Global Sensitivity Analysis in Physiologically Based Kinetic Modeling

Applying the global sensitivity analysis workflow to investigate the parameter uncertainty and sensitivity in physiologically based kinetic (PK) models, especially the physiologically based pharmacokinetic/toxicokinetic model with multivariate outputs. The package also provides some functions to check the convergence and sensitivity of model parameters. The workflow was first mentioned in Hsieh et al., (2018) , then further refined (Hsieh et al., 2020 ).


pksensi 1.1.0

Fix Bug:

  • Used single time point in solve_mcsim()

Update function:


  • Updated version = 6.1.0 in install_mcsim()
  • Adopt to file name in MCSim_under_R - "model.R.exe"


  • Change assignment n to monte_carlo in solve_mcsim()
  • Revise the default name of output to "sim.out" and "setpoint.out" in solve_mcsim()
  • Added solving message to track time spend in solve_mcsim()
  • Add assignment tell = T to automatically combine the output y in decoupling simulation x in solve_fun() and solve_mcsim()


  • Transfer the log-transformed value to natural scale in pksim()
  • Revise the discrete time condition to length(times) < 16 in heat_check()

pksensi 1.0.1

New vignette:

  • Add "PBTK 1-compartment model"
  • Add "Acetaminophen-PBPK model"

New example:

  • Update example in solve_mcsim()

New function:

  • Add pbtk1cpt_model()
  • Add pbpk_apap_model()
  • Add function mcsim_version()

NEW dataset:

  • Add APAP dataset

Fix Bug:

  • Fix the order argument in heat_check()
  • Add message in generate_infile()

Update function:

  • Remove argument params in solve_fun()
  • No need to define and in solve_mcsim()


  • Change function's name install_mcsim() to mcsim_install()

pksensi 1.0.0

  • Initial release in CRAN

Reference manual

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1.2.2 by Nan-Hung Hsieh, 4 months ago,

Report a bug at

Browse source code at

Authors: Nan-Hung Hsieh [aut, cre] , Brad Reisfeld [ctb] , Weihsueh A. Chiu [ctb]

Documentation:   PDF Manual  

GPL-3 | file LICENSE license

Imports ggplot2, data.table, deSolve, dplyr, getPass, magrittr, foreach, parallel, doParallel, reshape2

Suggests covr, knitr, rmarkdown, testthat

See at CRAN