Merge pull request #641 from nlmixr2/640-use-fast-compression-for-rxu…

…i-by-default

Add fast compression

DESCRIPTION

@@ -1,5 +1,5 @@
 Package: rxode2
-Version: 2.1.1
+Version: 2.1.1.9000
 Title: Facilities for Simulating from ODE-Based Models
 Authors@R: c(
    person("Matthew L.","Fidler",

NAMESPACE

@@ -147,6 +147,7 @@ S3method(rxUiGet,muRefTable)
 S3method(rxUiGet,multipleEndpoint)
 S3method(rxUiGet,mvFromExpression)
 S3method(rxUiGet,omega)
+S3method(rxUiGet,params)
 S3method(rxUiGet,paramsLine)
 S3method(rxUiGet,simulationIniModel)
 S3method(rxUiGet,simulationModel)

NEWS.md

@@ -1,3 +1,9 @@
+# rxode2 (development version)
+
+## Other changes
+
+- `rxUi` compression now defaults to fast compression
+
 # rxode2 2.1.0
 
 ## Breaking changes

R/rxUiGet.R

@@ -65,6 +65,65 @@ rxUiGet.stateDf <- function(x, ...) {
 }
 attr(rxUiGet.stateDf, "desc") <- "states and cmt number data.frame"
 
+#' @export
+#' @rdname rxUiGet
+rxUiGet.params <- function(x, ...) {
+  .x <- x[[1]]
+  .ini <- .x$iniDf
+  .w <- !is.na(.ini$ntheta) & is.na(.ini$err)
+  .pop <- .ini$name[.w]
+  .w <- !is.na(.ini$ntheta) & !is.na(.ini$err)
+  .resid <- .ini$name[.w]
+  .w <- !is.na(.ini$neta1)
+  .cnds <- unique(.ini$condition[.w])
+  .var <- lapply(.cnds,
+                 function(cnd) {
+                   .w <- which(.ini$condition == cnd &
+                                 .ini$neta1 == .ini$neta2)
+                   .ini$name[.w]
+                 })
+  .mv <- rxGetModel(.x)
+  .lin <- FALSE
+  .doseExtra <- character(0)
+  .mv <- rxModelVars(.x)
+  if (!is.null(.x$.linCmtM)) {
+    .lin <- TRUE
+    if (.mv$extraCmt == 2L) {
+      .doseExtra <- c("depot", "central")
+    } else if (.mv$extramt == 1L) {
+      .doseExtra <- "central"
+    }
+  }
+  .predDf <- .x$predDf
+  if (!.lin && any(.predDf$linCmt)) {
+    .lin <- TRUE
+    if (.mv$flags["ka"] == 1L) {
+      .doseExtra <- c("depot", "central")
+    } else {
+      .doseExtra <- "central"
+    }
+  }
+  .dose <- c(.doseExtra, .x$state)
+  names(.var) <- .cnds
+  .lhs <- .mv$lhs
+  .end <- .x$predDf$var
+  .end <- .end[.end %in% .lhs]
+  .lhs <- .lhs[!(.lhs %in% .end)]
+  .varLhs <- .x$varLhs
+  .primary <- .lhs[.lhs %in% .varLhs]
+  .secondary <- .lhs[!(.lhs %in% .primary)]
+  list(pop=.pop,
+       resid=.resid,
+       group=.var,
+       linCmt=.lin,
+       cmt=.dose,
+       output=list(primary=.primary,
+                   secondary=.secondary,
+                   endpoint=.end,
+                   state=.x$state))
+}
+attr(rxUiGet.params, "desc") <- "Parameter names"
+
 #' @export
 #' @rdname rxUiGet
 rxUiGet.theta <- function(x, ...) {

R/ui.R

@@ -445,7 +445,7 @@ rxUiDecompress <- function(ui) {
 rxUiCompress <- function(ui) {
   if (!inherits(ui, "rxUi")) return(ui)
   if (is.environment(ui)) {
-    .ret <- qs::qserialize(ui)
+    .ret <- qs::qserialize(ui, preset="fast")
     class(.ret) <- c("rxUi", "raw")
     return(.ret)
   }

tests/testthat/test-ui-param.R

@@ -0,0 +1,184 @@
+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))))
+
+})