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Rager JE, Koval LE, Hickman E, Ring C, Teitelbaum T, Cohen T, Fragola G, Zylka MJ, Engel LS, Lu K, Engel SM. The environmental neuroactive chemicals list of prioritized substances for human biomonitoring and neurotoxicity testing: A database and high-throughput toxicokinetics approach. ENVIRONMENTAL RESEARCH 2025; 266:120537. [PMID: 39638029 PMCID: PMC11753932 DOI: 10.1016/j.envres.2024.120537] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/03/2024] [Revised: 10/01/2024] [Accepted: 12/02/2024] [Indexed: 12/07/2024]
Abstract
There is a diversity of chemicals to which humans are potentially exposed. Few of these chemicals have linked human biomonitoring data, and most have very limited neurotoxicity testing. Of particular concern are environmental exposures impacting children, who constitute a population of heightened susceptibility due to rapid neural growth and plasticity, yet lack biomonitoring data compared to other age/population subgroups. This study set out to develop a prioritized list of neuroactive substances, titled the Environmental NeuRoactIve CHemicals (ENRICH) list, to be used as a defined screening library in the evaluation of human biological samples, with emphasis on early childhood-relevant environmental exposures. In silico database mining approaches were used to prioritize chemicals based upon likelihood of neuroactivity, human exposure, and feasible detection in biological samples. Evidence of neuroactivity was compiled across in vitro high-throughput screening, animal testing, and/or human epidemiological findings. Chemicals were considered for their likelihood of human exposure and detection presence in biological samples (including metabolites), with additional evidence indicating presence within child-relevant products. The resulting list of 1827 chemicals were ranked using a Chemical Prioritization Index. Manual inclusion/exclusion criteria were employed for the top-ranking chemical candidates to ensure that chemicals were within the study's scope (i.e., environmentally relevant) and, for the purposes of biomonitoring, had properties amenable to mass spectrometry methods. These elements were combined to produce the ENRICH list of 250 top-ranking chemicals, spanning pesticides and those used in home maintenance, personal care, cleaning products, vehicles, arts and crafts, and consumer electronics, among other sources. Chemicals were additionally evaluated for high-throughput toxicokinetics to predict how much of a chemical and/or its metabolite(s) may reach urine, as an example biological matrix for practical use in biomonitoring efforts. This novel study couples databases and in silico-based predictions to prioritize chemicals in the environment with potential neurological impacts for future study.
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Affiliation(s)
- Julia E Rager
- Department of Environmental Sciences and Engineering, Gillings School of Global Public Health, The University of North Carolina at Chapel Hill, 135 Dauer Drive, CB #7431, Chapel Hill, NC, 27599, USA; Institute for Environmental Health Solutions, Gillings School of Global Public Health, The University of North Carolina at Chapel Hill, 135 Dauer Drive, CB #7431, Chapel Hill, NC, 27599, USA; Center for Center for Environmental Medicine, Asthma and Lung Biology, School of Medicine, The University of North Carolina at Chapel Hill, 116 Manning Drive, CB #7325, Chapel Hill, NC, 27599, USA; Curriculum in Toxicology and Environmental Medicine, School of Medicine the University of North Carolina at Chapel Hill, Chapel Hill, 116 Manning Drive, CB #7325, Chapel Hill, NC, 27599, USA.
