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Ceftazidime (Conil 2007)

Source: vignettes/articles/Conil_2007_ceftazidime.Rmd
Conil_2007_ceftazidime.Rmd

Model and source 

mod_meta <- nlmixr2est::nlmixr(readModelDb("Conil_2007_ceftazidime"))$meta
#> ℹ parameter labels from comments will be replaced by 'label()'
  • Citation: Conil JM, Georges B, Lavit M, Laguerre J, Samii K, Houin G, Saivin S. A population pharmacokinetic approach to ceftazidime use in burn patients: influence of glomerular filtration, gender and mechanical ventilation. Br J Clin Pharmacol. 2007;64(1):27-35. doi:10.1111/j.1365-2125.2007.02857.x
  • Description: 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)
  • Article (DOI): https://doi.org/10.1111/j.1365-2125.2007.02857.x

This vignette validates the packaged Conil_2007_ceftazidime model – a two-compartment IV population PK model for ceftazidime in adult burn-ICU patients with creatinine clearance on CL and sex, mechanical ventilation, and creatinine clearance on the peripheral volume V2 – against the source publication’s Table 1 (baseline demographics), Table 2 (basic-model parameter estimates), and Table 3 (mean PK parameters in the four sex / ventilation strata).

Population

Conil 2007 studied 50 adult burn patients (38 male, 12 female; mean age 52.3 +/- 20.7 years; mean body weight 71.3 +/- 13.5 kg) at the University Hospital of Toulouse-Rangueil Burns Unit over a 4-year period (Conil 2007 Methods, “Subjects and sampling”; Table 1). Patients were treated during the secondary phase of their burn injury for local infection or sepsis. The cohort had a mean burned surface area of 23 +/- 13.5% of total body surface, UBS index 64.8 +/- 50.0, and Baux index 75.6 +/- 22.4. Mean serum creatinine was in the normal range (76.5 +/- 21.8 umol/L), mean creatinine clearance was 105.3 +/- 39.3 mL/min (range 33-191), and 16 patients (32%) required mechanical ventilation during ceftazidime treatment (Table 1).

Each patient received 6 g/24 h of ceftazidime administered as either three 2 g doses every 8 h or six 1 g doses every 4 h; each dose was given as a 20-minute IV infusion via electric syringe. Plasma ceftazidime was assayed by reversed-phase HPLC with UV detection at 260 nm (LLOQ 1 mg/L, calibration linear 1-100 mg/L); 237 concentrations were available from the 50 patients (mean 4.7 samples per patient).

The same information is available programmatically via the model’s population metadata:

str(mod_meta$population)
#> List of 14
#>  $ species       : chr "human"
#>  $ n_subjects    : int 50
#>  $ n_studies     : int 1
#>  $ age_range     : chr "15-90 years"
#>  $ age_median    : chr "52.3 years (mean +/- 20.7 SD)"
#>  $ weight_range  : chr "50-108 kg"
#>  $ weight_median : chr "71.3 kg (mean +/- 13.5 SD)"
#>  $ sex_female_pct: num 24
#>  $ race_ethnicity: chr "Not reported (French university-hospital burn-ICU population, Toulouse)"
#>  $ disease_state : chr "Burn injury during the secondary phase; treated for local infection or sepsis with ceftazidime; mean burned sur"| __truncated__
#>  $ dose_range    : chr "Ceftazidime 6 g/24 h administered as either three 2 g doses every 8 h or six 1 g doses every 4 h; each dose giv"| __truncated__
#>  $ regions       : chr "France (Burns Unit, University Hospital of Toulouse-Rangueil)"
#>  $ mech_vent_pct : num 32
#>  $ notes         : chr "Single-center observational study over 4 years, 50 patients with 237 serum ceftazidime concentrations (mean 4.7"| __truncated__

Source trace

The per-parameter origin is recorded as an in-file comment next to each ini() entry in inst/modeldb/specificDrugs/Conil_2007_ceftazidime.R. The table below collects them in one place. Final-model structural equations and IIV / residual values come from Conil 2007 Results (p. 31, “Final model” subsection); basic-model carry-forward values for Q IIV, V2 IIV, and the proportional residual come from Table 2 and the “Basic model” subsection of Results.

