publish point estimates for
these covariate coefficients (only graphical exposure-ratio forest plots
in Figure 2); the implemented model is the structural typical-value
model with covariate coefficients omitted (documented in
covariatesDataExcluded).
|
|
Rituximab
(Candelaria 2018)
|
Two-compartment population PK model of rituximab (and its biosimilar
RTXM83) with linear distribution and linear elimination from the central
compartment in patients with diffuse large B-cell lymphoma (DLBCL)
treated with rituximab-CHOP or RTXM83-CHOP (Candelaria 2018; pooled-arm
fit, all 5341 concentrations from both treatment arms)
|
|
Rituximab
(Chen 2024)
|
Two-compartment population PK of rituximab coupled to a CD19+
B-lymphocyte turnover PD model with saturable stimulation of B-cell
loss, in pediatric patients with frequent-relapsing or steroid-dependent
nephrotic syndrome
|
|
Rituximab
(Liang 2024)
|
Two-compartment quasi-steady-state target-mediated drug disposition
(TMDD) population PK/PD model for rituximab in adults with primary
membranous nephropathy, with CD20 as the target; outputs are rituximab
concentration and total CD20 (the molar surrogate for CD20+ B cell
count) (Liang 2024)
|
|
Rituximab
(Lioger 2017)
|
Two-compartment population PK model of rituximab in rheumatoid arthritis
patients, parameterised with first-order distribution (k12, k21) and
elimination (k10) rate constants (per Lioger 2017 Methods ‘Structural
pharmacokinetics model design’: rate-constant parameterisation gave
lower AIC, shrinkages, and Vc/elimination correlation than CL/Vc). Final
covariate model: BSA, sex, and rituximab treatment course on V1;
time-varying CD19+ B-cell count and IgG serum concentration on k10
(Lioger 2017 Table 2).
|
|
Rituximab
(Rozman 2017)
|
Two-compartment population PK model of rituximab in adults with diffuse
large B-cell lymphoma (DLBCL) receiving R-CHOP; total CL is the sum of a
time-stationary non-specific (IgG-catabolic) component cl_exp_inf and a
mono-exponentially decaying target-mediated component cl_exp_component *
exp(-cl_exp_kdes * time), with age and body weight on cl_exp_inf, sex on
V1 (central volume), and a post-hoc progression-free-survival event
indicator (PFS_EVENT) on cl_exp_kdes (Rozman 2017).
|
|
Rituximab
acr (Williams 2016)
|
Longitudinal ordered-categorical PD model of American College of
Rheumatology (ACR) response (ACR20 / ACR50 / ACR70) over time for
rituximab (both the proposed biosimilar PF-05280586 and the two
rituximab reference products sourced from the EU and US) in adults with
rheumatoid arthritis on background methotrexate with prior inadequate
response to one or more TNF-antagonist therapies (Williams 2016). The
model is a cumulative-probit latent-variable formulation with three
thresholds (ACR20, ACR50, ACR70 as an ordered categorical score in {0,
1, 2, 3}) and an exponential-onset time course for the population-mean
latent variable. Unlike the companion DAS28cfb model, no rituximab
exposure effect is included (Williams 2016 Results: ‘rituximab exposure
effects could not be supported in the ACR model’). The covariate model
includes seven baseline disease-activity components (TJ68, SJ66, log
CRP+1, PGA_PT, PhGA, PAIN, HAQ-DI) and two treatment-arm indicators
(PF-05280586 vs rituximab-EU, rituximab-US vs rituximab-EU) additive on
the log scale on both the maximum-effect parameter PMAX and the onset
half-life parameter, with rituximab-EU as the reference arm. Outputs
three continuous probabilities pACR20, pACR50, pACR70 = probability of
achieving at least ACR20/50/70 response at the observation time; a
single subject-level additive probit-scale eta captures between-subject
variability.
|
|
Rituximab
das28cfb (Williams 2016)
|
Longitudinal PD model of Disease Activity Score in 28 joints change from
baseline (DAS28cfb) for rituximab (both the proposed biosimilar
PF-05280586 and the two rituximab reference products sourced from the EU
and US) in adults with rheumatoid arthritis on background methotrexate
with prior inadequate response to one or more TNF-antagonist therapies
(Williams 2016). The model is an inhibitory-Emax-on-log-scale
exposure-response for the concentration-driven drug effect superimposed
on an exponential-onset placebo/background time course, with the outer
transformation DAS28cfb = 1 - exp(fnon-C(t) + fC(C)) so that improvement
is a negative change from baseline. The typical maximum
placebo/background effect PMAX and typical maximum drug effect Emax are
log-scale additive parameters with correlated between-subject etas; a
separate additive subject-level eta on the outer scale (etaCS) captures
the within-subject correlation induced by computing change from
baseline. Covariate model includes the individual components of baseline
disease activity (TJ28, SJ28, log CRP+1, patient global assessment) and
treatment-arm indicators on each of the three main structural parameters
(PMAX, kp, Emax) with rituximab-EU as the reference arm. This is a
PD-only extraction: the rituximab plasma concentration Cc is supplied as
a time-varying covariate CP_RITUXIMAB_UGML (the Williams 2016 popPK
model - the source of the individual predicted concentrations Cij
feeding the DAS28cfb model - was a two-compartment structural model
whose parameter values are not reported in the paper or its supplements;
users wanting to drive this PD model from a simulated PK source must
supply their own concentration trajectory).
|
|
Rituximab
pla2r (Liang 2024)
|
Empirical mono-exponential decline of the serum anti-PLA2R autoantibody
titer after rituximab in adults with primary membranous nephropathy;
fitted independently of the CD20+ B cell count, so it is a separate
model from the companion QSS TMDD PK/PD model (Liang 2024)
|
|
Rivaroxaban
(Willmann 2018)
|
Paediatric population PK model for oral rivaroxaban in children aged
0.5-18 years (Willmann 2018, EINSTEIN-Jr phase I). Linear
two-compartment model with first-order absorption from a depot and
first-order elimination from the central compartment; CL and central V
allometrically scaled to body weight (CL exponent 0.323 estimated; V
exponent 1 fixed); ka shifted between the undiluted-oral-suspension
formulation and the tablet / diluted-oral-suspension reference; relative
bioavailability F1 reduced for the 20 mg-equivalent body-weight-adjusted
dose relative to the 10 mg-equivalent reference.
|
|
Rivaroxaban
(Willmann 2021)
|
Pediatric population PK model for rivaroxaban developed on the
integrated EINSTEIN-Jr phase I / I-II / II / III dataset and interim PK
from part A of the UNIVERSE study (524 children, 1988 plasma
concentrations, age birth to <18 years, body weight 2.7-194 kg).
Two-compartment disposition with first-order absorption and first-order
elimination from the central compartment. Body weight enters as
estimated allometric scaling on CL, Q, Vc, and Vp, centred on the 82.48
kg median of the integrated adult popPK analysis (a shared exponent is
used for Vc and Vp). The undiluted ready-to-use oral suspension has a
lower first-order absorption rate constant ka than the other three
formulations (tablet, granules for oral suspension, and diluted
ready-to-use oral suspension), which share a common ka. Relative oral
bioavailability decreases with dose per body weight following an
exponential function carried over from the integrated adult popPK
analysis (anchored to F1 = 1 at 10 mg / 82.48 kg = 0.1213 mg/kg).
Inter-individual variability is on CL and F1 only (no IIV on Ka, Vc, Vp,
or Q); residual error is proportional. Age, eGFR (Schwartz and Rhodin),
serum creatinine, comedications (CYP3A4 inhibitors / inducers, P-gp
inhibitors), and Fontan status were tested and not retained.
|
|
Rivaroxaban
(Willmann 2022)
|
Adapted pediatric population PK model for rivaroxaban in 76 post-Fontan
congenital heart disease patients aged 2-8 years (body weight 9.8-25.3
kg) from the UNIVERSE study. Structural framework is inherited from the
EINSTEIN-Jr popPK model of Willmann 2021 (already extracted as
Willmann_2021_rivaroxaban): 2-compartment disposition with first-order
absorption from a depot, allometric body-weight scaling of CL, Vc, Vp,
and Q centred on the 82.48 kg adult reference weight, with all
structural parameters (ka, Vc, Vp, Q, and the three allometric
exponents) fixed to the Willmann 2021 EINSTEIN-Jr estimates. The
Willmann 2021 dose-dependent relative bioavailability function is
replaced by a bimodal age-binned F1 (post-Fontan patients aged <5
years vs. >=5 years). Apparent CL, the two F1 values, IIV on CL and
F1, and the proportional residual error are re-estimated on the
76-patient UNIVERSE dataset. The refined CL is 6.07 L/h at 82.48 kg
vs. 8.02 L/h in EINSTEIN-Jr (24% lower in post-Fontan patients). This
model was used to bridge doses for thromboprophylaxis in post-Fontan
patients aged 9 years or older or >=30 kg (the target extrapolation
population), leading to the US label of 7.5 mg once daily (30-<50 kg)
and 10 mg once daily (>=50 kg).
|
|
Rivipansel
(Tammara 2017)
|
Three-compartment IV population PK model for rivipansel in adults and
adolescents with sickle cell disease (SCD) and in healthy adult
volunteers (Tammara 2017). Rivipansel is a pan-selectin antagonist given
as a 20-minute IV infusion; renal excretion of unchanged drug is the
primary clearance mechanism. The integrated population PK model pools
109 subjects across three phase I studies (rivipansel studies 101, 102,
103) and one phase II SCD study (NCT01119833, Telen 2015). Clearance is
a power function of creatinine clearance (CRCL, raw Cockcroft-Gault
mL/min reference 150) with an additive 23.4% shift in the phase II SCD
cohort (STUDY_RIV201) attributed to glomerular hyperfiltration. The
central, first peripheral, and second peripheral volumes share a single
estimated body-weight exponent (0.569, reference 70 kg). The additive
and proportional residual error magnitudes differ between the phase I
and phase II cohorts and are selected per observation via STUDY_RIV201.
|
|
Rlyb212
(MocWilleford 2024)
|
Target-mediated drug disposition (TMDD) model of RLYB212, a recombinant
human anti-HPA-1a IgG1 monoclonal antibody, with simultaneous fit of
RLYB212 pharmacokinetics and HPA-1a-positive platelet dynamics in
HPA-1b/b healthy volunteers (Moc Willeford 2024). Two-compartment SC PK
for RLYB212 (central Vc, peripheral Vp, ka, CL) shares its central
volume with the HPA-1a-positive platelet distribution (target central),
which itself has a peripheral compartment (Vp_target) and first-order
natural degradation kdeg. RLYB212 and free receptor form a drug-receptor
complex in the central compartment via second-order kon and first-order
koff (both fixed at internal / literature values). A novel
threshold-gated phagocytic elimination pathway removes coated platelets
(both free receptor and complex) once receptor occupancy exceeds a fixed
threshold thres = 10%. Parameters and structure per Moc Willeford 2024
Table 2 and the supplement’s differential-equation appendix.
|
|
Roblitinib
(Wilbaux 2022)
|
Two-compartment population PK model for oral roblitinib (FGF401), a
selective FGFR4 inhibitor, in adults with hepatocellular carcinoma or
other FGF19-FGFR4-expressing solid tumors (Wilbaux 2022). The paper
describes a delayed zero-order absorption directly into the central
compartment (lag time Tlag before absorption starts, then duration Tk0
of the zero-order input rate) with linear elimination. Categorical
covariate effects on CL/F and V1/F for female sex (SEXF) and Asian race
(RACE_ASIAN) with non-Asian male as the reference; on Tk0 for fed vs
fasted (FED). Continuous power-form covariate effects: body weight on
V1/F (exponent 0.332), BMI on Tk0 (exponent -1.66), and administered
dose on Tk0 (exponent 0.983). The source paper reports these covariates
as identified but not clinically relevant based on simulated exposure
metrics. Diagonal IIV on Tlag, Tk0, CL/F, V1/F, and V2/F (Q/F fixed at 0
IIV per Table 1). Combined additive + proportional residual error.
|
|
Rocatinlimab
(Okada 2025)
|
Two-compartment population PK model with parallel linear and
time-dependent saturable (Michaelis-Menten) clearance and first-order
subcutaneous absorption for rocatinlimab (anti-OX40 mAb) in adults;
covariates body weight, albumin, plaque-psoriasis disease state, and
healthy-volunteer cohort indicator (Okada 2025)
|
|
Roflumilast
(Facius 2018)
|
Integrated population PK model for oral roflumilast and its primary
active metabolite roflumilast N-oxide in adult patients with severe
chronic obstructive pulmonary disease (COPD) (Facius 2018). The
structural model is the joint parent-metabolite model previously
developed by Lahu 2010 on 21 phase I + 2 phase II/III studies: a
two-compartment parent disposition with first-order absorption and a
shared lag time, and a two-compartment N-oxide disposition with
first-order absorption from a separate pre-systemic dose compartment
(relative bioavailability F5) plus complete first-order conversion from
the parent central compartment. All structural disposition parameters
and the F5 / KAm-to-KAp ratio are fixed to the Lahu 2010 base-model
estimates re-applied to OPTIMIZE via a Bayesian feedback MAXEVAL = 0
step; only the phase II-III dichotomous patient effects (on KA, parent
CL, N-oxide CL, and N-oxide central volume), the covariate effects, the
between-subject variability on parent and N-oxide clearance (with a
Box-Cox-shape transformation), and the log-additive residual errors were
estimated on the combined OPTIMIZE and REACT phase III dataset of 1238 +
461 patients. Covariates retained are body weight on all volume terms
and on N-oxide CL, smoking (current vs not-current) on parent and
N-oxide CL, age on parent and N-oxide CL, and sex on N-oxide CL. tPDE4i
(total phosphodiesterase-4 inhibitory activity), the exposure metric
used in the paper’s downstream PK/adverse-event and PK/time-to-event
models, is a per-dosing-interval summary derived from the predicted
average plasma concentrations and is not embedded in the ODE system; see
the vignette for the derivation.
|
|
Roflumilast
(Lahu 2010)
|
Joint parent-metabolite population PK model for oral roflumilast and its
primary active metabolite roflumilast N-oxide in adult healthy
volunteers and patients with moderate-to-severe COPD (Lahu 2010).
Roflumilast is described by a two-compartment model with first-order
absorption and a lag time; the absolute parent bioavailability is not
identifiable and is fixed at F1 = 1. Roflumilast N-oxide is described by
a one-compartment model with zero-order absorption (duration D1) and a
lag time, with relative bioavailability Frel fixed at 1 for the
null-covariate reference (also non-identifiable). Retained covariates on
roflumilast parameters are food on tlag and ka, sex / smoking /
race-Black / race-Hispanic / COPD on CL, and COPD on V1. Retained
covariates on roflumilast N-oxide parameters are food on D1; age / sex /
smoking / COPD on CL; body weight and COPD on Vd; and age / sex /
race-Black / race-Hispanic on Frel. Inter-individual variability is
reported on parent tlag, ka, CL, V1, Q, V2 (with a Q-V2 covariance) and
on N-oxide D1, CL, Vd (with a full 3x3 covariance block); no IIV is
reported on N-oxide tlag or on Frel. Residual error is proportional on
the linear- concentration scale (additive on the log-transformed
observation) for both observed analytes, fitted on the phase I dataset
(the more data-rich layer).
|
|
Rolofylline
(Stroh 2013)
|
Simultaneous three-output population PK model for IV rolofylline
(adenosine A1 receptor antagonist) and both M1-trans and M1-cis active
hydroxyl metabolites in 36 healthy adult male volunteers after single
1-60 mg IV infusions over 1-2 h (Stroh 2013, study KW-3902 IV-EU01).
Parent rolofylline disposition is two-compartment with linear total
clearance CL1 directing the entire parent loss to metabolite formation;
the fraction FM of formed material is converted directly to M1-cis while
(1 - FM) is converted to M1-trans. M1-trans disposition is
two-compartment with distributional clearance CL4 and an additional
unidirectional stereochemical interconversion clearance CL3 from
M1-trans to M1-cis. M1-cis disposition is one-compartment with
first-order clearance CL5. Random effects were not estimable for parent
and M1-trans distributional clearances (CL2, CL4) or for the M1-cis
central volume (V5) and were fixed to zero per the source. No covariates
were retained: the cohort was a single Phase 1 dose-escalation in white
male volunteers and the paper screened no demographic effects.
Structural identifiability of the final model was confirmed via the
DAISY software tool (Bellu et al.).
|
|
Romiplostim
(Petrov 2024)
|
Population PK/PD model for romiplostim in adults with chronic immune
thrombocytopenia (ITP). One-compartment first-order subcutaneous PK plus
an Emax stimulation of platelet precursor production into a
4-transit-compartment Friberg-style chain feeding circulating platelets,
with first-order platelet degradation. PK/PD backbone is the
healthy-volunteer population PK/PD model (Makarenko 2024); ITP-specific
platelet production (kin) and degradation (kdeg) constants and IIV(kdeg)
come from Petrov 2024 supplement Table S1. Default parameters are
non-splenectomized ITP patients with mechanism 1 (increased platelet
degradation, normal precursor production); see vignette for the other 3
subpopulation variants (non-splenectomized mechanism 2; splenectomized
mechanism 1; splenectomized mechanism 2).
|
|
Romiplostim
(Wang 2010)
|
Population PK/PD model for romiplostim in healthy subjects (Wang 2010
AAPS J). Pharmacodynamics-mediated drug disposition (PDMDD, a TMDD
subtype) two-compartment quasi-equilibrium PK with first-order SC
absorption, parallel linear (kel) and target-mediated (kint)
elimination, coupled to a Krzyzanski-style cytokinetic precursor +
platelet lifespan PD model with NP=10 megakaryocyte and NPLT=10 platelet
age-compartments. Romiplostim free serum concentration stimulates
platelet precursor production via a Hill function (Smax, SC50). The
total c-Mpl receptor concentration is taken proportional to the
circulating platelet count (Rtot = xi * PLT). Wang 2010 fit the model to
MEAN PK and platelet-count data from 32 healthy subjects after single IV
(0.3, 1, 10 ug/kg) or SC (0.1, 0.3, 1, 2 ug/kg) doses; no IIV was
estimated (the population approach failed for this complex model).
|
|
Romosozumab
(Stein 2018)
|
Two-compartment QSS TMDD typical-value fit for romosozumab
(anti-sclerostin mAb) used to illustrate the critical concentration
(Ccrit) for nonlinear PK (Stein and Peletier 2018 Table 1)
|
|
Ropivacaine
(Ollier 2015)
|
Semi-mechanistic population PK model for free and total ropivacaine
after transversus abdominis plane (TAP) nerve block in adult patients
undergoing liver resection surgery (Ollier 2015). One-compartment
first-order absorption disposition for free ropivacaine (Rfree) with
apparent clearance Cl/F and apparent volume V/F. Free ropivacaine binds
reversibly to a latent unbound-binding-site pool (target) that
approximates alpha-1 acid glycoprotein (AAG) via 1:1 mass-action
kinetics: binding rate kbind (fixed at 100 uM^-1 h^-1 per the paper’s
reported insensitivity of kb over 10^2 - 10^15 uM^-1 h^-1) and
dissociation constant Kd (fixed at 0.557 uM, prior-pinned in the paper
and reported without RSE). The bound species (complex) plus free species
give total ropivacaine. Binding-site production rate kin switches on at
12 h post-incision (the 2nd TAP bolus timepoint, representing the
postoperative-inflammation-driven onset of AAG acute-phase response).
Two retained covariates: allometric power on Vc for body weight
(reference 70 kg, exponent 1.28); multiplicative exponential effect on
Cl for major hepatic resection LIVER_RESECT_MAJOR = 1 (>=3 segments)
vs 0 (2 segments), reducing free ropivacaine clearance from 1310 L/h to
620 L/h (53% drop). The paper’s third retained covariate, a per-subject
postoperative fibrinogen-slope effect on kin (beta = 0.422), was dropped
in this packaged model because the population mean fibrinogen slope used
to centre the covariate was not reported in any source on disk; see
vignette Assumptions and deviations. Ropivacaine is dosed as 5 TAP
boluses of 3 mg/kg (10.9 umol/kg) at 0, 12, 24, 36, 48 h post-incision
by protocol. Concentrations throughout are in molar units (uM) matching
the paper.
|
|
Rosuvastatin
(Barnett 2018)
|
Two-compartment population PK model with first-order oral absorption for
a single 5 mg dose of rosuvastatin in healthy adult males (Barnett
2018), refit from the Tzeng 2008 structural form with simultaneous
plasma + urine fitting. The model includes separable biliary (CLb,RSV)
and renal (CLr,RSV) clearance components from the central compartment,
competitive rifampicin OATP1B inhibition of the biliary clearance via
KiRSV driven by the instantaneous plasma rifampicin concentration, and a
binary RIF-coadministration covariate that captures paper-reported
reductions of V1, V2, and Q during the rifampicin phase (Barnett 2018
Table 1: V1 430 -> 2.98 L, V2 865 -> 128 L, Q 45.3 -> 5.03 L/h
on RIF). Companion to modellib(‘Barnett_2018_coproporphyrin_I’); both
share the rifampicin perpetrator parameterisation in
modellib(‘Barnett_2018_rifampicin’).
|
|
Rosuvastatin
(Kakara 2014)
|
PD-only indirect-response Imax model for LDL-cholesterol lowering by
rosuvastatin (Kakara 2014). One LDL-C compartment with zero-order
synthesis Kin inhibited by Imax * DOSE / (ID50 + DOSE), where DOSE is
the current daily rosuvastatin dose (mg/day) supplied as a time-varying
covariate column. An additive 0.109 contribution to the inhibition
fraction is applied when ezetimibe is coadministered (CONMED_EZE = 1;
estimated on the n=12 rosuvastatin + ezetimibe subgroup in this paper).
The LDL-C synthesis-elimination loop is set up at steady state by
enforcing Kin = Baseline * Kout (Kout derived inside model() as Kin /
Baseline). Baseline LDL-C is age-scaled as 152 * (AGE/62)^(-0.240). Imax
(0.567), Kin (32.8 mg/dL/day), Baseline (152 mg/dL), the age power
exponent (-0.240), the ezetimibe INH contribution (0.109), and the IIV
magnitudes are shared with Kakara_2014_atorvastatin and
Kakara_2014_pitavastatin (one joint NONMEM 7.2 FOCE-INTER fit across 378
patients). Rosuvastatin ID50 = 1.04 mg per Kakara 2014 Table 2.
|
|
Rosuvastatin
(Macpherson 2015)
|
Two-compartment population PK model with first-order oral absorption for
rosuvastatin in pediatric patients (aged 6 to <18 years) with
heterozygous familial hypercholesterolemia (Macpherson 2015 Eur J Clin
Pharmacol). Apparent clearance scales with body weight (estimated power
exponent 0.352, reference 42 kg) and is 1.41-fold higher in males than
females. Residual error is proportional and switches between intensive
and sparse PK sampling phases.
|
|
Rosuvastatin
mbma (Yang 2010)
|
MBMA. Literature-based meta-analysis simple Emax dose-response model for
percentage reduction in low-density lipoprotein cholesterol (LDL-C) from
baseline in adult hypercholesterolemia patients receiving rosuvastatin.
Operates at the study-arm level over 14 dose-ranging trials (46
study-arm-mean effect samples; 9 Western trials and 5 Asian trials,
total N substantially larger than 46 because each arm pools many
patients). Output Cc is the study-arm mean percent LDL-C reduction from
baseline (unsigned: Cc = 50 means a 50 percent reduction). The placebo
intercept E0 (-0.802 percent, a small expected LDL-C increase under
placebo) and the Hill / sigmoidicity exponent (1) are fixed at the
values used by the source paper – E0 from prior literature [Mandema
2005, ref 15] and gamma after the sigmoidal Emax fit produced unstable
estimates. Race (Asian vs Western reference) is the only retained
covariate and acts on ED50: ED50_Asian = ED50_Western * 0.564
(i.e. roughly twofold-lower ED50 in Asians). Between-trial variability
is encoded as a single study-arm-level eta on the predicted output (SD
3.0 percent); residual error is additive (SD 3.1 percent). Baseline
LDL-C was screened but not retained. Suitable simulation scope is
study-arm-mean percent LDL-C reduction, NOT individual-subject LDL-C
trajectories. The model also predicts only the steady-state effect
(paper restricted to arms with at least 4 weeks of treatment).
|
|
Rucaparib
(Wang 2015)
|
Three-compartment IV population PK model coupled to a direct-effect Emax
PK/PD model for inhibition of poly(ADP-ribose) polymerase (PARP-1)
activity in peripheral blood lymphocytes (PBL) by rucaparib (AG-014699 /
PF-01367338) in adult cancer patients (Wang 2015 Phase 1 study
A4991002), with a power covariate effect of baseline PBL PARP activity
on the residual maximum-inhibition parameter Emin.
|
|
Rutin
rat (Chen 2024)
|
Preclinical (rat). Two-compartment intravenous pharmacokinetic model for
rutin (RT), one of eight constituents of guhong injection (GHI)
quantified in plasma, in male Sprague-Dawley rats subjected to 30 min
left-anterior-descending ligation followed by 1 h reperfusion
(myocardial ischemia/reperfusion, MI/R) (Chen 2024). GHI was given as a
single tail-vein injection of 2.5, 5 or 10 mL/kg; the rutin dose is the
GHI volume dose times its content in GHI (11.7 ug/mL), i.e. 29.25 ug/kg,
58.5 ug/kg, 117 ug/kg. Disposition was fitted separately in each dose
group with Drug and Statistics (DAS) v3.2.6, so V1, V2, CL1 and Q are
selected from the covariate DOSE_GHI_MLKG rather than through a
dose-covariate function the authors did not fit. Direct-effect
sigmoid-Emax models link the rutin plasma concentration to the
GHI-minus-model-group difference in creatine kinase-MB (CK-MB) and
cardiac troponin I (cTn I) (E = Emax * C^gamma / (ED50^gamma + C^gamma);
Tables 12, 14). Chen 2024 fitted a PK/PD model only for the
analyte/biomarker/dose combinations whose PLSR coefficient was negative,
so the effect of an unfitted combination is returned as zero rather than
extrapolated. No between-subject variability or residual error was
reported; every parameter is fixed at the published mean and the
residual SDs are fixed at zero.
|
|
Rwj416457
(Schmidt 2009)
|
In vitro (Staphylococcus aureus MRSA strain OC2878). Mechanism-based PD
model of bacterial-killing time-kill curves for RWJ-416457, an
investigational oxazolidinone (Schmidt 2009). Susceptibility-based
two-subpopulation structure: an active self-replicating susceptible pool
with logistic carrying-capacity limit and a dormant persister pool that
is insusceptible to killing; first-order S->P conversion (P->S
held fixed at 0), natural-death loss from both pools, exponential
turn-on of growth and of drug-induced killing, and Emax killing of the
susceptible subpopulation by the antibiotic. Drug concentration in the
Mueller-Hinton broth (MHB) declines first-order at the published
10%-over-24-h degradation rate; for dynamic syringe-replacement
experiments the user adds the dilution-equivalent rate to kdeg via
rxSolve(…, params = c(kdeg = )). The same joint fit is shared
with Schmidt_2009_linezolid (only EC50 and kdeg differ).
|
|
S
ketamine (Flint 2017)
|
Joint two-compartment S-ketamine + one-compartment S-norketamine
population PK model for continuous intravenous S-ketamine infusion
during prolonged sedation in pediatric intensive care patients aged
0.02-12.5 years (Flint 2017). The parent S-ketamine has two-compartment
disposition (CL = 112 L/h, V1 = 7.73 L, Q = 196 L/h, V2 = 545 L at 70
kg) and feeds the active metabolite S-norketamine, modelled as one
apparent central compartment with Clsnk/Fm = 53.2 L/h and Vsnk/Fm = 1 L
(fixed; Fm is not identifiable). Body weight is allometrically scaled
with fixed exponents 0.75 for clearances and 1.0 for volumes referenced
to 70 kg; time after the first S-ketamine dose acts as a linear positive
multiplier on Clsnk (0.870 percent per hour), the only retained
covariate at backward elimination.
|
|
S
methadone (Aruldhas 2021)
|
Population pharmacokinetic model for S-methadone and its S-EDDP
metabolite in post-operative paediatric surgical patients (Aruldhas
2021; 61 children aged 11-17 years given 0.1 mg/kg IV racemic methadone
intra-operatively followed by 0.1 mg/kg oral racemic methadone every 12
h as either a tablet or an oral suspension). S-methadone disposition is
a two-compartment model with first-order absorption (separate tablet and
suspension Ka values), an estimated absolute bioavailability F common to
both oral formulations, and a one-compartment S-EDDP metabolite whose
central volume is set equal to the S-methadone central volume (scaling
factor VF fixed to 1 due to metabolite unidentifiability). Total
S-methadone clearance CL scales allometrically with body weight (fixed
exponent 0.75, reference 70 kg). The fractional S-methadone clearance to
S-EDDP (CLF) is a linear function of the CYP2B6 activity score and the
number of active alleles of the intronic CYP3A4 SNP rs2246709 (Table 2
final model chosen in preference to the alternative rs11882424 model
because rs2246709 is more commonly genotyped in clinical laboratories).
