John Wambaugh and Robert Pearce, Schmitt method implementation by Jimena Davis, dynamic model adapted from code by R. Woodrow Setzer, Rabbit parameters from Nisha Sipes
Functions and data tables for simulation and statistical analysis of chemical toxicokinetics (TK) using data obtained from relatively high throughput, in vitro studies. Both physiologically-based (PBTK) and empirical (e.g., one compartment) TK models can be parameterized for sevral 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 and measurment limitations. Functions are also provided for exporting PBTK models to SBML and JARNAC for use with other simulation software. These functions and data provide a set of tools for in vitro-in vivo extrapolation (IVIVE) of high throughput screening data  (e.g., ToxCast) to real-world exposures via reverse dosimetry (also known as "RTK").

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>).
c(
person("John", "Wambaugh", email = "wambaugh.john@epa.gov", role = c("aut", "cre")),
person("Robert", "Pearce", role = c("aut")),
person("Caroline", "Ring", email = "cring@toxstrategies.com", role = c("aut")),
person("Greg", "Honda", email = "honda.gregory@epa.gov", role = c("aut")),
person("Mark", "Sfeir", email = "sfeir.mark@epa.gov", role = c("aut")),
person("Jimena", "Davis", role = c("ctb")),
person("James", "Sluka", email = "jsluka@indiana.edu", role = c("ctb")),
person("Nisha", "Sipes", email = "nisha.sipes@nih.gov", role = c("ctb")),
person("Barbara", "Wetmore", email = "wetmore.barbara@epa.gov", role = c("ctb")),
person("Woodrow", "Setzer", role = c("ctb"))
)
deSolve, msm, data.table, survey, mvtnorm, truncnorm, stats,
graphics, utils, magrittr
ggplot2, knitr, rmarkdown, R.rsp, GGally, gplots, scales,
EnvStats, MASS, RColorBrewer, TeachingDemos, classInt, ks,
stringr, reshape, reshape2, gdata, viridis, CensRegMod,
gmodels, colorspace
John Wambaugh [aut, cre],
Robert Pearce [aut],
Caroline Ring [aut],
Greg Honda [aut],
Mark Sfeir [aut],
Jimena Davis [ctb],
James Sluka [ctb],
Nisha Sipes [ctb],
Barbara Wetmore [ctb],
Woodrow Setzer [ctb]