tests/testthat/test_advan_with_covariates.R

In PKPDsim: Tools for Performing Pharmacokinetic-Pharmacodynamic Simulations

test_that("Analytic and ODE models with covariates are the same", {
  skip_on_cran()

  ## Create dataset
  dose <- 100
  interval <- 12
  n_days <- 2
  parameters <- list(
    CL = 10,
    V = 50,
    KA = 0.5,
    Q = 5,
    V2 = 100,
    Q2 = 3,
    V3 = 150,
    F1 = 1
  )
  t_obs <- seq(0, 40, .1)
  reg_bolus <- new_regimen(
    amt = dose,
    times = seq(0, interval * n_days * (24/interval), interval),
    type = "bolus"
  )
  ## there is slight difference in how bolus doses are handled.
  ## Analytical equation is perhaps more consistent, so not testing
  ## simulations at dose times. Should look into later.
  t_obs <- t_obs[! t_obs %in% reg_bolus$dose_times]
  covariates <- list(WT = new_covariate(80), CRCL=new_covariate(4.5))

  ## Using analytic equations model:
  data_ana <- sim(
    analytical = "1cmt_iv_bolus",
    parameters = parameters,
    covariates = covariates,
    regimen = reg_bolus,
    t_obs = t_obs,
    covariate_model = "CL = CL * (CRCL / 3)^0.75; V = V * (WT / 70.0)"
  )

  ## Using ODE model:
  mod1 <- new_ode_model(
    code = "
    dAdt[1] = -( (CL*pow(CRCL/3.0, 0.75)) / (V*WT/70.0) ) * A[1];
  ",
  covariates = covariates,
  obs = list(cmt = 1, scale = "V*WT/70.0"), dose = list(cmt = 1)
  )
  data_ode <- sim(
    ode = mod1,
    parameters = parameters,
    covariates = covariates,
    regimen = reg_bolus,
    t_obs = t_obs,
    duplicate_t_obs = TRUE,
    only_obs = TRUE
  )

  expect_equal(nrow(data_ana), nrow(data_ode))
  expect_equal(round(data_ana$y,4), round(data_ode$y, 4))
})