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Exposure Forecasting – ExpoCast – for Data-Poor Chemicals in Commerce and the Environment

Estimates of exposure are critical to prioritize and assess chemicals based on risk posed to public health and the environment. The U.S. Environmental Protection Agency (EPA) is responsible for regulating thousands of chemicals in commerce and the environment for which exposure data are limited. Sin...

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Autores principales: Wambaugh, John F., Rager, Julia E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9742338/
https://www.ncbi.nlm.nih.gov/pubmed/36347934
http://dx.doi.org/10.1038/s41370-022-00492-z
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author Wambaugh, John F.
Rager, Julia E.
author_facet Wambaugh, John F.
Rager, Julia E.
author_sort Wambaugh, John F.
collection PubMed
description Estimates of exposure are critical to prioritize and assess chemicals based on risk posed to public health and the environment. The U.S. Environmental Protection Agency (EPA) is responsible for regulating thousands of chemicals in commerce and the environment for which exposure data are limited. Since 2010 the EPA's ExpoCast ("Exposure Forecasting") project has sought to develop the data, tools, and evaluation approaches required to generate rapid and scientifically defensible exposure predictions for the full universe of existing and proposed commercial chemicals. This review article aims to summarize issues in exposure science that have been addressed through initiatives affiliated with ExpoCast. ExpoCast research has generally focused on chemical exposure as a statistical systems problem intended to inform thousands of chemicals. The project exists as a companion to EPA's ToxCast ("Toxicity Forecasting") project which has used in vitro high-throughput screening technologies to characterize potential hazard posed by thousands of chemicals for which there are limited toxicity data. Rapid prediction of chemical exposures and in vitro-in vivo extrapolation (IVIVE) of ToxCast data allow for prioritization based upon risk of adverse outcomes due to environmental chemical exposure. ExpoCast has developed 1) integrated modeling approaches to reliably predict exposure and IVIVE dose, 2) highly efficient screening tools for chemical prioritization, 3) efficient and affordable tools for generating new exposure and dose data, and 4) easily accessible exposure databases. The development of new exposure models and databases along with the application of technologies like non-targeted analysis and machine learning have transformed exposure science for data-poor chemicals. By developing high-throughput tools for chemical exposure analytics and translating those tools into public health decisions ExpoCast research has served as a crucible for identifying and addressing exposure science knowledge gaps.
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spelling pubmed-97423382023-05-08 Exposure Forecasting – ExpoCast – for Data-Poor Chemicals in Commerce and the Environment Wambaugh, John F. Rager, Julia E. J Expo Sci Environ Epidemiol Article Estimates of exposure are critical to prioritize and assess chemicals based on risk posed to public health and the environment. The U.S. Environmental Protection Agency (EPA) is responsible for regulating thousands of chemicals in commerce and the environment for which exposure data are limited. Since 2010 the EPA's ExpoCast ("Exposure Forecasting") project has sought to develop the data, tools, and evaluation approaches required to generate rapid and scientifically defensible exposure predictions for the full universe of existing and proposed commercial chemicals. This review article aims to summarize issues in exposure science that have been addressed through initiatives affiliated with ExpoCast. ExpoCast research has generally focused on chemical exposure as a statistical systems problem intended to inform thousands of chemicals. The project exists as a companion to EPA's ToxCast ("Toxicity Forecasting") project which has used in vitro high-throughput screening technologies to characterize potential hazard posed by thousands of chemicals for which there are limited toxicity data. Rapid prediction of chemical exposures and in vitro-in vivo extrapolation (IVIVE) of ToxCast data allow for prioritization based upon risk of adverse outcomes due to environmental chemical exposure. ExpoCast has developed 1) integrated modeling approaches to reliably predict exposure and IVIVE dose, 2) highly efficient screening tools for chemical prioritization, 3) efficient and affordable tools for generating new exposure and dose data, and 4) easily accessible exposure databases. The development of new exposure models and databases along with the application of technologies like non-targeted analysis and machine learning have transformed exposure science for data-poor chemicals. By developing high-throughput tools for chemical exposure analytics and translating those tools into public health decisions ExpoCast research has served as a crucible for identifying and addressing exposure science knowledge gaps. 2022-11 2022-11-08 /pmc/articles/PMC9742338/ /pubmed/36347934 http://dx.doi.org/10.1038/s41370-022-00492-z Text en http://www.nature.com/authors/editorial_policies/license.html#termsUsers may view, print, copy, and download text and data-mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use:http://www.nature.com/authors/editorial_policies/license.html#terms
spellingShingle Article
Wambaugh, John F.
Rager, Julia E.
Exposure Forecasting – ExpoCast – for Data-Poor Chemicals in Commerce and the Environment
title Exposure Forecasting – ExpoCast – for Data-Poor Chemicals in Commerce and the Environment
title_full Exposure Forecasting – ExpoCast – for Data-Poor Chemicals in Commerce and the Environment
title_fullStr Exposure Forecasting – ExpoCast – for Data-Poor Chemicals in Commerce and the Environment
title_full_unstemmed Exposure Forecasting – ExpoCast – for Data-Poor Chemicals in Commerce and the Environment
title_short Exposure Forecasting – ExpoCast – for Data-Poor Chemicals in Commerce and the Environment
title_sort exposure forecasting – expocast – for data-poor chemicals in commerce and the environment
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9742338/
https://www.ncbi.nlm.nih.gov/pubmed/36347934
http://dx.doi.org/10.1038/s41370-022-00492-z
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