Equation / parameter Value Source location
lcl (CL intercept; non-renal CL) log(1.08) Conil 2007 Results p. 31 final-model eqn CL = 1.08 + 0.0536 * CLCR
e_crcl_cl (CL slope on CRCL) 0.0536 L/h per mL/min Conil 2007 Results p. 31 final-model eqn
lvc (V1) log(18.81) Conil 2007 Results p. 31 final-model eqn V1 = 18.81 L; Table 3 reports 18.8 in all four strata
lvp (V2 baseline scale) log(2.69) Conil 2007 Results p. 31 final-model eqn TVV2 = 2.69 * (1 + 1.43*SEX) * (1 + 2.44*VENT) * (1 + 0.00414*CLCR)
e_sexf_vp (SEXF fractional effect on V2) 1.43 Conil 2007 Results p. 31 final-model eqn
e_mech_vent_vp (MECH_VENT fractional effect on V2) 2.44 Conil 2007 Results p. 31 final-model eqn
e_crcl_vp (CRCL fractional effect on V2) 0.00414 per mL/min Conil 2007 Results p. 31 final-model eqn
lq (Q) log(6.881) Conil 2007 Results p. 31 final-model eqn Q = 6.881 L/h; Table 3 reports 6.9 in all four strata
etalcl ~ 0.02528 log(0.16^2 + 1) Conil 2007 Results p. 31: “Interindividual variability in the clearance was decreased to 16%”
etalvc ~ 0.01676 log(0.13^2 + 1) Conil 2007 Results p. 31: “and that of the central volume of distribution to 13%”
etalq ~ 2.6520 log(3.63^2 + 1) Conil 2007 Table 2 basic-model row “Inter-compartmental clearance” CV 363% (final model silent; carried forward per operator standing instruction)
etalvp ~ 1.5280 log(1.90^2 + 1) Conil 2007 Table 2 basic-model row “Distribution volume of the peripheral compartment” CV 190% (final model silent; carried forward)
propSd <- 0.38 0.38 Conil 2007 Results p. 30 basic-model proportional CV 38% (final model silent; carried forward)
d/dt(central) / d/dt(peripheral1) n/a Conil 2007 Results p. 30 (“A two-compartment model… ADVAN3 TRANS4”); standard 2-cmt linear ODE form
Cc ~ prop(propSd) n/a Conil 2007 Results p. 30 (“a proportional error model best fitted the data”)

Virtual cohort

The original observed ceftazidime concentrations are not publicly available. The virtual cohort below reproduces the four sex / mechanical- ventilation strata of Conil 2007 Table 3, using the stratum-specific median CRCL the paper reports (males not ventilated 114 mL/min, females not ventilated 103, males ventilated 93, females ventilated 87). Each subject receives a single 2 g IV infusion over 20 minutes (rate = 6000 mg/h), sampled densely enough to characterize Cmax during the distribution phase and the terminal half-life out to 24 h.

set.seed(20260618)

# Per-stratum cohort definition matching Conil 2007 Table 3.
strata <- tibble::tribble(
  ~stratum,                 ~n,  ~SEXF, ~MECH_VENT, ~CRCL_median,
  "Males, not ventilated",  100L,    0,         0,          114,
  "Females, not ventilated", 100L,   1,         0,          103,
  "Males, ventilated",      100L,    0,         1,           93,
  "Females, ventilated",    100L,    1,         1,           87
)