The S-methadone central volume V2 is a linear function of the plasma
alpha-1 acid glycoprotein (AAG) concentration and the number of active
alleles of the ORM1 SNP rs17650. Between-subject variability is
estimated on CL, V2, peripheral volume, CLF, and S-EDDP clearance;
residual error is proportional for both S-methadone and S-EDDP.
|
|
S33138
(Bertrand 2011)
|
Joint parent-metabolite population PK model for the investigational
antipsychotic S33138 (parent) and its active metabolite S35424 in adults
with schizophrenia (Bertrand 2011). The final selected structural model
is a two-compartment back-transformation form with a presystemic dose
apportionment Fp into the parent depot vs (1 - Fp) into the metabolite
depot, a shared first-order absorption rate Ka, and four linear
elimination / interconversion clearances: parent elimination via other
pathways (CLpo), parent-to-metabolite formation (CLpm), metabolite
elimination via other pathways (CLmo), and metabolite
back-transformation to parent (CLmp). The two volumes (parent Vp and
metabolite Vm) are set equal to a single volume V for identifiability
per the source paper. CYP2D6 poor metabolizers carry a 34% decrease in
CLmo (the genetic covariate retained in the final model). Linear
dose-level effects on the bioavailability f and the parent-fraction Fp
are encoded with a 10 mg reference dose. Parameter values are from Table
IV ‘With the genetic covariate’ column (SAEM in MONOLIX, closed-form
coding, N = 99 patients with available CYP2D6 genotyping).
|
|
Sacituzumab
(Sathe 2024)
|
Coupled three-analyte population PK model for sacituzumab govitecan (SG,
the ADC; output Cc), free SN-38 (released payload; output Cc_sn38), and
total antibody (tAB; output Cc_tab) in adults with metastatic
triple-negative breast cancer and other solid tumors (Sathe 2024). All
three analytes are described by two-compartment models with body-weight
allometric scaling. SG carries IIV on CL and a baseline-albumin power
covariate on CL. Free SN-38 is generated from SG by a first-order
release rate KREL with apparent volumes fixed to literature values
(Klein 2002). tAB has time-dependent CL (asymptotic onset, max ~17%
reduction at t1/2 ~48 days), correlated IIV on CL and V1, and covariates
of baseline albumin (CL), tumor type (CL), and sex (V1). Simulation
requires dosing two compartments simultaneously (central and
central_tab) for each SG infusion event.
|
|
Sacituzumab
(Sathe 2025)
|
Updated coupled three-analyte population PK model for sacituzumab
govitecan (SG, the ADC; output Cc), free SN-38 (released payload; output
Cc_sn38), and total antibody (tAB; output Cc_tab) after pooling data
from TROPiCS-02 (HR+/HER2- mBC) with IMMU-132-01 and ASCENT (mTNBC + mUC
+ HR+/HER2- mBC + other solid tumors) (Sathe 2025). Structure is
identical to Sathe 2024 (see Sathe_2024_sacituzumab): three
two-compartment models with body-weight allometric scaling; SG has IIV
on CL and a baseline-albumin power covariate on CL; free SN-38 is
generated from SG central by a first-order release rate KREL with
apparent V1 and V2 fixed to literature values; tAB has time-dependent CL
(asymptotic onset), correlated IIV on CL and V1, and covariates of
baseline albumin (CL), tumor type (CL), and sex (V1). Parameter values
are the pooled 3-study updated estimates from Sathe 2025 Tables 2, 3,
and 4. Simulation requires dosing two compartments simultaneously
(central and central_tab) for each SG infusion event.
|
|
SAL003
(Peng 2024)
|
Two-compartment population PK model for SAL003, a novel anti-PCSK9 IgG4
monoclonal antibody, with first-order SC absorption (with lag time),
saturable Michaelis-Menten elimination from the central compartment, and
a body-weight effect on central volume, in Chinese healthy volunteers
and patients with hyperlipidemia (Peng 2024)
|
|
Salbutamol
(Heuberger 2018)
|
Semi-physiological PK simulation model for inhaled and oral salbutamol
with its sulphate metabolite (S-SAL) in adult elite athletes. Eight
compartments (gut, two-compartment parent disposition, parent plasma
metabolite arm, cumulative parent urine, cumulative S-SAL urine,
cumulative urine volume) with allometric scaling on disposition and
physiological scaling on the cardiac-output-driven urine production
rate, synthesised from literature (Auclair 2000 dog model, Morgan 1986
renal CL, Holt 1968 cardiac output, Moerkeberg 2009 haematocrit) and
calibrated to Haase 2009 inhaled-salbutamol data (Heuberger 2018).
|
|
Salbutamol
(Marques 2024)
|
One-compartment population PK model for inhaled salbutamol (600 ug
single dose, unit-dose dry-powder inhaler) in healthy adults, with
first-order absorption, no lag time, and linear elimination. Encodes the
EXTERNAL-VALIDATION fit to real clinical data (GSK study NCT01984086, n
= 30; Marques 2024 Table 4) – NOT the paper’s headline virtual-patient
model (Table 3), whose central volume of 0.02e-9 L is not solvable at
any ODE tolerance and overshoots the paper’s own observed Cmax by four
orders of magnitude. The authors declare a two-compartment structure,
but their clinical-data fit returned Q = 1.30e-7 L/h and V2 = 0 exactly,
both with relative standard errors above 1e6 percent (the authors’ own
footnote calls this overparametrization); the peripheral compartment
therefore carries no flux and k21 = Q/V2 is undefined, so the model is
encoded honestly as one compartment. No covariate effects are encoded:
the paper reports which covariates were significant but publishes no
coefficients, functional forms, or centering values anywhere in the
article or its supplement (see covariatesDataExcluded and the vignette
Errata).
|
|
Sapropterin
(Feillet 2008)
|
Two-compartment population PK model with first-order oral absorption, an
absorption lag, linear elimination, and an additive endogenous BH4
baseline for sapropterin dihydrochloride in adolescent and adult
patients with BH4-responsive phenylketonuria (Feillet 2008).
|
|
Sapropterin
(Muntau 2017)
|
One-compartment population PK model with first-order oral absorption, an
absorption lag, linear elimination, and an additive endogenous BH4
baseline for sapropterin dihydrochloride in pediatric patients <4
years with BH4-responsive phenylketonuria or mild hyperphenylalaninemia
(Muntau 2017 SPARK trial).
|
|
Sapropterin
(Qi 2014)
|
One-compartment population PK model with first-order oral absorption, an
absorption lag, linear elimination, and an additive endogenous BH4
baseline for sapropterin dihydrochloride in pediatric and adult patients
with phenylketonuria (Qi 2014).
|
|
Saquinavir
(vonHentig 2009)
|
One-compartment first-order-absorption population PK model for oral
ritonavir-boosted saquinavir (1000/100 mg BID) in 136 HIV-1-infected
adults including 13 pregnant women. Apparent oral clearance CL/F is
modulated by two retained covariates: a binary
atazanavir-coadministration indicator (CONMED_ATAZANAVIR; 49 of 136
patients on ATV 300 mg QD) as a power-of-binary multiplier
0.703^CONMED_ATAZANAVIR (30% CL reduction when atazanavir is
coadministered), and the per-subject ritonavir 12 h AUC
(CONMED_RTV_AUC_12h, cohort median 6.70355 mg*h/L) as a normalised power
form (CONMED_RTV_AUC_12h / 6.70355)^(-0.403). Saquinavir formulation
(Invirase hard gel vs Fortovase soft gel) was tested and not retained.
Inter-individual variability is estimated on CL/F (53.1% CV) and V/F
(54.8% CV); IIV on ka was rejected during model building. Residual error
was reported as an additive-error model but the additive SD value is not
reported anywhere in the paper – addSd is encoded as fixed(0) and the
vignette Errata documents the omission (von Hentig & Loetsch 2009).
|
|
Sarilumab
(Xu 2019)
|
Two-compartment population PK model for sarilumab in adults with
rheumatoid arthritis (Xu 2019), with first-order SC absorption and
parallel linear plus Michaelis-Menten (target-mediated) elimination from
the central compartment.
|
|
Sarilumab
anc (Ma 2020)
|
Indirect-response PopPK/PD model for absolute neutrophil count (ANC)
following subcutaneous sarilumab in adults with rheumatoid arthritis (Ma
2020). Sarilumab concentrations drive stimulation of ANC elimination
(margination); PK backbone is Xu 2019.
|
|
Sarilumab
das28crp (Ma 2020)
|
Indirect-response PK/PD model of sarilumab on the 28-joint disease
activity score by C-reactive protein (DAS28-CRP) in adults with
rheumatoid arthritis (Ma 2020). Sarilumab inhibits the DAS28-CRP
production rate (kin) via a sigmoid emax function that includes a
background DMARD placebo component (PLB). The PK driver is the
two-compartment, parallel linear + Michaelis-Menten model of Xu 2019
evaluated at its typical covariate-reference values (adult female, 71
kg, ADA-negative, commercial drug product, ALBR = 0.78, CrCl = 100
mL/min/1.73 m^2, baseline CRP = 14.2 mg/L).
|
|
Saxagliptin
rat (Wang 2024)
|
Preclinical (rat). Two-compartment PK model with first-order absorption
for orally (intragastric) administered saxagliptin (SAX), directly
linked to a sigmoidal Emax model WITHOUT a baseline term for the
parent-drug contribution to plasma dipeptidyl peptidase-4 (DPP-4)
inhibition, in streptozotocin plus high-fat-diet induced type 2 diabetic
male Sprague-Dawley rats. Wang 2024 Eq 1-3 write the disposition as
dA1/dt = FKaAa + (CL2/V2)A2 - (CL2/V)A1 - (CL/V)A1
and dA2/dt = (CL2/V)A1 - (CL2/V2)A2, i.e. CL2 is a conventional
inter-compartmental clearance (k12 = CL2/V, k21 = CL2/V2) and is encoded
here as lq. The PD model is Wang 2024 Eq 8, E = Emax C^Gam /
(EC50^Gam + C^Gam), applied directly to the plasma SAX concentration
with no effect compartment; the paper states explicitly that no
hysteresis was observed. IMPORTANT: the fitted DPP-4 inhibition ratio
for the parent drug is a DERIVED observation, not a directly measured
one. Wang 2024 substituted the measured 5-OH SAX concentrations obtained
after intragastric SAX into the separately fitted metabolite PK/PD model
(see modellib(‘Wang_2024_5hydroxysaxagliptin_rat’)) and subtracted the
resulting metabolite inhibition from the measured total inhibition:
In_SAX = In_(SAX+5OHSAX) - In_5OHSAX. The resulting EC50 ratio
EC50_5OHSAX = 0.46 * EC50_SAX is the paper’s central finding, confirming
in vivo the roughly two-fold weaker potency of the metabolite reported
in vitro. All volumes and clearances are body-weight normalised (mL/kg,
mL/h/kg), so ODE state amounts are in ng per kg body weight and the 10
mg/kg dose is supplied as amt = 1e7. Parameters are the arithmetic means
of three individually fitted rats (WinNonlin 8.1, naive individual
fitting); no population model and therefore no OMEGA was estimated, so
the model carries no eta terms and is intended for typical-value
simulation. The PK residual error was described as additive but its
magnitude was never reported, so addSd is FIXED at 0; the PD residual SD
(stdev0) IS reported and is used.
|
|
Scopolamine
(AlvarezJimenez 2016)
|
Two-compartment linear intravenous PK model for scopolamine hydrobromide
in healthy adults (18-78 years), coupled with 13 indirect-response EMAX
PD models describing neurophysiological, psychomotor, and cognitive
tests: 0-back reaction time, saccadic inaccuracy, saccadic peak
velocity, adaptive tracker performance, EEG alpha/delta/theta band power
in Fz-Cz and Pz-Oz leads, and N-back 0/1/2 correct-answer percentages
(log-odds). Age and body weight modify clearance; body weight modifies
peripheral volume; age modifies kIN for 0-back RT and delta/theta EEG
baselines and EC50 for saccadic peak velocity.
|
|
Scopolamine
(LiemMoolenaar 2011)
|
Two-compartment population PK model for IV scopolamine in healthy adults
(Liem-Moolenaar 2011, Table 2) with ten parallel effect-compartment
linear-concentration-effect PK/PD models for central-nervous-system
endpoints (Table 3): heart rate, saccadic peak velocity, adaptive
tracking, VAS external perception, body sway, VAS alertness, VAS
internal perception, smooth pursuit, VAS feeling high, and finger
tapping (with an additive time-trend on finger tapping). PK was fit to
90 healthy male volunteers given a single 0.5 mg scopolamine i.v.
infusion over 15 minutes; the ten PD endpoints were fit independently as
effect-compartment linear-slope models on the empirical-Bayes individual
PK profiles. PD parameter sets are grouped in Table 3 by equilibration
half-life (heart rate <0.5 h; saccadic peak velocity and adaptive
tracking 1-1.5 h; VAS external, body sway, VAS alertness, VAS internal,
smooth pursuit 2.5-3.5 h; VAS feeling high and finger tapping >8 h).
|
|
Selexipag
(Krause 2017)
|
Joint two-compartment parent + two-compartment metabolite population PK
model for oral selexipag and its active metabolite ACT-333679 in adults
with pulmonary arterial hypertension (Krause 2017, GRIPHON study).
First-order absorption with a fixed 0.668 h absorption lag delivers
selexipag into a two-compartment disposition with linear total clearance
CL/F (apparent total clearance, of which the rate constant kmet
describes the fraction converted to ACT-333679); the metabolite has its
own two-compartment disposition with first-order elimination via km.
Body weight (allometric on V_p/F and CL/F; on V_m/F), total bilirubin
(power on CL/F), sex (multiplicative on km), and a four-level
PAH-comedication categorical (naive / ERA only / PDE5 inhibitor only /
ERA + PDE5 combined; multiplicative on km) were retained as
statistically significant covariates.
|
|
Selumetinib
(Patel 2017)
|
Sequential two-compartment population PK model for oral selumetinib
(AZD6244, ARRY-142886) and its active metabolite N-desmethyl-selumetinib
in adults with advanced solid tumors pooled with children with recurrent
low-grade glioma (Patel 2017). Selumetinib disposition uses sequential
zero-order (release into the gut compartment over duration D1 with lag
ALAG1) and first-order (rate Ka) absorption with bioavailability
anchored at 1 under fasted conditions and reduced by an additive
food-effect coefficient under fed conditions; D1 and ALAG1 carry
additive food-effect coefficients. Body surface area (power on CL/F and
Vc/F), age (power on Vc/F), and alanine aminotransferase (negative power
on CL/F) modify selumetinib parameters; BSA (negative power) modifies
the fraction metabolized to N-desmethyl-selumetinib. The metabolite is
two-compartment with its central volume fixed equal to the parent
central volume to resolve identifiability; metabolite clearance and
intercompartmental clearance are apparent values.
|
|
Semaglutide
(CarlssonPetri 2018)
|
One-compartment population PK model for once-weekly subcutaneous
semaglutide (GLP-1 receptor agonist) in adults with type 2 diabetes,
pooled across five SUSTAIN phase III trials (Carlsson Petri 2018).
|
|
Semaglutide
(Overgaard 2019)
|
Two-compartment population PK model for subcutaneous semaglutide (GLP-1
receptor agonist) with first-order absorption and first-order
elimination, pooled across nine clinical pharmacology trials in healthy
volunteers and adults with type 2 diabetes (Overgaard 2019).
|
|
Semimechanistic
antibiotic pd (Nielsen 2007)
|
In vitro (Streptococcus pyogenes M12 NCTC P1800). Semimechanistic
time-kill pharmacokinetic/pharmacodynamic model of five antibiotics
(benzylpenicillin, cefuroxime, erythromycin, moxifloxacin, vancomycin)
against S. pyogenes. The bacterial system has two states: a growing
drug-susceptible population (bact_susceptible) and a resting
drug-insusceptible population (bact_resting) that captures phenotypic
persister-cell switching. Bacteria grow in the susceptible state at
first-order rate kgrowth, die in both states at first-order rate kdeath,
and transfer from susceptible to resting at rate kSR = (kgrowth -
kdeath) * (bact_susceptible + bact_resting) / Bmax so the total
population reaches Bmax at stationary phase (reverse transfer kRS is
fixed to 0). Each drug is dosed into its own PK compartment (pen, cxm,
ery, mxf, van; the compartment state IS the bath concentration in mg/L
per the in-vitro convention). Drug decays first-order via degradation
(kdeg fixed from stability experiments; nonzero only for
benzylpenicillin and cefuroxime). A biophase (effect) compartment
(pen_e, cxm_e, ery_e, mxf_e, van_e) equilibrates with the PK compartment
at first-order rate ke and drives the killing effect through a sigmoidal
Emax function DRUG = Emax * Ce^gamma / (Ce^gamma + EC50^gamma). DRUG
adds to the natural death rate on susceptible bacteria only (paper
equation 6). Multi-drug DRUG contributions sum; in monotherapy (as
fitted) only one drug is active. The starting inoculum is treated as
mix1 (all bacteria in the growing state) per the paper’s mixture-model
dominant mode; parameters fmix1 (0.747) and fpers (0.0529) are retained
as fixed documentation for the mix2 alternative starting condition.
|
|
Sepantronium
(Aoyama 2012)
|
One-compartment IV population PK model for sepantronium bromide (YM155),
a small-molecule survivin suppressant administered as a 7-day continuous
IV infusion every 21 days, with power-form covariate effects of
creatinine clearance and alanine aminotransferase and proportional
cancer-type effects (hormone-refractory prostate cancer and melanoma vs
non-small cell lung cancer) on clearance, in adults with NSCLC, HRPC, or
unresectable stage III/IV melanoma (Aoyama 2012)
|
|
Sertraline
(Cooper 2015)
|
One-compartment first-order absorption population PK model for
sertraline in overdose (Cooper 2015). Apparent clearance is increased
1.92-fold in subjects who received single-dose activated charcoal; the
model holds relative bioavailability F at 1 and a shifted lag time at 1
h, with between-subject variability on F, ts_lag, ka, Vc, and CL
absorbing the overdose-specific dose-amount and dose-time uncertainty.
|
|
Sertraline
(Zhang 2024)
|
One-compartment first-order absorption population PK model for
sertraline in Chinese psychiatric inpatients (Zhang 2024). Apparent oral
clearance decreases linearly with age around the 22-year cohort median
(CL/F = 76.1 * [1 - 0.0068 * (AGE - 22)] L/h); the absorption rate
constant is held at 0.098 1/h taken from Li 2013 because the
therapeutic-drug-monitoring dataset contained trough samples only and
the absorption phase was not identifiable.
|
|
Setrobuvir
(Canini 2018)
|
Integrated PK / viral-kinetic (VK) model for setrobuvir, a
non-nucleoside HCV NS5B polymerase inhibitor, in adults chronically
infected with HCV genotype 1a or 1b (Canini 2018). PK is a
two-compartment model with first-order absorption and an absorption lag
time, parameterised as rate constants (ka, ke, k12, k21) with central
volume Vc (Table 3, source rates in /h). PD is a sigmoid Emax inhibition
of virion production by central-compartment concentration, with
genotype-specific EC50 and Hill coefficient. VK is the standard
Neumann-style HCV model reduced to two ODE states (productively infected
cells and free virus) under the short-treatment assumption that
uninfected target cells remain at their pretreatment steady state; the
reduction is dI/dt = dcV - dI and dV/dt = (1 - e(t))I
- cV (equivalent to the paper’s target-fixed form with production
rate p normalised to 1, so I represents cV0 at baseline and its
value is a virion-production-rate surrogate rather than an absolute
infected-cell count). Genotype (HCV_GT1B binary) switches EC50, Hill,
and viral clearance rate c between the GT1a and GT1b typical values and
their independent IIVs. Data source: 77 subjects across 4 studies (three
healthy-volunteer PK studies A/B/C and one Phase 1 HCV-infected patient
PK+VK study D; treated patients received 200, 400, or 800 mg BID for 3
days). Suitable for simulating BID or ascending-dose setrobuvir regimens
and the resulting biphasic HCV RNA decline over 3 to 14 days by
genotype, and for reproducing the paper’s Figure 3 14-day projections.
NOT suitable beyond the on-treatment window studied (no
drug-resistant-variant emergence submodel, no long-term target-cell
repopulation).
|
|
Sevoflurane
(Shin 2014)
|
Pharmacodynamic sigmoid Emax model for the probability of recovery of
consciousness (ROC) vs end-tidal sevoflurane concentration (vol %)
during emergence from general anesthesia in pediatric dental-surgery
patients (Shin 2014). Mentality (intact vs severely mentally disabled,
MENT_DISABLED) stratifies both the concentration at 50% probability of
ROC (C50) and the Hill coefficient. NONMEM Bernoulli likelihood in the
source paper; this implementation exposes the typical-value probability
with a placeholder additive residual error (see vignette Assumptions and
deviations).
|
|
Sglt
qsp (Lu 2014)
|
QSP. Mechanistic systems pharmacology model of renal glucose
reabsorption by SGLT1 and SGLT2 along the proximal tubules in humans,
with optional competitive inhibition by an SGLT2 inhibitor (calibrated
to dapagliflozin; evaluated against canagliflozin). The proximal
convoluted tubules (PCT) are divided into six sub-segments (PCT1-6,
SGLT2-mediated reabsorption) and the proximal straight tubules into
three (PST1-3, SGLT1-mediated). Filtrate drains into a urinary bladder.
Plasma glucose (GLU, mmol/L) and plasma inhibitor (CINH, nmol/L) enter
as time-varying regressors through glomerular filtration. Calibrated by
hand-tuning in Berkeley Madonna v8.3.18 against the DeFronzo et
al. (2013) urinary glucose excretion data; evaluated against Polidori et
al. (2013), Mogensen (1971), and Wolf et al. (2009). 23 ODE states; no
fitted IIV or residual error (typical-individual mechanism model fit to
mean per-step data).
|
|
SHetA2
dog (Sharma 2018)
|
Preclinical (beagle dog). Two-compartment PK model with a 7-compartment
gastrointestinal (GI) transit absorption process for SHetA2 (a flexible
heteroarotinoid anti-cancer / chemoprevention drug) in beagle dogs after
intravenous (5 mg/kg) and oral (100, 400, 1500 mg/kg) administration.
Drug transits through 7 serial GI segments (stomach G1 = depot, then
transit1..transit6 = G2..G7) at a common transit rate kAT; absorption
occurs only from G2 (transit1, rate kA) and G7 (transit6, rate kA2).
Disposition (CL, V1, V2, CLD) is reported as absolute total values for a
typical 6.4-11.2 kg dog, fit by naive-pooled simultaneous IV+oral
least-squares (1/y^2 weighting) in Phoenix WinNonlin. No IIV was
reported. F, kA, kA2, and kAT are all dose-dependent; this file encodes
the 100 mg/kg parameter set (F=11.2%, kA=1.12/h, kA2=0.929/h,
kAT=0.532/h) as the typical value because 100 mg/kg is the new NOAEL
used to derive the first-in-human dose. Higher-dose parameter sets (400
and 1500 mg/kg) are documented in the vignette. Parameter values from
Sharma 2018 Table 3.
|
|
SHetA2
human (Sharma 2018)
|
Allometrically-scaled human (70 kg) projection. Two-compartment
intravenous PK model for SHetA2 (a flexible heteroarotinoid anti-cancer
/ chemoprevention drug) with disposition parameters scaled from
preclinical mouse / rat / dog data via simple allometry (CL = a * BW^b)
on a log-log plot (R^2 = 0.91-0.99 across CL, V1, V2, CLD; Sharma 2018
Fig 5). Clearance uses the maximum-life-span-potential (MLP) correction
to account for SHetA2’s hepatic metabolism (CL_MLP = 17.3 L/h vs 41.0
L/h by simple allometry). The model carries no parametric oral
absorption – the source paper simulated the oral profile (Fig 6)
externally by linking these disposition parameters to the Advanced
Compartmental Absorption and Transit (ACAT) model in GastroPlus 9.5,
because the preclinical kA values did not correlate across species and
could not be projected to humans. The predicted human oral
bioavailability was 18.8% (range 7.4-42%) at 10 mg/kg, very close to the
maximum extent of absorption observed in preclinical species at doses
<100 mg/kg (18.6%). Parameter values from Sharma 2018 Results
(Allometric scaling) and Prediction of human pharmacokinetics.
|
|
SHetA2
mouse (Sharma 2018)
|
Preclinical (mouse, CD2F1 female). Two-compartment PK model with
first-order absorption for SHetA2 (a flexible heteroarotinoid
anti-cancer / chemoprevention drug) in non-tumor-bearing CD2F1 female
mice after intravenous (20 mg/kg) and oral (20, 60 mg/kg)
administration. Disposition (CL, V1, V2, CLD) is reported as absolute
total values for a typical 20-28 g mouse, fit by naive-pooled
simultaneous IV+oral least-squares (1/y^2 weighting) in Phoenix
WinNonlin. No IIV was reported by the authors. Bioavailability F is
dose-dependent (17.7% at 20 mg/kg, 19.5% at 60 mg/kg) but kA is shared
across doses. Parameter values from Sharma 2018 Table 3.
|
|
SHetA2
rat (Sharma 2018)
|
Preclinical (rat, Crl:CD Sprague-Dawley). Two-compartment PK model with
first-order absorption for SHetA2 (a flexible heteroarotinoid
anti-cancer / chemoprevention drug) in Crl:CD (SD) rats after
intravenous (5 mg/kg single dose) and oral (100, 500, 2000 mg/kg/day for
28 days) administration. Disposition (CL, V1, V2, CLD) is reported as
absolute total values for a typical 260-347 g rat, fit by naive-pooled
simultaneous IV+oral least-squares (1/y^2 weighting) in Phoenix
WinNonlin. No IIV was reported. The absorption is slow with flip-flop
kinetics at the higher oral doses; kA was estimated as a single value
across doses (0.0755 1/h) while F is dose-dependent (1.03% at 100 mg/kg,
1.57% at 500 mg/kg, 0.560% at 2000 mg/kg). Parameter values from Sharma
2018 Table 3.
|
|
Sibutramine
(Han 2015)
|
Two-compartment population PK for the active mono-desmethyl metabolite
M1 plus a one-compartment PK for the downstream di-desmethyl metabolite
M2 of the appetite-suppressant prodrug sibutramine, combined with an
asymptotic exposure-response weight-loss PD model in Korean obese adults
with metabolic syndrome. Sibutramine is dosed orally and assumed to
convert entirely to M1 during absorption; M1 is then metabolised
entirely to M2 and M2 is the only elimination pathway. Drug effect
inhibits the rate of weight gain via a sigmoid Emax function of the
steady-state sum AUC of M1 and M2 (AUC_ss,sum, computed from the current
daily dose and the individual M1 and M2 clearances). A constant placebo
effect is acknowledged only in female subjects and scales with
mean-normalised baseline BMI.
|
|
Sifalimumab
(Narwal 2013)
|
Two-compartment population PK model for sifalimumab (anti-IFN-alpha
IgG1) in adult patients with systemic lupus erythematosus (Narwal 2013)
|
|
Sifalimumab
(Zheng 2016)
|
Two-compartment population PK model for sifalimumab (anti-IFN-alpha
human IgG1 monoclonal antibody) in adults with systemic lupus
erythematosus following repeat fixed intravenous doses (Zheng 2016).
|
|
Siltuximab
(Cao 2013)
|
Second-generation minimal physiologically-based PK (mPBPK) model for
siltuximab in adults (Cao 2013 Model A; clearance from plasma)
|
|
Siltuximab
(Nikanjam 2019)
|
Two-compartment population PK model for siltuximab (anti-IL-6) in adults
pooled across healthy volunteers and oncology cohorts including
Castleman’s disease, smoldering multiple myeloma, and other tumor types
(Nikanjam 2019)
|
|
Simvastatin
(Jin 2014)
|
Joint two-compartment population PK model for orally administered
simvastatin (lactone parent) and its active metabolite simvastatin acid
(open beta-hydroxyacid), describing atypical multiple-peak absorption
via three parallel mixed zero-and-first-order absorption processes and
non-equilibrium reversible interconversion between the two species (Jin
2014). The simvastatin lactone is delivered into three depot
compartments with fractional bioavailabilities F1, F2, F3 (sum = 1)
parameterised through two relative-bioavailability constants BA1 and
BA2, each depot has its own first-order absorption rate constant Ka1,
Ka2, Ka3, zero-order infusion duration D1, D2, D3, and absorption
lag-times ALAG1 = 0, ALAG2, ALAG3, the lactone disposes via a
2-compartment system with apparent clearance CL and inter-compartmental
clearance Q, the fraction FM of total parent CL is converted to
simvastatin acid (V_acid central fixed at 1 L for identifiability), and
a reverse clearance Q64 returns acid to the parent central compartment.
Age, body weight, and height were tested as covariates and not retained
in the final model. The source publication analysed data in molar units;
this packaged model preserves that choice – doses are expressed in nmol
and concentrations in nmol/L. The validation vignette demonstrates the
standard milligram-to-nanomole conversion using the simvastatin lactone
molecular weight.
|
|
Sirolimus
(Golubovic 2019)
|
Two-compartment population PK model for sirolimus in adult kidney
transplant recipients on triple immunosuppressive therapy (sirolimus +
mycophenolate mofetil + corticosteroids) developed from routine
therapeutic-drug-monitoring trough data with the NONMEM
informative-prior functionality (Golubovic 2019). Covariate effects on
CL/F: aspartate aminotransferase greater than 37 IU/L as a binary
indicator of elevated liver enzymes (-37 percent multiplicative effect
via power form 0.63^AST_HIGH) and age as a linear-deviation effect on
CL/F with reference age 44 years (coefficient -0.388 on AGE/44,
reproducing the 49 percent CL/F decrease from age 16 to age 64 reported
in the Discussion).
|
|
Sirolimus
(Jiao 2009)
|
One-compartment population PK model for oral sirolimus in Chinese adult
de novo renal transplant recipients on triple immunosuppression with
ciclosporin and corticosteroids (Jiao 2009). First-order absorption with
ka fixed at the literature value 0.752 1/h. Covariate effects on
apparent clearance: linear-deviation effects of total cholesterol and
whole-blood ciclosporin trough concentration centred on the cohort
medians, multiplicative power-form effects of concomitant silymarin and
glycyrrhizin co-therapy in hepatically impaired patients, and a
power-form effect of the current sirolimus daily dose centred at 2 mg.
Apparent volume of distribution carries a linear-deviation effect of
ciclosporin trough concentration.
|
|
Sirolimus
(Wu 2012)
|
Two-compartment population PK model for oral sirolimus with saturable
Michaelis-Menten absorption in patients with advanced cancer (Wu 2012).
Hematocrit power covariate on apparent oral clearance.
|
|
Sirukumab
(Xu 2011)
|
Two-compartment population PK model for sirukumab (anti-IL-6 human IgG1
kappa monoclonal antibody, CNTO 136) in healthy adults following a
single intravenous infusion, with first-order elimination from the
central compartment and allometric body-weight scaling (Xu 2011).
|
|
Sitafloxacin
(Rodjun 2023)
|
Population PK model for oral sitafloxacin as encoded by Rodjun 2023 for
Monte Carlo probability-of-target-attainment simulation against
carbapenem-, multidrug- and colistin-resistant Acinetobacter baumannii.
One compartment with first-order absorption in the fasted state.
Apparent clearance is entirely proportional to creatinine clearance
(CL/F = 2.58 x CrCL, with CrCL in L/h) and apparent volume is
proportional to body weight (V/F = 1.72 L/kg). Unbound concentration is
returned as Ccu using the reported unbound fraction of 0.388, because
the paper’s PK/PD target is the unbound AUC ratio fAUC/MIC > 30.
|
|
SKL10406
(Park 2014)
|
Two-compartment first-order oral absorption population PK with
effect-compartment Emax PK-PD model for striatal serotonin transporter
(SERT) occupancy by SKL10406 (a triple monoamine reuptake inhibitor
candidate) in healthy adult volunteers (Park 2014; EME variant, Table 3)
|
|
Sn38
organoid (Zhu 2023)
|
In vitro (patient-derived colorectal-cancer tumour organoids, PDTOs).
Exponential organoid-growth model with a sigmoidal Emax (Hill) killing
term describing the 96 h concentration-viability relationship of SN-38,
the active metabolite of irinotecan. A vehicle-control organoid and a
treated organoid grow in parallel; the reported readout is cell
viability, the ratio of treated to control organoid volume. This is the
in vitro half of the Zhu 2023 in vitro-to-in vivo translation: the same
Emax / EC50 / Hill parameters are carried into the human irinotecan
minimal-PBPK PK/PD model, see modellib(‘Zhu_2023_irinotecan’).
|
|
Snake
venom (Sanhajariya 2018)
|
Exploratory population PK meta-analysis of snake venom in humans
(Sanhajariya 2018): one-compartment model with zero-order input
(duration D1 = 1 h, fixed) and first-order elimination, fit in NONMEM
7.2 to 218 timed venom concentrations from 145 snakebite patients pooled
across 24 published case reports / series. Snake family (Elapidae vs
Viperidae) modifies F1; Viperidae is the reference (F1 = 1, fixed).
Authors describe the model as a preliminary prior for future
snake-envenoming PK modelling; F1 also absorbs the large bite-to-bite
variability in injected venom mass.
|
|
Sodium
nitrite qsp (VegaVilla 2013)
|
QSP. Mechanistic systems pharmacology model of the NO metabolome
(nitrite, nitrate) and methemoglobin (MetHb) in healthy adults receiving
a 48-hour intravenous infusion of sodium nitrite. Nine ODEs covering
plasma/RBC/tissue nitrite and nitrate, MetHb, NO and methemoglobin
reductase activity; nonlinear nitrite/nitrate renal clearance (linear
slope), entero-salivary nitrate-to-nitrite recycling, and
indirect-response stimulation of MetHb reductase. Time in minutes;
amounts in umol; concentrations in umol/L.
|
|
Somatropin
human (Thorsted 2016)
|
Translational (allometrically-scaled rat-to-human) population PKPD model
for recombinant human growth hormone (rhGH / somatropin) in
growth-hormone-deficient adult males. Structural parameter values are
derived from the Thorsted 2016 hypophysectomized-rat PKPD fit by
allometric scaling to a 70 kg reference subject (Table 3 of the source
paper): clearance terms (CL, Q) and Vmax with exponent 0.75;
distribution volumes (Vc, Vp) with exponent 0.9 (the
empirically-selected best-fit exponent for human i.v. data); first-order
absorption rate constants (ka1, ka2) and kout with exponent -0.25; KM
unscaled; Emax and EC50 unscaled. The s.c. absorption model is the
corrected form (Table 3 / Figure 5): bioavailability of the ka2 path
reduced from 0.833 (rat) to 0.500, and one transit compartment added to
the ka1 path. The IGF-1 indirect response uses kin = kout * R0 with R0
fixed to 65 ng/mL (human population mean per Laursen 1996) and is driven
directly by plasma rhGH (no effect-delay chain - the rat CPLAG chain is
intentionally dropped for the human prediction). Bodyweight gain is not
included in the human model. Variability is inherited from the rat PKPD
fit; residual error is fixed at the values used for the human-simulation
validation (Methods).
|
|
Somatropin
rat (Thorsted 2016)
|
Preclinical (hypophysectomized Sprague-Dawley rat). Mixed-effects PKPD
model for recombinant human growth hormone (rhGH / somatropin)
describing PK as a two-compartment model with parallel linear (CL) and
Michaelis-Menten (Vmax, KM) elimination, parallel first-order
subcutaneous absorption (ka1 direct path, ka2 delayed through one
transit compartment, with bioavailabilities F1 and F2), an indirect
response model for IGF-1 induction (stimulation of kin via a
three-compartment effect-delay chain feeding an Emax/EC50 stimulation),
and a linear bodyweight-gain model driven by IGF-1 above baseline.
