Package index • nlmixr2autoinit

Main Function

Primary function and control options for automated initial parameter estimation

getPPKinits(): Automated pipeline for generating initial estimates in population PK models
print(<getPPKinits>): Print method for getPPKinits objects
initsControl(): Create full control list for initial parameter estimation
fallback_control(): Control settings for fallback rules in parameter estimation
nca_control(): Control options for non-compartmental analysis
pooled_control(): Control settings for pooled data analysis
ss_control(): Internal control builder for steady-state evaluation

Graphic and NCA Methods

Naive pooled graphic methods and noncompartmental analysis

graphcal_iv(): Graphical calculation of clearance and volume of distribution (IV route)
graphcal_oral(): Graphical calculation of pharmacokinetic parameters for oral administration
run_graphcal(): Run graphical analysis of pharmacokinetic parameters
getnca(): Perform non-compartmental pharmacokinetic analysis
run_pooled_nca(): Performs non-compartmental analysis on pooled data
get_pooled_data(): Generate pooled data for pharmacokinetic analysis

Single-Point Methods

Adaptive single-point estimation functions

run_single_point(): Run full adaptive single-point PK analysis
run_single_point_base(): Run adaptive single-point pharmacokinetic analysis
run_single_point_extra(): Perform extended single-point pharmacokinetic calculations
run_ka_solution(): Estimate the absorption rate constant using pointwise methods
ka_calculation_md(): Calculate absorption rate constant (ka) in a multiple-dose one-compartment model
ka_calculation_sd(): Estimate absorption rate constant in a one-compartment oral model
ka_wanger_nelson(): Calculate the absorption rate constant using the Wagner-Nelson method

Parameter Sweeping

Model fitting and parameter sweeping across PK structures

Fit_1cmpt_iv(): Fit intravenous pharmacokinetic data to a one-compartment linear elimination model
Fit_1cmpt_mm_iv(): Fit intravenous pharmacokinetic data to a one-compartment model with Michaelis-Menten elimination
Fit_1cmpt_mm_oral(): Fit oral pharmacokinetic data to a one-compartment model with Michaelis-Menten elimination
Fit_1cmpt_oral(): Fit oral pharmacokinetic data to a one-compartment linear elimination model
Fit_2cmpt_iv(): Fit intravenous pharmacokinetic data to a two-compartment linear elimination model
Fit_2cmpt_oral(): Fit oral pharmacokinetic data to a two-compartment model
Fit_3cmpt_iv(): Fit intravenous pharmacokinetic data to a three-compartment linear elimination model
Fit_3cmpt_oral(): Fit oral pharmacokinetic data to a three-compartment linear elimination model
sim_sens_1cmpt_mm(): Parameter sweeping for a one-compartment Michaelis-Menten model
sim_sens_2cmpt(): Parameter sweeping for a two-compartment pharmacokinetic model
sim_sens_3cmpt(): Parameter sweeping for a three-compartment pharmacokinetic model

Variability Estimation

Residual and inter-individual variability estimation

getsigma(): Compute overall residual variability from elimination phase
getsigmas(): Estimate individual-level residual error from the elimination phase
getOmegas(): Generate ETA variance and covariance table

All Other Functions

Data processing and supporting utility functions

Fit_1cmpt_iv(): Fit intravenous pharmacokinetic data to a one-compartment linear elimination model
Fit_1cmpt_mm_iv(): Fit intravenous pharmacokinetic data to a one-compartment model with Michaelis-Menten elimination
Fit_1cmpt_mm_oral(): Fit oral pharmacokinetic data to a one-compartment model with Michaelis-Menten elimination
Fit_1cmpt_oral(): Fit oral pharmacokinetic data to a one-compartment linear elimination model
Fit_2cmpt_iv(): Fit intravenous pharmacokinetic data to a two-compartment linear elimination model
Fit_2cmpt_oral(): Fit oral pharmacokinetic data to a two-compartment model
Fit_3cmpt_iv(): Fit intravenous pharmacokinetic data to a three-compartment linear elimination model
Fit_3cmpt_oral(): Fit oral pharmacokinetic data to a three-compartment linear elimination model
approx.vc(): Approximate volume of distribution from observed Cmax
bin.time(): Bin time-concentration data using quantile or algorithmic binning
calculate_cl(): Calculate clearance using an adaptive single-point method
calculate_tad(): Calculate time after dose for pharmacokinetic data
calculate_vd(): Calculates volume of distribution from concentration data
eval_perf_1cmpt(): Evaluates predictive performance of a one-compartment model
fallback_control(): Control settings for fallback rules in parameter estimation
find_best_lambdaz(): Find the best terminal elimination rate constant (lambdaz)
force_find_lambdaz(): Forceful estimation of terminal slope
getOmegas(): Generate ETA variance and covariance table
getPPKinits(): Automated pipeline for generating initial estimates in population PK models
get_hf(): Estimate half-life from pooled pharmacokinetic data
get_pooled_data(): Generate pooled data for pharmacokinetic analysis
getnca(): Perform non-compartmental pharmacokinetic analysis
getsigma(): Compute overall residual variability from elimination phase
getsigmas(): Estimate individual-level residual error from the elimination phase
graphcal_iv(): Graphical calculation of clearance and volume of distribution (IV route)
graphcal_oral(): Graphical calculation of pharmacokinetic parameters for oral administration
hybrid_eval_perf_1cmpt(): Generate Unique Mixture Parameter Grid (with Deduplication and NA Removal)
initsControl(): Create full control list for initial parameter estimation
is_ss(): Determine steady state for pharmacokinetic observations
ka_calculation_md(): Calculate absorption rate constant (ka) in a multiple-dose one-compartment model
ka_calculation_sd(): Estimate absorption rate constant in a one-compartment oral model
ka_wanger_nelson(): Calculate the absorption rate constant using the Wagner-Nelson method
mark_dose_number(): Mark dose number
metrics.(): Calculate metrics for model predictive performance evaluation
nca_control(): Control options for non-compartmental analysis
nmpkconvert(): Expand additional dosing (ADDL) records for pharmacokinetic analysis
pooled_control(): Control settings for pooled data analysis
print(<getPPKinits>): Print method for getPPKinits objects
processData(): Process time–concentration dataset for pharmacokinetic analysis
run_graphcal(): Run graphical analysis of pharmacokinetic parameters
run_ka_solution(): Estimate the absorption rate constant using pointwise methods
run_pooled_nca(): Performs non-compartmental analysis on pooled data
run_single_point(): Run full adaptive single-point PK analysis
run_single_point_base(): Run adaptive single-point pharmacokinetic analysis
run_single_point_extra(): Perform extended single-point pharmacokinetic calculations
sim_sens_1cmpt_mm(): Parameter sweeping for a one-compartment Michaelis-Menten model
sim_sens_2cmpt(): Parameter sweeping for a two-compartment pharmacokinetic model
sim_sens_3cmpt(): Parameter sweeping for a three-compartment pharmacokinetic model
ss_control(): Internal control builder for steady-state evaluation
trapezoidal_linear(): Linear trapezoidal rule
trapezoidal_linear_up_log_down(): Linear-up and log-down trapezoidal rule
trimmed_geom_mean(): Computes the trimmed geometric mean