# Slight CRCL variability around the per-stratum median so the cohort is
# heterogeneous enough for stable NCA percentile bands; SD 10 mL/min is
# tight relative to the cohort-wide range (33-191) but realistic for an
# already-homogenized stratum.
make_stratum <- function(s, idx_offset) {
  n <- s$n
  crcl <- pmax(20, rnorm(n, mean = s$CRCL_median, sd = 10))
  tibble::tibble(
    id        = idx_offset + seq_len(n),
    stratum   = s$stratum,
    SEXF      = s$SEXF,
    MECH_VENT = s$MECH_VENT,
    CRCL      = crcl
  )
}

cov_tab <- bind_rows(
  make_stratum(strata[1, ], 0L),
  make_stratum(strata[2, ], 100L),
  make_stratum(strata[3, ], 200L),
  make_stratum(strata[4, ], 300L)
)

# Dosing: 2 g IV over 20 min; sampling 0 (pre-dose) through 24 h spanning
# the distribution and terminal phases (cohort half-life ~ 2-8 h per
# stratum, so 24 h covers 3-12 terminal half-lives).
dose_amt    <- 2000          # mg
infusion_h  <- 20 / 60       # 20 minutes
dose_rate   <- dose_amt / infusion_h
sample_times <- c(0, 1/3, 0.5, 1, 1.5, 2, 3, 4, 6, 8, 12, 18, 24)

make_subject <- function(row) {
  doses <- tibble::tibble(
    id   = row$id,        time = 0,
    evid = 1L,            amt  = dose_amt,
    rate = dose_rate,     dv   = NA_real_
  )
  obs <- tibble::tibble(
    id   = row$id,        time = sample_times,
    evid = 0L,            amt  = NA_real_,
    rate = NA_real_,      dv   = NA_real_
  )
  bind_rows(doses, obs) |>
    mutate(
      stratum   = row$stratum,
      SEXF      = row$SEXF,
      MECH_VENT = row$MECH_VENT,
      CRCL      = row$CRCL
    ) |>
    arrange(time, desc(evid))
}

events <- bind_rows(lapply(seq_len(nrow(cov_tab)), function(i) {
  make_subject(cov_tab[i, ])
}))

stopifnot(!anyDuplicated(unique(events[, c("id", "time", "evid")])))

Simulation 

mod         <- readModelDb("Conil_2007_ceftazidime")
mod_typical <- rxode2::zeroRe(mod)
#> ℹ parameter labels from comments will be replaced by 'label()'

sim_stoch <- rxode2::rxSolve(
  object = mod, events = events,
  keep   = c("stratum", "SEXF", "MECH_VENT", "CRCL")
) |>
  as.data.frame()
#> ℹ parameter labels from comments will be replaced by 'label()'

sim_typical <- rxode2::rxSolve(
  object = mod_typical, events = events,
  keep   = c("stratum", "SEXF", "MECH_VENT", "CRCL")
) |>
  as.data.frame()
#> ℹ omega/sigma items treated as zero: 'etalcl', 'etalvc', 'etalq', 'etalvp'
#> Warning: multi-subject simulation without without 'omega'

Replicate Table 3 – typical-value PK parameters by stratum

Conil 2007 Table 3 reports the typical-value CL, V1, Q, V2, total V, elimination rate kel = CL / V1, and apparent half-life t1/2 = ln(2) / kel for each of the four sex / ventilation strata evaluated at the stratum-specific median CRCL. The packaged model reproduces those values directly from the final-model equations:

stratum_typicals <- strata |>
  mutate(
    TVCL = 1.08 + 0.0536 * CRCL_median,
    TVV1 = 18.81,
    TVQ  = 6.881,
    TVV2 = 2.69 *
      (1 + 1.43    * SEXF)      *
      (1 + 2.44    * MECH_VENT) *
      (1 + 0.00414 * CRCL_median),
    TVtot   = TVV1 + TVV2,
    kel     = TVCL / TVV1,
    half_life_apparent = log(2) / kel
  ) |>
  transmute(
    Stratum            = stratum,
    n_paper            = c(27, 7, 11, 5),
    CRCL_mL_min        = CRCL_median,
    `CL (L/h)`         = round(TVCL, 2),
    `V1 (L)`           = round(TVV1, 2),
    `Q (L/h)`          = round(TVQ, 2),
    `V2 (L)`           = round(TVV2, 2),
    `V (L)`            = round(TVtot, 2),
    `kel (1/h)`        = round(kel, 3),
    `t1/2 apparent (h)` = round(half_life_apparent, 2)
  )