Reference rat body weight is 0.1 kg (100 g) and the allometric exponents
(0.75 / 1.0) are fixed.
|
|
Sonidegib
(Goel 2016)
|
Two-compartment population PK model for sonidegib (LDE225) in healthy
subjects and patients with advanced solid tumors with first-order
absorption, lag time, linear elimination, and dose-dependent
bioavailability (Goel 2016)
|
|
Sorafenib
(Jain 2011)
|
One-compartment population PK model for orally administered sorafenib in
patients with solid tumours (Jain 2011). Absorption is described by an
Erlang-style chain of four catenary GI transit compartments downstream
of an upstream absorption depot, all linked by a single first-order rate
constant ka (mean absorption transit time MAT = 5 / ka). Enterohepatic
recirculation is modelled by routing a fraction Fent of the drug leaving
the central compartment into a gallbladder reservoir, with periodic
release back to the most distal transit compartment gated by a smooth
Hill switch Ehc = tad^40 / (tad^40 + t’^40), where tad is the time since
the most recent dose; release becomes essentially full once tad exceeds
the gallbladder-emptying onset time t’. The irreversible elimination
rate constant ke equals the biliary excretion rate constant kb (= CL/V)
per the published assumption kb = ke. Body weight is the only retained
covariate (allometric exponent fixed to 1 on V/F, reference weight 80
kg).
|
|
Sotatercept
(AitOudhia 2024)
|
Two-compartment population pharmacokinetic model for sotatercept in
healthy post-menopausal women and patients with pulmonary arterial
hypertension (Ait-Oudhia 2024). First-order subcutaneous absorption with
logit-scale bioavailability (about 66%) and linear elimination from the
central compartment; time-varying body weight enters as a power
covariate on clearance (exponent 0.814) and central volume (exponent
1.02) with a 70 kg reference, and baseline serum albumin as a power
covariate on clearance (exponent -0.849) with a 4.5 g/dL reference.
Separate log-scale residual error magnitudes are used for healthy
participants and for patients with PAH. Intravenous doses go to the
central compartment and subcutaneous doses to the depot.
|
|
Sparsentan
(Wada 2023)
|
Two-compartment population PK model with lagged first-order absorption
for oral sparsentan (a single-molecule dual endothelin / angiotensin II
receptor antagonist, DEARA) pooled over nine phase I-III studies in 446
subjects: 236 healthy volunteers, 16 subjects with hepatic impairment,
and 194 patients with primary or genetic focal segmental
glomerulosclerosis (FSGS). Apparent oral clearance carries a first-order
CYP3A auto-induction term that steps CL/F from 3.88 L/h on the first
dosing day to 5.11 L/h thereafter (induction half-life fixed at 0.001
day, i.e. effectively instantaneous), multiplied by power effects of
alkaline phosphatase and creatinine clearance and by log-additive
effects of male sex and of moderate / strong CYP3A4 inhibitor
coadministration. Relative bioavailability is a power function of dose
clamped at 200 mg, producing less-than-dose-proportional exposure (Frel
= 1.41, 1.00, 0.71 at 200, 400, 800 mg). Race shifts the apparent
central volume, and formulation (whole tablet or crushed tablet against
the capsule reference) shifts both the absorption rate constant and the
absorption lag time. Residual error is combined proportional plus
additive, with the additive SD fixed at the 2 ng/mL assay lower limit of
quantitation.
|
|
Spectinamide
1599 mouse pbpk (Parmar 2023)
|
Minimal PBPK (mPBPK; author-coded ODEs, fitted in Monolix 2021R1).
Preclinical (BALB/c mouse, 20 g). Spectinamide 1599, an
anti-tuberculosis spectinomycin analogue, after intravenous,
subcutaneous, and intrapulmonary-aerosol dosing (Parmar 2023,
Pharmaceutics). Venous and arterial blood plus five tissues (lung,
spleen, liver, kidney, and a lumped ‘other’), each tissue split into a
rapid-equilibrium extracellular pool (vascular + interstitial, in
instantaneous equilibrium with blood through the blood-to-plasma ratio)
and a slow cellular pool coupled by a first-order influx K(I->C)
acting on the unbound fraction and a first-order back flux K(C->I).
The lung sits in series between venous and arterial blood; the spleen
drains portally into the liver; elimination is glomerular filtration
(GFR x fu) acting on the kidney extracellular pool. Subcutaneous doses
reach venous blood through depot with ka / F; intrapulmonary-aerosol
doses reach an epithelial-lining-fluid compartment (elf) through depot2
with its own ka / F, and the ELF exchanges with the lung cellular and
extracellular pools. Tissue concentrations (lung, spleen, liver, kidney)
are simultaneous outputs alongside venous plasma Cc. Two mass-balance
defects in the published equations are corrected here (venous outflow to
the lung, and hepatic outflow of the portal spleen flow); see the
vignette Errata.
|
|
Spectinamide
1599 rat pbpk (Parmar 2023)
|
Minimal PBPK (mPBPK; author-coded ODEs, fitted in Monolix 2021R1).
Preclinical (Sprague-Dawley rat, 225 g). Spectinamide 1599, an
anti-tuberculosis spectinomycin analogue, after a single intravenous
dose (Parmar 2023, Pharmaceutics). Rat-physiology counterpart of
Parmar_2023_spectinamide_1599_mouse_pbpk: the same structure and the
same jointly estimated distribution rate constants, with the
Sprague-Dawley physiology and rat-specific blood-to-plasma ratio and
unbound fraction substituted. Venous and arterial blood plus five
tissues (lung, spleen, liver, kidney, and a lumped ‘other’), each split
into a rapid-equilibrium extracellular pool (vascular + interstitial)
and a slow cellular pool coupled by a first-order influx K(I->C) on
the unbound fraction and a back flux K(C->I). Lung in series between
venous and arterial blood, spleen draining portally into the liver, and
elimination by glomerular filtration (GFR x fu) on the kidney
extracellular pool. Intravenous only: the paper reports no subcutaneous
or aerosol rat data and estimated Ka / F from mouse data alone, so no
absorption depot is included. Two mass-balance defects in the published
equations plus a flow-rounding inconsistency are corrected here; see the
vignette Errata.
|
|
Spectinamide
1810 mouse (Wagh 2021)
|
Preclinical (BALB/c mouse, Mycobacterium tuberculosis infection).
Population PK + PK/PD model for subcutaneous spectinamide 1810 in a
murine TB efficacy / dose-fractionation study. PK is a two-compartment
first-order absorption model with all volumes and clearances expressed
per kg body weight (mg/kg dosing, mg/L plasma); IIV is carried on CL/F
only (13.2% CV in infected animals). PK/PD couples the plasma central
concentration Cc to a hypothetical PAE (post-antibiotic effect)
compartment that tracks Cc whenever Cc exceeds the PAE concentration and
otherwise decays first-order at rate K_PAE; the PAE concentration drives
bacterial killing through a sigmoidal Emax (K_kill_max, EC50, Hill g) on
a one-population logistic-growth Mycobacterium tuberculosis model (K_gs
net growth rate, log10 N_max carrying capacity, log10 baseline CFU at
aerosol infection time). A binary STUDY_WAGH_2 covariate switches
K_kill_max from the study 1 typical value to the study 2 value via a
1.15 multiplicative factor; study-specific log10 CFU residual SDs are
exposed as parameters.
|
|
Spectinamide
1810 mouse pbpk (Parmar 2023)
|
Minimal PBPK (mPBPK; author-coded ODEs, fitted in Monolix 2021R1).
Preclinical (BALB/c mouse, 20 g). Spectinamide 1810, a structurally
close analogue of spectinamide 1599, after intravenous and subcutaneous
dosing (Parmar 2023, Pharmaceutics). Same structure as
Parmar_2023_spectinamide_1599_mouse_pbpk with the drug-specific
blood-to-plasma ratio and unbound fraction updated and the distribution
rate constants, Ka, F and residual errors re-estimated for 1810 (Table
7). Venous and arterial blood plus five tissues (lung, spleen, liver,
kidney, and a lumped ‘other’), each split into a rapid-equilibrium
extracellular pool (vascular + interstitial) and a slow cellular pool
coupled by a first-order influx K(I->C) on the unbound fraction and a
back flux K(C->I). Lung in series between venous and arterial blood,
spleen draining portally into the liver, and elimination by glomerular
filtration (GFR x fu) on the kidney extracellular pool. Subcutaneous
doses reach venous blood through depot with ka / F. No
intrapulmonary-aerosol route: the paper studied 1810 by the intravenous
and subcutaneous routes only. Two mass-balance defects in the published
equations plus a flow-rounding inconsistency are corrected here, and
Table 7’s three intravenous tissue residual errors are unrecoverable
transcription duplicates so they are fixed at zero; see the vignette
Errata.
|
|
Spectinamide
1810 rat pbpk (Parmar 2023)
|
Minimal PBPK (mPBPK; author-coded ODEs, fitted in Monolix 2021R1).
Preclinical (Sprague-Dawley rat, 225 g). Spectinamide 1810 after a
single intravenous dose (Parmar 2023, Pharmaceutics). Rat-physiology
counterpart of Parmar_2023_spectinamide_1810_mouse_pbpk: the same
structure and the same distribution rate constants, with the
Sprague-Dawley physiology and rat-specific blood-to-plasma ratio and
unbound fraction substituted. Venous and arterial blood plus five
tissues (lung, spleen, liver, kidney, and a lumped ‘other’), each split
into a rapid-equilibrium extracellular pool (vascular + interstitial)
and a slow cellular pool coupled by a first-order influx K(I->C) on
the unbound fraction and a back flux K(C->I). Lung in series between
venous and arterial blood, spleen draining portally into the liver, and
elimination by glomerular filtration (GFR x fu) on the kidney
extracellular pool. Intravenous only, and plasma is the only endpoint
with a reported residual error: the rat study sampled plasma alone. Two
mass-balance defects in the published equations plus a flow-rounding
inconsistency are corrected here; see the vignette Errata.
|
|
SPI
62 (Wu 2023)
|
Simultaneous population target-mediated drug disposition (TMDD) PK / PD
model for the small-molecule 11-beta-hydroxysteroid dehydrogenase type 1
(HSD-1) inhibitor SPI-62 (formerly ASP3662) in healthy adults (Wu 2023).
Oral absorption through a chain of four identical first-order transit
steps (depot -> transit1 -> transit2 -> transit3 -> central,
all governed by a single Ktr), two-compartment linear disposition
(central + peripheral1) with clearance CL and distribution flow Q, and
explicit second-order binding of SPI-62 in the central compartment to
its pharmacological target HSD-1 (association rate constant Kon,
dissociation rate constant Koff) to form a drug-target complex. The
total target amount Rtotal is held constant – no target synthesis or
degradation is included – so free target is Rtotal minus the complex
amount. This saturable, high-affinity / low-capacity binding is what
produces SPI-62’s striking nonlinear PK: extremely low plasma exposure
after the first low doses (most of the dose is trapped on target),
turning into linear PK with unusually high accumulation ratios once the
target is saturated by repeated dosing. Hepatic HSD-1 activity, measured
as the urinary ratio of (tetrahydrocortisol + allotetrahydrocortisol) to
tetrahydrocortisone expressed as a percentage of each subject’s own
baseline, is driven directly (no effect delay) by the
central-compartment SPI-62 concentration through an inhibitory sigmoid
Imax function with half-maximal inhibitory concentration IC50 and power
coefficient gamma. Fit by simultaneous PK-PD estimation in NONMEM 7.4.3
(FOCEI, ADVAN13) to pooled data from the SPI-62 first-in-human
single-ascending-dose (1-10 mg) and multiple-ascending-dose (0.2-2 mg
once daily) phase 1 trials. All PK parameters are apparent (per unit
bioavailability) because F is unknown. Exponential inter-individual
variability on Vcentral, CL, Ktr, Koff, Rtotal, and IC50; proportional
residual error on both the plasma concentration and the HSD-1 activity
endpoint. No covariates were retained: age, sex, body weight, and race
showed no meaningful relationship with any parameter, so the final model
equals the base model. Amounts are carried internally in nmol so that A
/ V is directly in nmol/L (= nM), the units of Kon, Koff, and IC50;
convert an mg dose to nmol by dividing by the SPI-62 molecular weight of
424.4 g/mol and multiplying by 1e6.
|
|
Spironolactone
qsp (Meid 2024)
|
QSP. Whole-body plasma-potassium homeostasis with renal handling along
the nephron and aldosterone feedback, pharmacologically modulated by the
mineralocorticoid-receptor antagonist spironolactone. Sixteen ODE
states: a three-transit oral spironolactone absorption chain plus a
spironolactone central concentration, a two-compartment canrenone
(active metabolite) disposition, an extracellular and an intracellular
potassium pool, luminal potassium amounts and principal-cell potassium
concentrations in the distal convoluted tubule (DCT), connecting tubule
/ cortical collecting duct (CNT/CCD) segments, cumulative urinary
potassium excretion, and a mineralocorticoid-receptor occupancy state.
Potassium is filtered at the glomerulus, reabsorbed in the proximal
tubule / loop of Henle in proportion to sodium reabsorption, secreted
into DCT / CNT / CCD lumen by Goldman-Hodgkin-Katz passive flux coupled
to Na/K-ATPase active basolateral uptake, and partly reabsorbed in the
medullary collecting duct. Aldosterone rises exponentially with plasma
potassium and falls with sodium intake, and scales luminal potassium
permeability; canrenone inhibits that pathway through an Emax
mineralocorticoid-receptor occupancy model. Five parameters carry
inter-individual variability and were the ones the source estimated per
patient by Bayesian maximum-a-posteriori updating from electronic health
records: potassium intake, sodium intake, extracellular fluid volume,
mineralocorticoid-receptor abundance, and a hyperaldosteronism effect.
The structural model is inherited unchanged from Maddah and Hallow 2022;
Meid 2024 Appendix C prints the complete operationalized rxode2 source
that this file transcribes.
|
|
Sugammadex
rocuronium (Kleijn 2011)
|
Integrated population PK-PD model for sugammadex-mediated reversal of
rocuronium-induced neuromuscular blockade (Kleijn 2011). Both sugammadex
and rocuronium have two-compartment PK from IV bolus dosing into the
central compartment; the sugammadex-rocuronium inclusion complex has its
own two-compartment PK with parameters set equal to free sugammadex (Bom
2002 framework). Complex formation is dynamic with fixed equilibrium
dissociation constant kd = 0.0559 uM and estimated dissociation rate k2
= 0.034 1/min (association k1 = k2 / kd = 0.61 1/(minuM)). The
rocuronium central concentration drives an effect compartment via ke0 =
0.134 1/min; neuromuscular blockade (T4/T1 twitch ratio x 100) follows a
sigmoid Emax form with Emax set equal to E0 so the readout decreases
monotonically from baseline E0 ~ 104 toward 0 as the effect-compartment
rocuronium concentration rises. Sugammadex-mediated reversal enters as
an additional first-order elimination of rocuronium from the effect
compartment driven by the central free-sugammadex concentration (ks =
0.033 1/(minuM)). Both plasma assays measured total drug (free +
complex), so the Cc and Cc_roc outputs return total sugammadex and total
rocuronium. Allometric scaling on all volumes (exponent 1), flows
(0.75), and rate constants (-0.25) at reference WT = 70 kg; sugammadex
CL is NOT allometrically scaled (creatinine-clearance covariate replaces
size scaling). All units are molar inside the model (dose in umol,
concentrations in uM); see vignette for mg-to-umol conversion with
rocuronium MW = 529.78 g/mol and sugammadex MW = 2178.01 g/mol
(octasodium salt).
|
|
Sugemalimab
(Wang 2024)
|
Two-compartment population PK model with sigmoidal-cl_hill_max
time-varying clearance for intravenous sugemalimab (anti-PD-L1 IgG4) in
adults with advanced solid tumours or lymphomas across nine Phase I-III
trials (Wang 2024)
|
|
Sulbactam
durlobactam (Cammarata 2024)
|
Combined four-compartment (two compartments per drug) population PK
model for the sulbactam-durlobactam combination, fitted simultaneously
to 373 subjects and 5,188 plasma concentrations pooled from six Phase 1
studies, one Phase 2 cUTI study, and one Phase 3 study in Acinetobacter
baumannii-calcoaceticus complex infections (Cammarata 2024). Total
clearance of each drug is the sum of a renal arm scaled by baseline
BSA-normalized creatinine clearance and a non-renal arm, split by a
fixed fraction excreted renally; total CL carries a further proportional
downward shift in subjects with CLcr < 30 mL/min/1.73 m^2. Body
weight acts as a power function on CL and central volume of both drugs;
infection type and East Asian region act as proportional shifts. The
paper’s two sub-models are integrated into the same file: a time-varying
hemodialysis gate multiplies total CL 6.24-fold (durlobactam) and
8.19-fold (sulbactam) while a session is running, and epithelial lining
fluid concentrations are returned as instantaneous ratios of the plasma
concentrations (37.2% and 53.3% of total drug). Durlobactam uses the
unsuffixed canonical compartment / parameter set; sulbactam carries the
sibling-drug suffix _sbt throughout.
|
|
Sulbactam
qsp (LopezArguello 2023)
|
QSP. In vitro (Pseudomonas aeruginosa PAO1). Whole-cell
penicillin-binding protein (PBP) covalent-binding model for sulbactam
(beta-lactamase inhibitor): seven coupled ODEs for the rate of net
influx of drug across the outer membrane into periplasm and the
competitive, mass-balanced acylation of six PBPs (1a, 1b, 2, 3, 4, 5/6)
counted as molecules per bacterial cell. The intact parameter switches
between the intact whole-cell assay (penetration-limited; drug enters
periplasm at Rate_Influx/access) and the lysed isolated-membrane assay
(no outer membrane; a vast excess of drug molecules is present at time
0).
|
|
Sulfadoxine
(Karunajeewa 2009)
|
Population PK model for sulfadoxine (SDOX) and its primary
N-acetylsulfadoxine (NASDOX) metabolite in 60 Papua New Guinean women
(30 pregnant, second or third trimester; 30 age-matched nonpregnant
controls) given a single oral 1,500 mg sulfadoxine / 75 mg pyrimethamine
dose for intermittent presumptive treatment of malaria in pregnancy
(Karunajeewa 2009). SDOX is described by first-order absorption (no lag)
into a 2-compartment disposition with separate non-metabolic clearance
CL/F (renal excretion) and metabolic formation clearance CLM/F that
drains SDOX into a 1-compartment NASDOX disposition. NASDOX elimination
clearance is fixed at 10 times the structural SDOX non-metabolic CL/F
(rapid formation-rate-limited renal excretion of the metabolite, Bell
1985). Allometric scaling is applied to all apparent volumes (exponent
1) and all apparent clearances (exponent 0.75) at reference WT = 70 kg.
Pregnancy is the only retained covariate, entering as an additive term
on the structural SDOX non-metabolic CL/F (+0.0181 L/h/70 kg). The
companion model for the co-administered pyrimethamine is shipped as
‘Karunajeewa_2009_pyrimethamine’ (separate NONMEM dataset, fit
independently in the source publication).
|
|
SulfadoxinePyrimethamine
(deKock 2017)
|
Joint popPK model for the antimalarial fixed-dose combination of
sulfadoxine (1500 mg) and pyrimethamine (75 mg) as intermittent
preventive treatment during pregnancy (IPTp) and after delivery in 98
women from Mali, Mozambique, Sudan, and Zambia (de Kock 2017).
Sulfadoxine has 2-compartment disposition with first-order absorption;
pyrimethamine has 3-compartment disposition with first-order absorption.
Apparent volumes and flow rates are allometrically scaled with total
body weight (exponents 1 and 0.75 respectively, reference WT = 60 kg).
Whole-blood predictions are derived from plasma predictions using
hematocrit and an estimated RBC-to-plasma partition ratio per drug.
Pregnancy effects on apparent CL differ by drug: sulfadoxine uses a
sigmoidal time-after-delivery effect (asymptotic -75.7%, T50 = 6.35
weeks, gamma = 4.90), while pyrimethamine uses a step contrast (+21.2%
postpartum). Pyrimethamine apparent CL is additionally -20.2% in the
Mozambique site. Residual country-specific scaling on the observed
whole-blood concentrations is fitted with Mali as the reference.
|
|
SulfadoxinePyrimethamine
(Odongo 2015)
|
Joint popPK model for the antimalarial fixed-dose combination of
sulfadoxine (1500 mg) and pyrimethamine (75 mg) administered as a single
oral dose for intermittent preventive treatment of malaria during
pregnancy (IPTp) in 34 non-pregnant and 87 pregnant Ugandan women dosed
in the second trimester, of whom 78 were redosed in the third trimester
(Odongo 2015). Each drug is described by a two-compartment model with
first-order absorption and an absorption lag time, with bioavailability
fixed at 1. Covariates on apparent CL/F (additive in L/h): pregnancy
status (both drugs), serum albumin (sulfadoxine only), and subject age
(pyrimethamine only). Covariates on apparent central volume V2/F
(exponential per-unit): gestational age at dose (both drugs) and body
weight (pyrimethamine only). Inter-individual variability is log-normal
and is not estimated on V2/F or V3/F for sulfadoxine, nor on Q/F for
pyrimethamine, in line with the paper’s over-parameterisation control.
|
|
Sumatriptan
(Lee 2015)
|
One-compartment population PK model for oral sumatriptan in healthy
Korean male volunteers (Lee 2015): two parallel absorption routes
(first-order absorption with lag time, and a transit-compartment chain
with the Savic 2007 analytical input form) into a single central
compartment with linear elimination. Captures the multiple-peaks
absorption phenomenon reported in oral sumatriptan.
|
|
Sunitinib
(Ait-Oudhia 2016)
|
Joint population PK/PD model for sunitinib and its equipotent active
metabolite SU12662 in adults with advanced hepatocellular carcinoma
(HCC) receiving 37.5 mg sunitinib PO QD. Parent drug and metabolite each
follow a 2-compartment oral PK structure with first-order absorption;
each oral sunitinib dose deposits Dose into the parent depot and fM *
Dose (fM = 0.21 fixed, Houk 2009) into the SU12662 depot. The active
free (unbound) drug concentration ACub = (1 - fb_D) * Cc + (1 - fb_M) *
Cc_su12662 (fb_D = 0.9, fb_M = 0.95 fixed, free fractions 0.1 and 0.05)
inhibits the zero-order production rate of plasma sVEGFR2, captured with
an indirect-response model dsVEGFR2/dt = kin / (1 + alpha * INH) - kout
* sVEGFR2 with INH = ACub / (kd + ACub) (kd = 4 ug/L fixed, Mendel 2003)
and kin = R0 * kout. Tumor volume follows a first-order growth dTG/dt =
kg * (1 - H(t)) * TG with kg derived from baseline tumor volume by kg =
ln(2) / (114 * TG0^0.14) (Taouli 2005) and H(t) = Imax * dsVEGFR2 /
(dsVEGFR2 + dIC50) with Imax = 1 fixed and dsVEGFR2 = R0 - sVEGFR2(t).
The paper reports a significant covariate effect of the DCE-MRI
volume-transfer constant Ktrans on dIC50 (power coefficient 2.12) but
the cohort-median Ktrans required to centre that effect is not reported
in the paper or supplements on disk; the effect is omitted from model()
and documented in the vignette. A Cox-style time-to-tumor progression
hazard h(t) = b0 * exp(b1 * dAUC24h_sVEGFR2) is described in the paper
but evaluated post-simulation in the vignette, not encoded as an ODE.
|
|
Sunitinib
(vanErp 2010)
|
One-compartment population PK model for oral sunitinib in cancer
patients with a mechanism-specific grapefruit-juice (GJ)
drug-interaction module. Sunitinib is absorbed first-order (ka, tlag)
into a single central compartment with linear elimination (CL/F, Vd/F).
A paper-specific intestinal CYP3A4-activity state (baseline 1, recovery
first-order with t1/2 = 23 h fixed from Greenblatt 2003) is fully
depleted to 0 by each GJ ingestion event. The relative bioavailability
is F = 1 + deltaF * (1 - cyp3a4), so simultaneous GJ + sunitinib intake
gives F = 1.11 (deltaF = 0.11) and the GJ-induced increase in sunitinib
exposure decays back to baseline with the CYP3A4 recovery half-life
(8.9% at 7 h, 5.3% at 24 h, 1.3% at 72 h, 0.07% at 1 week after the last
GJ dose). No covariates were retained in the final model. Eight
metastatic-cancer patients (1 female / 7 male, age 41-78 years) on
chronic sunitinib 25-50 mg once daily contributed 268 plasma
concentrations.
|
|
Sunitinib
(Yu 2015)
|
Integrated semi-physiological population PK model for oral sunitinib and
its equipotent active metabolite N-desethyl sunitinib (SU12662) in adult
cancer patients (n = 70 across three studies). Sunitinib is absorbed
first-order into a hypothetical hepatic enzyme compartment that sits
algebraically in equilibrium with the sunitinib central compartment via
hepatic blood flow Qh (fixed at 80 L/h for a 70 kg subject). Clearance
CL of sunitinib acts at the enzyme site (Cliv = (ka * depot + Qh / Vc *
central) / (Qh + CL)); fraction fm = 0.21 (fixed from Houk 2009) of the
cleared sunitinib appears as SU12662 input into the metabolite central
compartment, the rest is true (non-SU12662) sunitinib clearance. SU12662
follows a 2-compartment disposition with its own central and peripheral
volumes and inter-compartmental clearance. Body-weight allometric
scaling with fixed exponents 0.75 (clearance / flow: CL_sun, Qh,
CL_SU12662, Qi_SU12662) and 1.0 (volumes: Vc_sun, Vc_SU12662,
Vp_SU12662) is applied a priori with reference WT = 70 kg. IIV is
modelled with a 4 x 4 OMEGA BLOCK on Vc_sun, Vc_SU12662, CL_SU12662,
CL_sun with the paper’s reported correlations 0.48, 0.45, 0.53 and
remaining off-diagonals fixed to zero. Per-study residual proportional
error from Yu 2015 Table 2 is simplified to a single propSd /
propSd_su12662 pair populated from the Study 1 sigma^2 estimates (the
largest cohort: 50 patients, 703 samples); the smaller Study 2 + 3
residuals are noted in the vignette.
|
|
Sunitinib
irinotecan mouse (Wilson 2015)
|
Preclinical (mouse with HT-29 colorectal-cancer xenograft). Mechanistic
tumor-growth PD model for the antiangiogenic agent sunitinib (reduces
vascular carrying capacity) combined with the cytotoxic agent irinotecan
(three-stage transit-cell-death chain following Simeoni et al. 2004) and
an empirical interaction term (Wilson 2015 Equation 4) in which the
irinotecan transit-death rate kC depends on the cumulative
pre-irinotecan sunitinib exposure. Drug input is K-PD (no
pharmacokinetic data; each oral sunitinib or 5-min IV irinotecan dose
enters its drug-amount compartment with normalized magnitude 1).
|
|
Sunitinib
OS (Hansson 2013)
|
Parametric overall-survival (Weibull TTE) model in adults with
imatinib-resistant gastrointestinal stromal tumours (GIST) on sunitinib.
The hazard for death is a Weibull baseline (lam_haz, alfa_haz) modulated
log-linearly by the model-predicted relative change in soluble VEGFR-3
(sVEGFR-3) from individual baseline and by observed baseline tumour size
(sum of longest diameters, SLD). The sVEGFR-3 time course is simulated
in-model as a one-compartment indirect-response turnover with
simple-Imax inhibition of Kin driven by the per-cycle exposure summary
auc = DOSE / CLI. A parallel Weibull censoring hazard (lam_cens,
alfa_cens) is included so the model can drive prospective Kaplan-Meier
simulations with censoring per the paper’s published procedure. The
model has no PK ODE and consumes individual posthoc upstream-PD
parameters (BAS_SVEGFR3, MRT_SVEGFR3, EC50_SVEGFR3) and posthoc
upstream-PK clearance (CLI) plus observed baseline tumour size (TUMSZ,
mm) as data covariates. No IIV reported in the source for the OS or
censoring hazard parameters.
|
|
Tacrine
(Holford 1992)
|
Population pharmacodynamic disease-progression model for the cognitive
subscale of the Alzheimer’s Disease Assessment Scale (ADAS-cog, 0-70
score) in patients with probable Alzheimer’s disease treated with
tacrine. Linear disease progression (baseline S0 + alpha*time) with a
tacrine effect on the location of the progression curve (effect
compartment driven by IBW-normalised daily dose rate, no estimable PK
clearance because the response is slow relative to the 2-hour tacrine
plasma half-life) and a placebo effect with asymmetric onset /
elimination / tolerance dynamics (placebo response builds up during
treatment, dissipates after treatment ends, and develops tolerance
during continued treatment). Estimated by Holford and Peace 1992 on 909
patients (5253 ADAS-cog observations) pooled from two clinical trials of
identical design: US protocol 970-01 (n = 632) and French protocol
970-04 (n = 277). The French cohort takes multiplicative scale factors
on baseline status (FS04 = 1.08), placebo potency (Fpp4 = 1.76), and
placebo elimination half-time (Ft1/2el-p4 = 2.78). Inter-individual
variability is correlated across baseline S0, progression rate alpha,
and tacrine potency beta_a (block of three) with diagonal IIV on placebo
potency beta_p; the time constants of the effect compartments are
typical-value only. Residual error is proportional. NOTE: the lead
Holford 1992 PNAS 89:11471-11475 ‘Results and validation’ paper supplies
all parameter values but the exact ODE form of the placebo dynamics is
described in the companion methodology paper (PNAS 89:11466-11470) which
was not available on disk at extraction time; the ODE form here is the
field-standard reconstruction (asymmetric on/off placebo compartment
plus multiplicative tolerance) and is documented in the validation
vignette’s Assumptions and deviations section.
|
|
Tacrolimus
(AbdelJalil 2013)
|
One-compartment population PK model for oral tacrolimus in paediatric
liver transplant recipients (Abdel Jalil 2013), with first-order
absorption (ka fixed at the literature value 4.5 1/h), an apparent
volume of distribution fixed at the literature value 30 L/kg, allometric
(WT/13.2 kg)^0.75 scaling on apparent clearance with the theory-based
exponent fixed, multiplicative exponential effects of time
post-transplantation (days) and CYP3A5*1 carrier status on CL/F,
exponential (log-normal) inter-individual variability on CL/F, and
proportional residual error.
|
|
Tacrolimus
(Andrews 2017)
|
Two-compartment population PK model with first-order absorption and an
absorption lag time for twice-daily oral immediate-release tacrolimus
(Prograft and Modigraf) in paediatric renal transplant recipients during
the first 6 weeks post-transplantation (Andrews 2017). Apparent oral
clearance CL/F and apparent inter-compartmental clearance Q/F scale
allometrically with body weight at a fixed exponent of 0.75 referenced
to a 70 kg adult; apparent central volume V1/F and apparent peripheral
volume V2/F scale at a fixed exponent of 1.0; ka has no body-weight
scaling. CL/F additionally varies with CYP3A5 expresser status (1.04
multiplier for 3/3 or unknown genotype, 1.98 multiplier for
1/1 or 1/3 carriers; pooled with unknown because
Andrews 2017 explicitly groups 3/3 with unknown in the final
equation), donor source (0.74 multiplier for living-donor recipients vs
deceased-donor reference; equivalent to deceased-donor recipients having
~35% higher CL/F), eGFR (power exponent 0.19 centred at the cohort
median 69 mL/min/1.73 m^2 of adapted-Schwartz eGFR), and a piecewise
hematocrit effect (power exponent -0.44 centred at 0.3 L/L applied only
when HCT < 0.3 L/L). Inter-individual variability is diagonal on ka,
CL/F, V1/F, and V2/F. Residual error is a combined additive +
proportional model with separate immunoassay and LC-MS/MS magnitudes
selected by the per-sample IMMUNOASSAY indicator. Inter-occasion
variability (IOV) on CL/F (18% CV) and V2/F (35% CV) reported by Andrews
2017 Table 2 is NOT encoded structurally here (per the Brooks 2021
tacrolimus precedent) – the source paper does not define an operational
occasion column for the model-library use case; downstream users who
want to simulate IOV can add an OCC indicator and a per-occasion eta in
rxode2.
|
|
Tacrolimus
(Antignac 2007)
|
One-compartment population PK model for oral and intravenous tacrolimus
in adult kidney transplant recipients (Antignac 2007). First-order
absorption (ka fixed at 4.5 1/h from Jusko 1995), linear elimination,
simultaneous fit of IV and oral data to estimate bioavailability.
