Estimating provisional margins of exposure for data-poor chemicals using high-throughput computational methods

Estimating provisional margins of exposure for data-poor chemicals using high-throughput computational methods

Current computational technologies hold promise for prioritizing the testing of the thousands of chemicals in commerce. Here, a case study is presented demonstrating comparative risk-prioritization approaches based on the ratio of surrogate hazard and exposure data, called margins of exposure (MoEs)...

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Bibliographic Details
Main Authors: Chantel I. Nicolas, Matthew W. Linakis, Melyssa S. Minto, Kamel Mansouri, Rebecca A. Clewell, Miyoung Yoon, John F. Wambaugh, Grace Patlewicz, Patrick D. McMullen, Melvin E. Andersen, Harvey J. Clewell III
Format: Article
Language:English
Published: Frontiers Media S.A. 2022-10-01
Series:Frontiers in Pharmacology
Subjects:
Threshold of toxicological concern (TTC)
computational toxicology
in silico
high-throughput risk prioritization
margin of exposure (MoE)
Online Access:https://www.frontiersin.org/articles/10.3389/fphar.2022.980747/full

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https://www.frontiersin.org/articles/10.3389/fphar.2022.980747/full

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