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httkexamples: High-Throughput Toxicokinetics Examples

High throughput toxicokinetics ("HTTK") is the combination of 1) chemical-specific in vitro measurements or in silico predictions and 2) generic mathematical models, to predict absorption, distribution, metabolism, and excretion by the body. HTTK methods have been described by Pearce et al. (2017) (<doi:10.18637/jss.v079.i04>) and Breen et al. (2021) (<doi:10.1080/17425255.2021.1935867>). Here we provide examples (vignettes) applying HTTK to solve various problems in bioinformatics, toxicology, and exposure science. In accordance with Davidson-Fritz et al. (2025) (<doi:10.1371/journal.pone.0321321>), whenever a new HTTK model is developed, the code to generate the figures evaluating that model is added as a new vignettte.

Version: 0.0.1
Depends: R (≥ 2.10)
Imports: httk, rmarkdown, knitr, Rdpack
Suggests: dplyr, tidyverse, xlsx, Metrics, ggplot2, ggforce, ggpubr, ggrepel, viridis, ggpubr, grid, ggh4x, readr, ggforce, tidyr, stringr, pracma, cgwtools, openxlsx, ggstar, latex2exp, smatr, reshape, gdata, censReg, gmodels, gplots, scales, colorspace, gridExtra, rvcheck
Published: 2025-12-10
DOI: 10.32614/CRAN.package.httkexamples
Author: John Wambaugh ORCID iD [aut, cre], Robert Pearce ORCID iD [aut], Caroline Ring ORCID iD [aut], Greg Honda ORCID iD [aut], Matt Linakis ORCID iD [aut], Dustin Kapraun ORCID iD [aut], Kimberly Truong ORCID iD [aut], Meredith Scherer ORCID iD [aut], Annabel Meade ORCID iD [aut], Celia Schacht ORCID iD [aut], Elaina Kenyon ORCID iD [ctb]
Maintainer: John Wambaugh <john.wambaugh at UL.org>
License: MIT + file LICENSE
URL: https://chemicalinsights.ul.org/
NeedsCompilation: no
Citation: httkexamples citation info
Materials: README, NEWS
CRAN checks: httkexamples results

Documentation:

Reference manual: httkexamples.html , httkexamples.pdf
Vignettes: a) Pearce (2017): HTTK Basics (source, R code)
b) Ring (2017) HTTK-Pop: Generating subpopulations (source, R code)
c) Pearce (2017): Evaluation of Tissue Partitioning (source, R code)
d) Wambaugh (2018): Evaluating In Vitro-In Vivo Extrapolation (source, R code)
e) Frank (2018): Neuronal Network IVIVE (source, R code)
f) Honda (2019): Updated Armitage et al. (2014) Model (source, R code)
g) Wambaugh (2019): Uncertainty Monte Carlo (source, R code)
h) Linakis (2020): High Throughput Inhalation Model (source, R code)
i) Kapraun (2022): Human Gestational Model (source, R code)
j) Truong (2025) Full Human Gestational IVIVE (source, R code)
k) Wambaugh (Submitted): HTTK for PFAS (source, R code)
l) Meade (Submitted): High Throughput Dermal Exposure Model (source, R code)
m) Scherer (Submitted): In Vitro Distribution (source, R code)

Downloads:

Package source: httkexamples_0.0.1.tar.gz
Windows binaries: r-devel: httkexamples_0.0.1.zip, r-release: not available, r-oldrel: httkexamples_0.0.1.zip
macOS binaries: r-release (arm64): httkexamples_0.0.1.tgz, r-oldrel (arm64): httkexamples_0.0.1.tgz, r-release (x86_64): httkexamples_0.0.1.tgz, r-oldrel (x86_64): httkexamples_0.0.1.tgz

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They may not be fully stable and should be used with caution. We make no claims about them.
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