Clearance increases sigmoidally with days postoperation from a baseline
CLmin (at POD = 0) to 2 * CLmin asymptotically, with half-recovery at
TCL50 = 3.81 days and Hill exponent 2.54; clearance is multiplied by (1
+ theta_PRD) when concomitant prednisone dose exceeds 25 mg/day. No
covariates retained on V or F.
|
|
Tacrolimus
(Benkali 2010)
|
Two-compartment population PK model with Erlang-distributed transit
absorption (3 transit compartments) for once-daily extended-release oral
tacrolimus (Advagraf) in stable adult renal transplant recipients more
than 6 months post-transplant who were switched from twice-daily
ciclosporin (Benkali 2010), with a multiplicative CYP3A5*1-carrier
(expresser) effect on apparent clearance and combined additive +
proportional residual error.
|
|
Tacrolimus
(Bergmann 2014)
|
Two-compartment population PK model for oral tacrolimus in adult kidney
transplant recipients (Bergmann 2014), with first-order absorption after
a lag time, allometric (WT/70 kg)^0.75 scaling on apparent clearance,
multiplicative CYP3A5*1-carrier effect on CL/F, linear hematocrit and
post-transplant-day effects on CL/F, linear free prednisolone Cmax
effect on V1/F, correlated inter-individual variability across V1/F, ka,
and V2/F, and proportional residual error.
|
|
Tacrolimus
(Brooks 2021)
|
Two-compartment population pharmacokinetic model for IV
continuous-infusion tacrolimus in pediatric and young adult patients
undergoing allogeneic hematopoietic cell transplantation (Brooks 2021).
Allometric weight scaling on all PK parameters with fixed theoretic
exponents (0.75 on CL and Q, 1.0 on V and V2; reference weight 70 kg); a
structural ratio Fact fixed at 2.0 links Q to CL and V2 to V; and a
multiplicative azole-antifungal (voriconazole or posaconazole) factor of
0.8 on CL captures the CYP3A4/5 inhibitor co-treatment effect.
|
|
Tacrolimus
(Chen 2017)
|
One-compartment population PK model with first-order absorption and
absorption lag for low-dose oral tacrolimus (FK506, Prograf 0.5 mg
capsules) in Chinese adult and paediatric myasthenia-gravis (MG)
patients (Chen 2017). The absorption parameters ka and tlag are fixed at
values obtained from a supplementary dataset of healthy volunteers,
because the sparse-trough MG dataset is not informative about the
absorption phase. Apparent oral clearance CL/F (3.6 L/h typical) is
modulated by hematocrit and blood urea nitrogen through a multiplicative
power-of-covariate-ratio form referenced to cohort medians (HCT median
38.4 %, exponent 4.31; BUN median 4.2 mmol/L, exponent 1.42). Apparent
volume V/F is 1700 L typical with no retained covariate effects
(high-dose IV immunoglobulin treatment was tested as a covariate on V/F
but did not survive backward elimination). Inter-individual variability
is diagonal on CL/F (141.6% CV) and V/F (72.4% CV); no IIV is estimated
on ka or tlag. Residual variability is a pure proportional model (35.8%
CV) on whole-blood tacrolimus concentrations.
|
|
Tacrolimus
(CirrincioneDall 2011)
|
One-compartment population PK model with first-order absorption for oral
tacrolimus in pediatric liver transplant recipients (Cirrincione-Dall
2011 ACOP poster, Metrum Research Group). Apparent oral clearance CL/F
(25.8 L/h at a 70 kg reference) and apparent volume V/F (2490 L at a 70
kg reference) are estimated; allometric body-weight scaling is fixed at
exponent 0.75 on CL/F and 1.0 on V/F. The first-order absorption rate
constant ka is fixed at 4.48 1/h from literature because the sparse
therapeutic-drug-monitoring sampling could not identify it. CL/F
additionally varies (full covariate model) with post-operative day as
(POD/7)^0.409, with CYP3A5 expresser status as 1.24^CYP3A5_EXPR (missing
genotype data imputed as non-expressers), with AST as
(AST/510.5)^-0.0364, with albumin as (ALB/28)^-0.357, with hematocrit as
0.993^HCT (HCT entered as a fraction L/L, not as percent), and with age
as (AGE/2)^-0.0310. Inter-individual random variation on CL/F and V/F
was modeled exponentially with an estimated covariance of the two random
effects per the poster text; the off-diagonal covariance value itself is
not reported in the poster Table 2 so this implementation encodes
uncorrelated diagonal IIVs and documents the gap in the vignette Errata.
Residual error is a combined additive (SD 2.508 ng/mL) + proportional
(SD 0.3674 fraction) model on whole-blood tacrolimus concentrations.
|
|
Tacrolimus
(Dunlap 2025)
|
Two-compartment population pharmacokinetic model for oral
immediate-release tacrolimus in adult allogeneic hematopoietic cell
transplant (allo-HCT) recipients (Dunlap 2025): first-order absorption
with bioavailability fixed at 1; allometric (TBW/70 kg) scaling fixed at
0.75 on CL/F and Q/F and at 1 on V1/F and V2/F; exponential CYP3A5
intermediate / normal metabolizer phenotype effect on CL/F (CYP3A5 IM or
NM have ~2.14-fold higher CL/F than CYP3A5 PM); exponential
reduced-intensity-conditioning effect on CL/F (RIC recipients have ~37%
lower CL/F than myeloablative-conditioning recipients); inter-individual
variability on V1/F, CL/F, and V2/F; and an additive residual error of
2.51 ng/mL on the linear concentration scale.
|
|
Tacrolimus
(Grover 2011)
|
Two-compartment population PK model for oral tacrolimus in adult Native
American kidney transplant recipients (Grover 2011), with first-order
absorption after a lag time, no covariate effects (the Native American
cohort showed no association of age, sex, weight, BMI, or
post-transplant duration with PK parameters), and a placeholder
proportional residual error model (residual error was not reported in
the short communication).
|
|
Tacrolimus
(Hao 2018)
|
One-compartment population PK model with first-order absorption (no lag)
and first-order elimination for twice-daily oral immediate-release
tacrolimus (Prograf) in paediatric nephrotic-syndrome patients aged
2.7-17.3 years (Hao 2018). Apparent oral clearance CL/F scales
allometrically with body weight at a fixed exponent of 0.75 referenced
to a 70 kg adult; apparent volume of distribution V/F scales linearly
with body weight at a fixed exponent of 1.0 referenced to 70 kg; ka has
no body-weight scaling. CL/F additionally varies with CYP3A5 expresser
status (multiplicative factor 1.60 for 1/1 or 1/3
carriers vs the 3/3 nonexpresser reference). Inter-individual
variability is diagonal on ka, V/F, and CL/F (exponential / log-normal
model). Residual unexplained variability is proportional (paper text:
‘The proportional model best described residual variability’; Table 2
reports it under the ‘Residual variability (exponential)’ label, which
is the standard NONMEM additive-on-log-scale parameterisation equivalent
to proportional in linear space).
|
|
Tacrolimus
(JacoboCabral 2015)
|
Two-compartment population PK model for oral tacrolimus in Mexican
paediatric renal-transplant recipients (Jacobo-Cabral 2015): first-order
absorption with a lag time, no allometric scaling, three-level CYP3A5
genotype effect on apparent oral clearance (3/3 reference,
1/3 +50%, 1/1 +93%), formulation-type effects on Ka
and on relative bioavailability F (pooled Prograf + Framebin + Tenacrine
reference vs Limustin generic vs unrecorded), an exponential per-dose
effect on F centred at 2 mg, exponential inter-patient variability on
Ka, V/F and F, and a residual error described in the paper as additive
on the natural-log concentration scale (encoded as proportional residual
error in linear space, which is the standard nlmixr2 equivalent for SD
<= 0.15).
|
|
Tacrolimus
(Ji 2018)
|
One-compartment population pharmacokinetic model for oral tacrolimus in
Korean adult living-donor liver-transplant recipients during the first
14 days post-transplantation (Ji 2018). First-order absorption with ka
fixed at 4.48 1/h from prior reports; CL/F = 6.33 * POD^0.257 multiplied
by a combinational CYP3A5 recipient-and-donor categorical factor (2.314
if both recipient and donor are CYP3A5 expressers; 1.523 if the
recipient is a CYP3A5 expresser and the donor is a nonexpresser; 1.0
otherwise); V/F = 465 * POD^0.322; exponential IIV on CL/F and V/F;
combined proportional + additive residual error on whole-blood
tacrolimus concentration.
|
|
Tacrolimus
(Kassir 2014)
|
Two-compartment population PK model with first-order absorption and an
absorption lag time for twice-daily oral tacrolimus in paediatric liver
transplant recipients (Kassir 2014). Apparent oral clearance CL/F and
apparent inter-compartmental clearance Q2/F scale allometrically with
body weight at a fixed exponent of 0.75 referenced to the cohort median
weight of 20 kg; apparent central volume V1/F and apparent peripheral
volume V2/F scale at a fixed exponent of 1.0 to the same 20 kg
reference; the first-order absorption rate constant ka carries an
allometric exponent of -0.25 per Anderson and Holford theory. Apparent
peripheral volume V2/F was fixed to 290 L during estimation to stabilise
the model (Kassir 2014 Table 4 footnote). Inter-individual variability
is diagonal on CL/F, V1/F, and Q2/F (no IIV on ka, tlag, or V2/F).
Residual error is a proportional model. No covariates beyond body weight
were retained after stepwise covariate analysis – age, sex, type of
transplant, age of liver donor, time post-transplantation, liver
function tests, albumin, renal function (serum creatinine and creatinine
clearance), haematocrit, use of steroids, presence of clinically
relevant CYP3A4 inhibitors, and drug formulation were all screened and
dropped (Kassir 2014 Results ‘Analysis of covariates and sources of
variability’).
|
|
Tacrolimus
(Kim 2018)
|
Integrated population PK model of the tacrolimus (TAC) - mycophenolate
mofetil (MMF) drug-drug interaction in healthy Korean male volunteers
(Kim 2018, final integrated model). TAC follows a two-compartment model
with first-order absorption and a lag time; apparent oral clearance
(CL/F) is increased 1.48-fold in CYP3A5 expressers and is suppressed by
co-administered mycophenolic acid (MPA) through an inverse-exponential
interaction (CL/F = 13.8 / exp(0.0294Cmpa) 1.48^CYP3A5). MPA
(the active moiety of MMF) follows a two-compartment model with
first-order absorption; MPA is metabolised to MPAG (7-O-glucuronide; 85%
of metabolism) and AcMPAG (acyl glucuronide; 15%). MPAG undergoes
enterohepatic recirculation via a gallbladder compartment that empties
into the MPA absorption compartment during a meal-triggered window.
Tacrolimus concentrations are in ng/mL; MPA, MPAG and AcMPAG are in
ug/mL.
|
|
Tacrolimus
(Kirubakaran 2022)
|
Two-compartment population pharmacokinetic model for oral
immediate-release tacrolimus (Prograf) in adult heart transplant
recipients (Kirubakaran 2022): first-order absorption; FFM-allometric
scaling on CL/F and Q/F (exponent 0.75) and on V2/F and V3/F (exponent
1.0); haematocrit power effect on CL/F; and a state-dependent typical
CL/F (without vs with concomitant azole antifungal, 21.1 vs 4.2 L/h)
with a state-dependent CL/F BSV magnitude (61% vs 89.5% CV). Structural
PK was estimated with NONMEM PRIOR (NWPRI) support from the published
Sikma 2017 thoracic-transplant tacrolimus popPK model.
|
|
Tacrolimus
(Lu 2015)
|
Two-compartment population PK model with first-order absorption and lag
time for oral tacrolimus in pooled Chinese healthy volunteers and adult
orthotopic liver-transplant recipients (Lu 2015). Apparent peripheral
volume V3/F is fixed at the healthy-volunteer-only estimate (916 L).
Apparent clearance CL/F is reduced multiplicatively in liver-transplant
recipients and further modulated by an exponential serum ALT effect that
applies only to the transplant cohort.
|
|
Tacrolimus
(Moes 2016)
|
Two-compartment population pharmacokinetic model for oral once-daily
tacrolimus (Advagraf) in stable adult liver transplant recipients (Moes
2016), with first-order elimination from the central compartment and a
delayed first-order absorption phase described by three sequential
transit compartments sharing the absorption rate constant ka, a fixed
oral bioavailability F = 0.23, a categorical donor + recipient
CYP3A53 combination effect on apparent oral clearance (reference
both nonexpressers; donor nonexpresser + recipient 1 carrier +33%;
donor 1 carrier + recipient nonexpresser +33%; both 1 carriers
+71%), independent log-normal IIV on CL, Vc, and ka, and proportional
residual error on whole-blood concentration.
|
|
Tacrolimus
(MohammedAli 2023)
|
Two-compartment population PK model for once-daily extended-release
LCP-Tac tacrolimus (MeltDose technology, Envarsus) in stable adult renal
transplant recipients (Mohammed Ali 2023), parameterized in apparent
elimination clearance CL/F, apparent distributional clearance CLD/F and
apparent central and peripheral volumes Vc/F and Vp/F. Delayed
absorption is described by a Savic 2007 transit-compartment chain with
the number of transit compartments fixed at NN = 2 (mean transit time
MTT = 2.91 h) feeding a first-order absorption step ka into the central
compartment. A combined CYP3A4/CYP3A5 cluster phenotype (high,
intermediate and poor metabolizer, reconstructed inside model() from the
recipient CYP3A5 expresser status and the CYP3A4*22 rs35599367 carrier
indicator) gives three distinct typical CL/F values. Inter-individual
variability is carried on CL/F, Vc/F, Vp/F and MTT, with inter-occasion
variability on CL/F and a proportional residual error on whole-blood
concentrations.
|
|
Tacrolimus
(Passey 2011)
|
Steady-state apparent-clearance regression model for oral tacrolimus
trough concentrations in adult kidney-transplant recipients (Passey
2011). Encoded as a 1-compartment IV continuous-infusion model with a
nominal fixed central volume of distribution: at steady state, Cc =
dose-rate / CL/F is independent of V, so the rxode2 simulation
reproduces the paper’s regression-style trough prediction. Apparent
clearance CL/F is multiplied by five covariate factors: an
ordered-categorical days-post-transplant effect (3-5 = reference, 6-10 =
0.86, 11-180 = 0.71), three-level CYP3A5 genotype (CYP3A53/3 =
reference, CYP3A51/3 = 1.70, CYP3A51/1 = 2.00),
steroid-sparing immunosuppression protocol (0.70), a power-form age
effect ((Age/50)^-0.40), and concomitant calcium channel blocker
coadministration (0.94).
|
|
Tacrolimus
(Pei 2023)
|
One-compartment population PK model with first-order absorption and
elimination for oral tacrolimus in adult heart transplant recipients
(Pei 2023 Pharmaceutics, Phoenix NLME 8.3). Apparent oral clearance CL/F
carries four covariate effects: a power effect of total bilirubin, an
exponential effect of concomitant voriconazole, an exponential
three-level CYP3A53 (rs776746) genotype effect with the 3/*3
nonexpresser as reference, and an exponential IL-10 G-1082A (rs1800896)
heterozygote effect. Absorption rate constant fixed at 0.30 1/h; no
covariate was retained on Vd/F. Exponential IIV on both CL/F and Vd/F,
proportional residual error. This is the companion top-down model to the
whole-body PBPK model of the same paper (Pei_2023_tacrolimus_pbpk.R);
the two identify different covariates, which the paper’s Discussion
addresses explicitly.
|
|
Tacrolimus
(Prytula 2016)
|
Two-compartment population PK model with first-order absorption and a
fixed absorption lag time for twice-daily oral tacrolimus (Prograft) in
stable paediatric renal transplant recipients at least one year after
kidney transplantation (Prytula 2016). All apparent-PK parameters (CL/F,
Q/F, V1/F, V2/F, ka) scale allometrically with body weight at fixed
exponents (0.75 on CL/F and Q/F, 1 on V1/F and V2/F, -0.25 on ka)
referenced to a 70 kg adult; V2/F is fixed at 1090 L/70 kg during
covariate analysis; CL/F additionally varies with CYP3A51 carrier
status (1+0.45-fold higher in carriers vs 3/3 nonexpressers),
gamma-glutamyltransferase (power -0.21, centred at 13 U/L), and
haematocrit (power -0.59, centred at 0.34); eta_Q is perfectly
correlated with eta_CL and is constructed as iiv_q_scale etalcl
(iiv_q_scale = 2.0; the ‘IIV-CL-Q’ parameter in Table 2);
inter-individual variability is a 3x3 correlated block on (ka, CL/F,
V1/F); proportional residual error.
|
|
Tacrolimus
(Rower 2017)
|
One-compartment population pharmacokinetic model for oral / enteral
tacrolimus in paediatric heart transplant recipients (Rower 2017):
first-order absorption with fixed Ka = 3.43 1/h; AGE power effect on
apparent volume with exponent 0.775 and reference 5.7 years;
creatinine-clearance power effect on apparent elimination rate with
exponent 0.850 and reference 122.4 mL/min/1.73 m^2; concomitant
fluconazole reduces apparent elimination by 34%. Originally
parameterised in NONMEM ADVAN2 TRANS1 on (ke, V); converted here to the
canonical (CL/F, V/F) form via CL/F = ke * V, so the AGE effect
propagates to CL/F with the same exponent as on V/F.
|
|
Tacrolimus
(Storset 2014)
|
Theory-based two-compartment population pharmacokinetic model for oral
tacrolimus in adult kidney-transplant recipients (Storset 2014):
plasma-based disposition with first-order absorption and a lag time,
allometric scaling on fat-free mass, CYP3A5-expresser effects on plasma
clearance and oral bioavailability, a sigmoid-Emax prednisolone-driven
reduction in bioavailability, a first-day-post-transplant
bioavailability spike with subject-level random effect, and a saturable
haematocrit-dependent red-blood-cell-binding equation that maps plasma
concentration to whole-blood concentration.
|
|
Tacrolimus
(Wang 2024)
|
One-compartment population PK model with first-order absorption for
twice-daily oral tacrolimus (Prograf) trough concentrations in Chinese
adult renal transplant recipients (Wang 2024). The absorption rate
constant ka is held at 3.86 1/h because only pre-dose trough
concentrations (C0) were available. Apparent oral clearance CL/F carries
two exponential covariate effects: the CYP3A5 3-allele count (0 for
1/1, 1 for 1/3, 2 for 3/3; coefficient
-0.348, so CL/F falls to 70.6% and 49.9% of the 1/1 value for
1/3 and 3/*3 respectively) and hematocrit expressed as a
volume fraction (coefficient -0.122). Apparent central volume V/F
carries no covariate. Inter-individual variability is exponential and
diagonal on CL/F and V/F. Residual error is additive on log-transformed
concentrations, which is proportional error on the linear concentration
scale. Wang 2024 also builds MLP, SVR, and XGBoost machine-learning
predictors on top of this model’s post hoc individual predictions; those
are not ODE models and are outside the scope of this model file.
|
|
Tacrolimus
(Woillard 2011)
|
Two-compartment population PK model with Erlang-distributed transit
absorption (3 transit compartments) for oral tacrolimus in adult renal
transplant recipients pooled across the twice-daily immediate-release
Prograf formulation and the once-daily prolonged-release Advagraf
formulation (Woillard 2011), with multiplicative CYP3A5*1-carrier
(expresser) and power-scaled haematocrit effects on apparent clearance,
multiplicative formulation effects on the Erlang transit rate constant
and on apparent central volume, and combined additive plus proportional
residual error.
|
|
Tacrolimus
(Zhu 2014)
|
Two-compartment population PK model for oral tacrolimus in Chinese adult
liver transplant recipients (Zhu 2014), with first-order absorption, a
power-form joint DOSE x POD covariate effect on apparent clearance,
log-normal IIV on CL/F, V2/F, Q/F, V3/F, and ka, and proportional
residual error. Bioavailability was not estimated; the structural
disposition parameters are apparent values (CL/F, V/F, Q/F).
|
|
Tacrolimus
industry meta (Lu 2019)
|
Industry meta-analysis. Two-compartment population PK model for oral
tacrolimus immediate-release (IR-T; Prograf, twice daily) and
prolonged-release (PR-T; Advagraf / Astagraf XL, once daily)
formulations in adult and paediatric liver, kidney, and heart transplant
recipients (Lu 2019). Pooled individual-patient data from 8 Astellas
Phase II studies (n = 408 patients, 23,176 whole-blood concentration
records). Structural model: first-order absorption with
formulation-dependent Ka (PR-T ~50% slower than IR-T), fixed absorption
lag time, and two-compartment disposition with first-order elimination.
Significant covariates: Asian race on CL/F (+59% vs Whites); log-AST on
CL/F, Vc/F, Vp/F, and F1 (power normalised at LAST = 3.15, i.e., AST ~=
23.3 IU/L); female sex on Vc/F (-44.6% vs males); albumin on Vc/F and
F1; and Asian / Black race on F1 (Asians > Whites > Blacks). Type
of organ transplanted and adult-vs-paediatric population had no
significant effect on PK parameters.
|
|
Tacrolimus
metaanalysis (Nanga 2019)
|
MBMA. Two-compartment population PK meta-model for oral tacrolimus in
solid organ transplantation (Nanga 2019), built from pooled
individual-patient data across 7 historical NONMEM datasets (n = 281
paediatric + adult liver and kidney transplant recipients). Structural
model: first-order absorption with fixed lag time, time-varying
first-order elimination, allometric (WT/50 kg) scaling on apparent
clearance and apparent central volume, multiplicative reduction of CL/F
in hepatic-graft recipients, sigmoidal post-transplant-day recovery of
CL/F, and reduced relative bioavailability for the oral syrup
formulation. The literature-review summary table (Nanga 2019 Table 2: 76
published popPK models) is not used for parameter fitting and is not
reproduced here.
|
|
Tacrolimus
pbpk (Pei 2023)
|
PBPK (whole-body, SimBiology 5.8.2). Perfusion-limited 15-compartment
physiologically based model for oral tacrolimus in adult heart
transplant recipients (Pei 2023 Pharmaceutics). Thirteen well-stirred
flow-limited tissues (gut, spleen, pancreas, liver, muscle, kidney,
brain, heart, lung, skin, tendon, other, adipose) plus arterial and
venous blood, on the Levitt PKQuest standard-human physiology (organ
weights and per-kg perfusions from Table S1, 70 kg / 25 percent body fat
reference). Gut, spleen and pancreas drain into the liver via the portal
vein; the liver is the only eliminating organ. Rodgers and Rowland
tissue-to-plasma partition coefficients (Table S2) are converted to
tissue-to-blood by the blood-to-plasma ratio BPR and multiplied by a Kp
scaling factor. BPR is hematocrit-dependent through the red-cell binding
capacity Bmax and affinity constant KD (Eq 5). Hepatic blood clearance
follows the well-stirred extraction ratio (Eq 3) scaled by the CYP3A5 /
CYP3A4 metabolic fractions and genotype-specific activity levels (Eq 6),
with an optional reversible voriconazole inhibition term (supplement Eq
1-2) driven by a user-supplied voriconazole whole-blood concentration.
Absorption is first-order from a depot into the gut compartment with a
fixed absorbed fraction Fg = 0.2 (Eq 2). Ka, KD, Bmax and CLint are the
four fitted parameters (Table 3, heart-transplant model-building
column); no IIV or residual-error variance was reported. Observation is
venous whole blood. NOTE: the paper’s printed Kp scaling factor of 350
is refuted by the paper’s own Tables S5 and 6 by 4-11 fold; the model
uses 9.15 = 11.9 / 1.3, the mouse-to-human average-Kp ratio the Methods
sentence motivates. See the vignette Errata.
|
|
Tacrolimus
thoracic (Sikma 2020)
|
Two-compartment population pharmacokinetic model for oral whole-blood
tacrolimus in 30 adult thoracic organ transplant recipients (10 heart,
20 lung) during the first 6 postoperative days at the University Medical
Center Utrecht intensive care unit (Sikma 2020 EJDMP). Apparent
clearance CL/F, apparent volumes V1/F and V2/F, inter-compartmental
clearance Q/F, and first-order absorption rate ka are estimated;
bioavailability F is fixed at 1. Only the inter-individual variability
of CL/F was identifiable in the source dataset; all other IIV elements
were not estimated. Inter-occasion (dose-to-dose) variability dominated
the variance structure but is not encoded structurally in this
extraction. No covariates were retained in the final model.
|
|
Tacrolimus
unbound plasma (Sikma 2020)
|
Two-compartment population PK model for whole-blood (Cc), unbound plasma
(Cupc), and total plasma (Ctpc) tacrolimus in 30 adult thoracic-organ
(10 heart + 20 lung) transplant recipients during the first 6
postoperative days (Sikma 2020). First-order oral absorption with ka, F,
and the within-PK fixed-parameter variabilities inherited from a
previously estimated tacrolimus model; non-linear saturable binding of
tacrolimus to erythrocytes (UPC = WBC * Kd / (Bmax * HCT - WBC)) with
the maximum erythrocyte binding capacity Bmax scaled by hematocrit, and
a linear non-specific plasma binding constant Nplasma linking unbound to
total plasma (TPC = Nplasma * UPC).
|
|
Tafenoquine
(Charles 2007)
|
One-compartment first-order-absorption population PK model for oral
tafenoquine in adult Australian soldiers on weekly malaria prophylaxis
(Charles 2007)
|
|
Tafenoquine
(Edstein 2001)
|
One-compartment population PK model for oral tafenoquine in 135 male
Thai soldiers receiving 400 mg base for malaria prophylaxis (monthly
n=104 or weekly n=31). The final model carries correlated IIV on
apparent clearance and apparent volume of distribution (rho ~ 0.71) plus
separate IIV on the first-order absorption rate constant; no covariates
retained (centred age and weight on V/F and a prior-malaria indicator on
CL/F were screened but not deemed to have sufficient clinical impact to
alter the base model).
|
|
Tak
079 (Roepcke 2018)
|
Preclinical (cynomolgus monkey). Two-compartment QSS-TMDD population PK
model plus three PK-PD lymphocyte-depletion models (NK-cell turnover
with Emax on elimination; B-cell four-transit-compartment chain with
Emax on the circulating depletion rate; T-cell direct-response with
Emax) for the cytolytic anti-CD38 human IgG1-kappa monoclonal antibody
TAK-079 pooled from eight monkey studies (dose 0.03-100 mg/kg IV / SC).
