Fit_1cmpt_mm_iv: Fit intravenous pharmacokinetic data to a one-compartment...

In nlmixr2autoinit: Automatic Generation of Initial Estimates for Population Pharmacokinetic Modeling

Fit intravenous pharmacokinetic data to a one-compartment model with Michaelis-Menten elimination

Description

Fits intravenous (IV) pharmacokinetic data to a one-compartment model with Michaelis-Menten (nonlinear) elimination using the naive pooled data approach. Supports multiple estimation methods available in nlmixr2, and optionally returns only predicted concentrations to reduce memory use in simulation workflows.

Usage

Fit_1cmpt_mm_iv(
  data,
  est.method,
  input.vmax,
  input.km,
  input.vd,
  input.add,
  return.pred.only = FALSE,
  ...
)

Arguments

data	A data frame of IV pharmacokinetic data formatted for nlmixr2.
est.method	Estimation method to use in nlmixr2, one of: "rxSolve", "nls", "nlm", "nlminb", or "focei".
input.vmax	Initial estimate of the maximum elimination rate (Vmax).
input.km	Initial estimate of the Michaelis constant (Km).
input.vd	Initial estimate of the volume of distribution (V).
input.add	Initial estimate of the additive residual error.
return.pred.only	Logical; if TRUE, returns a data frame with only predicted concentrations (cp) for all observations in the input data.
...	Optional arguments passed to nlmixr2(), such as a custom control = foceiControl(...) or other control objects.

Value

If return.pred.only = TRUE, returns a data.frame with a single column cp (predicted concentrations). Otherwise, returns a fitted model object produced by nlmixr2.

Author(s)

Zhonghui Huang

Examples

 
dat <- Bolus_1CPTMM
# Fit using 'nls'
Fit_1cmpt_mm_iv(
  data = dat,
  est.method = "nls",
  input.vmax = 1000,
  input.km = 250,
  input.vd = 70,
  input.add = 10)

# Return only predicted concentrations
Fit_1cmpt_mm_iv(
  data = dat,
  est.method = "rxSolve",
  input.vmax = 1000,
  input.km = 250,
  input.vd = 70,
  input.add = 0,
  return.pred.only = TRUE
  )
  

nlmixr2autoinit documentation built on Nov. 14, 2025, 1:07 a.m.