nlmixr2autoinit (version 1.0.0)

run_npd_1cmpt_mm_iv: Run and evaluate a one-compartment IV Michaelis-Menten model

Description

Fits a one-compartment intravenous pharmacokinetic model with Michaelis-Menten elimination using a naive pooled data approach and evaluates model performance based on prediction error metrics.

Usage

run_npd_1cmpt_mm_iv(
  dat,
  est.method = "nls",
  npdmm_inputvmax = exp(1),
  npdmm_inputkm = exp(1),
  npdmm_inputcl = exp(1),
  npdmm_inputvd = exp(1),
  input.add = 1,
  km_threshold = FALSE
)

Value

A list containing parameter estimates and prediction error metrics.

Arguments

dat

A data frame containing pharmacokinetic data in standard nlmixr2 format.

est.method

Estimation method used in nlmixr2. Defaults to "nls".

npdmm_inputvmax

Initial estimate for Vmax. Defaults to exp(1), corresponding to a log-scale value of 1.

npdmm_inputkm

Initial estimate for Km. Defaults to exp(1), corresponding to a log-scale value of 1.

npdmm_inputcl

Initial estimate for clearance (CL). Defaults to exp(1) , corresponding to a log-scale value of 1.

npdmm_inputvd

Initial estimate for volume of distribution (Vd). Defaults to exp(1), corresponding to a log-scale value of 1.

input.add

Additive error term. Defaults to 1.

km_threshold

Logical value. If TRUE, initial estimates for Vmax and Km are calculated based on the maximum observed concentration.

Author

Zhonghui Huang

Details

Rows where EVID == 2 are excluded before model fitting. The model is fitted using Fit_1cmpt_mm_iv. When km_threshold = TRUE, initial estimates for Vmax and Km are derived from the dataset to provide a representative starting point for nonlinear elimination.

See Also

Fit_1cmpt_mm_iv

Examples

# \donttest{
run_npd_1cmpt_mm_iv(
  dat = Bolus_1CPT,
  npdmm_inputcl = 4,
  npdmm_inputvd = 70,
  km_threshold = TRUE
)
# }