PK covariate: route of administration on Vc (SC vs IV).
|
|
Tamibarotene
pediatric (Azechi 2024)
|
Two-compartment population PK model with first-order absorption and an
absorption lag time for oral tamibarotene (synthetic retinoid
RAR-alpha/beta agonist) in pediatric and young-adult patients (4-23
years) with recurrent or refractory solid tumors (Azechi 2024). Apparent
oral clearance CL/F, apparent central volume V1/F, and apparent
peripheral volume V2/F scale linearly with body surface area (BSA)
referenced to the cohort mean of 0.995 m^2 (Table 1);
inter-compartmental clearance Q/F, the absorption rate constant ka, and
the absorption lag time tlag have no covariate effects. tlag was held
fixed at 0.95 h in the published final model (the authors judged the
post-covariate Tlag estimate of ~1.8 h to have low physiological
validity and fell back to the pre-covariate value). Residual error is
proportional with a 42.4% magnitude. The Methods section specifies an
exponential IIV model on all five PK parameters but the paper reports no
per-parameter omega magnitudes and no supplement exists; per operator
decision (sidecar request-001 q1 = A, 2026-06-21) the five eta terms are
encoded as fixed(0) so the published structural IIV declaration is
preserved while remaining faithful to the absence of reported variance
values. See the vignette Assumptions and deviations section for the
resulting limitations on VPC-style validation.
|
|
Tamsulosin
(Tsuda 2010)
|
One-compartment population PK model for oral modified-release tamsulosin
hydrochloride in paediatric patients (2-16 years) with neuropathic and
non-neuropathic bladder (Tsuda 2010), with first-order absorption after
a lag time, allometric (WT/70)^0.75 on apparent clearance and (WT/70)^1
on apparent central volume (allometric exponents fixed at theory
values), a power-form alpha-1-acid glycoprotein (AAG/20 uM) effect on
both CL/F and V/F, correlated inter-individual variability on CL/F and
V/F, independent IIV on ka, and a combined additive + proportional
residual error.
|
|
Taranabant
(Li 2010)
|
Three-compartment population PK model for oral taranabant in healthy and
obese adults (Li 2010)
|
|
Taspoglutide
mbma (Li 2015)
|
MBMA. Coupled PD model-based meta-analysis of taspoglutide (long-acting
human glucagon-like peptide-1 analogue, once-weekly SC) net efficacy on
fasting plasma glucose (FPG) and glycosylated hemoglobin (HbA1c) in type
2 diabetes. Each endpoint is the sum of an exponential-to-asymptote
placebo response (Pmax, Kp) and a saturable Emax drug response (Dmax,
IC50, Kdrug) approached exponentially over time. The FPG drug effect is
driven by the study-arm-mean taspoglutide concentration between weeks 2
and 4 (Cavg; supplied as the METRIC_TASPO_C covariate: 0 / 59.85 / 119.7
pmol/L for placebo / 10 mg / 20 mg QW). The HbA1c drug effect is driven
by the model-predicted drug-induced FPG change (i.e. the
placebo-adjusted FPG response feeds the HbA1c Emax). Estimated on
digitised study-arm-mean PD data from 8 published clinical trials of
taspoglutide monotherapy or add-on therapy in type 2 diabetes (3,702
patients pooled, 8-52 week treatment durations); a ninth trial
(Rosenstock 2013) was held out for external validation. Placebo Pmax and
Kp were fitted on the placebo-only subset first and held fixed in the
final combined PD model. Between-trial variability (ITV) is encoded as
study-level etas (one eta per parameter); the model is suitable for
simulating study-arm-mean PD outcomes and is NOT suitable for
individual-subject simulation. Residual error is a proportional/power
model on each endpoint (the small power-correction term is simplified to
a plain proportional error in this implementation; see vignette
Assumptions and deviations).
|
|
Taurine
rat (Catalan-Latorre 2018)
|
Preclinical (rat). Population PK model for taurine
(2-aminoethylsulphonic acid) in male Wistar rats after IV bolus or oral
gavage administration (1, 10, or 100 mg per animal). Two-compartment
disposition (central and peripheral1) with zero-order endogenous
formation Q0, first-order passive oral absorption ka, first-order
inter-compartmental distribution (K12, K21), and non-linear renal
elimination described as two parallel Michaelis-Menten processes:
saturable tubular secretion (Vms, Kms) and saturable tubular
reabsorption (Vmr, Kmr), with net elimination = secretion -
reabsorption. Oral bioavailability was modelled as 100% (passive
diffusion; not altered by nutritional status). Protein-energy
undernutrition (MAL_NOURISH = 1) reduces the secretion Vmax by 9.4%
relative to well-nourished animals; no other PK parameter depends on
nutritional status. Initial conditions in the central and peripheral
compartments are set from the analytic positive root of the no-dose
steady-state quadratic so that the endogenous taurine concentration is
reproduced at t = 0.
|
|
Tazobactam
(CohenWolkowiez 2014)
|
One-compartment population PK model for tazobactam in premature and term
infants under 61 days postnatal age (Cohen-Wolkowiez 2014); linear
body-weight scaling on CL and V (fixed exponent = 1), and PMA, serum
creatinine and concomitant gentamicin coadministration as covariates on
CL.
|
|
Tazobactam
(Nichols 2016)
|
One-compartment population PK model for tazobactam in critically ill
children (1-9 years) receiving extended-infusion piperacillin-tazobactam
(Nichols 2016); IV zero-order input, first-order elimination, a
multiplicative female-sex effect on CL, and a linear-additive WT effect
on CL centered at the cohort median 18 kg.
|
|
Tazobactam
qsp (LopezArguello 2023)
|
QSP. In vitro (Pseudomonas aeruginosa PAO1). Whole-cell
penicillin-binding protein (PBP) covalent-binding model for tazobactam
(beta-lactamase inhibitor): seven coupled ODEs for the rate of net
influx of drug across the outer membrane into periplasm and the
competitive, mass-balanced acylation of six PBPs (1a, 1b, 2, 3, 4, 5/6)
counted as molecules per bacterial cell. The intact parameter switches
between the intact whole-cell assay (penetration-limited; drug enters
periplasm at Rate_Influx/access) and the lysed isolated-membrane assay
(no outer membrane; a vast excess of drug molecules is present at time
0).
|
|
Tebipenem
(Ganesan 2023)
|
Two-compartment population PK model with two absorption transit
compartments for tebipenem, the active moiety of the oral carbapenem
pro-drug tebipenem pivoxil hydrobromide (TBP-PI-HBr), pooled across
three phase 1 studies and the phase 3 ADAPT-PO trial in adults with
complicated urinary tract infection / acute pyelonephritis (Ganesan
2023; 746 subjects, 3448 plasma concentrations). Apparent oral clearance
is split into an additive non-renal arm (power function of creatinine
clearance) and a renal arm (sigmoidal Hill function of creatinine
clearance) that drives a cumulative urine compartment; the summed CL/F
carries a linear body-surface-area effect. Central volume scales with
height and peripheral volume with body surface area, both shifted by
infection status. The absorption rate constant switches on fed status,
is shifted by infection status, and carries a dose effect confined to
the crossover thorough-QT study (study 104). Interindividual variability
on CL/F is cohort-specific (healthy subjects vs infected patients) and
Ka carries both IIV and two-occasion interoccasion variability.
|
|
Tefibazumab
(Cao 2013)
|
Second-generation minimal physiologically-based PK (mPBPK) model for
tefibazumab in adults (Cao 2013 Model A; clearance from plasma)
|
|
Teicoplanin
(Chen 2023)
|
Two-compartment IV infusion population PK model for teicoplanin in
critically ill adults with sepsis in the intensive care unit, with
CKD-EPI estimated glomerular filtration rate as a power covariate on
clearance (Chen 2023)
|
|
Teicoplanin
(Wi 2017)
|
Two-compartment IV bolus population PK model for teicoplanin in adult
patients receiving venoarterial extracorporeal membrane oxygenation
(VA-ECMO) for cardiogenic shock, with binary within-subject ECMO
indicators on the central volume of distribution (V1) and
inter-compartmental clearance (Q) and a binary CRRT indicator on the
peripheral volume of distribution (V2) (Wi 2017)
|
|
Teicoplanin
(Zhao 2015)
|
Two-compartment IV-injection population PK model for teicoplanin in 85
children with malignant hematological disease (Zhao 2015). Body weight
enters Vc and Vp with the fixed allometric exponent 1 and enters CL and
Q with the fixed allometric exponent 0.75; Schwartz-formula creatinine
clearance enters CL via a power exponent estimated at 0.606. Reference
subject: WT = 27.1 kg, CRCL = 179 mL/min. The published model was used
to derive age-band mg/kg dosing (18 mg/kg for infants, 14 mg/kg for
children, 12 mg/kg for adolescents) and a patient-tailored daily dose
(target AUC * CL_i) to attain the AUC(0,24 h) target of 750 mg.L/h.
|
|
Telapristone
(Morris 2011)
|
Population PK model for telapristone (CDB-4124, a selective
progesterone-receptor antagonist developed for endometriosis and uterine
fibroids) and its active monodemethylated metabolite CDB-4453 (Morris
2011). Parent is a two-compartment model with first-order oral
absorption (no lag); metabolite is a one-compartment model with apparent
volume V3/F fixed to 1 L for identifiability (Fmet is not separately
identifiable from V3, so the estimated fmetest is interpreted as the
ratio Fmet / V3 in 1/L). A NONMEM $MIXTURE
block splits parent CL/F into a high-CL fast-eliminator subpopulation
(CL/F = 11.6 L/h, population fraction P = 0.251) and a low-CL
slow-eliminator subpopulation (CL/F = 3.34 L/h, P = 0.749); the
mechanism is hypothesized in the Discussion to be polymorphic CYP3A5
activity but not directly tested. The mixture assignment is supplied as
the binary covariate MIX_FAST_ELIM (1 = fast eliminator, 0 = slow
eliminator) drawn per subject from a Bernoulli(0.251). The only retained
clinical covariate is moderate renal impairment (RENALIMP_MOD), which
produces a 74% proportional decrease in the telapristone absorption rate
constant Ka relative to the healthy / mild-renal-impaired reference
cohort. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Luo_2024_CES1_cirrhosis.html">Temocapril
pbpk (Luo 2024)</a> </td>
<td style="text-align:left;"> PBPK (semi-mechanistic, custom
WinNonlin 8.1 implementation). Joint temocapril + temocaprilat
disposition in healthy adults and in liver cirrhosis (Child-Pugh A/B/C).
Temocapril is an inactive ester prodrug hydrolysed by hepatic CES1 to
the active diacid temocaprilat. Temocaprilat is eliminated by BOTH renal
and biliary routes, with biliary clearance twice the renal clearance
(Section 3.1.5); biliary excretion is MRP2-mediated and is scaled in
cirrhosis by the Table 1 MRP2 content ratio. The semi-PBPK circuit is
stomach, three small-intestinal lumen segments (duodenum / jejunum /
ileum), the matching three gut-wall segments, portal vein, liver, kidney
and a one-compartment systemic compartment. Cirrhosis is applied by
switching the Child-Pugh-specific physiology of Table 1 (organ blood
flows, functional liver volume, GI transit rates, GFR, plasma-binding
protein concentrations, hepatic CES1 content) and rescaling CLint,
CLint,K, Peff and Vsys through Eq 1-6. Deterministic: the paper's
virtual populations are uniform 80-120% draws on the drug parameters,
not lognormal random effects, so no IIV is encoded. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Mazzocco_2015_temozolomide.html">Temozolomide
(Mazzocco 2015)</a> </td>
<td style="text-align:left;"> Tumour growth inhibition (TGI)
model for low-grade glioma (LGG) treated with first-line temozolomide
chemotherapy (Mazzocco 2015): three tumour-tissue compartments
(proliferative, non-damaged quiescent, damaged quiescent) coupled to a
K-PD virtual drug compartment, with logistic proliferative growth
(carrying capacity K fixed at 100 mm), treatment-induced damage of both
proliferative and quiescent tissues, time-dependent acquired resistance
of the proliferative tissue only, and tumour-genotype covariate effects
of TP53 mutation status on TMZ efficacy and 1p/19q codeletion status on
the damaged-quiescent-to-proliferative repair rate. Observation is mean
tumour diameter (MTD = P + Q + Qp) in millimetres. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Baheti_2011_tenofovir.html">Tenofovir
(Baheti 2011)</a> </td>
<td style="text-align:left;"> Two-compartment
first-order-absorption population PK model for plasma tenofovir (TFV) in
HIV-1-infected adults on once-daily tenofovir disoproxil fumarate (TDF)
coupled with a stimulatory indirect-response (Dayneka 1993) model for
intracellular tenofovir diphosphate (TFV-DP) in peripheral blood
mononuclear cells; plasma TFV drives TFV-DP formation through a
sigmoidal Emax stimulation function. Creatinine clearance enters CL/F
and Vc/F via a power covariate. Fitted sequentially (PK first, PD with
PK individual post-hoc Bayes estimates fixed). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Thoueille_2023_tenofovir_ckd.html">Tenofovir
alafenamide (Thoueille 2023)</a> </td>
<td style="text-align:left;"> Joint two-analyte population PK
model fitting tenofovir alafenamide and its active moiety tenofovir
simultaneously in people living with HIV, with complete irreversible
prodrug conversion and creatinine clearance, age, ethnicity and potent
P-glycoprotein-inhibitor comedication on apparent tenofovir clearance.
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Lu_2016_tenofovir.html">Tenofovir
combined (Lu 2016)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model with first-order absorption and an absorption lag time for
tenofovir (300 mg oral TDF once daily) in HIV-1-uninfected African
adults receiving once-daily preexposure prophylaxis (Lu 2016, Partners
PrEP Study). Combined variant: parameters estimated using a combined
data set in which patient-reported dosing records were replaced with
MEMS electronic adherence monitoring records where available. Absorption
rate constant Ka is fixed at 1.5 /h; absorption lag time ALAG1 = 0.41 h.
Apparent oral clearance (CL/F) carries a power-form covariate effect on
creatinine clearance (raw Cockcroft-Gault, mL/min) centred at the cohort
mean 106 mL/min. Diagonal IIV on CL/F, V1/F, and Ka; combined additive +
proportional residual error. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Chen_2016_tenofovir_emtricitabine.html">Tenofovir
emtricitabine (Chen 2016)</a> </td>
<td style="text-align:left;"> Linked population PKPD model for
daily oral co-administered tenofovir (TFV, given as the prodrug TDF 300
mg = TFV 136 mg) and emtricitabine (FTC 200 mg) in HIV-positive and
HIV-negative adults (Chen 2016 Cell-PrEP study). Each parent drug is
described by a two-compartment first-order-absorption plasma popPK
model. Each parent feeds a hybrid first-order-formation + saturation
link into its intracellular triphosphate anabolite in peripheral blood
mononuclear cells (TFV-DP, FTC-TP), modelled with a two-compartment
'recycle' elimination structure where a fraction R of the eliminated
drug re-enters the central intracellular compartment. Each anabolite
inhibits the zero-order production rate of two endogenous
deoxynucleoside triphosphates via an Emax indirect-response model with
Kout fixed to 1/day and Emax fixed to 1: TFV-DP inhibits dATP and dGTP
(deoxypurines); FTC-TP inhibits dCTP and TTP (deoxypyrimidines). The
dGTP effect waned over time and is described by an additional
1/(1+t^gamma) time factor. Sex is a covariate on FTC plasma Vc/F and
HIV-infection status is a covariate on FTC-TP Kf. Intended for
simulating analog:dNTP molar ratios (TFV-DP:dATP, FTC-TP:dCTP) for
various dosing strategies, e.g., the IPERGAY on-demand PrEP regimen.
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Thoueille_2023_tenofovir_ckd.html">Tenofovir
full (Thoueille 2023)</a> </td>
<td style="text-align:left;"> One-compartment population PK
model for tenofovir after oral tenofovir alafenamide in people living
with HIV, with creatinine clearance, age, ethnicity and potent
P-glycoprotein-inhibitor comedication on apparent clearance (full final
covariate model). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Granda_2024_kidney_pbpk.html">Tenofovir
pbpk (Granda 2024)</a> </td>
<td style="text-align:left;"> PBPK (mechanistic kidney, 35
states). Individualised prediction of tenofovir renal clearance from
per-subject biomarker measurements of kidney blood flow and
OAT1/3-mediated tubular secretory capacity, on top of tracer-measured
GFR (Granda 2024, Clin Transl Sci). The kidney is resolved into 11
longitudinal subsegments (proximal tubule S1-S3, descending and
ascending loop of Henle, distal tubule, and five collecting-duct
subsegments), each with a tubular lumen, a tubular epithelial cell and a
peritubular blood subspace (33 states), plus a systemic blood
compartment and a bladder. Mechanisms: unbound glomerular filtration,
OAT1/3-mediated active secretion in the proximal tubule only,
pH-dependent bidirectional passive diffusion along the whole nephron,
and CKD tubular-flow adaptation. The structural equations, segment
volumes, surface areas, tubular pH profile and adaptive flow factors are
the Huang & Isoherranen 2018 / 2020 framework; Granda 2024 replaces
the framework population defaults for kidney blood flow and secretory
clearance with per-subject measured / fitted values. Predicts each
subject's tenofovir renal clearance from their measured GFR and kidney
blood flow plus the kynurenic-acid-derived secretory capacity, scaled by
0.033. Reproduces the Predicted TFV CLr column of Table 4. Deterministic
typical-value model: the paper reports no IIV and no residual error.
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Lu_2016_tenofovir.html">Tenofovir
prdi (Lu 2016)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model with first-order absorption for tenofovir (300 mg oral TDF once
daily) in HIV-1-uninfected African adults receiving once-daily
preexposure prophylaxis (Lu 2016, Partners PrEP Study). PRDI variant:
parameters estimated using patient-reported dosing information with a
steady-state assumption. Apparent oral clearance (CL/F) carries a
power-form covariate effect on creatinine clearance (raw
Cockcroft-Gault, mL/min) centred at the cohort median 106 mL/min.
Diagonal IIV on CL/F only; combined additive + proportional residual
error. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Thoueille_2023_tenofovir_ckd.html">Tenofovir
reduced (Thoueille 2023)</a> </td>
<td style="text-align:left;"> One-compartment population PK
model for tenofovir after oral tenofovir alafenamide in people living
with HIV, with creatinine clearance on apparent clearance (reduced
model, used by the authors for all chronic-kidney-disease simulations).
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Hamren_2008_tesaglitazar.html">Tesaglitazar
(Hamren 2008)</a> </td>
<td style="text-align:left;"> Mechanistic parent +
acyl-glucuronide population PK model for tesaglitazar (a dual PPAR
alpha/gamma agonist) in 41 adult subjects with varying degrees of renal
function (Hamren 2008). Parent tesaglitazar follows a two-compartment
disposition with first-order oral absorption (ka fixed at 1.5 1/h, F
fixed at 1); renal clearance CLrt = 0.027 L/h directs parent to a
cumulative urine compartment, and metabolic clearance CLmt = 1.91 L/h
generates the acyl glucuronide metabolite. The metabolite follows a
one-compartment disposition (Vcm = 8.5 L) with saturable
Michaelis-Menten renal clearance (Vmax = 0.188 umol/h, Km = 0.041
umol/L) routing to a cumulative urine compartment, linear non-renal
clearance (CLnrm = 1.2 L/h), and biliary excretion (kbm = 11.7 1/h) into
a paper-specific gut compartment. The gut compartment releases
interconverted parent tesaglitazar back into the parent central
compartment at rate kicv = 0.79 1/h, completing the futile-cycle
interconversion loop that the source paper proposes as the mechanism for
increased tesaglitazar exposure in renal-impairment subjects.
Covariates: BSA-normalized renal function CRCL
(iohexol-clearance-measured GFR, mL/min/1.73 m^2; linear centered slope
on CLrt and direct linear normalised scaling on metabolite Vmax),
per-subject free fraction FU (% by ultrafiltration; linear centered
slope on CLmt), sex SEXF (women have 31% lower CLrt than men),
concomitant probenecid CONMED_PROBENECID (75% reduction of both CLrt and
metabolite Vmax), and body weight WT (shared centered linear slope on
Vct and Vpt). Concentrations are molar (umol/L) and amounts are molar
(umol) throughout to match the Michaelis-Menten parameterisation of the
acyl-glucuronide renal elimination; the user converts mg-of-tesaglitazar
doses to umol using the molecular weight of 408.45 g/mol (1 mg = 2.45
umol). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Lehr_2010_tesofensine.html">Tesofensine
(Lehr 2010)</a> </td>
<td style="text-align:left;"> Joint parent (tesofensine) +
metabolite (M1, CYP3A4-formed) population PK and effect-compartment
PK/PD model in mild Alzheimer's disease (Lehr 2010 Phase IIa fit; 62
patients across two 4-week placebo-controlled studies). Parent is
one-compartment with first-order absorption (ka FIXED from upstream
Phase I popPK) and parallel elimination through a metabolite-formation
arm (CL_met = parent -> M1 flux) and a non-formation arm (CL_non-met
= elimination via routes other than M1 formation). M1 is one-compartment
with apparent volume FIXED at 0.768-fold of the parent apparent volume
(mouse-derived ratio, Lehr 2010 ref 17). Tesofensine and M1 each drive
their own effect compartment (shared keo FIXED at a small value,
equivalent to a long effect-equilibration half-life); the combined drug
effect on ADAS-Cog uses an extended Emax with competitive interaction in
which the M1 effect-compartment concentration is divided by 5 to reflect
the in-vivo M1 potency one-fifth that of the parent (Lehr 2010 Methods,
ref 17). The ADAS-Cog observation equals the sum of drug, placebo, and
disease-progression contributions (change from each subject's baseline).
The placebo bi-exponential model (onset rate keq, offset rate kel_pla,
scaling beta_pla) is fully FIXED to literature values from a published
large-AD-cohort placebo model (Lehr 2010 ref 34); the linear
disease-progression slope is FIXED at 6 ADAS-Cog points/year (Lehr 2010
ref 26). Emax is negative (a clinically meaningful ADAS-Cog improvement
is a score reduction); the sign is applied inside model() while |Emax|
is the ini-scale magnitude carried with multiplicative IIV. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Matsumoto_2005_TF_505.html">TF
505 (Matsumoto 2005)</a> </td>
<td style="text-align:left;"> Two-compartment
first-order-absorption population PK model for the oral
5-alpha-reductase inhibitor TF-505 coupled to an indirect-response PD
model for plasma dihydrotestosterone (DHT, expressed as percent of
basal) in which the DHT synthesis rate kin is modulated by a 24-h
circadian cosine; fit to single- and multiple-dose data from healthy
adult male Japanese volunteers (Matsumoto 2005). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Rovei_1982_theophylline.html">Theophylline
(Rovei 1982)</a> </td>
<td style="text-align:left;"> One-compartment oral PK model for
theophylline tablets (Rovei 1982): first-order absorption with lag time
in healthy adult volunteers across single oral doses of 125-500 mg.
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Suda_2008_theophylline.html">Theophylline
(Suda 2008)</a> </td>
<td style="text-align:left;"> Steady-state population PK model
for oral theophylline in 52 Japanese premature neonates and infants with
apnea (Suda 2008). One-compartment first-order absorption structure;
oral clearance CL/F is the only structural parameter the paper estimates
(steady-state trough analysis Css = R / CL/F). Body-weight allometric
scaling and a binary indicator for the Apnecut formulation (vs the
in-house theophylline-alcohol comparator) on CL/F. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Yano_1993_theophylline.html">Theophylline
(Yano 1993)</a> </td>
<td style="text-align:left;"> One-compartment IV-infusion
population PK model for theophylline (Yano 1993 Paper II) in 55 adult
inpatients with stable chronic airway obstruction; clearance and volume
of distribution are log-linear functions of arterial PaCO2 and a binary
hepatic-dysfunction indicator. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/elDesoky_1997_theophylline_pediatric_asthma.html">Theophylline
pediatric asthma (elDesoky 1997)</a> </td>
<td style="text-align:left;"> One-compartment IV PK model for
theophylline in 15 Egyptian pediatric patients (age 2-12 yr, weight
12-30 kg) treated for an acute asthma attack (elDesoky 1997).
Aminophylline given as a 30-min loading infusion (6 mg/kg) followed by
12 hr of continuous maintenance infusion (1 mg/kg/h); theophylline
concentrations measured at 0.75, 7, and 13.25 hr. Parameter values taken
from the Standard Calculations (SC) column of Table 2, which is
independent of the Bayesian-prior population data and is treated by the
authors as the reference (true) values. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Almquist_2016_ticagrelor.html">Ticagrelor
(Almquist 2016)</a> </td>
<td style="text-align:left;"> Preclinical (mouse, C57Bl/6
male). Mechanistic interaction PK model for ticagrelor, its active
metabolite (TAM, AR-C124910XX), and the ticagrelor-neutralising Fab
antibody fragment MEDI2452 in mouse (Almquist 2016). Three-compartment
disposition for ticagrelor and TAM (shared plasma V, tissue V1, V2; V1
in instantaneous equilibrium with V); MEDI2452 lives in plasma V only
and reversibly binds the free fractions of ticagrelor and TAM with rate
kon and dissociation constant Kd; both free MEDI2452 and the two
MEDI2452-drug complexes are eliminated together at the Fab clearance
Cl_f (no recycling). Naive-pooled fit (no IIV); multiplicative
log-normal residual error on five plasma assays. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/LopezArguello_2023_pbp_binding_pseudomonas.html">Ticarcillin
qsp (LopezArguello 2023)</a> </td>
<td style="text-align:left;"> QSP. In vitro (Pseudomonas
aeruginosa PAO1). Whole-cell penicillin-binding protein (PBP)
covalent-binding model for ticarcillin (penicillin): seven coupled ODEs
for the rate of net influx of drug across the outer membrane into
periplasm and the competitive, mass-balanced acylation of six PBPs (1a,
1b, 2, 3, 4, 5/6) counted as molecules per bacterial cell. The intact
parameter switches between the intact whole-cell assay
(penetration-limited; drug enters periplasm at Rate_Influx/access) and
the lysed isolated-membrane assay (no outer membrane; a vast excess of
drug molecules is present at time 0). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Chen_2023_tilmicosin.html">Tilmicosin
(Chen 2023)</a> </td>
<td style="text-align:left;"> Preclinical (piglet, Duroc x
Landrace x Yorkshire crossbred). Sigmoidal Emax PK/PD-integration model
for the antibacterial effect of orally administered tilmicosin against
Pasteurella multocida serovar D:7 (strain C44-15, MIC = 0.25 ug/mL) in
subcutaneously implanted tissue-cage fluid (TCF). Chen 2023 Section 2.6
parameterises the antibacterial effect over a 24 h dosing interval as E
= E0 + (Emax - E0) * Ce^N / (EC50^N + Ce^N), where E is the MAGNITUDE of
the log10(CFU/mL) reduction accrued over that interval (positive =
kill), E0 is the corresponding change in the untreated control, and Ce
is a PK/PD index. The packaged model uses the paper's best-correlating
index AUC24h/MIC (R^2 = 0.92, versus 0.90 for Cmax/MIC and 0.83 for
%T>MIC), formed as the per-interval covariate AUC_TILM divided by the
parameter mic. Parameters from Chen 2023 Table 2: Emax = 1.09
log10(CFU/mL), E0 = 0.003 log10(CFU/mL), EC50 = 26.66 h, Hill N = 2.69.
The bacterial density bact (linear CFU/mL) is integrated as d/dt(bact) =
-ln(10) * (E / 24) * bact so that log10(bact) falls by exactly E across
each 24 h interval, reproducing the paper's per-interval model exactly
at every time the paper actually counted bacteria (24 h boundaries
only). There is NO PK component: tilmicosin exposure enters as the
externally supplied per-interval AUC_TILM, because Chen 2023 analysed
the tissue-cage-fluid concentrations non-compartmentally in WinNonlin
(Table 1 reports NCA AUC0-24h, Cmax and T>MIC per dose group per
dosing day) and reported no structural PK model. Neither between-subject
variability nor a residual error magnitude was reported, so no eta
parameters are present and addSd is FIXED at 0; the model is intended
for typical-value simulation. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/PerezRuixo_2006_tipifarnib.html">Tipifarnib
(PerezRuixo 2006)</a> </td>
<td style="text-align:left;"> Three-compartment population PK
model for oral and IV tipifarnib in healthy subjects and adult cancer
patients (Perez-Ruixo 2006). Sequential zero-order release into the
depot (duration D1) followed by first-order absorption (Ka) into the
central compartment, with absorption lag time, linear elimination, two
peripheral compartments, and bioavailability fixed at 26.7 percent.
Covariate effects retained in the final model are total bilirubin on CL
(power exponent -0.103 centred at 9 umol/L) and body weight on V2
(linear scaling, exponent fixed at 1, centred at 70 kg);
healthy-vs-cancer cohort multipliers apply to CL, V2, Q4, V4, and Ka; a
solution-vs-solid formulation indicator scales D1, Ka, and tlag. The
mixture-model lag-time subpopulation (71.7 percent subpop 1 vs 28.3
percent subpop 2) is collapsed to the typical subpop-1 lag time for
library simulation use; correlated IIVs with paper-reported correlation
1 (Q3-V3, CL-Q4, CL-V4) are encoded as derived etas via the published
variance-expansion factors. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Stein_2019_Tisagenlecleucel.html">Tisagenlecleucel
(Stein 2019)</a> </td>
<td style="text-align:left;"> Cellular kinetic model for
tisagenlecleucel CAR-T cells in pediatric and young adult patients with
relapsed or refractory B-cell acute lymphoblastic leukemia (Stein 2019).
Single-infusion expansion-then-biexponential-decline analytical model:
transgene levels grow exponentially at rate rho up to Tmax, after which
effector cells decline at rate alpha and a fraction FB transitions to
memory cells declining at rate beta. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Budha_2023_tislelizumab.html">Tislelizumab
(Budha 2023)</a> </td>
<td style="text-align:left;"> Three-compartment population PK
model for intravenous tislelizumab (anti-PD-1 IgG4) in patients with
advanced tumors (Budha 2023) </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/McLaughlin_2024_tld_1.html">Tld
1 (McLaughlin 2024)</a> </td>
<td style="text-align:left;"> Joint parent (entrapped) + free +
metabolite (doxorubicinol) population PK model for TLD-1, a novel
small-diameter pegylated liposomal doxorubicin, in 30 adults with
advanced solid tumours (McLaughlin 2024 phase I dose-escalation, SAKK
65/16 / NCT03387917). Structure: one-compartment liposomal-entrapped
reservoir (V1) with linear release into the free-doxorubicin central
compartment (release rate krel = CL1/V1); free doxorubicin disposition
is two- compartment (Vc, Vp, Q) with linear metabolism-to-doxorubicinol
clearance (CL); doxorubicinol is one-compartment with linear elimination
(Vc_doxol, CL_doxol). Body surface area (BSA, reference 1.75 m^2) is the
only retained covariate, entering as a power model on the
free-doxorubicin central (V2 exponent 4.47) and peripheral (V3 exponent
11.5) volumes. Inter-individual variability is fitted on CL1 (release),
V1 (shared-eta scale 0.643 of ome_CL1), CL2 (free->doxol) and CL4
(doxol elimination); inter-occasion variability on CL1, CL2, V1, V2 from
Table 2 is documented but not encoded structurally here (nlmixr2lib has
no canonical occasion-column convention; see Hempel 2003 / Hong 2006
precedents). Residual error is log-transformed-both-sides additive on
the log scale -- equivalent to proportional in nlmixr2's linear space
and encoded here as separate propSd per analyte. Distinct from Hempel
2003 (paediatric liposomal daunorubicin, total drug only) and
Varatharajan 2016 (free daunorubicin + daunorubicinol in adult AML, no
liposomal reservoir). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Hennig_2013_tobra.html">Tobra
(Hennig 2013)</a> </td>
<td style="text-align:left;"> Two-compartment intravenous
population PK model for tobramycin in adults and children with and
without cystic fibrosis (Hennig 2013); fat-free mass allometric scaling
on CL/Q (estimated exponent) and on V1/V2 (linear), sex-specific
reference CL and V1, piecewise-linear age effect on CL with breakpoint
at 18 years, and a power effect of the SCR_mean/SCR ratio on CL.
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Conil_2010_tobramycin.html">Tobramycin
(Conil 2010)</a> </td>
<td style="text-align:left;"> Two-compartment IV population PK
model for tobramycin in adult ICU patients receiving once-daily
aminoglycoside therapy for nosocomial Gram-negative infections (Conil
2010); additive linear covariate effects of Cockcroft-Gault creatinine
clearance and height on CL, with no IIV on Q or V2. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Hennig_2008_tobramycin.html">Tobramycin
(Hennig 2008)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model for once-daily IV tobramycin in paediatric cystic fibrosis
patients (Hennig 2008), with allometric weight scaling on CL, Q, Vc, and
Vper (reference 70 kg, exponent 3/4 for clearances and 1 for volumes),
full-block correlated between-subject variability on CL/Vc/Vper, a fixed
30 min infusion duration into the central compartment, and an estimated
lag time between infusion start and drug entry into the patient's vein.
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Livio_2014_tobramycin.html">Tobramycin
(Livio 2014)</a> </td>
<td style="text-align:left;"> One-compartment population PK
model with first-order absorption for systemic tobramycin released from
an implanted calcium-sulfate bone-graft substitute (Osteoset T) in
adults undergoing orthopedic surgery (Livio 2014); clearance equated to
Cockcroft-Gault creatinine clearance under the assumption that absorbed
tobramycin is exclusively eliminated by glomerular filtration, and
absolute bioavailability differing between the 10 g (262 mg tobramycin)
and 20 g (524 mg tobramycin) Osteoset T cast cohorts. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Ting_2014_tobramycin_inhaled.html">Tobramycin
inhaled (Ting 2014)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model for inhaled tobramycin powder (TIP / TOBI Podhaler) in cystic
fibrosis patients (Ting 2014), with first-order absorption from a depot
compartment and apparent (post-bioavailability) clearance and volumes.
Body mass index (BMI) and baseline FEV1 percent-predicted are power-form
covariates on apparent central volume of distribution (reference 18.8
kg/m^2 and 62.1 % respectively). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Marier_2002_tobramycin_rat_conventional.html">Tobramycin
rat conventional (Marier 2002)</a> </td>
<td style="text-align:left;"> Preclinical (rat).
Two-compartment population PK model for the conventional (non-liposomal)
formulation of tobramycin (Tobi inhalation solution, PathoGenesis) after
a single 1,200 ug intratracheal dose to male Sprague-Dawley rats with
chronic Burkholderia cepacia (strain BC 1368) pulmonary infection.
NONMEM ADVAN4 (depot, central, peripheral) parameterised in
rate-constant form: first-order absorption ka into a lung central
compartment carrying drug amount (not concentration -- volumes of
distribution were not fitted because the dependent variable was the
amount of tobramycin recovered from homogenised lung tissue, calculated
as the measured tissue concentration times the lung volume per animal),
inter-compartmental rate constants k12 and k21 between central and
peripheral, first- order elimination kel from central, and a fitted lung
bioavailability FL accounting for the fraction of the intratracheal dose
actually reaching the lung tissue compartment. Comparator arm for
Marier_2002_tobramycin_rat_liposomal; the conventional formulation shows
faster absorption, faster elimination, and ~8-fold lower lung AUC than
the liposomal formulation in the source paper (Table 1, Results).
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Marier_2002_tobramycin_rat_liposomal.html">Tobramycin
rat liposomal (Marier 2002)</a> </td>
<td style="text-align:left;"> Preclinical (rat).
Two-compartment population PK model for the liposomal formulation of
tobramycin (DPPC:DMPG 10:1 phospholipids, 230-400 nm extruded) after a
single 1,200 ug intratracheal dose to male Sprague-Dawley rats with
chronic Burkholderia cepacia (strain BC 1368) pulmonary infection.
