nlmixr2autoinit (version 1.0.0)

Fit_1cmpt_mm_iv: 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,
  ...
)

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.

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.

Author

Zhonghui Huang

Examples

 # \donttest{
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
  )
  # }