knitr::kable(
  stratum_typicals,
  caption = paste(
    "Conil 2007 Table 3 reproduction. n_paper is the stratum size in the",
    "published cohort; the simulated values come from the packaged",
    "model's final-model equations evaluated at the per-stratum",
    "median CRCL."
  ),
  align = c("l", "r", "r", "r", "r", "r", "r", "r", "r", "r")
)
Conil 2007 Table 3 reproduction. n_paper is the stratum size in the published cohort; the simulated values come from the packaged model’s final-model equations evaluated at the per-stratum median CRCL.
Stratum n_paper CRCL_mL_min CL (L/h) V1 (L) Q (L/h) V2 (L) V (L) kel (1/h) t1/2 apparent (h)
Males, not ventilated 27 114 7.19 18.81 6.88 3.96 22.77 0.382 1.81
Females, not ventilated 7 103 6.60 18.81 6.88 9.32 28.13 0.351 1.98
Males, ventilated 11 93 6.06 18.81 6.88 12.82 31.63 0.322 2.15
Females, ventilated 5 87 5.74 18.81 6.88 30.59 49.40 0.305 2.27

Compared against the published Table 3 the model reproduces every value to within rounding tolerance (males not vent: CL 7.19 vs 7.2 published, V2 3.96 vs 4.0; females not vent: CL 6.60 vs 6.6, V2 9.32 vs 9.3; males vent: CL 6.07 vs 6.1, V2 12.82 vs 12.8; females vent: CL 5.74 vs 5.7, V2 30.59 vs 30.6).

Typical-value concentration-time profiles by stratum 

sim_typical |>
  filter(time > 0) |>
  group_by(stratum, time) |>
  summarise(Cc = median(Cc, na.rm = TRUE), .groups = "drop") |>
  ggplot(aes(time, Cc, colour = stratum)) +
  geom_line(linewidth = 0.9) +
  scale_y_log10() +
  labs(
    x = "Time (h)",
    y = "Ceftazidime in serum (mg/L, log scale)",
    title    = "Typical-value concentration-time profiles by stratum",
    subtitle = paste(
      "Single 2 g IV infusion over 20 min;",
      "per-stratum median CRCL from Conil 2007 Table 3"
    ),
    colour   = "Stratum"
  ) +
  theme_minimal() +
  theme(legend.position = "bottom")

Stochastic VPC by stratum 

sim_stoch |>
  filter(time > 0) |>
  group_by(stratum, time) |>
  summarise(
    Q05  = quantile(Cc, 0.05, na.rm = TRUE),
    Q50  = quantile(Cc, 0.50, na.rm = TRUE),
    Q95  = quantile(Cc, 0.95, na.rm = TRUE),
    .groups = "drop"
  ) |>
  ggplot(aes(time, Q50)) +
  geom_ribbon(aes(ymin = Q05, ymax = Q95), fill = "gray70", alpha = 0.5) +
  geom_line(linewidth = 0.7) +
  facet_wrap(~ stratum, nrow = 2) +
  scale_y_log10() +
  labs(
    x = "Time (h)",
    y = "Ceftazidime in serum (mg/L, log scale)",
    title    = "Stochastic VPC by stratum",
    subtitle = "Median (line) and 5th-95th percentile band (ribbon)"
  ) +
  theme_minimal()

PKNCA validation

PKNCA computes Cmax, Tmax, AUC0-Inf, and the terminal half-life on the stochastic simulation. The Conil 2007 publication does not tabulate NCA values (its Table 3 is structural-model-based with an apparent half-life ln(2) / (CL / V1) that excludes distributional decay), so the PKNCA values are presented here against Table 3 as a coarse cross-reference and against the dose-divided-by-CL expectation as an exact sanity check. The NCA terminal half-life is the true terminal half-life of the two-compartment model and is expected to be longer than Table 3’s apparent half-life, particularly for strata with a large peripheral volume V2.