NONMEM ADVAN4 (depot, central, peripheral) parameterised in rate-
constant form: first-order absorption ka into a lung central compartment
carrying drug amount (not concentration -- volumes of distribution were
not fitted because the dependent variable was the amount of tobramycin
recovered from homogenised lung tissue, calculated as the measured
tissue concentration times the lung volume per animal),
inter-compartmental rate constants k12 and k21 between central and
peripheral, first-order elimination kel from central, and a fitted lung
bioavailability FL accounting for the fraction of the intratracheal dose
actually reaching the lung tissue compartment. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Bastida_2018_tocilizumab.html">Tocilizumab
(Bastida 2018)</a> </td>
<td style="text-align:left;"> One-compartment population PK
model for intravenous tocilizumab in adults with rheumatoid arthritis
(Bastida 2018), with parallel first-order linear and Michaelis-Menten
elimination from the central compartment; total body weight and
time-varying C-reactive protein on linear CL. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Frey_2010_tocilizumab.html">Tocilizumab
(Frey 2010)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model for tocilizumab in adults with moderate-to-severe rheumatoid
arthritis (Frey 2010), with parallel first-order linear and
Michaelis-Menten elimination from the central compartment. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Frey_2013_tocilizumab.html">Tocilizumab
(Frey 2013)</a> </td>
<td style="text-align:left;"> Indirect-response PK/PD model of
tocilizumab on the 28-joint Disease Activity Score (DAS28) in adults
with rheumatoid arthritis (Levi/Grange/Frey 2013, OPTION + TOWARD phase
III pool, n = 1703 patients with 12,618 DAS28 observations). Tocilizumab
inhibits the DAS28 production rate kin via a sigmoid emax function whose
driving concentration is the sum of circulating tocilizumab and a
constant DMARD background term expressed in tocilizumab concentration
units. The PK driver is the two-compartment, parallel linear +
Michaelis-Menten model of Frey 2010 (PMID 20097931), reused unchanged
for the exposure-response analysis. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Jorga_2000_tolcapone.html">Tolcapone
fluctuators (Jorga 2000)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model with first-order absorption (no lag) for tolcapone in parkinsonian
patients with fluctuating levodopa response, with effects of lean body
weight and serum protein on clearance, lean body weight and dose group
on central volume, serum albumin and dose group on peripheral volume,
and concomitant food on bioavailability (Jorga 2000, fluctuator dataset,
n=215) </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Jorga_2000_tolcapone.html">Tolcapone
nonfluctuators (Jorga 2000)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model with first-order absorption and absorption lag for tolcapone in
parkinsonian patients with stable (non-fluctuating) levodopa response,
with effects of creatinine clearance on clearance, serum protein on
central volume, and concomitant food on bioavailability (Jorga 2000,
nonfluctuator dataset, n=60) </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Yamamoto_2023_tominersen.html">Tominersen
(Yamamoto 2023)</a> </td>
<td style="text-align:left;"> Six-compartment population PK
model for tominersen (2'-O-methoxyethyl antisense oligonucleotide
targeting huntingtin mRNA) following intrathecal lumbar-puncture
administration in adults with Huntington's disease (Yamamoto 2023). Two
coupled three-compartment subsystems: the intrathecal bolus enters the
central CSF compartment, which exchanges with two CNS-tissue
compartments and drains unidirectionally into the plasma central
compartment via CL_CSF (bioavailability F1 and F2 both fixed to 1); the
plasma central compartment has two peripheral compartments and
first-order elimination. Baseline CSF total protein, age, and antidrug
antibodies are covariates on CL_CSF; body weight is an allometric power
covariate on all plasma clearances and volumes, and antidrug antibodies
and female sex are covariates on plasma CL. Residual error is additive
on the log scale (lognormal) for both CSF and plasma, each with
interindividual variability on the residual magnitude. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Ahmed_2015_topiramate.html">Topiramate
(Ahmed 2015)</a> </td>
<td style="text-align:left;"> Population PK/PD model of
topiramate (TPM) and its acute effect on phonemic generative fluency
(Controlled Oral Word Association, COWA) in healthy adult volunteers
given single oral or intravenous doses of 50-100 mg (Ahmed 2015).
Two-compartment popPK with first-order absorption and elimination, oral
bioavailability ~108%, allometric body-weight scaling on CL/Q (fixed
3/4) and Vc/Vp (fixed 1); separate proportional residual errors for oral
and IV cohorts. PD: COWA = baseline * practice_factor * exp(-KE * Cc),
where the practice factor inflates baseline by 12% beginning with the
fourth (and subsequent) COWA test administration and KE = 0.157 L/mg
gives a 14.5% drop in COWA per 1 mg/L rise in plasma TPM. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Lee_2024_topiramate.html">Topiramate
(Lee 2024)</a> </td>
<td style="text-align:left;"> One-compartment population PK
model with first-order absorption and elimination for topiramate (TPM)
in Korean adults with epilepsy undergoing routine therapeutic drug
monitoring (Lee 2024). Apparent clearance CL/F carries an additive
enzyme-inducing antiseizure-medication term (separate coefficients in
L/h for phenytoin, carbamazepine, oxcarbazepine and phenobarbital), a
power effect of creatinine clearance normalized to 90 mL/min, and a
power effect of the topiramate daily dose normalized to 100 mg/day;
apparent volume Vd/F scales allometrically with body weight (exponent
fixed at 1) centred at 62 kg. Absorption rate constant fixed at 2 /h.
Inter-individual variability on CL/F only (31.0 %CV) with a proportional
residual error of 27.8%. The structural model was carried from Bae 2016
and all parameters were re-estimated on the present
therapeutic-drug-monitoring dataset. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Vuu_2016_topiramate_dog.html">Topiramate
dog (Vuu 2016)</a> </td>
<td style="text-align:left;"> Preclinical (dog). Population
two-compartment intravenous PK model for topiramate (TPM) in dogs with
naturally-occurring epilepsy (Vuu 2016). Stable-labelled TPM was given
as a 5-min IV infusion at 10 mg/kg (n = 4) or 20 mg/kg (n = 3); pooled
across the low- and high-dose data, a two- compartment model with
first-order elimination from the central compartment described the
disposition best. Concomitant phenobarbital (CONMED_PB) was identified
as an enzyme-inducer covariate on systemic clearance via an exponential
effect (Cl = tvCl * exp(dCl * CONMED_PB)), yielding a 5.64-fold higher
CL in PB-coadministered dogs. Per-kg structural parameters (Vc, Vp, CL,
Q) are scaled to absolute units by individual body weight (WT, kg)
inside the model; the dose in the event table is therefore absolute mg
(mg/kg dose times WT). IIV is exponential on Vc and CL; residual error
is proportional (~15%). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Leger_2004_topotecan.html">Topotecan
(Leger 2004)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model for oral and intravenous topotecan in adult cancer patients, with
first-order absorption + lag time for the oral route, additive linear
creatinine-clearance plus linear-ordinal WHO performance-status effects
on CL, and linear body-weight effect on the central volume of
distribution (Leger 2004) </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Roberts_2016_topotecan.html">Topotecan
(Roberts 2016)</a> </td>
<td style="text-align:left;"> One-compartment population
pharmacokinetic model for oral topotecan lactone in infants and very
young children with primary central nervous system tumours (Roberts
2016). First-order absorption into a depot compartment is followed by
first-order elimination from a central compartment. Apparent volume of
distribution (V/F) and apparent clearance (CL/F) are scaled by body
surface area as power functions centred on the cohort median (0.57 m^2);
the ABCG2 rs4148157 G>A variant (heterozygous AG or homozygous AA
carriers pooled vs the GG reference) carries an exponential covariate
effect on the absorption rate constant Ka, yielding an approximately
2-fold higher Ka in carriers than in GG homozygotes. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Saleh_2023_leicns_pk30_mouse_brain.html">Topotecan
mouse pbpk (Saleh 2023)</a> </td>
<td style="text-align:left;"> PBPK (LeiCNS-PK3.0 CNS
physiologically-based model, mouse version). Preclinical (mouse, CD1
nude). Nine-compartment CNS PBPK model predicting unbound topotecan
concentrations in brain extracellular fluid (brain ECF) after a single 4
mg/kg intravenous dose. The CNS structure is the mouse
re-parameterisation of LeiCNS-PK3.0: brain microvasculature
(brain_vascular), brain ECF, a phospholipid brain-cell-membrane binding
compartment (brain_cell_membrane), brain intracellular fluid
(brain_icf), lysosomes (brain_lysosome), and the four CSF compartments
(lateral ventricles, third + fourth ventricles, cisterna magna,
subarachnoid space) draining in series back to plasma. Transport across
the BBB and BCSFB is the sum of a paracellular clearance (Qp, charged +
neutral drug) and a transcellular clearance (Qt, neutral drug only,
scaled by pH-dependent neutral fractions PHF and by asymmetry factors AF
that encode active transport). Every CNS parameter is fixed to mouse
physiology (Table III) or derived from the drug's physicochemical
properties (Table I); none was fitted here. The BBB asymmetry factors
are back-calculated from Kp,uu,BBB = 0.21 (taken from ref [57]; Table
V). The plasma PK model is the empirical two-compartment model of Table
IV (in-house NONMEM fit) and acts purely as a forcing function: brain
uptake does not deplete plasma, exactly as published. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Jeong_2022_torsemide.html">Torsemide
(Jeong 2022)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model for oral torsemide in healthy Korean adult males (Jeong 2022),
with first-order absorption after a lag time, proportional residual
error, and categorical genotype covariates: OATP1B1 *15 haplotype
(intermediate / poor transporter) reduces apparent central volume, and
CYP2C9 extensive-metabolizer phenotype increases apparent oral clearance
and apparent inter-compartmental clearance. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Baverel_2015_tralokinumab.html">Tralokinumab
(Baverel 2015)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model for tralokinumab in adolescent (12-17 y) and adult subjects with
asthma or healthy volunteers (Baverel 2015), with parallel subcutaneous
absorption (first-order with lag plus zero-order over a fixed duration),
allometric body-weight scaling on disposition parameters, and an
additional 15% lower clearance in adolescents. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Soehoel_2022_tralokinumab.html">Tralokinumab
(Soehoel 2022)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model for tralokinumab (Soehoel 2022) in adults with moderate-to-severe
atopic dermatitis, with SC first-order absorption and allometric
body-weight effects. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Mercier_2014_tramadol_tapentadol.html">Tramadol
tapentadol mbma (Mercier 2014)</a> </td>
<td style="text-align:left;"> MBMA. Longitudinal model-based
meta-analysis pain-intensity time-course model comparing tramadol and
tapentadol in adults with chronic non-malignant pain (osteoarthritis,
back pain, neuropathic pain, and other chronic non-malignant pain), fit
to arm-level summary data from 45 double-blind Phase II/III randomized
clinical trials representing 81 treatment arms and approximately 12,985
patients. Pain intensity on a normalized 0-10 scale is described by a
logistic (expit) latent-scale model: PI(t) = 10 * expit(Base + R * (1 -
exp(-k*t))), where the extent-of-reduction term R has an Emax-in-dose
form for tramadol: R = R_Pla * (1 + theta_Base * logit(PI0/10) +
theta_Trm * Dose_trm / (Dose_trm + ED50) * TRAMADOL + theta_Tap *
TAPENTADOL). Between-study-arm variability enters additively on Base (SD
0.313 on the latent scale) and exponentially on R (SD 0.065). The
residual variance is inversely proportional to per-arm sample size N;
the paper reports two scale-dependent residual SDs (VAS/continuous SD
0.260 and categorical SD 0.205) and this file exposes the dominant VAS
SD as the primary residual, with the categorical SD documented in ini()
and in the vignette Assumptions/Errata. Suitable simulation scope is
study-arm-mean pain-intensity time-course over 0-15 weeks (one 52-week
trial contributed but the paper's simulations use 12 weeks); NOT
individual-patient predictions. Tramadol was studied over a wide dose
range (adequate to characterize a dose-response); tapentadol was only
studied over 100-250 mg bid (no dose-response estimable), so the
tapentadol effect is a single per-arm indicator effect. The paper also
fit separate logistic MBMA sub-models for adverse events (constipation,
nausea, vomiting, dizziness, somnolence) and drop-outs (due to adverse
event, lack of efficacy); those sub-models are reported only as
graphical odds ratios in Figs 3-4 with no tabulated logistic intercepts
or slopes, so they are NOT extracted here (see vignette Errata for the
omission). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Dunn_2025_tranexamicAcid.html">TranexamicAcid
(Dunn 2025)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model for tranexamic acid (TXA) with parallel first-order intramuscular
and first-order oral absorption (oral lag time) and first-order
elimination, in pregnant individuals receiving IV, IM, or oral TXA for
prevention or treatment of postpartum hemorrhage (Dunn 2025).
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Bruno_2005_trastuzumab.html">Trastuzumab
(Bruno 2005)</a> </td>
<td style="text-align:left;"> Two-compartment linear population
PK model for intravenous trastuzumab in adults with HER2-positive
metastatic breast cancer (MBC) or advanced solid tumors; covariate
effects of number of metastatic sites (>= 4) and baseline HER2 shed
extracellular domain (ECD) on clearance, and body weight and ECD on
central volume (Bruno 2005, first published trastuzumab popPK).
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/LeTilly_2021_trastuzumab.html">Trastuzumab
(LeTilly 2021)</a> </td>
<td style="text-align:left;"> Two-compartment serum/CSF
population PK model for trastuzumab after intrathecal and intravenous
administration in adults with HER2+ breast cancer leptomeningeal
metastases (Le Tilly 2021); zero-order serum-to-CSF transfer plus
first-order CSF-to-serum return, with a Friberg-style chain of latent
target (HER2) transit compartments and irreversible binding-driven
elimination of trastuzumab in the CSF compartment. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Marcantonio_2022_efa.html">Trastuzumab
(Marcantonio 2022)</a> </td>
<td style="text-align:left;"> QSP. Two-compartment monospecific
anti-receptor mechanistic PKPD model of trastuzumab-HER2 binding in
adults with HER2-overexpressing breast cancer (Marcantonio 2022 Early
Feasibility Assessment, Case Study 2/3). Drug administered IV as a
bivalent (valency = 2) antibody that binds membrane HER2 (in central and
peripheral compartments) and soluble HER2 (the shed extracellular
domain) via independent binding events with identical Kd. All species
eliminate first-order; drug bound to membrane receptor eliminates at the
receptor's rate; drug bound to soluble receptor eliminates at the drug's
rate. Only soluble species (Ab_00, Ab_0S, Ab_S0, Ab_SS, S1) distribute
between central and peripheral; membrane-bound drug forms (Ab_0R, Ab_R0,
Ab_RR, Ab_RS, Ab_SR) stay in their compartment. The endogenous HER2
ligand is not resolved (paper sets its concentration to effectively
zero) so L1 and L1R1 species are omitted here. Parameters FIXED from
paper Table S7 and JSON run file; disease and toxicity compartments are
omitted per paper Case Study 2 text. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Quartino_2016_trastuzumab.html">Trastuzumab
(Quartino 2016)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model with parallel linear and Michaelis-Menten nonlinear elimination
from the central compartment and first-order subcutaneous absorption
(with bioavailability) for trastuzumab (Herceptin) administered IV or as
a fixed 600 mg manual-syringe SC dose in women with HER2-positive early
breast cancer; covariates body weight (on CL, Vc, Vp) and ALT (on CL)
(Quartino 2016, HannaH study) </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Quartino_2019_trastuzumab.html">Trastuzumab
(Quartino 2019)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model with parallel linear and Michaelis-Menten nonlinear elimination
from the central compartment for intravenous trastuzumab (Herceptin) in
patients with metastatic breast cancer, early breast cancer, advanced
gastric cancer, or other solid tumors (Quartino 2019) </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Reijers_2016_trastuzumab.html">Trastuzumab
(Reijers 2016)</a> </td>
<td style="text-align:left;"> Three-compartment population PK
model with parallel linear and Michaelis-Menten nonlinear elimination
from the central compartment for intravenous trastuzumab in healthy male
volunteers from a phase I biosimilarity trial of the FTMB biosimilar vs
Herceptin reference product (Reijers 2016, combined model on all dose
levels 0.49-6.44 mg/kg); covariates are lean body mass on central volume
of distribution V1 and BMI on the linear elimination rate constant ke.
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/deVriesSchultink_2018_cardiotoxicity.html">Trastuzumab
LVEF (deVriesSchultink 2018)</a> </td>
<td style="text-align:left;"> Effect-compartment PD model for
left-ventricular ejection fraction (LVEF) decline during adjuvant
trastuzumab treatment in HER2-positive early breast cancer (de Vries
Schultink 2018). Trastuzumab pharmacokinetics are an inlined
deterministic forcing function from the previously published Bruno 2005
two-compartment linear popPK (de Vries Schultink 2018 Methods: 'The
trastuzumab PK profiles were obtained using fixed effect parameters from
a previously published PK model for HER2-positive breast cancer patients
[18]'); typical population values plus WT / HER2_ECD / MET_GE4 covariate
effects are retained from Bruno 2005 Table 3. Cardiac damage is
generated by cumulative trastuzumab concentration via an effect
compartment Ceff that integrates plasma Ctrastuzumab and decays at rate
log(2)/T1/2rec; LVEF declines through a sigmoid Emax expression LVEF =
LVEF0 * (1 - Ceff / (Ceff + EC50)), and the EC50 is modulated by the
per-subject peak post-anthracycline troponin T (TROPONIN_T_MAX), with a
higher TROPONIN_T_MAX lowering EC50 and increasing sensitivity to
trastuzumab-induced cardiotoxic decline. Companion file
`deVriesSchultink_2018_anthracycline_troponinT.R` supplies the upstream
K-PD anthracycline-troponin T model whose peak output is used here as a
covariate. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/FehlingKaschek_2019_trastuzumab_skbr3.html">Trastuzumab
skbr3 (FehlingKaschek 2019)</a> </td>
<td style="text-align:left;"> In vitro (SKBR3 cell line).
Mechanistic ODE model of trastuzumab-induced HER2 receptor
internalization with two cell-membrane phenotypes (ruffled vs flat);
Model B of Fehling-Kaschek 2019, no recycling or degradation.
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Yin_2021_trastuzumabDeruxtecan.html">TrastuzumabDeruxtecan
(Yin 2021)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model for intact trastuzumab deruxtecan (T-DXd, DS-8201, anti-HER2
antibody-drug conjugate) with linear elimination and covariate effects
of body weight, albumin, baseline tumor size, sex, and Japan-country
indicator in patients with HER2-positive breast cancer or other
HER2-expressing solid tumors (Yin 2021) </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Asiimwe_2025_trastuzumab_ADCs_mbma.html">TrastuzumabDeruxtecan
mbma (Asiimwe 2025)</a> </td>
<td style="text-align:left;"> MBMA. Two-compartment linear
population PK model of trastuzumab deruxtecan (T-DXd, DS-8201, Enhertu,
anti-HER2 antibody-drug conjugate) fitted by model-based meta-analysis
to summary-level concentration-time data digitised from 4 published
clinical trials in patients with HER2-positive breast, non-small-cell
lung, gastric/GEJ, colorectal and other solid tumors. Between-study
variability (BSV) is a study-level random effect on CL and Vc (block
correlation 0.915) representing differences in inclusion criteria across
trials and dose-escalation arms treated as separate studies. Residual
error is proportional + additive on serum concentration (ng/mL) and was
weighted by the square root of each trial's sample size during fitting;
the tabulated parameter estimates are the unweighted values and
simulation of a study of N subjects should scale the residual SD by
1/sqrt(N). Suitable simulation scope is study-arm-mean cycle-1
concentration-time profiles, NOT individual-patient concentrations.
Parameter values are the T-DXd column of Asiimwe 2025 Table 1 (Monolix
2024R1). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Lu_2014_trastuzumabemtansine.html">Trastuzumabemtansine
(Lu 2014)</a> </td>
<td style="text-align:left;"> Linear two-compartment population
PK model of trastuzumab emtansine (T-DM1, anti-HER2 antibody-drug
conjugate) with first-order elimination from the central compartment in
patients with HER2-positive locally advanced or metastatic breast cancer
(Lu 2014) </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Asiimwe_2025_trastuzumab_ADCs_mbma.html">TrastuzumabEmtansine
mbma (Asiimwe 2025)</a> </td>
<td style="text-align:left;"> MBMA. Two-compartment linear
population PK model of trastuzumab emtansine (T-DM1, anti-HER2
antibody-drug conjugate) fitted by model-based meta-analysis to
summary-level concentration-time data digitised from 14 published
clinical trials in patients with HER2-positive metastatic breast cancer
and other HER2-positive solid tumors. Between-study variability (BSV) is
a study-level random effect on CL and Vc (block correlation 0.825)
representing differences in inclusion criteria and the pooling of Phase
I dose-escalation arms as separate 'studies'. Residual error is
proportional + additive on serum concentration (ng/mL) and was weighted
by the square root of each trial's sample size during fitting; the
tabulated parameter estimates are the unweighted values and simulation
of a study of N subjects should scale the residual SD by 1/sqrt(N).
Suitable simulation scope is study-arm-mean cycle-1 concentration-time
profiles, NOT individual-patient concentrations. Parameter values are
the T-DM1 column of Asiimwe 2025 Table 1 (Monolix 2024R1). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Bender_2014_trastuzumabEmtansine_mechanistic.html">TrastuzumabEmtansine
mechanistic (Bender 2014)</a> </td>
<td style="text-align:left;"> Mechanistic DAR0-DAR7 catenary
deconjugation PK model for trastuzumab emtansine (T-DM1) in cynomolgus
monkeys (default) and rats (Bender 2014): each DAR moiety distributes
into a shared three-compartment backbone and deconjugates sequentially
toward naked trastuzumab (DAR0); uses five shared upper-chain rate
constants (k7->3) plus separate k_2->1 and k_1->0. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Bender_2014_trastuzumabEmtansine_reduced.html">TrastuzumabEmtansine
reduced (Bender 2014)</a> </td>
<td style="text-align:left;"> Reduced three-compartment
population PK model for trastuzumab emtansine (T-DM1) and naked
trastuzumab (DAR0) in cynomolgus monkeys (default) and rats (Bender
2014): single lumped T-DM1 conjugate species deconjugates into DAR0 via
a single deconjugation clearance; both species share V1/V2/V3 and
distributional clearances. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Hwang_2022_tremelimumab.html">Tremelimumab
(Hwang 2022)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model for tremelimumab (anti-CTLA-4 IgG2 kappa) with regimen-dependent
sigmoidal time-varying clearance in adults with advanced solid tumours,
dosed as monotherapy or in combination with durvalumab (Hwang 2022)
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Danielak_2017_treosulfan.html">Treosulfan
(Danielak 2017)</a> </td>
<td style="text-align:left;"> Two-compartment IV-infusion
population PK model for treosulfan (TREO) in pediatric patients
undergoing conditioning prior to hematopoietic stem cell transplantation
(Danielak 2017). Allometric body-weight scaling normalised to a 70 kg
adult typical value with exponents fixed at 0.75 on CL and 1 on V1 and
V2; Q has no weight covariate. Correlated IIV on CL and V1 (Cl-V1
correlation 0.714); independent IIV on Q. Proportional residual error.
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Park_2014_triflusal.html">Triflusal
(Park 2014)</a> </td>
<td style="text-align:left;"> One-compartment population PK
with first-order metabolite-formation kinetics for the active triflusal
metabolite hydroxy-4-(trifluoromethyl) benzoic acid (HTB) in healthy
Korean male volunteers, with a binary probability PD model for
inhibition of platelet aggregation (IPA). Triflusal is an antiplatelet
prodrug; only HTB is measured analytically. NONMEM ADVAN2 TRANS2 is used
by the source paper -- the canonical depot compartment carries triflusal
and the canonical first-order rate constant (here `lka`) plays the role
of the paper's HTB formation rate constant kf (0.341 1/h). Apparent oral
clearance CL/F (0.200 L/h at 71.65 kg) and apparent oral volume V/F
(8.300 L at 71.65 kg) describe HTB disposition; F absorbs the unknown
fraction of triflusal converted to HTB. Body weight is the only retained
covariate and enters as a power on CL/F (exponent 0.845) and direct
proportionality on V/F (exponent fixed to 1). PD endpoint is binary IPA
= 1 when platelet aggregation < 74% else 0; the instantaneous
probability of IPA is a sigmoid Hill function of HTB concentration,
prob_ipa = Cc^gamma / (EC50^gamma + Cc^gamma), with EC50 = 84.9 ug/mL
and gamma = 19.2 (BSV on gamma fixed to 0). The Hill exponent is very
steep (quantal-like concentration-response). Parameter values from Park
2014 Table 2 Estimates column. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Lee_2023_tripegfilgrastim.html">Tripegfilgrastim
(Lee 2023)</a> </td>
<td style="text-align:left;"> Semi-mechanistic population PK/PD
model for tripegfilgrastim (a PEGylated long-acting recombinant human
G-CSF) and absolute neutrophil count (ANC) in healthy Korean adults and
Korean pediatric patients with solid tumors receiving chemotherapy.
Subcutaneous drug enters a depot compartment and is absorbed at
first-order rate KSC into a total-drug compartment.
Pharmacodynamics-mediated drug disposition (PDMDD) uses a
quasi-equilibrium quadratic between total drug and the circulating
G-CSF-receptor pool, giving free drug (FDC) and bound complex (RDC).
Free drug is cleared linearly (CLD/VD) and bound drug is internalised
(KINT). Granulopoiesis is a five-state receptor chain (stem ->
mitotic -> post-mitotic I -> post-mitotic II -> circulating
blood receptors) with baselines KP/KTR and KP/KC; ANC = 1000 * RB / SR.
Drug binding stimulates receptor production (ST1 = 1 + STM1*driver) and
bone-marrow transit (ST2 = 1 + STM2*driver), where the driver is the
fraction of receptors bound by exogenous drug plus endogenous G-CSF.
Endogenous G-CSF is carried as its own turnover compartment (fixed KIN,
KEL, GCSF0 from Quartino 2014) and a negative-feedback term FB =
(RB0/RB)^GAM modulates receptor production. Chemotherapy is a KPD
virtual compartment with lag LAG; its output (KCHM*CHM) scaled by CHMSL
adds to the mitotic-cell elimination rate. Study population
(DIS_HEALTHY) shifts VD and KD, age scales KSC (exponent -0.97,
reference 18.5 y), body weight scales KINT (exponent 1.7, reference 55.1
kg), and baseline ANC scales KP (exponential, reference 2106 cells/uL).
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Tornoe_2006_HPG_axis.html">Triptorelin
(Tornoe 2006)</a> </td>
<td style="text-align:left;"> Population PK/PD model of the
hypothalamic-pituitary-gonadal (HPG) axis after a single 3.75 mg
subcutaneous (s.c.) depot injection of the GnRH agonist triptorelin in
healthy adult males. PK is a two-compartment disposition model with a
combined zero-order burst (fraction Fr of dose released over duration t
into central) and a two-step first-order s.c. absorption (lymphatic
delay) for the remaining (1 - Fr) fraction. PD is a four-state HPG-axis
feedback model (feedback compartment F, LH pool P, LH, testosterone Te)
with sigmoidal Emax stimulation of LH pool release by triptorelin and a
negative interaction (F^-1) from the feedback compartment on LH
synthesis and release; testosterone secretion is stimulated by LH via a
sigmoidal Emax model. ke_LH, ke_F, lambda, LH_base, and Te_base are the
triptorelin-study-specific values from Table 4. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Grimm_2023.html">Trontinemab
(Grimm 2023)</a> </td>
<td style="text-align:left;"> Trontinemab PK model in non-human
primates (Grimm 2023): two-compartment plasma PK with Michaelis-Menten
elimination and brain-region effect-compartment distribution
(brain_cerebellum, brain_hippocampus, brain_striatum, brain_cortex,
choroid plexus, CSF). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Pouzin_2022_tusamitamab.html">Tusamitamab
(Pouzin 2022)</a> </td>
<td style="text-align:left;"> Integrated multi-analyte
semi-mechanistic population PK model of tusamitamab ravtansine
(SAR408701, anti-CEACAM5 IgG1-SPDB-DM4 ADC) in adults with advanced
solid tumors (Pouzin 2022): explicit two-compartment disposition for
DAR1-DAR8 ADC species and a separate naked-antibody (NAB) chain sharing
Vc/Vp/Q, irreversible first-order DAR_n -> DAR_(n-1) deconjugation
feeding a one-compartment DM4 catabolite that converts to MeDM4.
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Lee_2023_tylosin.html">Tylosin
Apleuropneumoniae healthy (Lee 2023)</a> </td>
<td style="text-align:left;"> Preclinical (pig, crossbred Duroc
x (Landrace x Yorkshire)). Ex vivo sigmoidal Emax PK/PD-integration
model for the antibacterial effect of tylosin against Actinobacillus
pleuropneumoniae (challenge isolate BA2000013) in plasma drawn from
healthy pigs after a single 20 mg/kg intramuscular dose. Lee 2023
Section 2.8 parameterises the drug effect over a 24 h ex vivo incubation
as E = E0 - (Emax * C^gamma) / (C^gamma + EC50^gamma), where E is the
SIGNED log10(CFU/mL) difference between 0 and 24 h of incubation
(positive = net growth, negative = net kill), E0 is that same 24 h
change in the drug-free control, and C is the PK/PD index AUC24h/MIC.
Parameters from Lee 2023 Table 3, column 'A. pleuropneumoniae /
Healthy': Emax = 7.19 log10 CFU/mL, EC50 = 1.21 h, E0 = 2.84 log10
CFU/mL, gamma = 2.76. The parameterisation was confirmed numerically
against the paper's own independently printed rows: Emax - E0 reproduces
exactly (4.35), and solving E = 0 and E = -3 returns AUC24h/MIC = 1.037
and 2.057 h versus the published 0.98 and 1.97 h. The bacterial density
bact (linear CFU/mL) is integrated as d/dt(bact) = ln(10) * (E / 24) *
bact so that log10(bact) changes by exactly E across each 24 h window,
reproducing the paper's model at the only times bacteria were counted.
There is NO PK component: Lee 2023 analysed the plasma concentrations
non-compartmentally in WinNonlin 8.3 (Section 2.7; Table 2 reports only
Cmax, Tmax, T1/2, AUC, Vz/F, Cl/F and MRT) and published no structural
PK model, so exposure enters as the externally supplied covariate
AUCMIC_TYLO. That covariate carries the AUC24h/MIC RATIO directly
because Lee 2023 never reports the challenge isolates' own MIC -- only
that strains 'with MIC values similar to the MIC90' were chosen -- so no
MIC can be sourced to split the ratio into numerator and denominator.
Neither between-subject variability nor a residual error magnitude was
reported (the +/- values in Table 3 are standard deviations of point
estimates across the n = 3 animals whose plasma was used, not estimated
variance components), so there are no eta parameters and addSd is FIXED
at 0; the model is intended for typical-value simulation. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Lee_2023_tylosin.html">Tylosin
Apleuropneumoniae infected (Lee 2023)</a> </td>
<td style="text-align:left;"> Preclinical (pig, crossbred Duroc
x (Landrace x Yorkshire)). Ex vivo sigmoidal Emax PK/PD-integration
model for the antibacterial effect of tylosin against Actinobacillus
pleuropneumoniae (challenge isolate BA2000013) in plasma drawn from
co-infected pigs after a single 20 mg/kg intramuscular dose. Lee 2023
Section 2.8 parameterises the drug effect over a 24 h ex vivo incubation
as E = E0 - (Emax * C^gamma) / (C^gamma + EC50^gamma), where E is the
SIGNED log10(CFU/mL) difference between 0 and 24 h of incubation
(positive = net growth, negative = net kill), E0 is that same 24 h
change in the drug-free control, and C is the PK/PD index AUC24h/MIC.
Parameters from Lee 2023 Table 3, column 'A. pleuropneumoniae /
Infected': Emax = 7.34 log10 CFU/mL, EC50 = 1.33 h, E0 = 2.76 log10
CFU/mL, gamma = 1.86. The parameterisation was confirmed numerically
against the paper's own independently printed rows: Emax - E0 reproduces
exactly (4.58), and solving E = 0 and E = -3 returns AUC24h/MIC = 1.013
and 2.666 h versus the published 1.03 and 2.54 h. The bacterial density
bact (linear CFU/mL) is integrated as d/dt(bact) = ln(10) * (E / 24) *
bact so that log10(bact) changes by exactly E across each 24 h window,
reproducing the paper's model at the only times bacteria were counted.
There is NO PK component: Lee 2023 analysed the plasma concentrations
non-compartmentally in WinNonlin 8.3 (Section 2.7; Table 2 reports only
Cmax, Tmax, T1/2, AUC, Vz/F, Cl/F and MRT) and published no structural
PK model, so exposure enters as the externally supplied covariate
AUCMIC_TYLO. That covariate carries the AUC24h/MIC RATIO directly
because Lee 2023 never reports the challenge isolates' own MIC -- only
that strains 'with MIC values similar to the MIC90' were chosen -- so no
MIC can be sourced to split the ratio into numerator and denominator.
