if (!.Call(`_rxode2_isIntel`)) {
  test_that("ui props", {

    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$props,
                 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)),
                      cmtProp=NULL))

    expect_equal(obj_odes$props,
                 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")),
                      cmtProp=data.frame(Compartment="depot", Property="f")))


    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$props,
                 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)),
                      cmtProp=NULL))

  })

  test_that("linCmt single compartment parses correctly", {

    mod <- function() {
      ini({
        cl <- 0.1
        vc <- 4
        err.sd <- 0.1
      })
      model({
        Cc <- linCmt(cl, vc)
        Cc ~ add(err.sd)
      })
    }

    mod <- mod()

    expect_error(mod$props, NA)

    expect_equal(mod$props,
                 list(pop = c("cl", "vc"),
                      resid = "err.sd",
                      group = structure(list(), names = character(0)),
                      linCmt = TRUE,
                      cmt = "central",
                      output = list(primary = character(0),
                                    secondary = character(0),
                                    endpoint = "Cc",
                                    state = character(0)),
                      cmtProp=NULL))

  })

  test_that("state based endpoint", {

    oncology_sdm_lobo_2002 <- function() {
      description <- "Signal transduction model for delayed concentration effects on cancer cell growth"
      reference <- "Lobo ED, Balthasar JP. Pharmacodynamic modeling of chemotherapeutic effects: Application of a transit compartment model to characterize methotrexate effects in vitro. AAPS J. 2002;4(4):212-222. doi:10.1208/ps040442"
      depends<-"Cc"
      units<-list(time="hr")
      # Values for lkng, ltau, lec50, and kmax are for methotrexate from Lobo 2002,
      # Table 2.  propErr and addErr are added as reasonable values though not from
      # Lobo 2002 where no value is apparent in the paper.
      ini({
        lkng <- log(0.02) ; label("Cell net growth rate (growth minus death) (1/hr)")
        ltau <- log(34.1) ; label("Mean transit time of each transit compartment (hr)")
        lec50 <- log(0.1) ; label("Drug concentration reducing the cell growth by 50% (ug/mL)")
        kmax <- 0.29 ; label("Maximum drug-related reduction in cell growth (1/hr)")
        tumorVolpropSd <- c(0, 0.3) ; label("Proportional residual error (fraction)")
        tumorVoladdSd <- c(0, 50, 1000) ; label("Additive residual error (tumor volume units)")
      })
      model({
        # Cc is the drug concentration
        kng <- exp(lkng)
        tau <- exp(ltau)
        ec50 <- exp(lec50)
        drugEffectTumorVol <- kmax*Cc/(ec50 + Cc)
        tumorVol(0) <- tumorVol0
        d/dt(tumorVol) <- kng*tumorVol - transit4*tumorVol
        d/dt(transit1) <- (drugEffectTumorVol - transit1)/tau
        d/dt(transit2) <- (transit1 - transit2)/tau
        d/dt(transit3) <- (transit2 - transit3)/tau
        d/dt(transit4) <- (transit3 - transit4)/tau
        tumorVol ~ prop(tumorVolpropSd) + add(tumorVoladdSd)
      })
    }

    rx_obj = rxode2::rxode2(oncology_sdm_lobo_2002)

    expect_equal(rx_obj$props$output$endpoint, "tumorVol")
  })
}