httk: High-Throughput Toxicokinetics

Functions and data tables for simulation and statistical analysis of chemical toxicokinetics ("TK") as in Pearce et al. (2017) <doi:10.18637/jss.v079.i04>. 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 <doi:10.1016/j.envint.2017.06.004>) and measurement limitations. 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 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 <doi:10.1093/toxsci/kfv171>).

Package details

AuthorJohn 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] (<>)
MaintainerJohn Wambaugh <>
Package repositoryView on CRAN
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httk documentation built on March 2, 2020, 9:06 a.m.