Neither between-subject variability nor a residual error magnitude was
reported (the +/- values in Table 3 are standard deviations of point
estimates across the n = 3 animals whose plasma was used, not estimated
variance components), so there are no eta parameters and addSd is FIXED
at 0; the model is intended for typical-value simulation. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Lee_2023_tylosin.html">Tylosin
Pmultocida healthy (Lee 2023)</a> </td>
<td style="text-align:left;"> Preclinical (pig, crossbred Duroc
x (Landrace x Yorkshire)). Ex vivo sigmoidal Emax PK/PD-integration
model for the antibacterial effect of tylosin against Pasteurella
multocida (challenge isolate BA1700127) in plasma drawn from healthy
pigs after a single 20 mg/kg intramuscular dose. Lee 2023 Section 2.8
parameterises the drug effect over a 24 h ex vivo incubation as E = E0 -
(Emax * C^gamma) / (C^gamma + EC50^gamma), where E is the SIGNED
log10(CFU/mL) difference between 0 and 24 h of incubation (positive =
net growth, negative = net kill), E0 is that same 24 h change in the
drug-free control, and C is the PK/PD index AUC24h/MIC. Parameters from
Lee 2023 Table 3, column 'P. multocida / Healthy': Emax = 6.98 log10
CFU/mL, EC50 = 1.17 h, E0 = 3.49 log10 CFU/mL, gamma = 4.78. The
parameterisation was confirmed numerically against the paper's own
independently printed rows: Emax - E0 reproduces exactly (3.49), and
solving E = 0 and E = -3 returns AUC24h/MIC = 1.170 and 2.009 h versus
the published 1.10 and 1.99 h. The bacterial density bact (linear
CFU/mL) is integrated as d/dt(bact) = ln(10) * (E / 24) * bact so that
log10(bact) changes by exactly E across each 24 h window, reproducing
the paper's model at the only times bacteria were counted. There is NO
PK component: Lee 2023 analysed the plasma concentrations
non-compartmentally in WinNonlin 8.3 (Section 2.7; Table 2 reports only
Cmax, Tmax, T1/2, AUC, Vz/F, Cl/F and MRT) and published no structural
PK model, so exposure enters as the externally supplied covariate
AUCMIC_TYLO. That covariate carries the AUC24h/MIC RATIO directly
because Lee 2023 never reports the challenge isolates' own MIC -- only
that strains 'with MIC values similar to the MIC90' were chosen -- so no
MIC can be sourced to split the ratio into numerator and denominator.
Neither between-subject variability nor a residual error magnitude was
reported (the +/- values in Table 3 are standard deviations of point
estimates across the n = 3 animals whose plasma was used, not estimated
variance components), so there are no eta parameters and addSd is FIXED
at 0; the model is intended for typical-value simulation. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Lee_2023_tylosin.html">Tylosin
Pmultocida infected (Lee 2023)</a> </td>
<td style="text-align:left;"> Preclinical (pig, crossbred Duroc
x (Landrace x Yorkshire)). Ex vivo sigmoidal Emax PK/PD-integration
model for the antibacterial effect of tylosin against Pasteurella
multocida (challenge isolate BA1700127) in plasma drawn from co-infected
pigs after a single 20 mg/kg intramuscular dose. Lee 2023 Section 2.8
parameterises the drug effect over a 24 h ex vivo incubation as E = E0 -
(Emax * C^gamma) / (C^gamma + EC50^gamma), where E is the SIGNED
log10(CFU/mL) difference between 0 and 24 h of incubation (positive =
net growth, negative = net kill), E0 is that same 24 h change in the
drug-free control, and C is the PK/PD index AUC24h/MIC. Parameters from
Lee 2023 Table 3, column 'P. multocida / Infected': Emax = 7.04 log10
CFU/mL, EC50 = 1.06 h, E0 = 3.41 log10 CFU/mL, gamma = 2.90. The
parameterisation was confirmed numerically against the paper's own
independently printed rows: Emax - E0 reproduces exactly (3.63), and
solving E = 0 and E = -3 returns AUC24h/MIC = 1.037 and 2.359 h versus
the published 1.12 and 2.36 h. The bacterial density bact (linear
CFU/mL) is integrated as d/dt(bact) = ln(10) * (E / 24) * bact so that
log10(bact) changes by exactly E across each 24 h window, reproducing
the paper's model at the only times bacteria were counted. There is NO
PK component: Lee 2023 analysed the plasma concentrations
non-compartmentally in WinNonlin 8.3 (Section 2.7; Table 2 reports only
Cmax, Tmax, T1/2, AUC, Vz/F, Cl/F and MRT) and published no structural
PK model, so exposure enters as the externally supplied covariate
AUCMIC_TYLO. That covariate carries the AUC24h/MIC RATIO directly
because Lee 2023 never reports the challenge isolates' own MIC -- only
that strains 'with MIC values similar to the MIC90' were chosen -- so no
MIC can be sourced to split the ratio into numerator and denominator.
Neither between-subject variability nor a residual error magnitude was
reported (the +/- values in Table 3 are standard deviations of point
estimates across the n = 3 animals whose plasma was used, not estimated
variance components), so there are no eta parameters and addSd is FIXED
at 0; the model is intended for typical-value simulation. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Zuo_2016_UDCA.html">UDCA
(Zuo 2016)</a> </td>
<td style="text-align:left;"> Systems model. Enterohepatic
recirculation of ursodeoxycholic acid (UDCA) and its glycine (GUDCA) and
taurine (TUDCA) conjugates in healthy adults, with adaptation to primary
biliary cirrhosis (PBC). 19 ODEs across stomach, intestine, portal vein,
blood, liver, biliary system, and feces compartments per analyte; oral
square-wave absorption (0.5 h) and meal/snack-modulated
biliary-to-intestinal flux. No IIV or residual error - typical-value
mechanistic simulation only. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Kim_2016_udenafil.html">Udenafil
(Kim 2016)</a> </td>
<td style="text-align:left;"> Parent-metabolite population PK
model for oral udenafil and its active metabolite DA-8164 in healthy
subjects and patients with mild (Child-Pugh A) and moderate (Child-Pugh
B) hepatic impairment (Kim 2016). Two-compartment udenafil with
first-order absorption and an absorption lag time, two parallel
parent-side clearances (CLp/F = non-metabolic apparent clearance, CLpm/F
= apparent formation clearance to DA-8164) feeding a two-compartment
metabolite. Central and peripheral apparent volumes are assumed equal
for parent and metabolite (the fraction metabolised f_m and the
metabolite volume of distribution are not separately identifiable from
this dataset). Mass-balance is preserved by multiplying the formation
flux into the metabolite central compartment by the molecular-weight
ratio Rpm = MW(DA-8164) / MW(udenafil) = 405.4 / 516.66. Prothrombin
time expressed as INR (PT) acts on CLpm/F via a power covariate
normalised to the cohort median 1.13: CLpm/F = theta1 *
(PT/1.13)^theta10 with theta10 = -1.65 (decrease in CLpm/F with
increasing PT). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Galluppi_2021_ulotaront.html">Ulotaront
(Galluppi 2021)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model with first-order oral absorption for ulotaront (SEP-363856), a
trace amine-associated receptor 1 (TAAR1) agonist with 5-HT1A agonist
activity in phase III development for schizophrenia. Pooled analysis of
nine studies (seven phase I, one phase II acute, one 6-month open-label
extension) in 404 adult subjects (99 healthy volunteers and 305 patients
with schizophrenia). Body weight was estimated as a power-form covariate
on the clearance parameters (CL/F, Q/F) and the volume parameters (Vc/F,
Vp/F); disease status, sex, race (Asian vs non-Asian), and age were
retained as full-model covariates on CL/F only. IIV on CL/F, Vc/F, ka,
Vp/F is modelled as a full 4x4 correlated BLOCK. Residual error is
proportional-only per AIC/BIC (Galluppi 2021). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/AlSallami_2016_unfractionatedHeparin.html">UnfractionatedHeparin
(AlSallami 2016)</a> </td>
<td style="text-align:left;"> One-compartment population PK +
linear pharmacodynamic model for unfractionated heparin (UFH) in
paediatric patients receiving a single high intravenous bolus dose
during cardiac angiography (Al-Sallami 2016). Fat-free mass (FFM) scales
heparin clearance linearly and total body weight (WT) scales the central
volume of distribution linearly. The PD layer is a linear
concentration-effect model relating activated partial thromboplastin
time (aPTT) to plasma heparin concentration (E0 + slope x Cc). The IV
bolus was modelled in the source paper as a 0.1 h zero-order input
(theta_D1 = 0.1 h, fixed); reproduce this in simulation by dosing the
central compartment with rate = -2 to engage the model-defined duration.
PD parameters were estimated sequentially via PPP&D with the PK
parameters fixed at the values reported in Table 2. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Jia_2015_unfractionatedHeparin.html">UnfractionatedHeparin
(Jia 2015)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model with first-order elimination for unfractionated heparin (UFH)
administered as multiple intravenous bolus injections during
cardiopulmonary bypass (CPB) in adult Chinese cardiac surgery patients
(Jia 2015). Plasma UFH exposure was inferred from anti-FIIa chromogenic
activity. No covariates were retained in the final model (age, body
weight, and sex were tested via forward inclusion / backward elimination
and none met the p < 0.001 retention threshold). Concentrations are
reported in IU/mL of anti-FIIa activity; doses are in IU (1 mg UFH = 125
IU). The published model also describes instantaneous neutralization of
central-compartment UFH at protamine sulfate dosing (see vignette for
the simulation pattern); the structural ODEs here are the standard
two-compartment IV bolus form. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Klunder_2017_upadacitinib.html">Upadacitinib
(Klunder 2017)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model with first-order absorption and an absorption lag time for oral
upadacitinib (ABT-494), a selective JAK1 inhibitor, in healthy adults
and adults with rheumatoid arthritis (Klunder 2017, pooled phase I +
phase IIb analysis). Statistically significant covariates retained in
the final model: population (RA vs healthy) on CL/F, sex on CL/F and
Vc/F, baseline creatinine clearance on CL/F (raw Cockcroft-Gault, not
BSA-normalized), and total body weight on Vc/F. ISV is reported
separately for healthy subjects and RA patients on CL/F and Vc/F, and is
encoded here as paired healthy / RA structural means with
cohort-specific log-normal random effects gated by DIS_HEALTHY.
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/vandenBerg_2021_uprifosbuvir.html">Uprifosbuvir
pbpk (vandenBerg 2021)</a> </td>
<td style="text-align:left;"> PBPK-PD (minimal PBPK;
well-stirred liver + Qgut gut wall + intrahepatic UXP/CXP nucleotide
cycle) for uprifosbuvir (MK-3682), an HCV NS5B nucleoside polymerase
inhibitor, and its plasma metabolites M5 and M6, with a sigmoid Emax
link from intrahepatic UXP to viral inhibition (epsilon). 22 ODE
compartments (gut absorption + transit chains, hepatic + portal-vein +
central + two peripherals for parent, intrahepatic UXP/CXP cycle, M5 and
M6 central + M5 gut transit chain, pseudo-M4 gut pool). All parameters
fixed at the final NONMEM point estimates (Tables 1-6 of van den Berg
2021). Supports i.v. (25 mg), tablet oral (150-750 mg) and capsule oral
(50-400 mg) dosing in HV and HCV patients, with optional itraconazole
DDI encoded via covariate multipliers. All amounts are in nmol;
concentrations in nmol/L. Framework adapted from the Brill et al. 2016
midazolam mPBPK with metabolite. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Aguiar_2021_ustekinumab.html">Ustekinumab
(Aguiar 2021)</a> </td>
<td style="text-align:left;"> Population
pharmacokinetic-pharmacodynamic model for ustekinumab in adults with
Crohn's disease (Aguiar 2021): two-compartment quasi-equilibrium TMDD
model for ustekinumab and the unbound IL-12/IL-23 p40 target, linked to
fecal calprotectin via an indirect-response model with target-driven
stimulation of FC production. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Marcantonio_2022_efa.html">Ustekinumab
(Marcantonio 2022)</a> </td>
<td style="text-align:left;"> QSP. One-compartment monospecific
anti-ligand mechanistic PKPD model of ustekinumab-p40 binding in adults
with plaque psoriasis (Marcantonio 2022 Early Feasibility Assessment,
Case Study 3). Ustekinumab binds the shared p40 subunit of IL-12 and
IL-23 with bivalent binding (valency = 2 per Benson 2011); model treats
p40 as the soluble target and its cognate receptor (IL-12R-beta1) as the
membrane binding partner. Structure identical to the Marcantonio 2022
anti-ligand family; parameters FIXED from paper Table S3. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Vezina_2010_valganciclovir.html">Valganciclovir
(Vezina 2010)</a> </td>
<td style="text-align:left;"> One-compartment population PK
model for ganciclovir following oral valganciclovir prophylaxis in
pediatric solid organ transplant recipients at risk for Epstein-Barr
virus disease (Vezina 2010). First-order absorption with no covariates
retained in the final model; doses are mg of valganciclovir uncorrected
for molecular weight, and the apparent CL/F and V/F absorb both oral
bioavailability and the molar conversion from valganciclovir to
ganciclovir. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Vezina_2014_valganciclovir.html">Valganciclovir
(Vezina 2014)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model for ganciclovir after oral valganciclovir prophylaxis in
paediatric and adult solid organ transplant recipients (Vezina 2014).
First-order absorption with fixed lag time and rate, allometric (WT/70
kg) scaling on apparent CL/F and Q/F (exponent 0.75) and on V2/F and
V3/F (exponent 1.0), and a power-form effect of body-weight-adjusted
creatinine clearance on CL/F (reference 60 mL/min). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Zhang_2023_valproic_acid_protein_binding.html">Valproic
acid base (Zhang 2023)</a> </td>
<td style="text-align:left;"> One-compartment population PK
model with first-order absorption for total plasma valproic acid in
Chinese children with epilepsy (Zhang 2023 base model). Linear clearance
with no covariates on CL/F or V/F; formulation-specific absorption rate
constants FIXED from the literature (syrup 2.64 1/h reference,
conventional tablet 1.57 1/h, sustained-release tablet 0.46 1/h). This
is the reference model against which the paper's five protein-binding
non-linearity strategies are compared; see
modellib('Zhang_2023_valproic_acid_exponent') for the daily-dose power
model. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Zhang_2023_valproic_acid_protein_binding.html">Valproic
acid ddemax (Zhang 2023)</a> </td>
<td style="text-align:left;"> One-compartment population PK
model with first-order absorption for total plasma valproic acid in
Chinese children with epilepsy (Zhang 2023 Model III, the dose-dependent
maximum effect model). Apparent clearance rises with the patient's own
total daily dose through a sigmoid-Emax term, CL/F = CLp/F * (1 + Emax *
DD^gamma / (DD50^gamma + DD^gamma)), with Emax, gamma and DD50 all FIXED
to the values of Ding 2015. Formulation-specific absorption rate
constants FIXED from the literature (syrup 2.64 1/h reference,
conventional tablet 1.57 1/h, sustained-release tablet 0.46 1/h). The
weakest of the five non-linearity strategies the authors compare - its
objective function value is worse than the linear base model's - and it
is packaged for fidelity to the published comparison; see
modellib('Zhang_2023_valproic_acid_nonsaturable') for the strategy the
authors recommend. DD50 is not reported by Zhang 2023 and is carried
over from Ding 2015; see the vignette Errata. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Zhang_2023_valproic_acid_protein_binding.html">Valproic
acid exponent (Zhang 2023)</a> </td>
<td style="text-align:left;"> One-compartment population PK
model with first-order absorption for total plasma valproic acid in
Chinese children with epilepsy (Zhang 2023 Model V, the simple exponent
model). Apparent clearance follows a power function of the patient's own
daily dose per kilogram, CL/F = CLp/F * (DD/25)^0.658, with DD in
mg/kg/day and a reference daily dose of 25 mg/kg/day; this is the
empirical dose-dependence strategy the authors contrast against
mechanistic protein-binding models. Formulation-specific absorption rate
constants FIXED from the literature (syrup 2.64 1/h reference,
conventional tablet 1.57 1/h, sustained-release tablet 0.46 1/h). Best
prediction-based performance of the five strategies (MDPE 1.50%, MAPE
17.68%) but the authors conclude it does not describe the underlying
non-linearity; see modellib('Zhang_2023_valproic_acid_base') for the
reference model. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Zhang_2023_valproic_acid_protein_binding.html">Valproic
acid langmuir (Zhang 2023)</a> </td>
<td style="text-align:left;"> One-compartment population PK
model with first-order absorption for valproic acid in Chinese children
with epilepsy (Zhang 2023 Model II, the Langmuir protein-binding model).
The disposition is carried on the UNBOUND concentration Cu =
central/(V/F) with linear unbound clearance; the observed TOTAL plasma
concentration is reconstructed as Cc = Cu + Cb, where the bound
concentration follows the single-site Langmuir isotherm Cb = Bm * Cu /
(Kd + Cu) with Bm and Kd FIXED to the literature values of Ueshima 2008.
Formulation-specific absorption rate constants FIXED from the literature
(syrup 2.64 1/h reference, conventional tablet 1.57 1/h,
sustained-release tablet 0.46 1/h). One of five protein-binding
non-linearity strategies the authors compare; see
modellib('Zhang_2023_valproic_acid_nonsaturable') for the linear
non-saturable extension the authors ultimately preferred. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Zhang_2023_valproic_acid_protein_binding.html">Valproic
acid nonsaturable (Zhang 2023)</a> </td>
<td style="text-align:left;"> One-compartment population PK
model with first-order absorption for valproic acid in Chinese children
with epilepsy (Zhang 2023 Model IV, the linear non-saturable binding
model - the strategy the authors conclude is best suited to valproate
protein-binding non-linearity). The disposition is carried on the
UNBOUND concentration Cu = central/(V/F) with linear unbound clearance;
the observed TOTAL plasma concentration is reconstructed as Cc = Cu +
Cb, where the bound concentration adds a linear non-saturable term to
the Langmuir isotherm, Cb = Bm * Cu / (Kd + Cu) + NS * Cu, with Bm, Kd
and NS FIXED to the values of Gu 2021. Formulation-specific absorption
rate constants FIXED from the literature (syrup 2.64 1/h reference,
conventional tablet 1.57 1/h, sustained-release tablet 0.46 1/h). Best
simulation-based behaviour of the five strategies compared; see
modellib('Zhang_2023_valproic_acid_langmuir') for the pure Langmuir form
it extends. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Zhang_2023_valproic_acid_protein_binding.html">Valproic
acid onebindingsite (Zhang 2023)</a> </td>
<td style="text-align:left;"> One-compartment population PK
model with first-order absorption for valproic acid in Chinese children
with epilepsy (Zhang 2023 Model I, the one-binding-site protein-binding
model). The disposition is carried on the UNBOUND concentration Cu =
central/(V/F) with linear unbound clearance; the observed TOTAL plasma
concentration is reconstructed as Cc = Cu + Cb, where the albumin-bound
concentration follows the one-binding-site isotherm Cb = N * K * Cu *
ALB / (1 + K * Cu) with N and K FIXED to the adult literature values of
Dutta 2007. Formulation-specific absorption rate constants FIXED from
the literature (syrup 2.64 1/h reference, conventional tablet 1.57 1/h,
sustained-release tablet 0.46 1/h). One of five protein-binding
non-linearity strategies the authors compare; see
modellib('Zhang_2023_valproic_acid_base') for the linear reference
model. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Williams_2012_valproic_acid_pediatric.html">Valproic
acid pediatric (Williams 2012)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model for valproic acid in pediatric patients with epilepsy (Williams
2012). Allometric weight scaling on CL/Q (fixed 0.75) and Vc/Vp (fixed
1.0); estimated age power (-0.267) on Vc; reference weight 70 kg,
reference age 8.5 years. Default first-order oral absorption is for
divalproex sodium enteric-coated sprinkle (Ka 1.2 1/h, ALAG 1 h, FIXED);
other formulations (syrup K0=410 mg/h, capsule Ka=2 1/h, tablet Ka=4.1
1/h with ALAG=2 h) require overriding lka/ltlag at simulation time.
Direct IV dosing into the central compartment is supported. Residual
error defaults to the TDM-subset proportional SD (CV 34.8%); paper also
reports a TRIAL-subset SD (CV 4.6%) for the IV-infusion subset.
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Kim_2015_valsartan.html">Valsartan
(Kim 2015)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model for valsartan with zero-order absorption in healthy adult Korean
male volunteers (Kim 2015) </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Alqahtani_2018_vancomycin.html">Vancomycin
(Alqahtani 2018)</a> </td>
<td style="text-align:left;"> Two-compartment IV population PK
model for vancomycin used as prophylactic antibiotic in 28 adult
patients undergoing open heart surgery with cardiopulmonary bypass
(Alqahtani 2018). Clearance scales by power exponent with
Cockcroft-Gault creatinine clearance (raw mL/min, reference 83.5) and
serum albumin (g/L, reference 35.5); central volume scales by power
exponent with body weight (kg, reference 79.6). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Buelga_2005_vancomycin.html">Vancomycin
(Buelga 2005)</a> </td>
<td style="text-align:left;"> One-compartment IV
intermittent-infusion population PK model for vancomycin in adult
patients with hematological malignancies (Buelga 2005). CL is a purely
multiplicative function of Cockcroft-Gault creatinine clearance (CL
[L/h] = 1.08 x CLCR [L/h]) and V is a purely multiplicative function of
total body weight (V [L] = 0.98 x TBW [kg]). Exponential
inter-individual variability on CL and V with an estimated CL-V
correlation; additive residual error in mg/L. The AML-1 and AML-2
subpopulation-specific models from the same paper are not packaged here;
only the general final model (Table 4) is implemented. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Chung_2013_vancomycin.html">Vancomycin
(Chung 2013)</a> </td>
<td style="text-align:left;"> One-compartment IV-infusion
population PK model for vancomycin in Korean adults with normal serum
creatinine (Chung 2013). CL and V are described by centered-linear
additive deviations on age, total body weight, serum creatinine (CL
only), and sex, plus a power-law effect of serum cystatin C on CL
(reference 0.91 mg/L, exponent -0.78); cystatin C is the dominant CL
covariate, accounting for ~62% of the inter-individual variability in CL
even within the SCr <= 1.2 mg/dL inclusion window. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Goti_2018_vancomycin.html">Vancomycin
(Goti 2018)</a> </td>
<td style="text-align:left;"> Two-compartment IV population PK
model for vancomycin in hospitalized adults with and without
intermittent hemodialysis (Goti 2018). Volumes scaled allometrically to
body weight (reference 70 kg, fixed linear exponent), CL scaled by
Cockcroft-Gault creatinine clearance with a power exponent (reference
120 mL/min), and intermittent hemodialysis acts as a multiplicative
factor on CL (0.7) and central volume (0.5). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Grimsley_1999_vancomycin.html">Vancomycin
(Grimsley 1999)</a> </td>
<td style="text-align:left;"> One-compartment IV-infusion
population PK model for vancomycin in neonates and young infants
(Grimsley 1999). Developed from routine therapeutic-drug-monitoring data
in 59 neonates (347 concentrations). Clearance scales linearly with body
weight and inversely with serum creatinine concentration (CL = 3.56 * WT
/ CREAT, L/h, WT in kg, CREAT in umol/L); central volume scales linearly
with body weight (V = 0.669 * WT, L/kg). The covariate-coupled CL form
(no separately estimated exponents) is reported by the paper as the
entire structural model. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Ji_2017_vancomycin.html">Vancomycin
(Ji 2017)</a> </td>
<td style="text-align:left;"> One-compartment IV
(intermittent-infusion) population PK model for vancomycin in Chinese
adult patients (Ji 2017). Clearance is scaled by raw Cockcroft-Gault
creatinine clearance (centered linear term, reference 80 mL/min) and by
age (power of (75/age), reference 75 years); the volume of distribution
is a single typical value. Developed from steady-state trough
therapeutic-drug-monitoring data. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Jung_2024_vancomycin.html">Vancomycin
(Jung 2024)</a> </td>
<td style="text-align:left;"> Two-compartment IV population PK
model for vancomycin in critically ill children (90 days to <18
years) in the PICU who are not on extracorporeal therapy (Jung 2024).
Clearance and intercompartmental clearance scale allometrically with
body weight (exponent 0.75, reference 20 kg) and clearance additionally
scales as a power function of bedside-Schwartz estimated GFR (exponent
0.5259, reference 141 mL/min/1.73 m^2); central and peripheral volumes
scale linearly with body weight (exponent 1, reference 20 kg). Residual
variability is a log error model. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Li_2018_vancomycin.html">Vancomycin
(Li 2018)</a> </td>
<td style="text-align:left;"> One-compartment IV-infusion
population PK model for vancomycin in critically ill Chinese ICU
neonates (Li 2018). CL scales allometrically with body weight (reference
2.9 kg, exponent 1.55) and as an inverse power of serum creatinine
(reference 23.3 umol/L, exponent 0.337 on the SCr_ref/SCr ratio). V
scales allometrically with body weight (reference 2.9 kg, exponent
1.05). IIV is on CL only; residual error is proportional. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/MarquesMinana_2010_vancomycin.html">Vancomycin
(MarquesMinana 2010)</a> </td>
<td style="text-align:left;"> One-compartment IV-infusion
population PK model for vancomycin in neonates (Marques-Minana 2010).
Developed from 70 NICU neonates (postmenstrual age 25.1-48.1 weeks;
weight 0.7-3.7 kg). Weight-normalized clearance is linear in
postmenstrual age and increased by concomitant amoxicillin-clavulanic
acid; weight-normalized volume of distribution is decreased by
concomitant spironolactone. Additive interindividual variability on CL
and V per the paper's Step 4 error-model selection; additive residual
error. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Moore_2016_vancomycin.html">Vancomycin
(Moore 2016)</a> </td>
<td style="text-align:left;"> Two-compartment IV population PK
model for vancomycin in adult patients on extracorporeal membrane
oxygenation (ECMO) therapy (Moore 2016). Linear (additive) covariate
effects on CL (Cockcroft-Gault creatinine clearance), Vc, and Vp (body
weight), each centered on the cohort median (CRCL 84 mL/min; WT 95 kg).
Proportional residual error; IIV on CL and Vc only (Q and Vp had no
IIV). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Nielsen_2011_antibacterial_efficacy.html">Vancomycin
(Nielsen 2011)</a> </td>
<td style="text-align:left;"> In vitro (Streptococcus pyogenes
M12 NCTC P1800). Semimechanistic PKPD model of vancomycin time-kill
kinetics; two-stage bacterial life-cycle (proliferating drug-sensitive S
and non-growing drug-insensitive R) with sigmoidal Emax killing of S via
an effect compartment; first-order drug elimination (ke set per in vitro
kinetic-system flow rate); drug-specific degradation kdeg fixed at zero.
Parameter values are from the combined static and dynamic estimation in
Table 3. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Revilla_2010_vancomycin.html">Vancomycin
(Revilla 2010)</a> </td>
<td style="text-align:left;"> One-compartment IV population PK
model for vancomycin in critically ill adult medical ICU patients
(Revilla 2010). Clearance is the sum of a renal arm proportional to
weight-normalised creatinine clearance and a non-renal arm scaling as
AGE^-0.24; central volume of distribution is per kg with a >2-fold
increase when serum creatinine exceeds 1 mg/dL. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Roberts_2011_vancomycin.html">Vancomycin
(Roberts 2011)</a> </td>
<td style="text-align:left;"> One-compartment IV population PK
model for vancomycin administered by continuous infusion in adult septic
critically ill ICU patients (Roberts 2011). Volume of distribution
scales linearly with total body weight (1.53 L/kg); clearance scales
linearly with BSA-normalized 24-hour urinary creatinine clearance
referenced to 100 mL/min/1.73 m^2 (4.58 L/h at the reference).
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Shen_2024_vancomycin.html">Vancomycin
(Shen 2024)</a> </td>
<td style="text-align:left;"> One-compartment IV-infusion
population PK model for vancomycin in 386 Southern Chinese children
(Shen 2024). Clearance uses an age-cutoff structure at 2 years: a
separate typical clearance AND a separate body-weight allometric
exponent are estimated in each age stratum (2.59 L/h with exponent 0.38
for age > 2 years; 1.98 L/h with exponent 0.739 for age <= 2
years), both normalized to a 12 kg reference weight, with a shared
Cockcroft-Gault creatinine-clearance power effect (exponent 0.517,
reference 75 mL/min). Central volume scales linearly with body weight
(22.4 L at 12 kg). Additive residual error is estimated separately for
each of the two study centers. Both strata share the volume, the CLcr
exponent and the clearance IIV in a single joint NONMEM fit. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Staatz_2005_gentamicin_vancomycin.html">Vancomycin
(Staatz 2005)</a> </td>
<td style="text-align:left;"> One-compartment IV population PK
model for vancomycin in adult cardiothoracic-surgery patients with
unstable renal function (Staatz 2005). Clearance scales linearly with
raw Cockcroft-Gault creatinine clearance centred at the population
median (57 mL/min); volume of distribution scales linearly with body
weight (typical-value reported per kg). Vancomycin did not benefit from
the Wahlby 2004 baseline-CrCl + change-from-baseline (BCOV+DCOV)
decomposition in the paper -- the simpler covariate form was retained as
the final vancomycin model -- so this implementation reproduces the
paper's published vancomycin final model exactly. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Zhao_2014_vancomycin.html">Vancomycin
(Zhao 2014)</a> </td>
<td style="text-align:left;"> One-compartment IV-infusion
population PK model for vancomycin in 70 children with malignant
hematological disease (Zhao 2014). Clearance scales with body weight by
power exponent (reference 20.2 kg, exponent 0.677) and with
Schwartz-formula creatinine clearance by power exponent (reference 191
mL/min/1.73 m^2, exponent 1.03); central volume scales with body weight
by power exponent (reference 20.2 kg, exponent 0.838). Vancomycin
clearance was substantially higher than in pediatric populations without
cancer; the published patient-tailored daily dose is target AUC * CL_i.
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Ravva_2009_varenicline.html">Varenicline
(Ravva 2009)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model with first-order absorption and lag-time for varenicline in adult
smokers (Ravva 2009): apparent clearance scales with creatinine
clearance and race; central volume scales with body weight, age, and
race; peripheral disposition uses fixed allometric exponents on weight.
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Wang_2014_vatalanib.html">Vatalanib
(Wang 2014)</a> </td>
<td style="text-align:left;"> One-compartment population PK
model for oral vatalanib in adults with myelodysplastic syndrome (CALGB
10105); apparent oral clearance carries a first-order auto-induction
term that rises from a pre-induction value toward a steady-state
post-induction value over the first 7 days of therapy, lagged
first-order absorption, log-normal residual error on the
natural-log-transformed concentration; no covariates retained in the
final model (Wang 2014). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Rosario_2015_vedolizumab.html">Vedolizumab
(Rosario 2015)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model for vedolizumab (humanised anti-alpha4-beta7 integrin IgG1
monoclonal antibody) with parallel linear and Michaelis-Menten
elimination in adults with moderately-to-severely active ulcerative
colitis or Crohn's disease and healthy volunteers (Rosario 2015).
