Non-animal framework based on new approach methodologies (NAMs) for chemical hazard identification and risk assessment. (IMAGE)
Caption
Non-animal framework based on new approach methodologies (NAMs) for chemical hazard identification and risk assessment. The framework comprises three modules: (1) high-throughput screening to address toxicity data gaps and select candidate priority chemicals; (2) artificial intelligence/machine learning–enabled, mechanism-based identification of key toxic structures, biomarkers and pathways from multi-source NAM data (for example, multi-omics and adverse outcome pathways [AOPs]); and (3) quantitative risk evaluation that integrates absorption, distribution, metabolism and excretion (ADME), physiologically based toxicokinetics (PBTK) and quantitative in vitro–in vivo extrapolation (QIVIVE), supported by in vitro and organoid validation, to derive health- and ecology-based thresholds for chemicals requiring strict control.
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Environmental Science and Ecotechnology
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