sim_nca <- sim_stoch |>
  filter(!is.na(Cc)) |>
  select(id, time, Cc, stratum)

# Ensure a time=0 row per (id, stratum); for IV bolus / infusion the
# pre-dose concentration is 0.
sim_nca <- bind_rows(
  sim_nca,
  sim_nca |> distinct(id, stratum) |> mutate(time = 0, Cc = 0)
) |>
  distinct(id, stratum, time, .keep_all = TRUE) |>
  arrange(id, stratum, time)

dose_df <- events |>
  filter(evid == 1L) |>
  select(id, time, amt, stratum)

conc_obj <- PKNCA::PKNCAconc(
  data    = as.data.frame(sim_nca),
  formula = Cc ~ time | stratum + id,
  concu   = "mg/L",
  timeu   = "h"
)
dose_obj <- PKNCA::PKNCAdose(
  data    = as.data.frame(dose_df),
  formula = amt ~ time | stratum + id,
  doseu   = "mg"
)

intervals <- data.frame(
  start       = 0,
  end         = Inf,
  cmax        = TRUE,
  tmax        = TRUE,
  aucinf.obs  = TRUE,
  half.life   = TRUE
)

nca_data <- PKNCA::PKNCAdata(conc_obj, dose_obj, intervals = intervals)
nca_res  <- suppressWarnings(PKNCA::pk.nca(nca_data))

Comparison against Table 3

The reference values are derived from Conil 2007 Table 3: the apparent half-life is ln(2) / (CL / V1) (Table 3 row “Half-life (h)”), and AUCinf is Dose / CL at the per-stratum typical CL. Cmax is not tabulated in the paper – Table 3 reports structural parameters but no peak concentration – so the simulated Cmax appears here without a reference value for comparison.

published <- tibble::tribble(
  ~stratum,                 ~aucinf.obs, ~half.life,
  "Males, not ventilated",  2000 / 7.2,  1.81,
  "Females, not ventilated",2000 / 6.6,  1.98,
  "Males, ventilated",      2000 / 6.1,  2.15,
  "Females, ventilated",    2000 / 5.7,  2.27
)

cmp <- nlmixr2lib::ncaComparisonTable(
  simulated     = nca_res,
  reference     = published,
  by            = "stratum",
  params        = c("aucinf.obs", "half.life"),
  units         = c(aucinf.obs = "mg*h/L", half.life = "h"),
  tolerance_pct = 30
)

knitr::kable(
  cmp,
  caption = paste(
    "Simulated NCA vs Conil 2007 Table 3 reference values.",
    "AUC0-Inf reference = Dose / CL with the per-stratum typical CL;",
    "t1/2 reference = Table 3 apparent half-life (= ln(2) * V1 / CL,",
    "the central-compartment elimination half-life, NOT the true",
    "terminal half-life). The two-compartment model's true terminal",
    "half-life is longer than the apparent half-life, particularly for",
    "strata with a large peripheral V2, so the NCA half-life is",
    "expected to exceed Table 3 by a stratum-dependent factor."
  ),
  align = c("l", "l", "r", "r", "r")
)
Simulated NCA vs Conil 2007 Table 3 reference values. AUC0-Inf reference = Dose / CL with the per-stratum typical CL; t1/2 reference = Table 3 apparent half-life (= ln(2) * V1 / CL, the central-compartment elimination half-life, NOT the true terminal half-life). The two-compartment model’s true terminal half-life is longer than the apparent half-life, particularly for strata with a large peripheral V2, so the NCA half-life is expected to exceed Table 3 by a stratum-dependent factor.
NCA parameter stratum Reference Simulated % diff
AUC0-∞ (obs) (mg*h/L) Males, not ventilated 278 279 +0.6%
AUC0-∞ (obs) (mg*h/L) Females, not ventilated 303 299 -1.4%
AUC0-∞ (obs) (mg*h/L) Males, ventilated 328 333 +1.4%
AUC0-∞ (obs) (mg*h/L) Females, ventilated 351 342 -2.5%
t½ (h) Males, not ventilated 1.81 2.5 +38.0%*
t½ (h) Females, not ventilated 1.98 3.5 +76.6%*
t½ (h) Males, ventilated 2.15 4.29 +99.7%*
t½ (h) Females, ventilated 2.27 6.99 +208.0%* 
fn <- attr(cmp, "footnote")
if (!is.null(fn)) cat(fn)
#> * differs from reference by more than ±30%.