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Waterhouse_2024_vedolizumab.html">Vedolizumab
(Waterhouse 2024)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model with first-order (linear) elimination for vedolizumab (humanised
anti-alpha4-beta7 integrin IgG1 monoclonal antibody) as acute
graft-versus-host disease (aGvHD) prophylaxis in adults undergoing
allogeneic hematopoietic stem cell transplantation (allo-HSCT)
(Waterhouse 2024). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Syvanen_2011_verapamil_rat.html">Verapamil
rat (Syvanen 2011)</a> </td>
<td style="text-align:left;"> Preclinical (rat, male
Sprague-Dawley). Population mixed-effects popPK model for
(R)-[11C]verapamil in plasma and whole-brain PET tissue, fit by Syvanen
et al. (2011, BMC Med Imaging) as part of a PET study comparing
P-glycoprotein (P-gp) functionality at the blood-brain barrier between
kainate-induced post-status-epilepticus rats (n = 22) and saline-treated
controls (n = 20), with paired tariquidar (15 mg/kg IV) vs vehicle
co-administration arms. The structural model is a three-compartment
plasma disposition (central + 2 peripherals) coupled to a
two-compartment brain model (brain_csf = fast-exchange brain compartment
connected to plasma via Qin in / Qout out; brain_deep = deep-brain
compartment exchanging with brain_csf via Qbr). Plasma curves are
complete-metabolite- corrected before fitting, so the model describes
intact (R)-[11C]verapamil kinetics only. Body weight is the only
continuous covariate (allometric on plasma CL, reference weight 0.3084
kg). Tariquidar co-administration multiplies Vp1 by 1.20, Vbr1 by 2.41,
and Qin by 12.0; the kainate-induced post-SE state multiplies Vbr1 by
1.32 (no significant effect on Qin or Qout); both categorical effects
use the paper's theta^COV multiplicative form (Equation 5). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Landersdorfer_2012_vildagliptin.html">Vildagliptin
(Landersdorfer 2012)</a> </td>
<td style="text-align:left;"> Mechanism-based population PK
plus DPP-4 activity model for vildagliptin in patients with type 2
diabetes. Target-mediated drug disposition with capacity-limited
slow-tight binding of vildagliptin to DPP-4 in plasma and tissue and
partial hydrolysis of vildagliptin by DPP-4. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Schmitt_2018_vinflunine.html">Vinflunine
(Schmitt 2018)</a> </td>
<td style="text-align:left;"> Combined population PK / PD model
for IV vinflunine in adult cancer patients (Schmitt 2018, 18 phase I/II
trials, n=372). Four-compartment IV-infusion popPK with creatinine
clearance, body surface area, body weight, and PEGylated liposomal
doxorubicin co-administration covariates, plus a five-compartment
Friberg-style semi-mechanistic myelosuppression PD model for absolute
neutrophil count (proliferation + 3 transit + circulation; linear drug
effect 1 - slope*Cc on proliferation; (circ0/circ)^gamma feedback).
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Petric_2023_vinpocetine.html">Vinpocetine
(Petric 2023)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model for apovincaminic acid (AVA), the active de-esterified metabolite
of vinpocetine, in healthy adult male volunteers dosed with vinpocetine
(Petric 2023). Only AVA (not the parent vinpocetine) is modelled; the
reported CL/F, V1/F, Q/F, V2/F apparent parameters fold the fraction of
the vinpocetine dose that appears in plasma as AVA and the vinpocetine
oral bioavailability into the /F term. Absorption is described as a
zero-order input of duration Tk0 into the central compartment preceded
by an absorption lag Tlag. Formulation is the only significant
covariate: the sustained-release beta-cyclodextrin complex Ultra Vinca
is the reference; the Cavinton immediate-release tablet and the
extemporaneous 10 mg / 5 mL oral solution enter as log-additive shifts
on Tk0 and V1/F. Between-subject variability is placed on Tlag, Tk0,
CL/F, V1/F, Q/F, V2/F with a correlation of 0.72 between CL/F and V1/F.
Residual error is proportional. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Cao_2013_visilizumab.html">Visilizumab
(Cao 2013)</a> </td>
<td style="text-align:left;"> Second-generation minimal
physiologically-based PK (mPBPK) model for visilizumab in adults (Cao
2013 Model A; clearance from plasma) </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Lu_2015_vismodegib.html">Vismodegib
(Lu 2015)</a> </td>
<td style="text-align:left;"> Semi-mechanism-based
one-compartment population pharmacokinetic model for vismodegib
(GDC-0449, oral Hedgehog pathway inhibitor) in adults with advanced
solid tumors and healthy volunteers. First-order absorption, first-order
elimination of unbound drug, and saturable fast-equilibrium binding to
alpha-1-acid glycoprotein (AAG) jointly describe total and unbound
plasma vismodegib concentrations. AAG is supplied as a time-varying
covariate (uM); covariates retained on disposition are age (power on
CLunbound, reference 60 years) and body weight (power on Vc, reference
75 kg); formulation (Phase I dry-blend capsule vs Phase II
wet-granulation commercial capsule) and population (healthy volunteer vs
patient) shift Ka and relative bioavailability F (Lu 2015). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Bauer_2023_vonWillebrandFactor.html">VonicogAlfa
(Bauer 2023)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model for von Willebrand factor:ristocetin cofactor activity (VWF:RCo)
after intravenous recombinant von Willebrand factor (rVWF, vonicog alfa)
coupled to an indirect-response PK/PD model for endogenous factor VIII
activity (FVIII:C), from Bauer 2023. VWF:RCo disposition is linear
two-compartment with first-order elimination from the central
compartment plus an additive endogenous background activity E_VWF, fixed
at half the assay LLOQ (0.5 IU/dL) for von Willebrand disease (VWD) type
3. CL and Q are allometrically scaled by body weight with a fixed
exponent of 0.75, Vc and Vp with a fixed exponent of 1, both referenced
to 75 kg; Vc additionally decreases with hematocrit as (HCT/40)^-0.334.
FVIII:C is a turnover pool with zero-order production kin = FVIII0 *
kout and first-order removal kout (15.9 1/h) that VWF:RCo inhibits
through an Imax function, 1 - Imax * VWF:RCo / (IC50 + VWF:RCo), so that
rising VWF:RCo protects FVIII from clearance; FVIII0 is the theoretical
baseline FVIII:C at VWF:RCo = 0 IU/dL and scales with hematocrit as
(HCT/39)^-0.571. Fitted to 1664 VWF:RCo samples from 79 patients across
four studies (VWD types 1, 2, 3 and severe hemophilia A) and 686 FVIII:C
samples from the 41 patients of the two phase 3 VWD studies. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Akbar_2025_voriconazole.html">Voriconazole
(Akbar 2025)</a> </td>
<td style="text-align:left;"> One-compartment population
pharmacokinetic model with first-order elimination for intravenous
voriconazole in adult and pediatric Pakistani cancer patients receiving
therapeutic drug monitoring (Akbar 2025); creatinine clearance and
primary cancer diagnosis are covariates on clearance </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Chen_2015_voriconazole.html">Voriconazole
(Chen 2015)</a> </td>
<td style="text-align:left;"> One-compartment population
pharmacokinetic model with first-order elimination for intravenous
voriconazole in Chinese adult critically ill patients with pulmonary
disease (Chen 2015); direct bilirubin enters as a power-form covariate
on clearance. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Friberg_2012_voriconazole.html">Voriconazole
(Friberg 2012)</a> </td>
<td style="text-align:left;"> Integrated population
pharmacokinetic model for voriconazole in children, adolescents, and
adults (Friberg 2012). Two-compartment with first-order oral absorption
and mixed linear plus nonlinear (Michaelis-Menten with time-dependent
Vmax) elimination; allometric scaling on all clearance terms (exponent
0.75) and on volumes (exponent 1.0) with 70 kg reference;
population-specific Vmax,inh, Q, ka, and Alag for children, adolescents,
and adults; CYP2C19 heterozygous extensive or poor metabolizer adults
have fully blocked nonlinear clearance (Vmax,inh = 100%). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Han_2010_voriconazole.html">Voriconazole
(Han 2010)</a> </td>
<td style="text-align:left;"> Two-compartment population
pharmacokinetic model with first-order absorption and first-order
elimination for intravenous and oral voriconazole in adult lung
transplant recipients during the early postoperative period (Han 2010).
Bioavailability is estimated for the oral route. The base structural
model is reported as the primary result; three separate single-covariate
sub-models -- cystic fibrosis (CF) and postoperative time (POT) on
bioavailability, and body weight (WT) on peripheral volume -- are
reported in the paper but were not combined into a final model; the
base-model typical-value parameter estimates are encoded here, and the
three covariate sub-models are reproduced in the validation vignette.
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Karlsson_2009_voriconazole.html">Voriconazole
(Karlsson 2009)</a> </td>
<td style="text-align:left;"> Two-compartment population
pharmacokinetic model with Michaelis-Menten elimination for voriconazole
in pediatric patients aged 2 to <12 years (Karlsson 2009), pooled
from three open-label intravenous and oral studies; first-order oral
absorption with bioavailability, no lag time; all disposition parameters
proportional to body weight; CYP2C19 metabolizer status (heterozygous
extensive metabolizers pooled with poor metabolizers) and alanine
aminotransferase as covariates on clearance; residual error stratified
by CYP2C19 metabolizer group </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Lin_2018_voriconazole.html">Voriconazole
(Lin 2018)</a> </td>
<td style="text-align:left;"> One-compartment population
pharmacokinetic model with first-order absorption for intravenous and
oral voriconazole in Chinese adult renal transplant recipients receiving
therapeutic drug monitoring (Lin 2018); CYP2C19 phenotype enters as a
covariate on clearance, postoperative time as a covariate on oral
bioavailability, and body weight as a power-form covariate on volume of
distribution. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Muto_2015_voriconazole.html">Voriconazole
(Muto 2015)</a> </td>
<td style="text-align:left;"> Two-compartment population
pharmacokinetic model with first-order absorption (lag time, oral
bioavailability) and parallel linear plus time-dependent
Michaelis-Menten elimination for voriconazole in 21 immunocompromised
Japanese pediatric subjects (Muto 2015). Vmax declines with time after
the first dose toward Vmax * (1 - Vmax_inh) with half-time T50; the
maximum inhibition fraction Vmax_inh is fixed to 1 (full inhibition) for
CYP2C19 heterozygous-extensive-metabolizer or poor-metabolizer subjects
and modeled on the logit scale otherwise. Allometric scaling on all
clearances (exponent 0.75) and all volumes (exponent 1) to a 70 kg
reference; oral bioavailability F1 is modeled on the logit scale with a
Manly-transformed log-normal random effect. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Wahlby_2004_time_varying_covariates.html">Voriconazole
(Wahlby 2004)</a> </td>
<td style="text-align:left;"> Pediatric (2-11 years)
two-compartment population PK model for intravenous voriconazole in 35
children, demonstrating Wahlby 2004's extended covariate-model
formulation. All disposition parameters scale linearly with body weight.
Final-model clearance depends on the time-varying log-ratio
(log(ALP/ALP_BASE), 'log(DALKP)' in the source) and on log(ALT) with
individual variability in both covariate-effect coefficients (Wahlby
2004 Eq 3 demonstrated). A binary CYP2C19 non-extensive-metabolizer
indicator (PM + heterozygous-EM versus homozygous-EM) multiplicatively
modifies CL. Underlying structural PK comes from Walsh TJ et al.
(Antimicrob Agents Chemother 2004;48(6):2166-2172) and the Karlsson 1995
(J Pharmacokin Biopharm 1998;26(2):207-246) sigma-IIV residual-error
pattern is approximated in this entry. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Naik_2016_vortioxetine.html">Vortioxetine
(Naik 2016)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model for vortioxetine in adult patients with major depressive disorder
or generalized anxiety disorder, with first-order oral absorption,
region-specific oral clearance, and linear creatinine-clearance and
height effects on CL/F (Naik 2016) </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Qi_2024_vosoritide.html">Vosoritide
(Qi 2024)</a> </td>
<td style="text-align:left;"> One-compartment population PK
model with first-order elimination and change-point first-order
absorption (the absorption rate constant switches from Ka1 to Ka2 at an
estimated time after each dose) for subcutaneous vosoritide (BMN 111, a
C-type natriuretic peptide analog) in children with achondroplasia aged
0.95-15 years, pooled from five clinical trials (Qi 2024). Body weight
is a power covariate on CL/F (exponent 0.356) and on V/F (exponent
1.09), both referenced to 20 kg. Relative bioavailability rises
exponentially with time on treatment and is 56% higher for the 0.2 mg/mL
dosing solution used only in study 111-202. Study-level random effects
nested inside the subject-level IIV on CL/F and V/F reproduce the
paper's secondary study identity number (SIDN) hierarchy, and separate
log-scale residual errors are carried for the ELISA and the
electrochemiluminescence assays. The model was used to derive the
eight-band weight-band dosing regimen of Qi 2024 Table 6. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Huang_2017_vrc01.html">Vrc01
(Huang 2017)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model for VRC01 (HIV-1 broadly neutralizing IgG1 monoclonal antibody) in
healthy adults after IV or SC administration (Huang 2017) </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Huynh_2026_VRC07523LS.html">VRC07523LS
(Huynh 2026)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model with zero-order subcutaneous absorption, allometric weight
scaling, and binary effects of age (adult vs infant) and repeat dosing
for the broadly neutralizing HIV-1 monoclonal antibody VRC07-523LS in
healthy adults and HIV-exposed infants (Huynh 2026). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Bauer_2023_vonWillebrandFactor.html">VwfFviii
humateP (Bauer 2023)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model for von Willebrand factor:ristocetin cofactor activity (VWF:RCo)
after intravenous plasma-derived von Willebrand factor / factor VIII
concentrate (pdVWF/FVIII; Humate-P, VWF:RCo/FVIII:C 2.4:1) coupled to an
indirect-response PK/PD model for factor VIII activity (FVIII:C), from
Bauer 2023. The structure is the one developed for recombinant VWF (see
modellib('Bauer_2023_vonicogAlfa')) refitted to the plasma-derived
product: linear two-compartment VWF:RCo disposition with first-order
elimination from the central compartment plus an additive endogenous
background E_VWF fixed at half the assay LLOQ (0.5 IU/dL) for von
Willebrand disease (VWD) type 3, allometric body weight on CL and Q
(exponent 0.75) and on Vc and Vp (exponent 1) with a 75 kg reference,
and (HCT/40)^-0.334 on Vc. FVIII:C is a turnover pool whose first-order
removal kout is inhibited by VWF:RCo through 1 - Imax * VWF:RCo / (IC50
+ VWF:RCo). Because the product delivers FVIII as well as VWF, a volume
of distribution for FVIII (V FVIII = 32.9 dL) is added so that the
administered FVIII:C dose enters the FVIII pool; the elimination of
plasma-derived FVIII is assumed identical to that of endogenous FVIII
and is therefore carried by kout. The system-specific parameters FVIII0,
kout and the hematocrit effect on FVIII0 are fixed to the
recombinant-VWF model estimates. VWF:RCo clearance is roughly twice that
of recombinant VWF (4.14 vs 2.10 dL/h), giving a 1.76-fold shorter mean
residence time. Fitted to 281 VWF:RCo and FVIII:C samples from 20
patients with VWD type 3. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Savic_2010_warfarin.html">Warfarin
(Savic 2010)</a> </td>
<td style="text-align:left;"> Population PKPD model for orally
dosed warfarin in adult subjects, presented as the worked illustration
of MONOLIX 3.1's SAEM algorithm for ordered-categorical PD data. PK:
one-compartment with first-order absorption and a lag time. PD link:
effect compartment driven by central amount via rate constant ke0. PD
endpoint: a three-category recoding of percent prothrombin complex
activity (PCA) with cutoffs 50% and 33% (Y=0 if PCA > 50%, Y=1 if 33%
<= PCA <= 50%, Y=2 if PCA < 33%), described by a proportional-
odds (cumulative-logit) model with random intercept driven by
effect-site warfarin concentration. The PD categorisation is
acknowledged by the authors (Page 6) as 'done for illustration purpose
only ... not recommended in the real analysis'; this extraction is the
registry's founding example of an ordered- categorical PD likelihood and
the authors' caveat applies. All parameter values are from the MONOLIX
output in Fig. 4. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Xia_2024_warfarin.html">Warfarin
(Xia 2024)</a> </td>
<td style="text-align:left;"> K-PD warfarin PK/PD model for
adult Han Chinese (Alfalfa-Warfarin-PPK/PD; Xia 2024). PK parameters
fixed from the Hamberg model; PD EC50 re-estimated, with VKORC1 -1639
G/A and CYP2C9 *1/*2/*3 allele-specific contributions, body-weight power
scaling, and amiodarone effect on EC50. Two parallel coagulation-factor
transit chains drive INR. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Falkenhagen_2023_warfarin_qsp.html">Warfarin
qsp (Falkenhagen 2023)</a> </td>
<td style="text-align:left;"> QSP-derived mechanism-based
warfarin/INR pharmacodynamic model (Falkenhagen 2023). Obtained by
systematically reducing the 62-ODE / 174-parameter Wajima 2009
blood-coagulation quantitative systems pharmacology model down to 6 ODEs
and 11 structural parameters, while guaranteeing under 10% relative INR
error for at least 95% of a diverse virtual population. One-compartment
oral warfarin PK inhibits vitamin K hydroquinone (VKH2) synthesis
through an Imax function; VKH2 in turn drives the synthesis of
coagulation Factors II, VII, and X, each modelled as a turnover pool
holding its own pre-stimulus steady state. The INR is recovered
algebraically as a power law in the product of the three relative factor
concentrations, INR = INR0 * (II/II0 * VII/VII0 * X/X0)^gamma with gamma
= -0.1975. CYP2C9 *1/*2/*3 allele counts set warfarin clearance and
VKORC1 -1639 G/A allele counts set IC50, both as per-allele sums. All
parameter values are the Wajima 2009 reference parameterization carried
through the reduction; no parameter was estimated from clinical data in
this paper. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Hamberg_2007_warfarin_pkpd_pgx.html">Warfarin
r (Hamberg 2007)</a> </td>
<td style="text-align:left;"> R-warfarin population PK
(1-compartment, first-order absorption) with age as the only structural
covariate on CL_R (Hamberg 2007). R-warfarin was not found to contribute
(additive or competitive) to the INR PD; the companion file
Hamberg_2007_warfarin_s carries the S-warfarin PK and the INR PD model.
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Lane_2011_warfarin.html">Warfarin
r (Lane 2011)</a> </td>
<td style="text-align:left;"> R-warfarin population PK
(1-compartment, first-order absorption) in adults on long-term warfarin
therapy (Lane 2011). Bodyweight, age, CYP2C19 rs3814637 genotype, and
CYP3A4 rs2242480 (CYP3A4*1G) genotype influence apparent clearance;
volume of distribution carries no covariates. Block correlation between
random effects on CL and V. S-warfarin is reported separately in the
same paper (modellib('Lane_2011_warfarin_s')). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Hamberg_2007_warfarin_pkpd_pgx.html">Warfarin
s (Hamberg 2007)</a> </td>
<td style="text-align:left;"> S-warfarin population PK
(2-compartment, first-order absorption) coupled to an inhibitory-Emax
INR PD model with two parallel transit-compartment chains (6 + 1)
driving the anticoagulant response (Hamberg 2007). CYP2C9 genotype and
age are predictors for S-warfarin clearance; VKORC1 -1639G>A genotype
is a predictor for INR sensitivity (EC50). R-warfarin is reported
separately (modellib('Hamberg_2007_warfarin_r')). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Lane_2011_warfarin.html">Warfarin
s (Lane 2011)</a> </td>
<td style="text-align:left;"> S-warfarin population PK
(1-compartment, first-order absorption) in adults on long-term warfarin
therapy (Lane 2011). Bodyweight, age, sex, and CYP2C9 diplotype
influence apparent clearance; volume of distribution carries no
covariates. Block correlation between random effects on CL and V.
R-warfarin is reported separately in the same paper
(modellib('Lane_2011_warfarin_r')). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Zhou_2016_warfarin_vk2.html">Warfarin
vk2 (Zhou 2016)</a> </td>
<td style="text-align:left;"> Two-drug population PK/PD model
for warfarin and intravenous vitamin K2 (menatetrenone) in Japanese
adults with atrial fibrillation undergoing catheter ablation. Warfarin
and vitamin K2 each have a 1-compartment PK with fixed
volumes-of-distribution (Vd1 = 0.183 L/kg for warfarin from Sato 2006;
Vd3 = 0.051 L/kg for vitamin K2 from the Eisai product information) and
fixed warfarin elimination rate (k10 = 0.0129 1/h); only the vitamin K2
elimination rate (k30) and the indirect-response PD parameters (ks, kd,
IC50, Emax, EC50) were estimated from 579 INR observations in 100
patients. Warfarin inhibits clotting-factor synthesis (Emax = 1 -
Cp1/(Cp1 + IC50)) while vitamin K2 stimulates it (1 + Emax_vk2 *
Cp3/(Cp3 + EC50)); a binary renal-impairment indicator (CREAT >= 1.1
mg/dL in men or >= 0.8 mg/dL in women) reduces IC50 to 61.4% of
normal. The model predicts thrombotest (TT, %); INR is recovered from TT
via the Gogstad 1986 quadratic conversion (Equation 4). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Zhang_2024_XZP5610.html">XZP5610
(Zhang 2024)</a> </td>
<td style="text-align:left;"> One-compartment oral PK model for
the non-steroidal FXR agonist XZP-5610 (NASH) in healthy Chinese adults,
forward-predicted from SD rat and beagle dog preclinical PK by
allometric scaling (Zhang 2024): first-order absorption from a depot
with bioavailability, linear elimination from central. Every parameter
is a cross-species prediction used for first-in-human dose selection,
not an estimate fitted to human data; the paper reports no IIV and no
residual error for it. The companion whole-body PBPK model in the same
paper was built in PK-Sim v11.2 and is not reproducible from the
published sources (no ODEs, organ volumes, blood flows, or per-tissue
partition coefficients are reported). </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Adams_1998_zalcitabine.html">Zalcitabine
(Adams 1998)</a> </td>
<td style="text-align:left;"> One-compartment
first-order-absorption population PK model for oral zalcitabine (ddC) in
HIV-infected adults (Adams 1998). Apparent clearance (CL/F = 14.8 L/h)
and apparent volume of distribution (V/F = 87.6 L) were estimated from
sparse-sampling clinic data; the absorption rate constant was not
estimable in Adams 1998 (paper Discussion p. 412) and is fixed in this
model to ka = 2.5 /h from primary single-dose PK data (Klecker 1988). No
baseline covariates (age, sex, total body weight, calculated creatinine
clearance, food, concomitant zidovudine) improved the basic fit and none
were retained in the final model. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/deVriesSchultink_2020_zenocutuzumab.html">Zenocutuzumab
(deVriesSchultink 2020)</a> </td>
<td style="text-align:left;"> Two-compartment population PK
model with parallel linear and Michaelis-Menten non-linear elimination
from the central compartment for intravenous zenocutuzumab (MCLA-128), a
bispecific IgG1 (anti-HER2 x anti-HER3) monoclonal antibody, in patients
with various advanced solid tumors (de Vries Schultink 2020) </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Fauchet_2013_zidovudine.html">Zidovudine
(Fauchet 2013)</a> </td>
<td style="text-align:left;"> One-compartment population PK
model for oral zidovudine (ZDV) and its glucuronide metabolite
3'-azido-3'-deoxy-5'-glucuronylthymidine (G-ZDV) in HIV-1-infected
children, infants, and adolescents (Fauchet 2013, retrospective
Paris-area therapeutic-drug-monitoring cohort, n = 247, age 0.5-18
years). First-order absorption with a fixed ka = 2.86 1/h (inherited
from Panhard 2007) delivers ZDV into a one-compartment central
compartment with apparent total clearance CL_p/F and apparent volume
V/F. The metabolite is described by a single G-ZDV state driven by a
lumped metabolic formation rate constant CL_m/V_m and a first-order
metabolite elimination rate constant k_el. The metabolite distribution
volume V_m is not identifiable from plasma data alone and is set
structurally to 1 L (same convention used by Lee 2016 for raltegravir
glucuronide). Body weight enters as an estimated power-allometric
covariate on CL_p/F (exponent 0.858) and on V/F (exponent 0.534),
centered on the cohort median 32.2 kg; age, sex, dosage form, and
antiretroviral cotreatments (3TC, ddI, ABC, LPV, RTO, NFV, NVP, EFV)
were all tested and none was retained at p < 0.01. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/Mitra_2026_ziftomenib.html">Ziftomenib
(Mitra 2026)</a> </td>
<td style="text-align:left;"> Sequential two-stage population
PK model for oral ziftomenib (a potent, selective, oral menin inhibitor
for R/R NPM1-mutated acute myeloid leukemia) and its two active
metabolites KO-739 and KO-516 (Mitra 2026 Kura Oncology KOMET-001 +
KO-MEN-003). Parent PK is a 2-compartment model with first-order
absorption, absorption lag time, and linear elimination from the central
compartment; oral bioavailability F1 is fixed at 0.129 (identifiability
constraint from the human ADME + absolute-BA study KO-MEN-005). Each
metabolite is 2-compartment with linear elimination; the metabolic
clearance is split between KO-739 and KO-516 by a fixed 1:1
in-vitro-anchored biotransformation ratio (FM_KO516 = 0.5), with the
total metabolized fraction FM held fixed at 0.535 after an initial
identifiability-limited estimation. Covariate effects retained in the
final model: FED and PPI on parent F1 (logit-scale shifts +3.21 fed;
-0.520 PPI = 6.09x and 0.627x multipliers on F1), PPI on parent Ka
(log-scale shift -0.485 = 0.616x), FED on parent absorption lag time
(log-scale shift +0.322 = 1.38x), strong CYP3A4 inhibitor on parent CL/F
(log-scale -0.778 = 0.459x), healthy-volunteer status on parent CL/F
(log-scale +0.950 = 2.59x), healthy-volunteer status on FM (logit-scale
-1.62 = 0.348x multiplier on FM), strong CYP3A4 inhibitor on KO-739 CL
(log-scale -1.64 = 0.195x), strong CYP3A4 inhibitor on KO-516 CL
(log-scale -0.802 = 0.449x), healthy-volunteer status on KO-739 Vc
(log-scale -1.62 = 0.197x), and healthy-volunteer status on KO-516 Vc
(log-scale -1.87 = 0.154x). No effect of NPM1-m vs KMT2A-r mutational
status, body weight, sex, race, age, mild/moderate renal or hepatic
impairment, or P-gp inhibitor coadministration on ziftomenib PK. IIV:
parent 47.3% CV on CL and 120% CV on Vc; metabolites 74.7% (KO-739 CL),
110% (KO-739 Vc), 162% (KO-739 Q), 31.2% (KO-516 CL), 191% (KO-516 Vc),
118% (KO-516 Q), and 56.8% CV on FM (all independent diagonals).
Inter-occasion variability on F1 (Omega 1.06 corresponding to 137.3% CV)
reported in the parent NONMEM run across 3 occasions is not encoded
structurally here (no operational occasion column is defined for the
model-library use case; see vignette Assumptions and deviations).
Residual error: proportional 43.7% CV on parent Cc; proportional 45.2%
CV plus additive 0.128 ng/mL on Cc_ko739; proportional 36.4% CV on
Cc_ko516. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/PiresdeMello_2018_zika_FAV_HFIM.html">Zika
FAV HFIM (PiresdeMello 2018)</a> </td>
<td style="text-align:left;"> In vitro (HUH-7 human hepatoma
cells, hollow-fiber infection model). Refined translational
mechanism-based pharmacodynamic (MBM) model of Zika virus replication
and inhibition by favipiravir (FAV) under dynamic, human-like FAV
concentration-time profiles. Twelve-state model: uninfected host cells
(uninfected) with logistic-growth replication limited by carrying
capacity HOSTmax; five sequential infected host cell stages
(infected1..infected5) representing the delay from infection to virus
release; five intracellular virus transit compartments (vi1..vi5) for
viral maturation; and extracellular virus (vextra) as the observation
output (log10 PFU/mL). FAV inhibits viral RNA release between vi4 and
vi5 via a simple Imax/IC50 inhibition function (Eq 8). FAV concentration
is a time-varying covariate (CONC_FAV_UM) driven externally by the
user-supplied clinical PK profile. Parameters are the HFIM column of
Table 1; drug-effect parameters (Imax_FAV, IC50_FAV) and the additive
residual SD are shared estimates with the parallel plate assay co-fit
reported in the same paper. </td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/PiresdeMello_2018_zika_FAV_IFN_RBV.html">Zika
FAV IFN RBV (PiresdeMello 2018)</a> </td>
<td style="text-align:left;"> In vitro (Vero cells).
Translational mechanism-based pharmacodynamic (MBM) model of Zika virus
replication and inhibition by favipiravir (FAV), interferon alpha (IFN),
and ribavirin (RBV) as monotherapy and in two-drug combinations.
Eight-state model: uninfected (U) and infected (I) host cells, five
intracellular virus transit compartments (vi1..vi5) capturing maturation
delay, and extracellular virus (vextra) as the observation output (log10
PFU/mL). IFN inhibits cellular infection via a sigmoidal Hill function;
FAV and RBV both inhibit the vi4 -> vi5 maturation transit; RBV
additionally causes first-order cytotoxicity to both uninfected and
infected host cells. FAV+RBV antagonism is encoded via a
competitive-interaction factor PSI (= 1 monotherapy, = 1.37
combination). Drug concentrations are static covariates -- the in vitro
experiment fixes nominal concentrations for the 4-day window. All
parameters fixed at the Table 1 point estimates; the between-curve CVs
reported in Table 1 are not encoded as etas (typical-value mechanism).
</td>
</tr>
<tr>
<td style="text-align:left;"> <a
href="https://nlmixr2.github.io/nlmixr2lib/articles/PillaReddy_2013_panss_subscales.html">Ziprasidone
panss subscales (PillaReddy 2013)</a> </td>
<td style="text-align:left;"> Population PK/PD model for
ziprasidone against the three PANSS subscales (positive, negative,
general) in adults with schizophrenia from Pilla Reddy 2013 Part II. The
PK sub-model is the one-compartment ziprasidone structural model from
Part I (PMID 23473810) Table 2: first-order absorption ka = 0.07 1/h,
apparent oral clearance CL/F = 54 L/h, apparent central volume of
distribution Vc/F = 87.5 L. The PD sub-model has three outputs that
share the Weibull placebo time- course form Pplacebo = Pmax * (1 -
exp(-(t/TD)^POW)) but each subscale carries its own placebo Pmax, TD,
POW (Part II Table 1) and ziprasidone's own Emax / EC50 / KT triplet per
subscale (Part II Table 2). The KT for ziprasidone PANSS positive and
general (0.048 and 0.035 1/day) is the
common-across-atypical-antipsychotic value; the KT for the negative
subscale (0.0073 1/day) was estimated separately per drug and is the
slowest of any compared drug, consistent with Part II's report that
ziprasidone has the longest onset for negative symptoms (more than 3
weeks half-time vs 5 days for haloperidol). The exponential
time-to-event dropout sub-model from Part II Table 4 is documented in
population$dropout_model but not encoded in the model body.
|
|
Zolbetuximab
(Yamada 2025)
|
Two-compartment population PK model of zolbetuximab (anti-CLDN18.2 IgG1
mAb) with zero-order IV input and time-dependent clearance in patients
with locally advanced unresectable or metastatic
gastric/gastroesophageal junction (G/GEJ) adenocarcinoma (Yamada 2025)
|
|
ZoledronicAcid
(Mori 2018)
|
Kinetic-pharmacodynamic (K-PD) PK / bone-turnover-marker / lumbar-spine
BMD model for once-yearly intravenous zoledronic acid (ZOL) 5 mg in
Japanese patients with primary osteoporosis (ZONE study). A virtual
effect-site amount A receives the administered dose and decays
first-order at rate KD; the drug-effect signal KDA enters a
sigmoidal Imax factor with Hill coefficient Gamma and half-effect EKD50
that inhibits the zero-order synthesis Kin of the serum bone-resorption
marker (tartrate-resistant acid phosphatase 5b, TRACP-5b), which is
eliminated first-order at Kout. The observed marker carries a
multiplicative disease-progression / supplementation drift (1 + Slope
t + Emax * t / (T50 + t)) capturing the daily oral calcium +
vitamin D + magnesium supplementation effect pooled with natural
osteoporosis progression (the two effects could not be separated because
all subjects received the supplements). Lumbar-spine BMD follows an
effect-compartment ODE with rate Ke0 whose target is BMD0 + Scale *
(marker - Marker0), where Scale (negative) is the marker-to-BMD
coupling. Baseline TRACP-5b (TRACP5B_BL) enters EKD50, Slope, T50, and
(active-arm-only) Scale as a power-model covariate centred on the cohort
reference 400 mU / dL.
|
|
Zonisamide
(Hashimoto 1994)
|
Steady-state Michaelis-Menten population PK model for zonisamide in 68
Japanese epileptic patients (pediatric + adult) on chronic oral
zonisamide. A power-of-weight body-size factor scales both volume of
distribution and Vmax; concomitant carbamazepine multiplicatively
increases Vmax (Hashimoto 1994 Eqs. 1-4).
|