Description

Generic models and chemical-specific data for simulation and statistical analysis of chemical toxicokinetics ("TK") as described by 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 (for example, one compartment) "TK" models can be parameterized with the data provided for thousands of chemicals, multiple exposure routes, and various species. The models consist of systems of ordinary differential equations which are solved using compiled (C-based) code for speed. A Monte Carlo sampler is included, which allows for simulating human biological variability (Ring et al., 2017 <doi:10.1016/j.envint.2017.06.004>) and propagating parameter uncertainty. 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 (for example, Tox21, ToxCast) to real-world exposures via reverse dosimetry (also known as "RTK") (Wetmore et al., 2015 <doi:10.1093/toxsci/kfv171>).

Author(s)

John Wambaugh, Robert Pearce, Caroline Ring, Gregory Honda, Nisha Sipes, Jimena Davis, Barbara Wetmore, Woodrow Setzer, Mark Sfeir

See Also

PowerPoint Presentation: High-Throughput Toxicokinetics (HTTK) R package

doi: 10.18637/jss.v079.i04Pearce et al. (2017): httk: R Package for High-Throughput Toxicokinetics

doi: 10.1093/toxsci/kfv171Wetmore et al. (2015): Incorporating High-Throughput Exposure Predictions With Dosimetry-Adjusted In Vitro Bioactivity to Inform Chemical Toxicity Testing

doi: 10.1093/toxsci/kfv118Wambaugh et al. (2015): Toxicokinetic Triage for Environmental Chemicals

doi: 10.1007/s10928-017-9548-7Pearce et al. (2017): Evaluation and calibration of high-throughput predictions of chemical distribution to tissues

doi: 10.1016/j.envint.2017.06.004Ring et al. (2017): Identifying populations sensitive to environmental chemicals by simulating toxicokinetic variability

doi: 10.1021/acs.est.7b00650Sipes et al. (2017): An Intuitive Approach for Predicting Potential Human Health Risk with the Tox21 10k Library

doi: 10.1093/toxsci/kfy020Wambaugh et al. (2018): Evaluating In Vitro-In Vivo Extrapolation of Toxicokinetics

doi: 10.1371/journal.pone.0217564Honda et al. (2019): Using the concordance of in vitro and in vivo data to evaluate extrapolation assumptionss

doi: 10.1093/toxsci/kfz205Wambaugh et al. (2019): Assessing Toxicokinetic Uncertainty and Variability in Risk Prioritization

doi: 10.1038/s41370-020-0238-yLinakis et al. (2020): Development and evaluation of a high throughput inhalation model for organic chemicals

EPA's ExpoCast (Exposure Forecasting) Project