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Cutting-edge computational chemical exposure research at the U.S. Environmental Protection Agency
Timothy J Buckley1, Peter P Egeghy1, Kristin Isaacs1
1U.S. Environmental Protection Agency, Office of Research & Development, Center for Computational Toxicology & Exposure (CCTE), 109 TW Alexander Drive, Research Triangle Park, NC 27711, United States.
Environment International
|July 21, 2023
Summary
Exposure science is advancing with computational methods to forecast chemical exposures for a rapidly expanding chemical landscape. This approach supports risk management and sustainable initiatives for environmental protection.
Area of Science:
- Environmental chemistry and toxicology
- Computational toxicology and exposure science
- Risk assessment and management
Background:
- Traditional exposure science focused on "after the fact" and single-chemical assessments.
- The chemical landscape is constantly expanding, necessitating faster assessment methods.
- Advancements in computational tools are crucial for keeping pace with new chemicals and exposures.
Purpose of the Study:
- To provide an overview of computational exposure science approaches, accomplishments, and future plans.
- To highlight the U.S. Environmental Protection Agency's Office of Research and Development (EPA/ORD) initiatives.
- To support population exposure assessment and chemical prioritization for risk management.
Main Methods:
- Creation of a curated, web-accessible chemical database (DSSTox) identifying over 1.2 million unique substances.
- Development and application of predictive exposure models utilizing data, quantitative structure-activity relationship (QSAR) models, and machine learning/artificial intelligence.
- Integration of data resources across the exposure continuum, including high-resolution mass spectrometry (HRMS) non-targeted analysis (NTA) for large-scale chemical measurement.
Main Results:
- Establishment of the DSSTox database for comprehensive chemical characterization.
- Development of predictive models for timely and efficient estimation of chemical exposure and uncertainty for numerous chemicals.
- Implementation of scalable measurement capabilities through advanced analytical techniques.
Conclusions:
- Computational exposure science is essential for modern risk assessment and management.
- These advancements enable proactive identification and prioritization of chemicals of concern.
- Exposure forecasts support stakeholders in exploring sustainable initiatives like green chemistry for environmental and economic prosperity.
Keywords:
Chemical curationComputational exposure scienceHigh-throughputMachine learningNon-targeted analysis (NTA)Predictive exposure modelingUncertainty