Simulated Cmax by stratum 

cmax_tbl <- as.data.frame(nca_res$result) |>
  filter(PPTESTCD == "cmax") |>
  group_by(stratum) |>
  summarise(
    `Median Cmax (mg/L)` = round(median(PPORRES, na.rm = TRUE), 1),
    `Q05  Cmax (mg/L)`   = round(quantile(PPORRES, 0.05, na.rm = TRUE), 1),
    `Q95  Cmax (mg/L)`   = round(quantile(PPORRES, 0.95, na.rm = TRUE), 1),
    .groups = "drop"
  )

knitr::kable(
  cmax_tbl,
  caption = paste(
    "Simulated Cmax after a single 2 g 20-minute IV infusion.",
    "Conil 2007 does not tabulate Cmax in Table 3; the values are",
    "presented here as a sanity check that simulated peak",
    "concentrations are in the expected clinical range",
    "(~80-130 mg/L for a 2 g IV dose into V1 ~ 18.8 L)."
  ),
  align = c("l", "r", "r", "r")
)
Simulated Cmax after a single 2 g 20-minute IV infusion. Conil 2007 does not tabulate Cmax in Table 3; the values are presented here as a sanity check that simulated peak concentrations are in the expected clinical range (~80-130 mg/L for a 2 g IV dose into V1 ~ 18.8 L).
stratum Median Cmax (mg/L) Q05 Cmax (mg/L) Q95 Cmax (mg/L)
Females, not ventilated 94.9 67.6 116.4
Females, ventilated 91.4 60.2 113.4
Males, not ventilated 92.7 77.1 111.7
Males, ventilated 93.8 65.4 114.5

Assumptions and deviations

  • IIV on Q and V2 and the residual error are carried forward from the basic model. Conil 2007 Results p. 31 explicitly reports only the final-model IIV on CL (16%) and V1 (13%); the section is silent on IIV for Q and V2 in the final model and on the final-model residual error. Per the operator’s standing instruction (sidecar response, 2026-06-17), silence is interpreted as “unchanged from the basic model” rather than “dropped to zero.” The packaged model therefore carries the basic-model values forward: Q IIV 363% (Table 2 row “Inter-compartmental clearance”), V2 IIV 190% (Table 2 row “Distribution volume of the peripheral compartment”), and proportional residual CV 38% (Results p. 30, “The residual variability… was 38%”). The 363% Q IIV is unusually large but matches the reported basic-model value verbatim; downstream users who simulate VPCs will see a wide spread on Q-driven distribution.

  • MECH_VENT canonical newly ratified. Conil 2007 uses a binary indicator VENT (0 = not ventilated, 1 = mechanically ventilated) on the peripheral volume V2. No existing entry in inst/references/covariate-columns.md covered the concept (the OXYSUP_HIGH entry pools mechanical ventilation with high-flow oxygen in the Lin 2024 casirivimab analysis but is structurally a different stratification). This PR ratifies the new canonical MECH_VENT – a binary mechanical-ventilation treatment-status indicator with general scope, following the precedent of HEMODIAL and CRRT_STATUS. The orientation matches the source paper directly (0 = no MV, 1 = MV).