| | - Lauren E Koval
- Department of Environmental Sciences and Engineering, Gillings School of Global Public Health, The University of North Carolina at Chapel Hill, 135 Dauer Drive, CB #7431, Chapel Hill, NC, 27599, USA; Institute for Environmental Health Solutions, Gillings School of Global Public Health, The University of North Carolina at Chapel Hill, 135 Dauer Drive, CB #7431, Chapel Hill, NC, 27599, USA
| | - Elise Hickman
- Department of Environmental Sciences and Engineering, Gillings School of Global Public Health, The University of North Carolina at Chapel Hill, 135 Dauer Drive, CB #7431, Chapel Hill, NC, 27599, USA; Institute for Environmental Health Solutions, Gillings School of Global Public Health, The University of North Carolina at Chapel Hill, 135 Dauer Drive, CB #7431, Chapel Hill, NC, 27599, USA; Center for Center for Environmental Medicine, Asthma and Lung Biology, School of Medicine, The University of North Carolina at Chapel Hill, 116 Manning Drive, CB #7325, Chapel Hill, NC, 27599, USA; Curriculum in Toxicology and Environmental Medicine, School of Medicine the University of North Carolina at Chapel Hill, Chapel Hill, 116 Manning Drive, CB #7325, Chapel Hill, NC, 27599, USA
| | - Caroline Ring
- Center for Computational Toxicology and Exposure, Office of Research and Development, United States Environmental Protection Agency, 109 T.W. Alexander Drive, Mail Drop D143-02, PO Box 12055, Research Triangle Park, NC, 27711, USA
| | - Taylor Teitelbaum
- Department of Environmental Sciences and Engineering, Gillings School of Global Public Health, The University of North Carolina at Chapel Hill, 135 Dauer Drive, CB #7431, Chapel Hill, NC, 27599, USA
| | - Todd Cohen
- Department of Neurology, School of Medicine, The University of North Carolina at Chapel Hill, 115 Mason Farm Road, CB #7250, Chapel Hill, NC, USA; Department of Cell Biology and Physiology, School of Medicine, The University of North Carolina at Chapel Hill, 111 Mason Farm Road, CB #7545, Chapel Hill, NC, USA; UNC Neuroscience Center, School of Medicine, The University of North Carolina at Chapel Hill, 116 Manning Drive, CB #7250, Chapel Hill, NC, USA
| | - Giulia Fragola
- Department of Neurology, School of Medicine, The University of North Carolina at Chapel Hill, 115 Mason Farm Road, CB #7250, Chapel Hill, NC, USA
| | - Mark J Zylka
- Department of Cell Biology and Physiology, School of Medicine, The University of North Carolina at Chapel Hill, 111 Mason Farm Road, CB #7545, Chapel Hill, NC, USA; UNC Neuroscience Center, School of Medicine, The University of North Carolina at Chapel Hill, 116 Manning Drive, CB #7250, Chapel Hill, NC, USA
| | - Lawrence S Engel
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, 135 Dauer Drive, CB #7435, Chapel Hill, NC, 27599, USA
| | - Kun Lu
- Department of Environmental Sciences and Engineering, Gillings School of Global Public Health, The University of North Carolina at Chapel Hill, 135 Dauer Drive, CB #7431, Chapel Hill, NC, 27599, USA; Institute for Environmental Health Solutions, Gillings School of Global Public Health, The University of North Carolina at Chapel Hill, 135 Dauer Drive, CB #7431, Chapel Hill, NC, 27599, USA; Curriculum in Toxicology and Environmental Medicine, School of Medicine the University of North Carolina at Chapel Hill, Chapel Hill, 116 Manning Drive, CB #7325, Chapel Hill, NC, 27599, USA
| | - Stephanie M Engel
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, 135 Dauer Drive, CB #7435, Chapel Hill, NC, 27599, USA
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Tariq F, Ahrens L, Alygizakis NA, Audouze K, Benfenati E, Carvalho PN, Chelcea I, Karakitsios S, Karakoltzidis A, Kumar V, Mora Lagares L, Sarigiannis D, Selvestrel G, Taboureau O, Vorkamp K, Andersson PL. Computational Tools to Facilitate Early Warning of New Emerging Risk Chemicals. TOXICS 2024; 12:736. [PMID: 39453156 PMCID: PMC11511557 DOI: 10.3390/toxics12100736] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/30/2024] [Revised: 09/30/2024] [Accepted: 10/09/2024] [Indexed: 10/26/2024]
Abstract
Innovative tools suitable for chemical risk assessment are being developed in numerous domains, such as non-target chemical analysis, omics, and computational approaches. These methods will also be critical components in an efficient early warning system (EWS) for the identification of potentially hazardous chemicals. Much knowledge is missing for current use chemicals and thus computational methodologies complemented with fast screening techniques will be critical. This paper reviews current computational tools, emphasizing those that are accessible and suitable for the screening of new and emerging risk chemicals (NERCs). The initial step in a computational EWS is an automatic and systematic search for NERCs in literature and database sources including grey literature, patents, experimental data, and various inventories. This step aims at reaching curated molecular structure data along with existing exposure and hazard data. Next, a parallel assessment of exposure and effects will be performed, which will input information into the weighting of an overall hazard score and, finally, the identification of a potential NERC. Several challenges are identified and discussed, such as the integration and scoring of several types of hazard data, ranging from chemical fate and distribution to subtle impacts in specific species and tissues. To conclude, there are many computational systems, and these can be used as a basis for an integrated computational EWS workflow that identifies NERCs automatically.
