An automated computational data pipeline to rapidly acquire, score, and rank toxicological data for ecological hazard assessment.

Autor: Schaupp CM; Oak Ridge Institute for Science and Education, Oak Ridge, Tennessee, USA.; US Environmental Protection Agency, Great Lakes Toxicology and Ecology Division, Center for Computational Toxicology and Exposure, Duluth, Minnesota, USA., Byrne G; General Dynamics Information Technology Inc., Supporting USEPA IV (MAINES) Contract, Research Triangle Park, North Carolina, USA., Chan M; USEPA, Center for Computational Toxicology and Exposure, Scientific Computing and Data Curation Division, Data Management and Mining Branch, Research Triangle Park, North Carolina, USA., Haggard DE; USEPA, Center for Computational Toxicology and Exposure, Scientific Computing and Data Curation Division, Data Management and Mining Branch, Research Triangle Park, North Carolina, USA., Hazemi M; Oak Ridge Institute for Science and Education, Oak Ridge, Tennessee, USA.; US Environmental Protection Agency, Great Lakes Toxicology and Ecology Division, Center for Computational Toxicology and Exposure, Duluth, Minnesota, USA., Jankowski MD; USEPA, Region 10 Office, Laboratory Services & Applied Science Division, Risk Evaluation Branch, Seattle, Washington, USA., LaLone CA; US Environmental Protection Agency, Great Lakes Toxicology and Ecology Division, Center for Computational Toxicology and Exposure, Duluth, Minnesota, USA., LaTier A; USEPA, Region 10 Office, Laboratory Services & Applied Science Division, Risk Evaluation Branch, Seattle, Washington, USA., Mattingly KZ; Spec-Pro Professional Services, Duluth, Minnesota, USA., Olker JH; US Environmental Protection Agency, Great Lakes Toxicology and Ecology Division, Center for Computational Toxicology and Exposure, Duluth, Minnesota, USA., Renner J; USEPA, Scientific Computing and Data Curation Division, Center for Computational Toxicology and Exposure, Data Management and Mining Branch, Duluth, Minnesota, USA., Sharma B; USEPA, Center for Computational Toxicology and Exposure, Scientific Computing and Data Curation Division, Data Management and Mining Branch, Research Triangle Park, North Carolina, USA., Villeneuve DL; US Environmental Protection Agency, Great Lakes Toxicology and Ecology Division, Center for Computational Toxicology and Exposure, Duluth, Minnesota, USA.
Jazyk: angličtina
Zdroj: Integrated environmental assessment and management [Integr Environ Assess Manag] 2024 Nov; Vol. 20 (6), pp. 2203-2217. Date of Electronic Publication: 2024 May 16.
DOI: 10.1002/ieam.4945
Abstrakt: Biological Evaluations support Endangered Species Act (ESA) consultation with the US Fish and Wildlife Service and National Marine Fisheries Service by federal action agencies, such as the USEPA, regarding impacts of federal activities on threatened or endangered species. However, they are often time-consuming and challenging to conduct. The identification of pollutant benchmarks or guidance to protect taxa for states and tribes when USEPA has not yet developed criteria recommendations is also of importance to ensure a streamlined approach to Clean Water Act program implementation. Due to substantial workloads, tight regulatory timelines, and the often-protracted length of ESA consultations, there is a need to streamline the development of biological evaluation toxicity assessments for determining the impact of chemical pollutants on ESA-listed species. Moreover, there is limited availability of species-specific toxicity data for many contaminants, further complicating the consultation process. New approach methodologies are being increasingly used in toxicology and chemical safety assessment to rapidly and cost-effectively provide data that can fill gaps in hazard and/or exposure characterization. Here, we present the development of an automated computational pipeline-RASRTox (Rapidly Acquire, Score, and Rank Toxicological data)-to rapidly extract and categorize ecological toxicity benchmark values from curated data sources (ECOTOX, ToxCast) and well-established quantitative structure-activity relationships (TEST, ECOSAR). As a proof of concept, points-of-departure (PODs) generated in RASRTox for 13 chemicals were compared against benchmark values derived using traditional methods-toxicity reference values (TRVs) and water quality criteria (WQC). The RASRTox PODs were generally within an order of magnitude of corresponding TRVs, though less concordant compared with WQC. The greatest utility of RASRTox, however, lies in its ability to quickly and systematically identify critical studies that may serve as a basis for screening value derivation by toxicologists as part of an ecological hazard assessment. As such, the strategy described in this case study can potentially be adapted for other risk assessment contexts and stakeholder needs. Integr Environ Assess Manag 2024;20:2203-2217. © 2024 Society of Environmental Toxicology & Chemistry (SETAC). This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.
(© 2024 Society of Environmental Toxicology & Chemistry (SETAC). This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.)
Databáze: MEDLINE
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