httk: High-Throughput Toxicokinetics

Pre-made models that can be rapidly tailored to various chemicals and species using chemical-specific in vitro data and physiological information. These tools allow incorporation of chemical toxicokinetics ("TK") and in vitro-in vivo extrapolation ("IVIVE") into bioinformatics, as described by Pearce et al. (2017) (<doi:10.18637/jss.v079.i04>). Chemical-specific in vitro data characterizing toxicokinetics can be been obtained from relatively high-throughput experiments. The chemical-independent ("generic") physiologically-based ("PBTK") and empirical (for example, one compartment) "TK" models included here can be parameterized with in vitro data or in silico predictions which are provided for thousands of chemicals, multiple exposure routes, and various species. The models are systems of ordinary differential equations that are solved using compiled (C-based) code for speed. A Monte Carlo sampler is included for simulating human biological variability (Ring et al., 2017 <doi:10.1016/j.envint.2017.06.004>) and propagating parameter uncertainty (Wambaugh et al., 2019 <doi:10.1093/toxsci/kfz205>). Empirically calibrated methods are included for predicting tissue:plasma partition coefficients and volume of distribution (Pearce et al., 2017 <doi:10.1007/s10928-017-9548-7>). These functions and data provide a set of tools for using IVIVE to convert concentrations from high-throughput screening experiments (for example, Tox21, ToxCast) to real-world exposures via reverse dosimetry (also known as "RTK") (Wetmore et al., 2015 <doi:10.1093/toxsci/kfv171>).

Version: 2.2.1
Depends: R (≥ 2.10)
Imports: deSolve, msm, data.table, survey, mvtnorm, truncnorm, stats, graphics, utils, magrittr, purrr, methods, Rdpack
Suggests: ggplot2, knitr, rmarkdown, R.rsp, GGally, gplots, scales, EnvStats, MASS, RColorBrewer, TeachingDemos, classInt, ks, stringr, reshape, reshape2, viridis, gmodels, colorspace, cowplot, ggrepel, dplyr, forcats, smatr, gridExtra, testthat
Published: 2022-09-24
Author: John Wambaugh ORCID iD [aut, cre], Sarah Davidson ORCID iD [aut], Robert Pearce ORCID iD [aut], Caroline Ring ORCID iD [aut], Greg Honda ORCID iD [aut], Mark Sfeir [aut], Matt Linakis ORCID iD [aut], Dustin Kapraun ORCID iD [aut], Miyuki Breen ORCID iD [ctb], Shannon Bell ORCID iD [ctb], Xiaoqing Chang ORCID iD [ctb], Todor Antonijevic ORCID iD [ctb], Jimena Davis [ctb], James Sluka ORCID iD [ctb], Nisha Sipes ORCID iD [ctb], Barbara Wetmore ORCID iD [ctb], Woodrow Setzer ORCID iD [ctb]
Maintainer: John Wambaugh <wambaugh.john at>
License: GPL-3
Copyright: This package is primarily developed by employees of the U.S. Federal government as part of their official duties and is therefore public domain.
NeedsCompilation: yes
Citation: httk citation info
Materials: README NEWS
CRAN checks: httk results


Reference manual: httk.pdf
Vignettes: b) Frank et al. (2018): Creating IVIVE Figure (Fig. 6)
d) Honda et al. (2019): Updated Armitage et al. (2014) Model
1) Introduction to HTTK
f) Kapraun et al. (2022): Creating All Figures
e) Linakis et al. (2020): Analysis and Figure Generation
a) Ring et al. (2017) Vignette 1: Generating subpopulations
c) Wambaugh et al. (2018): Creating All Figures


Package source: httk_2.2.1.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): httk_2.2.1.tgz, r-oldrel (arm64): httk_2.2.1.tgz, r-release (x86_64): httk_2.2.1.tgz, r-oldrel (x86_64): httk_2.2.1.tgz
Old sources: httk archive

Reverse dependencies:

Reverse suggests: pksensi


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