if (!.Call(`_rxode2_isIntel`)) { test_that("ui params", { fun_odes <- function() { description <- "Dupilumab PK model (Kovalenko 2020)" reference <- "Kovalenko P, Davis JD, Li M, et al. Base and Covariate Population Pharmacokinetic Analyses of Dupilumab Using Phase 3 Data. Clinical Pharmacology in Drug Development. 2020;9(6):756-767. doi:10.1002/cpdd.780" # Model 1 from table 1 and supplementary Table 2 in the publication and its # supplement. covariateData <- list( WT = "Body weight in kg" ) ini({ lvc <- log(2.48); label("central volume (L)") lke <- log(0.0534); label("elimination rate (1/d)") lkcp <- log(0.213); label("central-to-peripheral rate (1/d)") Mpc <- 0.686; label("ratio of kcp and kpc (kpc is peripheral to central rate with units of 1/d)") lka <- log(0.256); label("absorption rate (1/d)") lMTT <- log(0.105); label("mean transit time (d)") lVm <- log(1.07); label("maximum target-mediated rate of elimination (mg/L/d)") Km <- fixed(0.01); label("Michaelis-Menten constant (mg/L)") lfdepot <- log(0.643); label("Bioavailability (fraction)") e_wt_vc <- 0.711; label("Exponent of weight on central volume (unitless)") etalvc ~ 0.192 etalke ~ 0.285 etalka ~ 0.474 etalvm ~ 0.236 etamtt ~ 0.525 # etamtt is assumed to be on log-scale MTT to prevent negative values; this is a difference relative to Supplementary Table 2 cppropSd <- 0.15; label("Proportional residual error (fraction)") cpaddSd <- fixed(0.03); label("Additive residual error (mg/L)") }) model({ # Weight normalization to 75 kg is assumed based on prior publication. It # is not specified in the current publication: # Kovalenko P, DiCioccio AT, Davis JD, et al. Exploratory Population PK # Analysis of Dupilumab, a Fully Human Monoclonal Antibody Against # IL-4Ralpha, in Atopic Dermatitis Patients and Normal Volunteers. CPT # Pharmacometrics Syst Pharmacol. 2016;5(11):617-624. doi:10.1002/psp4.12136 vc <- exp(lvc + etalvc)*(WT/75)^e_wt_vc ke <- exp(lke + etalke) kcp <- exp(lkcp) ka <- exp(lka + etalka) MTT <- exp(lMTT + etamtt) Vm <- exp(lVm + etalvm) # Derived parameters kpc <- kcp/Mpc ktr <- (3 + 1)/MTT d/dt(depot) <- -ktr*depot d/dt(transit1) <- ktr*(depot - transit1) d/dt(transit2) <- ktr*(transit1 - transit2) d/dt(transit3) <- ktr*transit2 - ka*transit3 # Linear and Michaelis-Menten clearance d/dt(central) <- ka*transit3 - ke*central - kcp*central + kpc*periph - central*(Vm/(Km + central/vc)) d/dt(periph) <- kcp*central - kpc*periph f(depot) <- exp(lfdepot) # No unit conversion is required to change mg/L (dosing amount/central # volume unit) to mg/L (measurement unit) Cc <- central/vc Cc ~ add(cpaddSd) + prop(cppropSd) }) } fun_ana <- function() { description <- "Two compartment PK model with linear clearance for average monoclonal antibodies (Davda 2014)" reference <- "Davda JP, Dodds MG, Gibbs MA, Wisdom W, Gibbs JP. A model-based meta-analysis of monoclonal antibody pharmacokinetics to guide optimal first-in-human study design. MAbs. 2014;6(4):1094-1102. doi:10.4161/mabs.29095" ini({ lfdepot <- log(0.744) ; label("Subcutaneous bioavailability (fraction)") lka <- log(0.282) ; label("Absorption rate (Ka, 1/day)") lcl <- log(0.200) ; label("Clearance (CL, L/day)") lv <- log(3.61) ; label("Central volume of distribution (V, L)") lvp <- log(2.75) ; label("Peripheral volume of distribution (Vp, L)") lq <- log(0.747) ; label("Intercompartmental clearance (Q, L/day)") allocl <- 0.865 ; label("Allometric exponent on clearance and intercompartmental clearance (unitless)") allov <- 0.957 ; label("Allometric exponent on volumes of distribution (unitless)") etafdepot ~ 0 etaka ~ 0.416 etacl + etav + etavp ~ c(0.0987, 0.0786, 0.116, 0.0377, 0.0619, 0.0789) etaq ~ 0.699 prop.err <- 0.144 ; label("Proportional residual error (fraction)") }) model({ # WT is body weight in kg fdepot <- exp(lfdepot + etafdepot) ka <- exp(lka + etaka) wtnorm <- log(WT/70) cl <- exp(lcl + allocl*wtnorm + etacl) q <- exp(lq + allocl*wtnorm + etaq) v <- exp(lv + allov*wtnorm + etav) vp <- exp(lvp + allov*wtnorm + etavp) Cc <- linCmt() f(depot) <- fdepot # Units are dosing units/L (typically mg/L = ug/mL) Cc ~ prop(prop.err) }) } obj_ana = rxode2(fun_ana) obj_odes = rxode2(fun_odes) expect_equal(obj_ana$params, list(pop = c("lfdepot", "lka", "lcl", "lv", "lvp", "lq", "allocl", "allov"), resid = "prop.err", group = list(id = c("etafdepot", "etaka", "etacl", "etav", "etavp", "etaq")), linCmt = TRUE, cmt = c("depot", "central"), output = list(primary = c("fdepot", "ka", "wtnorm", "cl", "q", "v", "vp"), secondary = character(0), endpoint = "Cc", state = character(0)))) expect_equal(obj_odes$params, list(pop = c("lvc", "lke", "lkcp", "Mpc", "lka", "lMTT", "lVm", "Km", "lfdepot", "e_wt_vc"), resid = c("cppropSd", "cpaddSd"), group = list(id = c("etalvc", "etalke", "etalka", "etalvm", "etamtt")), linCmt = FALSE, cmt = c("depot", "transit1", "transit2", "transit3", "central", "periph"), output = list(primary = c("vc", "ke", "kcp", "ka", "MTT", "Vm", "kpc"), secondary = "ktr", endpoint = "Cc", state = c("depot", "transit1", "transit2", "transit3", "central", "periph")))) fun_ana2 <- function() { description <- "Two compartment PK model with linear clearance for average monoclonal antibodies (Davda 2014)" reference <- "Davda JP, Dodds MG, Gibbs MA, Wisdom W, Gibbs JP. A model-based meta-analysis of monoclonal antibody pharmacokinetics to guide optimal first-in-human study design. MAbs. 2014;6(4):1094-1102. doi:10.4161/mabs.29095" ini({ lfdepot <- log(0.744) ; label("Subcutaneous bioavailability (fraction)") lka <- log(0.282) ; label("Absorption rate (Ka, 1/day)") lcl <- log(0.200) ; label("Clearance (CL, L/day)") lv <- log(3.61) ; label("Central volume of distribution (V, L)") lvp <- log(2.75) ; label("Peripheral volume of distribution (Vp, L)") lq <- log(0.747) ; label("Intercompartmental clearance (Q, L/day)") allocl <- 0.865 ; label("Allometric exponent on clearance and intercompartmental clearance (unitless)") allov <- 0.957 ; label("Allometric exponent on volumes of distribution (unitless)") etafdepot ~ 0 etaka ~ 0.416 etacl + etav + etavp ~ c(0.0987, 0.0786, 0.116, 0.0377, 0.0619, 0.0789) etaq ~ 0.699 prop.err <- 0.144 ; label("Proportional residual error (fraction)") }) model({ # WT is body weight in kg fdepot <- exp(lfdepot + etafdepot) ka <- exp(lka + etaka) wtnorm <- log(WT/70) cl <- exp(lcl + allocl*wtnorm + etacl) q <- exp(lq + allocl*wtnorm + etaq) v <- exp(lv + allov*wtnorm + etav) vp <- exp(lvp + allov*wtnorm + etavp) linCmt() ~ prop(prop.err) f(depot) <- fdepot # Units are dosing units/L (typically mg/L = ug/mL) }) } tmp <- fun_ana2() expect_equal(tmp$params, list(pop = c("lfdepot", "lka", "lcl", "lv", "lvp", "lq", "allocl", "allov"), resid = "prop.err", group = list(id = c("etafdepot", "etaka", "etacl", "etav", "etavp", "etaq")), linCmt = TRUE, cmt = c("depot", "central"), output = list(primary = c("fdepot", "ka", "wtnorm", "cl", "q", "v", "vp"), secondary = character(0), endpoint = character(0), state = character(0)))) }) }