Literature DB >> 25145659

Incorporating population variability and susceptible subpopulations into dosimetry for high-throughput toxicity testing.

Barbara A Wetmore1, Brittany Allen2, Harvey J Clewell2, Timothy Parker2, John F Wambaugh3, Lisa M Almond4, Mark A Sochaski2, Russell S Thomas1.   

Abstract

Momentum is growing worldwide to use in vitro high-throughput screening (HTS) to evaluate human health effects of chemicals. However, the integration of dosimetry into HTS assays and incorporation of population variability will be essential before its application in a risk assessment context. Previously, we employed in vitro hepatic metabolic clearance and plasma protein binding data with in vitro in vivo extrapolation (IVIVE) modeling to estimate oral equivalent doses, or daily oral chemical doses required to achieve steady-state blood concentrations (Css) equivalent to media concentrations having a defined effect in an in vitro HTS assay. In this study, hepatic clearance rates of selected ToxCast chemicals were measured in vitro for 13 cytochrome P450 and five uridine 5'-diphospho-glucuronysyltransferase isozymes using recombinantly expressed enzymes. The isozyme-specific clearance rates were then incorporated into an IVIVE model that captures known differences in isozyme expression across several life stages and ethnic populations. Comparison of the median Css for a healthy population against the median or the upper 95th percentile for more sensitive populations revealed differences of 1.3- to 4.3-fold or 3.1- to 13.1-fold, respectively. Such values may be used to derive chemical-specific human toxicokinetic adjustment factors. The IVIVE model was also used to estimate subpopulation-specific oral equivalent doses that were directly compared with subpopulation-specific exposure estimates. This study successfully combines isozyme and physiologic differences to quantitate subpopulation pharmacokinetic variability. Incorporation of these values with dosimetry and in vitro bioactivities provides a viable approach that could be employed within a high-throughput risk assessment framework.
© The Author 2014. Published by Oxford University Press on behalf of the Society of Toxicology. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Entities:  

Keywords:  In vitro in vivo extrapolation; dosimetry; population variability; reaction phenotyping; risk assessment; toxicokinetics

Mesh:

Substances:

Year:  2014        PMID: 25145659     DOI: 10.1093/toxsci/kfu169

Source DB:  PubMed          Journal:  Toxicol Sci        ISSN: 1096-0929            Impact factor:   4.849


  33 in total

1.  Toxicokinetic Triage for Environmental Chemicals.

Authors:  John F Wambaugh; Barbara A Wetmore; Robert Pearce; Cory Strope; Rocky Goldsmith; James P Sluka; Alexander Sedykh; Alex Tropsha; Sieto Bosgra; Imran Shah; Richard Judson; Russell S Thomas; R Woodrow Setzer
Journal:  Toxicol Sci       Date:  2015-06-16       Impact factor: 4.849

2.  Identifying populations sensitive to environmental chemicals by simulating toxicokinetic variability.

Authors:  Caroline L Ring; Robert G Pearce; R Woodrow Setzer; Barbara A Wetmore; John F Wambaugh
Journal:  Environ Int       Date:  2017-06-16       Impact factor: 9.621

3.  Completing the Link between Exposure Science and Toxicology for Improved Environmental Health Decision Making: The Aggregate Exposure Pathway Framework.

Authors:  Justin G Teeguarden; Yu-Mei Tan; Stephen W Edwards; Jeremy A Leonard; Kim A Anderson; Richard A Corley; Molly L Kile; Staci M Simonich; David Stone; Robert L Tanguay; Katrina M Waters; Stacey L Harper; David E Williams
Journal:  Environ Sci Technol       Date:  2016-02-10       Impact factor: 9.028

4.  An Intuitive Approach for Predicting Potential Human Health Risk with the Tox21 10k Library.

Authors:  Nisha S Sipes; John F Wambaugh; Robert Pearce; Scott S Auerbach; Barbara A Wetmore; Jui-Hua Hsieh; Andrew J Shapiro; Daniel Svoboda; Michael J DeVito; Stephen S Ferguson
Journal:  Environ Sci Technol       Date:  2017-09-06       Impact factor: 9.028

Review 5.  Incorporating population-level genetic variability within laboratory models in toxicology: From the individual to the population.

Authors:  Peter Dornbos; John J LaPres
Journal:  Toxicology       Date:  2017-12-21       Impact factor: 4.221

Review 6.  In vitro to in vivo extrapolation for high throughput prioritization and decision making.

Authors:  Shannon M Bell; Xiaoqing Chang; John F Wambaugh; David G Allen; Mike Bartels; Kim L R Brouwer; Warren M Casey; Neepa Choksi; Stephen S Ferguson; Grazyna Fraczkiewicz; Annie M Jarabek; Alice Ke; Annie Lumen; Scott G Lynn; Alicia Paini; Paul S Price; Caroline Ring; Ted W Simon; Nisha S Sipes; Catherine S Sprankle; Judy Strickland; John Troutman; Barbara A Wetmore; Nicole C Kleinstreuer
Journal:  Toxicol In Vitro       Date:  2017-12-05       Impact factor: 3.500

7.  Evaluating In Vitro-In Vivo Extrapolation of Toxicokinetics.

Authors:  John F Wambaugh; Michael F Hughes; Caroline L Ring; Denise K MacMillan; Jermaine Ford; Timothy R Fennell; Sherry R Black; Rodney W Snyder; Nisha S Sipes; Barbara A Wetmore; Joost Westerhout; R Woodrow Setzer; Robert G Pearce; Jane Ellen Simmons; Russell S Thomas
Journal:  Toxicol Sci       Date:  2018-05-01       Impact factor: 4.849

8.  In vitro screening for population variability in toxicity of pesticide-containing mixtures.

Authors:  Nour Abdo; Barbara A Wetmore; Grace A Chappell; Damian Shea; Fred A Wright; Ivan Rusyn
Journal:  Environ Int       Date:  2015-09-19       Impact factor: 9.621

9.  Conceptual Framework To Extend Life Cycle Assessment Using Near-Field Human Exposure Modeling and High-Throughput Tools for Chemicals.

Authors:  Susan A Csiszar; David E Meyer; Kathie L Dionisio; Peter Egeghy; Kristin K Isaacs; Paul S Price; Kelly A Scanlon; Yu-Mei Tan; Kent Thomas; Daniel Vallero; Jane C Bare
Journal:  Environ Sci Technol       Date:  2016-10-18       Impact factor: 9.028

10.  Prediction of metabolism-induced hepatotoxicity on three-dimensional hepatic cell culture and enzyme microarrays.

Authors:  Kyeong-Nam Yu; Sashi Nadanaciva; Payal Rana; Dong Woo Lee; Bosung Ku; Alexander D Roth; Jonathan S Dordick; Yvonne Will; Moo-Yeal Lee
Journal:  Arch Toxicol       Date:  2017-11-22       Impact factor: 5.153

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