  • CL covariate equation is additive linear on the linear scale. Conil 2007 final-model equation CL = 1.08 + 0.0536 * CLCR is an additive intercept-plus-slope model with no centering / scaling / normalization of CRCL. The packaged model encodes this as cl <- (exp(lcl) + e_crcl_cl * CRCL) * exp(etalcl) with exp(lcl) = 1.08 L/h and e_crcl_cl = 0.0536 L/h per mL/min. At zero CRCL the model gives CL = 1.08 L/h (non-renal baseline), which is biologically meaningful (a small fraction of ceftazidime is cleared by non-renal routes); at the cohort-wide range (33-191 mL/min) CL spans 2.85-11.32 L/h, consistent with the paper’s reported four-stratum range of 5.7-7.2 L/h at the per-stratum median CRCL.

  • V2 covariates are chained multiplicative fractional changes, not multiplicative percent or exponential terms. Conil 2007 final-model equation V2 = 2.69 * (1 + 1.43*SEX) * (1 + 2.44*VENT) * (1 + 0.00414*CLCR) is a chained product of (1 + e * COV) factors. This is the form the paper uses literally (Results p. 31, equation block); the packaged model preserves the chain rather than collapsing it to a single exponential or power form. The four-strata reproduction in “Replicate Table 3” confirms the form is correct.

  • CRCL stored under the canonical CRCL column despite NOT being BSA-normalized. The canonical CRCL column accepts raw Cockcroft-Gault mL/min when the source paper does not BSA-normalize (precedent: Delattre_2010_amikacin.R for raw Cockcroft-Gault in a Belgian ICU cohort). Conil 2007 Methods records the Cockcroft-Gault equation as their CLCR derivation, with the standard 0.85 correction factor applied to women; no BSA normalization is mentioned. The per-model covariateData[[CRCL]]$units and notes document this. Reference values listed in the canonical entry (80, 90, 100 mL/min/1.73 m^2) are for BSA-normalized estimates and should not be used as a comparison anchor for Conil 2007’s raw mL/min values.

  • Independent (diagonal) IIV between CL, V1, V2, and Q. Conil 2007 reports the IIV model as theta_i = theta_pop * exp(eta_i) (Results p. 30, basic-model section) with eta drawn from a normal distribution. The paper does not state whether OMEGA was diagonal or block-structured and reports a single CV per parameter with no off-diagonal covariance estimates, consistent with diagonal OMEGA. The packaged model uses diagonal IIV; this is consistent with the reported information but cannot be cross-checked against the original NONMEM control stream (not on disk).

  • omega^2 = log(CV^2 + 1). Conil 2007 reports interindividual variability as CV%; the corresponding log-normal variance was computed via omega^2 = log(CV^2 + 1) – the standard NONMEM/PsN back-transformation – and entered as the eta... initial value.

  • Race / ethnicity not modeled. Conil 2007 does not report race composition; the cohort is a French university-hospital burn-ICU population. The analysis did not test race as a covariate and so no race effect is included.

  • NCA terminal half-life differs from Table 3 apparent half-life. Conil 2007 Table 3 reports t1/2 = ln(2) * V1 / CL (computed from kel = CL / V1), which is the central-compartment elimination half- life – NOT the true terminal half-life of the two-compartment model. The simulated NCA half-life captures the true terminal slope and is longer than Table 3’s apparent half-life by a stratum- dependent factor (largest in the ventilated-females stratum, where V2 is largest relative to V1). The 30% tolerance flag used in the comparison table accommodates this methodological gap rather than flagging a model defect.

  • Dose units. The model uses mg for dose and mg/L for concentration (paper convention for ceftazidime). With dose in mg and volumes in L, the ratio central / vc directly gives mg/L; no scale factor is applied.

  • Single-dose simulation in this vignette. Conil 2007’s data collection captured trough and peak samples 24 h and 48 h after treatment start across q4h or q8h dosing regimens. The vignette simulates a single 2 g dose for NCA simplicity; multi-dose simulation (3 doses q8h or 6 doses q4h) is mechanically straightforward (add additional dose rows in the event table).