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The chemical landscape of high-throughput new approach methodologies for exposure

Abstract

The rapid characterization of risk to humans and ecosystems from exogenous chemicals requires information on both hazard and exposure. The U.S. Environmental Protection Agency’s ToxCast program and the interagency Tox21 initiative have screened thousands of chemicals in various high-throughput (HT) assay systems for in vitro bioactivity. EPA’s ExpoCast program is developing complementary HT methods for characterizing the human and ecological exposures necessary to interpret HT hazard data in a real-world risk context. These new approach methodologies (NAMs) for exposure include computational and analytical tools for characterizing multiple components of the complex pathways chemicals take from their source to human and ecological receptors. Here, we analyze the landscape of exposure NAMs developed in ExpoCast in the context of various chemical lists of scientific and regulatory interest, including the ToxCast and Tox21 libraries and the Toxic Substances Control Act (TSCA) inventory. We examine the landscape of traditional and exposure NAM data covering chemical use, emission, environmental fate, toxicokinetics, and ultimately external and internal exposure. We consider new chemical descriptors, machine learning models that draw inferences from existing data, high-throughput exposure models, statistical frameworks that integrate multiple model predictions, and non-targeted analytical screening methods that generate new HT monitoring information. We demonstrate that exposure NAMs drastically improve the coverage of the chemical landscape compared to traditional approaches and recommend a set of research activities to further expand the development of HT exposure data for application to risk characterization. Continuing to develop exposure NAMs to fill priority data gaps identified here will improve the availability and defensibility of risk-based metrics for use in chemical prioritization and screening.

Impact

This analysis describes the current state of exposure assessment-based new approach methodologies across varied chemical landscapes and provides recommendations for filling key data gaps.

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Fig. 1: Characterization of the chemical inventory in terms of known sectors of use, function, and structure.
Fig. 2: Availability of traditional (reported) use data and NAM chemical use descriptors for the combined chemical inventory.
Fig. 3: Monitoring information for inventory chemicals, organized by media category.
Fig. 4: HT exposure model and evaluation NAMs have greatly improved the number of chemicals in regulatory inventories with exposure estimates.
Fig. 5: Availability of traditional TK data, TK NAMs, and exposure NAMs for 9404 chemicals with in vitro data.

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Data availability

All data analyzed in this paper are available at data.gov, indexed by first author and title.

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Acknowledgements

We would like to thank Drs. Zachary Stanfield and Daniel Vallero of EPA Office of Research and Development and Tariq Francis and Andy Nong of Health Canada for their technical review of this manuscript. The information in this document has been funded wholly or in part by the US Environmental Protection Agency. It does not signify that the contents necessarily reflect the views of the U.S. EPA or U.S. CPSC, nor does mention of trade names or commercial products constitute endorsement or recommendation for use. The paper has been subjected to the U.S. EPA review process and approved for publication. No funding sources are associated with this study.

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KKI performed data analyses and drafted figures, tables, and text. PE, KD, KP, AZ, CR, JRS, BAW, EMU, AJW, and JW developed/provided exposure NAM or cheminformatic datasets and contributed to text.

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Correspondence to Kristin K. Isaacs.

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Isaacs, K.K., Egeghy, P., Dionisio, K.L. et al. The chemical landscape of high-throughput new approach methodologies for exposure. J Expo Sci Environ Epidemiol 32, 820–832 (2022). https://doi.org/10.1038/s41370-022-00496-9

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