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Affiliation(s)
- Farina Tariq
- Department of Chemistry, Umeå University, 901 87 Umeå, Sweden;
| | - Lutz Ahrens
- Department of Aquatic Sciences and Assessment, Swedish University of Agricultural Sciences (SLU), 756 51 Uppsala, Sweden;
| | - Nikiforos A. Alygizakis
- Department of Chemistry, National and Kapodistrian University of Athens, 15772 Athens, Greece;
| | - Karine Audouze
- University Paris Cité, INSERM U1124, 75006 Paris, France; (K.A.); (O.T.)
| | - Emilio Benfenati
- Department of Environmental Health Sciences, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, 20156 Milano, Italy; (E.B.); (G.S.)
| | - Pedro N. Carvalho
- Department of Environmental Science, Aarhus University, 8000 Roskilde, Denmark; (P.N.C.); (K.V.)
| | - Ioana Chelcea
- Department of Chemistry, Umeå University, 901 87 Umeå, Sweden;
- Department of Chemical and Pharmaceutical Safety, Research Institutes of Sweden (RISE), 103 33 Stockholm, Sweden
| | - Spyros Karakitsios
- HERACLES Research Center on the Exposome and Health, Center for Interdisciplinary Research and Innovation, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece; (S.K.); (A.K.); (D.S.)
- Environmental Engineering Laboratory, Department of Chemical Engineering, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece
| | - Achilleas Karakoltzidis
- HERACLES Research Center on the Exposome and Health, Center for Interdisciplinary Research and Innovation, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece; (S.K.); (A.K.); (D.S.)
- Environmental Engineering Laboratory, Department of Chemical Engineering, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece
| | - Vikas Kumar
- Environmental Analysis and Management Using Computer Aided Process Engineering (AGACAPE), Institut d’Investigació Sanitària Pere Virgili (IISPV), Universitat Rovira i Virgili (URV), 43204 Reus, Spain;
- German Federal Institute for Risk Assessment (BfR), Max-Dohrn-Str. 8-10, 10589 Berlin, Germany
| | - Liadys Mora Lagares
- Laboratory for Cheminformatics, Theory Department, National Institute of Chemistry, 1000 Ljubljana, Slovenia;
| | - Dimosthenis Sarigiannis
- HERACLES Research Center on the Exposome and Health, Center for Interdisciplinary Research and Innovation, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece; (S.K.); (A.K.); (D.S.)
- Environmental Engineering Laboratory, Department of Chemical Engineering, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece
- National Hellenic Research Foundation, 11635 Athens, Greece
- University School of Advanced Study IUSS, 27100 Pavia, Italy
| | - Gianluca Selvestrel
- Department of Environmental Health Sciences, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, 20156 Milano, Italy; (E.B.); (G.S.)
| | - Olivier Taboureau
- University Paris Cité, INSERM U1124, 75006 Paris, France; (K.A.); (O.T.)
| | - Katrin Vorkamp
- Department of Environmental Science, Aarhus University, 8000 Roskilde, Denmark; (P.N.C.); (K.V.)
