Skip to contents

Parameter sweeping for a one-compartment Michaelis-Menten model

Source: R/sim_sens_params.R
sim_sens_1cmpt_mm.Rd

Performs parameter sweeping by varying pharmacokinetic parameters in a one-compartment model with Michaelis-Menten elimination.

Usage

sim_sens_1cmpt_mm(
  dat,
  sim_vmax = list(mode = "auto", values = NULL, est.cl = NULL),
  sim_km = list(mode = "auto", values = NULL),
  sim_vd = list(mode = "manual", values = NULL),
  sim_ka = list(mode = "manual", values = NULL),
  route = c("iv", "oral"),
  ncores = 2,
  verbose = TRUE
)

Arguments

dat

A data frame containing raw time–concentration data in the standard nlmixr2 format.

sim_vmax

List specifying Vmax:

  • mode: "manual" or "auto"

  • values: numeric vector if mode = "manual"

  • est.cl: required if mode = "auto"

sim_km

List specifying Km:

  • mode: "manual" or "auto"

  • values: numeric vector if mode = "manual"

sim_vd

List specifying Vd:

  • 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 and model fit metrics.

Details

The function generates a parameter grid and performs model fitting for each combination using Fit_1cmpt_mm_iv. Parameters can be specified manually or automatically derived. Model predictions and fit metrics are computed for each simulation to assess parameter sensitivity.

See also

Fit_1cmpt_mm_iv, Fit_1cmpt_mm_oral

Author

Zhonghui Huang

Examples

# \donttest{
# Example: IV dosing scenario with automatic Vmax and Km
out <- sim_sens_1cmpt_mm(
  dat = Bolus_1CPTMM[Bolus_1CPTMM$ID<50,],
  sim_vmax = list(mode = "auto", est.cl = 4),
  sim_km   = list(mode = "auto"),
  sim_vd   = list(mode = "manual", values = 70),
  sim_ka   = list(mode = "manual", values = NA),
  route = "iv"
)
head(out[out$rRMSE2==min(out$rRMSE2),])
#> # A tibble: 1 × 11
#>    Vmax    Km    Vd    Ka      APE   MAE  MAPE  RMSE rRMSE1 rRMSE2
#>   <dbl> <dbl> <dbl> <dbl>    <dbl> <dbl> <dbl> <dbl>  <dbl>  <dbl>
#> 1 1427.  178.    70    NA 1697957.  599.  36.5 1286.   78.9   63.1
#> # ℹ 1 more variable: Cumulative.Time.Sec <dbl>
# }