This package is considered a duplicate. The official version of this package is found at:https://ucl-pharmacometrics.r-universe.dev/nlmixr2autoinit

Package: nlmixr2autoinit 1.0.1

Zhonghui Huang

nlmixr2autoinit: Automatic Generation of Initial Estimates for Population Pharmacokinetic Modeling

Provides automated methods for generating initial parameter estimates in population pharmacokinetic modeling. The pipeline integrates adaptive single-point methods, naive pooled graphic approaches, noncompartmental analysis methods, and parameter sweeping across pharmacokinetic models. It estimates residual unexplained variability using either data-driven or fixed-fraction approaches and assigns pragmatic initial values for inter-individual variability. These strategies are designed to improve model robustness and convergence in 'nlmixr2' workflows. For more details see Huang Z, Fidler M, Lan M, Cheng IL, Kloprogge F, Standing JF (2025) <doi:10.1007/s10928-025-10000-z>.

Authors:Zhonghui Huang [aut, cre], Joseph Standing [ctb], Matthew Fidler [ctb], Frank Kloprogge [ctb]

nlmixr2autoinit_1.0.1.tar.gz
nlmixr2autoinit_1.0.1.tar.gz(r-4.6-any)
nlmixr2autoinit_1.0.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
nlmixr2autoinit/json (API)

# Install 'nlmixr2autoinit' in R:

install.packages('nlmixr2autoinit', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/ucl-pharmacometrics/nlmixr2autoinit/issues

Pkgdown/docs site:https://ucl-pharmacometrics.github.io

On CRAN:

1.92 score 1 packages 14 scripts 160 downloads 51 exports 149 dependencies

Last updated from:0c4c41d541. Checks:1 FAIL, 3 OK. Indexed: no.

Target	Result	Time
linux-devel-x86_64	FAIL	213
source / vignettes	OK	238
linux-release-x86_64	OK	219
wasm-release	OK	152

Exports:approx.vc bin.time calculate_cl calculate_tad calculate_vd eval_perf_1cmpt fallback_control find_best_lambdaz Fit_1cmpt_iv Fit_1cmpt_mm_iv Fit_1cmpt_mm_oral Fit_1cmpt_oral Fit_2cmpt_iv Fit_2cmpt_oral Fit_3cmpt_iv Fit_3cmpt_oral force_find_lambdaz get_hf get_pooled_data getnca getOmegas getPPKinits getsigma getsigmas graphcal_iv graphcal_oral hybrid_eval_perf_1cmpt initsControl is_ss ka_calculation_md ka_calculation_sd ka_wanger_nelson mark_dose_number metrics.nca_control nmpkconvert pooled_control processData run_graphcal run_ka_solution run_pooled_nca run_single_point run_single_point_base run_single_point_extra sim_sens_1cmpt_mm sim_sens_2cmpt sim_sens_3cmpt ss_control trapezoidal_linear trapezoidal_linear_up_log_down trimmed_geom_mean

Dependencies:armadillo4r askpass assertthat backports base64enc BH binom bit bit64 bitops boot bslib cachem cellranger checkmate class classInt cli clipr cluster colorspace commonmark cpp11 cpp4r crayon curl data.table Deriv desc DescTools digest dparser dplyr e1071 evaluate Exact expm farver fastmap fontawesome forcats foreign Formula fs generics ggplot2 ggtext gld glue gridExtra gridtext gtable haven highr Hmisc hms htmlTable htmltools htmlwidgets httr inline isoband jpeg jquerylib jsonlite KernSmooth knitr labeling lattice lbfgsb3c lifecycle litedown lmom lotri magrittr markdown MASS Matrix memoise mime minpack.lm minqa mvtnorm n1qn1 nlme nlmixr2 nlmixr2data nlmixr2est nlmixr2extra nlmixr2plot nnet numDeriv openssl pander pillar pkgconfig png PreciseSums prettyunits progress progressr proxy purrr qs2 R6 rappdirs RColorBrewer Rcpp RcppArmadillo RcppEigen RcppParallel RCurl readr readxl rematch rex rlang rmarkdown rootSolve rpart rstudioapi rxode2 rxode2ll S7 sass scales sitmo StanHeaders stringfish stringi stringr survival symengine sys tibble tidyr tidyselect tinytex tzdb utf8 vctrs viridisLite vpc vroom withr xfun xgxr xml2 yaml

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

Package: nlmixr2autoinit 1.0.1

nlmixr2autoinit: Automatic Generation of Initial Estimates for Population Pharmacokinetic Modeling

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Help Manual

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