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Bianchi E, Costa E, Harrill J, Deford P, LaRocca J, Chen W, Sutake Z, Lehman A, Pappas-Garton A, Sherer E, Moreillon C, Sriram S, Dhroso A, Johnson K. Discovery Phase Agrochemical Predictive Safety Assessment Using High Content In Vitro Data to Estimate an In Vivo Toxicity Point of Departure. JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY 2024. [PMID: 39033510 DOI: 10.1021/acs.jafc.4c03094] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/23/2024]
Abstract
Utilization of in vitro (cellular) techniques, like Cell Painting and transcriptomics, could provide powerful tools for agrochemical candidate sorting and selection in the discovery process. However, using these models generates challenges translating in vitro concentrations to the corresponding in vivo exposures. Physiologically based pharmacokinetic (PBPK) modeling provides a framework for quantitative in vitro to in vivo extrapolation (IVIVE). We tested whether in vivo (rat liver) transcriptomic and apical points of departure (PODs) could be accurately predicted from in vitro (rat hepatocyte or human HepaRG) transcriptomic PODs or HepaRG Cell Painting PODs using PBPK modeling. We compared two PBPK models, the ADMET predictor and the httk R package, and found httk to predict the in vivo PODs more accurately. Our findings suggest that a rat liver apical and transcriptomic POD can be estimated utilizing a combination of in vitro transcriptome-based PODs coupled with PBPK modeling for IVIVE. Thus, high content in vitro data can be translated with modest accuracy to in vivo models of ultimate regulatory importance to help select agrochemical analogs in early stage discovery program.
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Affiliation(s)
- Enrica Bianchi
- Corteva Agriscience, Indianapolis ,Indiana 46268, United States
| | | | - Joshua Harrill
- Center for Computational Toxicology and Exposure, United States Environmental Protection Agency, Research Triangle Park ,North Carolina 27709, United States
| | - Paul Deford
- Corteva Agriscience, Indianapolis ,Indiana 46268, United States
| | - Jessica LaRocca
- Corteva Agriscience, Indianapolis ,Indiana 46268, United States
| | - Wei Chen
- Corteva Agriscience, Indianapolis ,Indiana 46268, United States
| | - Zachary Sutake
- Corteva Agriscience, Indianapolis ,Indiana 46268, United States
| | - Audrey Lehman
- Corteva Agriscience, Indianapolis ,Indiana 46268, United States
| | | | - Eric Sherer
- Corteva Agriscience, Indianapolis ,Indiana 46268, United States
| | | | | | - Andi Dhroso
- Corteva Agriscience, Indianapolis ,Indiana 46268, United States
| | - Kamin Johnson
- Corteva Agriscience, Indianapolis ,Indiana 46268, United States
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Zhang X, Li Z. Profiling population-wide exposure to environmental chemicals: A case study of naphthalene. CHEMOSPHERE 2024; 358:142217. [PMID: 38704043 DOI: 10.1016/j.chemosphere.2024.142217] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/19/2024] [Revised: 04/20/2024] [Accepted: 04/30/2024] [Indexed: 05/06/2024]
Abstract
Long-term exposure to environmental chemicals can detrimentally impact human health, and understanding the relationship between age distribution and levels of external and internal exposure is crucial. Nonetheless, existing methods for assessing population-wide exposure across age groups are limited. To bridge this research gap, we introduced a modeling approach designed to assess both chronic external and internal exposure to chemicals at the population level. The external and internal exposure assessments were quantified in terms of the average daily dose (ADD) and steady-state blood concentration of the environmental chemical, respectively, which were categorized by age and gender groups. The modeling process was presented within a spreadsheet framework, affording users the capability to execute population-wide exposure analyses across a spectrum of chemicals. Our simulation outcomes underscored a salient trend: younger age groups, particularly infants and children, exhibited markedly higher ADD values and blood concentrations of environmental chemicals compared to their older counterparts. This observation is due to the elevated basal metabolic rate per unit of body weight characteristic of younger individuals, coupled with their diminished biotransformation kinetics of xenobiotics within their livers. These factors collectively contribute to increased intake rates of environmental chemicals per unit of body weight through air and food consumption, along with heightened bioaccumulation of these chemicals within their bodies (e.g., blood). Furthermore, we augmented the precision of the external and internal exposure assessment by incorporating the age distribution across the population. The simulation outcomes unveiled that, to estimate the central tendency of the population's exposure levels, employing the baseline value group (age group 21-30) or the surrogate age of 25 serves as a simple yet dependable approach. However, for comprehensive population protection, our recommendation aligns with conducting exposure assessments for the younger age groups (age group 0-11). Future studies should integrate individual-level exposure assessment, analyze vulnerable population groups, and refine population structures within our developed model.
