httk (2.0.1)

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High-Throughput Toxicokinetics.

Functions and data tables for simulation and statistical analysis of chemical toxicokinetics ("TK") as in Pearce et al. (2017) . Chemical-specific in vitro data have been obtained from relatively high throughput experiments. Both physiologically-based ("PBTK") and empirical (e.g., one compartment) "TK" models can be parameterized for several hundred chemicals and multiple species. These models are solved efficiently, often using compiled (C-based) code. A Monte Carlo sampler is included for simulating biological variability (Ring et al., 2017 ) and measurement limitations. Calibrated methods are included for predicting tissue:plasma partition coefficients and volume of distribution (Pearce et al., 2017 ). These functions and data provide a set of tools for in vitro-in vivo extrapolation ("IVIVE") of high throughput screening data (e.g., Tox21, ToxCast) to real-world exposures via reverse dosimetry (also known as "RTK") (Wetmore et al., 2015 ).

Maintainer: John Wambaugh
Author(s): John Wambaugh [aut, cre] (<>), Robert Pearce [aut] (<>), Caroline Ring [aut] (<>), Greg Honda [aut] (<>), Mark Sfeir [aut], Matt Linakis [aut] (<>), Jimena Davis [ctb], James Sluka [ctb] (<>), Nisha Sipes [ctb] (<>), Barbara Wetmore [ctb], Woodrow Setzer [ctb] (<>)

License: GPL-3

Uses: data.table, deSolve, magrittr, msm, mvtnorm, purrr, survey, truncnorm, R.rsp, RColorBrewer, TeachingDemos, classInt, colorspace, gdata, ggplot2, gmodels, gplots, gtools, ks, reshape, smatr, MASS, stringr, GGally, gridExtra, reshape2, scales, knitr, CensRegMod, EnvStats, dplyr, rmarkdown, cowplot, viridis, ggrepel, forcats

Released about 1 month ago.

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