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Parameter sweeping for a three-compartment pharmacokinetic model

Source: R/sim_sens_params.R
sim_sens_3cmpt.Rd

Performs parameter sweeping by varying pharmacokinetic parameters in a three-compartment model under IV or oral dosing. Parameter combinations include Vc, Vp1, Vp2, Q1, Q2, CL, and Ka (oral only).

Usage

sim_sens_3cmpt(
  dat,
  sim_vc = list(mode = "manual", values = NULL),
  sim_vp = list(mode = c("auto", "manual"), values = NULL),
  sim_vp2 = list(mode = c("auto", "manual"), values = NULL),
  sim_q = list(mode = c("auto", "manual"), values = NULL, auto.strategy = c("scaled",
    "fixed")),
  sim_q2 = list(mode = c("auto", "manual"), values = NULL, auto.strategy = c("scaled",
    "fixed")),
  sim_cl = list(mode = "manual", values = NULL),
  sim_ka = list(mode = "manual", values = NULL),
  route = c("iv", "oral"),
  ncores = 2,
  verbose = TRUE
)

Arguments

dat

Pharmacokinetic dataset.

sim_vc

List specifying Vc:

  • mode: must be "manual"

  • values: numeric vector

sim_vp

List specifying Vp1:

  • mode: "manual" or "auto"

  • values: numeric vector if manual

sim_vp2

List specifying Vp2:

  • mode: "manual" or "auto"

  • values: numeric vector if manual

sim_q

List specifying Q1:

  • mode: "manual" or "auto"

  • values: numeric vector if manual

  • auto.strategy: "scaled" or "fixed" when auto

sim_q2

List specifying Q2:

  • mode: "manual" or "auto"

  • values: numeric vector if manual

  • auto.strategy: "scaled" or "fixed" when auto

sim_cl

List specifying CL:

  • mode: must be "manual"

  • values: numeric vector

sim_ka

List specifying Ka (oral route only):

  • mode: must be "manual"

  • values: numeric vector

route

Dosing route, either "iv" or "oral". Default is "iv".

ncores

Number of cores to use for parallelization, passed to rxControl(). Default is 2.

verbose

Logical (default = TRUE). Controls whether progress information is displayed during parameter sweeping. When TRUE, a dynamic progress bar is shown using the progressr package to indicate simulation status and elapsed time. When FALSE, progress output is suppressed and the function runs silently.

Value

A data frame containing parameter combinations with model fit metrics.

Details

The function generates a parameter grid and evaluates each combination using Fit_3cmpt_iv or Fit_3cmpt_oral. Model predictions and fit metrics are calculated for each simulation to assess parameter influence and identify optimal regions of the parameter space. Parameters can be provided manually or derived automatically.

See also

Fit_3cmpt_iv, Fit_3cmpt_oral

Author

Zhonghui Huang

Examples

# \donttest{
out <- sim_sens_3cmpt(
  dat = Bolus_2CPT[Bolus_2CPT$ID<6,],
  sim_cl = list(mode = "manual", values = 4),
  sim_vc = list(mode = "manual", values = 50),
  sim_vp = list(mode = "auto"),
  sim_vp2 = list(mode = "auto"),
  sim_q  = list(mode = "auto", auto.strategy = "scaled"),
  sim_q2 = list(mode = "auto", auto.strategy = "scaled"),
  route = "iv",verbose=FALSE
)
head(out[out$rRMSE2==min(out$rRMSE2),])
#> # A tibble: 1 × 14
#>      Vc   Vp1   Vp2    Q1    Q2    CL    Ka    APE   MAE  MAPE  RMSE rRMSE1
#>   <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>  <dbl> <dbl> <dbl> <dbl>  <dbl>
#> 1    50    50    50     8     8     4    NA 47071.  162.  63.3  278.   49.9
#> # ℹ 2 more variables: rRMSE2 <dbl>, Cumulative.Time.Sec <dbl>
# }