honda2023.data

<p>In vitro Caco-2 membrane permeabilities characterize how readily absobed/transported
a chemical is. These measurements are all for the apical-to-basal Caco-2
orientation.
These data were either measured by EPA or collected by other others, as
indicated by the column 'Data Origin'.
Anywhere that the values is reported by three numbers separated by a comma 
(this also happens for plasma protein binding) the three values are: median, 
lower 95 percent confidence intervals, upper 95 percent confidence interval. Unless you are 
doing monte carlo work it makes sense to ignore the second and third values.</p>

datasets

Pre-made models that can be rapidly tailored to various chemicals
and species using chemical-specific in vitro data and physiological
information. These tools allow incorporation of chemical
toxicokinetics ("TK") and in vitro-in vivo extrapolation ("IVIVE")
into bioinformatics, as described by Pearce et al. (2017)
(<doi:10.18637/jss.v079.i04>). Chemical-specific
in vitro data characterizing toxicokinetics have been obtained
from relatively high-throughput experiments.   The
chemical-independent ("generic") physiologically-based ("PBTK") and empirical
(for example, one compartment) "TK" models included here can be
parameterized with in vitro data or in silico predictions which are
provided for thousands of chemicals, multiple exposure routes,
and various species. High throughput toxicokinetics ("HTTK") is the
combination of in vitro data and generic models. We establish the
expected accuracy of HTTK for chemicals without in vivo data
through statistical evaluation of HTTK predictions for chemicals
where in vivo data do exist. The models are systems of ordinary
differential equations that are developed in MCSim and solved
using compiled (C-based) code for speed. A Monte Carlo sampler is
included for simulating human biological variability
(Ring et al., 2017 <doi:10.1016/j.envint.2017.06.004>)
and propagating parameter uncertainty
(Wambaugh et al., 2019 <doi:10.1093/toxsci/kfz205>).
Empirically 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 using IVIVE to
convert concentrations from high-throughput screening experiments
(for example, Tox21, ToxCast) to real-world exposures via reverse
dosimetry (also known as "RTK")
(Wetmore et al., 2015 <doi:10.1093/toxsci/kfv171>).

John Wambaugh

httk

High-Throughput Toxicokinetics

Sarah Davidson-Fritz

Robert Pearce

Caroline Ring

Greg Honda

Mark Sfeir

Matt Linakis

Dustin Kapraun

Nathan Pollesch

Miyuki Breen

Shannon Bell

Xiaoqing Chang

Todor Antonijevic

Jimena Davis

Elaina Kenyon

Katie Paul Friedman

Celia Schacht

Meredith Scherer

James Sluka

Noelle Sinski

Nisha Sipes

Barbara Wetmore

Lily Whipple

Woodrow Setzer

honda2023.data function

<p>An object of class <code>data.frame</code> with 634 rows and 5 columns.</p>

Format

Measured Caco-2 Apical-Basal Permeability Data — honda2023.data

Measured Caco-2 Apical-Basal Permeability Data

Column Name	Description	Units
DTXSID	EPA's DSSTox Structure ID (https://comptox.epa.gov/dashboard)
Pab	Apical-to-basal Caco-2 permeability	10^-6 cm/s
Data Origin	The reference which collected/generated the measurement
Test	Whether (1) or not (0) the data was withheld from model building to be used in the QSPR test set
CAS	Chemical Abstracts Service Registry Number

honda2023.data: Measured Caco-2 Apical-Basal Permeability Data

Description

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References