Add an indirect response model to a PK model
Arguments
- ui
rxode2 model
- stim
what type of stimulation indirect response model:
- `in`: stimulation of input
- `out`: stimulation of output
- inhib
what type of inhibition indirect response model:
- `in`: inhibition of input
- `out`: inhibition of output
- hill
Boolean stating if a hill sigmoid coefficient will be added
- ek
simulation linear constant
- ik
inhibition linear constant
- emax
Emax parameter
- ec50
EC50 parameter
- imax
maximum inhibitory concentration
- ic50
concentration where half of the Imax occurs
- kin
this is the kin parameter name
- kout
this is the kout parameter name
- g
hill coefficient
- cc
the concentration value
- R
drug response compartment
- effect
the effect variable that will be modeled
See also
Other Indirect response:
addIndirectLin(),
convertKinR0()
Examples
readModelDb("PK_2cmt_no_depot") |>
addIndirect(stim="in",hill=TRUE)
#>
#>
#> ── rxode2-based free-form 3-cmt ODE model ──────────────────────────────────────
#> ── Initalization: ──
#> Fixed Effects ($theta):
#> lcl lvc lvp lq propSd lkin lkout effectSd
#> 1.000000 3.000000 5.000000 0.100000 0.500000 0.100000 0.100000 0.100000
#> lEmax lEC50 lgg
#> 0.100000 0.100000 -2.302585
#>
#> States ($state or $stateDf):
#> Compartment Number Compartment Name
#> 1 1 central
#> 2 2 peripheral1
#> 3 3 R
#> ── Multiple Endpoint Model ($multipleEndpoint): ──
#> variable cmt dvid*
#> 1 Cc ~ … cmt='Cc' or cmt=4 dvid='Cc' or dvid=1
#> 2 effect ~ … cmt='effect' or cmt=5 dvid='effect' or dvid=2
#> * If dvids are outside this range, all dvids are re-numered sequentially, ie 1,7, 10 becomes 1,2,3 etc
#>
#> ── Model (Normalized Syntax): ──
#> function() {
#> ini({
#> lcl <- 1
#> label("Clearance (CL)")
#> lvc <- 3
#> label("Central volume of distribution (V)")
#> lvp <- 5
#> label("Peripheral volume of distribution (Vp)")
#> lq <- 0.1
#> label("Intercompartmental clearance (Q)")
#> propSd <- c(0, 0.5)
#> label("Proportional residual error (fraction)")
#> lkin <- 0.1
#> label("zero order response production(kin)")
#> lkout <- 0.1
#> label("first order rate response loss (kout)")
#> effectSd <- c(0, 0.1)
#> label("additive error for effect")
#> lEmax <- 0.1
#> label("Maximum effect (Emax)")
#> lEC50 <- 0.1
#> label("Concentration of 50% Emax (Emax)")
#> lgg <- -2.30258509299405
#> label("logit-constrained Hill coefficient g")
#> })
#> model({
#> Emax <- exp(lEmax)
#> EC50 <- exp(lEC50)
#> g <- expit(lgg, 0.1, 10)
#> kin <- exp(lkin)
#> kout <- exp(lkout)
#> cl <- exp(lcl)
#> vc <- exp(lvc)
#> vp <- exp(lvp)
#> q <- exp(lq)
#> kel <- cl/vc
#> k12 <- q/vc
#> k21 <- q/vp
#> d/dt(central) <- kel * central - k12 * central + k21 *
#> peripheral1
#> d/dt(peripheral1) <- k12 * central - k21 * peripheral1
#> Cc <- central/vc
#> Cc ~ prop(propSd)
#> R(0) <- kin/kout
#> d/dt(R) <- kin * (1 + Emax * Cc^g/(Cc^g + EC50^g)) -
#> kout * R
#> effect <- R
#> effect ~ add(effectSd)
#> })
#> }
readModelDb("PK_2cmt_no_depot") |>
addIndirect(inhib="out", imax=1)
#>
#>
#> ── rxode2-based free-form 3-cmt ODE model ──────────────────────────────────────
#> ── Initalization: ──
#> Fixed Effects ($theta):
#> lcl lvc lvp lq propSd lkin lkout effectSd
#> 1.0 3.0 5.0 0.1 0.5 0.1 0.1 0.1
#> lImax lIC50
#> 0.1 0.1
#>
#> States ($state or $stateDf):
#> Compartment Number Compartment Name
#> 1 1 central
#> 2 2 peripheral1
#> 3 3 R
#> ── Multiple Endpoint Model ($multipleEndpoint): ──
#> variable cmt dvid*
#> 1 Cc ~ … cmt='Cc' or cmt=4 dvid='Cc' or dvid=1
#> 2 effect ~ … cmt='effect' or cmt=5 dvid='effect' or dvid=2
#> * If dvids are outside this range, all dvids are re-numered sequentially, ie 1,7, 10 becomes 1,2,3 etc
#>
#> ── Model (Normalized Syntax): ──
#> function() {
#> ini({
#> lcl <- 1
#> label("Clearance (CL)")
#> lvc <- 3
#> label("Central volume of distribution (V)")
#> lvp <- 5
#> label("Peripheral volume of distribution (Vp)")
#> lq <- 0.1
#> label("Intercompartmental clearance (Q)")
#> propSd <- c(0, 0.5)
#> label("Proportional residual error (fraction)")
#> lkin <- 0.1
#> label("zero order response production(kin)")
#> lkout <- 0.1
#> label("first order rate response loss (kout)")
#> effectSd <- c(0, 0.1)
#> label("additive error for effect")
#> lImax <- 0.1
#> label("Maximum effect (Imax)")
#> lIC50 <- 0.1
#> label("Concentration of 50% Imax (Imax)")
#> })
#> model({
#> Imax <- exp(lImax)
#> IC50 <- exp(lIC50)
#> kin <- exp(lkin)
#> kout <- exp(lkout)
#> cl <- exp(lcl)
#> vc <- exp(lvc)
#> vp <- exp(lvp)
#> q <- exp(lq)
#> kel <- cl/vc
#> k12 <- q/vc
#> k21 <- q/vp
#> d/dt(central) <- kel * central - k12 * central + k21 *
#> peripheral1
#> d/dt(peripheral1) <- k12 * central - k21 * peripheral1
#> Cc <- central/vc
#> Cc ~ prop(propSd)
#> R(0) <- kin/kout
#> d/dt(R) <- kin - kout * R * (1 - Imax * Cc/(Cc + IC50))
#> effect <- R
#> effect ~ add(effectSd)
#> })
#> }