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Revisiting and updating chemical groupings with new approach methodologies (Presentation by Dan Chang)
Citation:
Fay, K., K. Markey, K. Mansouri, J. Prindiville, G. Patlewicz, A. Richard, R. Lougee, Mahmoud A. Shobair, M. Lewis, E. Saluck, AND D. Chang. Revisiting and updating chemical groupings with new approach methodologies (Presentation by Dan Chang). ICCVAM RAWG, Virtual, Virtual, May 29, 2020. https://doi.org/10.23645/epacomptox.12564074
Impact/Purpose:
This work seeks to address the problem of integration, use and application of NAMs in a regulatory setting supporting TSCA efforts and the TSCA Alternative Testing Strategy. Furthermore, this work seeks to develop a systematic method/workflow to incorporate NAM data into category development. Findings from this work will potentially influence how program office partners and the international community can use NAM information (both in silico and in vitro) to develop chemical categories pes. with regards to data poor chemistry domains. Current work includes collaboration with program office (OPPT and OSCP) as well as international partners (Canada) as part of the larger international APCRA workgroup effort.
Description:
Chemical categorization, or grouping, is routinely employed to capture and report salient chemistry and toxicity correlations as well as to consider analogs for chemicals that have limited empirical information. One prominent application of chemical grouping used by chemical regulators is the Ecological Structure Activity Relationship (EcoSAR) model, which predicts the toxicity of classes of chemicals to various aquatic species. There is a continual need to update chemical categories and predictive models as new information on chemical hazards becomes available, especially given that a large proportion of industrial substances are not classifiable by EcoSAR and similar tools. This study employed hierarchical clustering approaches to evaluate whether potential refinements could be made to the current EcoSAR classes using chemical fingerprint and in vitro biological activity information. Refinements included building sub-categories for broad, existing EcoSAR classes (e.g., neutral organics), as well as identifying new categories to address substances currently unclassifiable by EcoSAR. An ensemble tree-based binary classification model was developed to predict narcotic or specific-acting aquatic toxicity modes of action. The model was trained on chemical fingerprint (ToxPrints), in vitro biological activity (ToxCast and Tox21 high-throughput screening data), or both. It was then used to predict aquatic toxicity mode of action (narcosis vs specific-acting) for chemicals classified as neutral organics or unclassifiable by the current version of EcoSAR. Chemotype and activity enrichments for those chemicals predicted to be specific-acting identified features useful for refining EcoSAR classes, including several bond chemotypes (e.g., sulfonyl, sulfide, sulfonate, alkyl-tri-halo, and benzopyran) and in vitro assay activity (e.g., Novascreen ENZ assays). This approach identified data gaps in the biological activity inventory, potential analogs for chemicals that may fit the suggested new categories and suggests specific high-throughput assays that may be most useful for informing reductions in animal testing.
URLs/Downloads:
DOI: Revisiting and updating chemical groupings with new approach methodologies (Presentation by Dan Chang)
RAWG2020_WEBINAR_KFAY_DCHANG_FINAL.PDF (PDF, NA pp, 799.41 KB, about PDF)