High-Throughput Toxicokinetics
Description
Generic models and chemical-specific data for simulation and
statistical analysis of chemical toxicokinetics ("TK") as
described by Pearce et al. (2017) .
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 )
and propagating parameter uncertainty. 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 (for example, Tox21, ToxCast) to real-world
exposures via reverse dosimetry (also known as "RTK")
(Wetmore et al., 2015 ).