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Affiliation(s)
- Xiaoyu Zhang
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, Guangdong 518107, China
| | - Zijian Li
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, Guangdong 518107, China.
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Chiu WA. Invited Perspective: Uneven Progress Addressing Population Variability in Human Health Risk Assessment. ENVIRONMENTAL HEALTH PERSPECTIVES 2024; 132:31305. [PMID: 38498339 PMCID: PMC10947099 DOI: 10.1289/ehp13461] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/07/2023] [Revised: 08/03/2023] [Accepted: 02/06/2024] [Indexed: 03/20/2024]
Affiliation(s)
- Weihsueh A. Chiu
- Department of Veterinary Physiology and Pharmacology, Texas A&M University, College Station, Texas, USA
- Interdisciplinary Faculty of Toxicology, Texas A&M University, College Station, Texas, USA
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Buckley TJ, Egeghy PP, Isaacs K, Richard AM, Ring C, Sayre RR, Sobus JR, Thomas RS, Ulrich EM, Wambaugh JF, Williams AJ. Cutting-edge computational chemical exposure research at the U.S. Environmental Protection Agency. ENVIRONMENT INTERNATIONAL 2023; 178:108097. [PMID: 37478680 PMCID: PMC10588682 DOI: 10.1016/j.envint.2023.108097] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/21/2023] [Revised: 06/05/2023] [Accepted: 07/12/2023] [Indexed: 07/23/2023]
Abstract
Exposure science is evolving from its traditional "after the fact" and "one chemical at a time" approach to forecasting chemical exposures rapidly enough to keep pace with the constantly expanding landscape of chemicals and exposures. In this article, we provide an overview of the approaches, accomplishments, and plans for advancing computational exposure science within the U.S. Environmental Protection Agency's Office of Research and Development (EPA/ORD). First, to characterize the universe of chemicals in commerce and the environment, a carefully curated, web-accessible chemical resource has been created. This DSSTox database unambiguously identifies >1.2 million unique substances reflecting potential environmental and human exposures and includes computationally accessible links to each compound's corresponding data resources. Next, EPA is developing, applying, and evaluating predictive exposure models. These models increasingly rely on data, computational tools like quantitative structure activity relationship (QSAR) models, and machine learning/artificial intelligence to provide timely and efficient prediction of chemical exposure (and associated uncertainty) for thousands of chemicals at a time. Integral to this modeling effort, EPA is developing data resources across the exposure continuum that includes application of high-resolution mass spectrometry (HRMS) non-targeted analysis (NTA) methods providing measurement capability at scale with the number of chemicals in commerce. These research efforts are integrated and well-tailored to support population exposure assessment to prioritize chemicals for exposure as a critical input to risk management. In addition, the exposure forecasts will allow a wide variety of stakeholders to explore sustainable initiatives like green chemistry to achieve economic, social, and environmental prosperity and protection of future generations.
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Affiliation(s)
- Timothy J Buckley
- U.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.
| | - Peter P Egeghy
- U.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
| | - Kristin Isaacs
- U.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
| | - Ann M Richard
- U.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
| | - Caroline Ring
- U.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
| | - Risa R Sayre
- U.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
| | - Jon R Sobus
- U.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
| | - Russell S Thomas
- U.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
| | - Elin M Ulrich
- U.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
| | - John F Wambaugh
- U.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
| | - Antony J Williams
- U.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
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Wambaugh JF, Rager JE. Exposure forecasting - ExpoCast - for data-poor chemicals in commerce and the environment. JOURNAL OF EXPOSURE SCIENCE & ENVIRONMENTAL EPIDEMIOLOGY 2022; 32:783-793. [PMID: 36347934 PMCID: PMC9742338 DOI: 10.1038/s41370-022-00492-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/28/2022] [Revised: 10/21/2022] [Accepted: 10/21/2022] [Indexed: 05/10/2023]
Abstract
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 2009 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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Affiliation(s)
- John F Wambaugh
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. EPA, Research Triangle Park, NC, USA.
- Department of Environmental Sciences & Engineering, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
| | - Julia E Rager
- Department of Environmental Sciences & Engineering, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
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