Use of computational toxicology models to predict toxicological points of departure: A case study with triazine herbicides
- PMID: 36584090
- DOI: 10.1002/bdr2.2144
Use of computational toxicology models to predict toxicological points of departure: A case study with triazine herbicides
Abstract
Background: Atrazine simazine and propazine, widely used triazine herbicides on food crops and in residential areas, disrupt the neuroendocrine system raising human health concerns. USEPA developed a PBPK model based on triazine common Mode of Action (MOA)-suppression of luteinizing hormone surge in female rats-to generate human regulatory points of departure (POD: mg/kg/day). We compared triazine Human Administered Equivalent Dose (AEDHuman mg/kg/day) predictions from open access computational tools to the PBPK PODs to assess concordance.
Methods: Computational tools were the following: ToxCast/Tox21 in vitro assays; Toxicogenomic databases to assess concordance with ToxCast/Tox21 targets; integrated chemical environment (ICE) models with ToxCast/Tox21 inputs to predict AEDHuman PODs and population-based age-refined high throughput toxicokinetics (HTTK-Pop) to compare to age-related PBPK PODs.
Results: ToxCast/Tox21 assays identified critical targets in the triazine common MOA and gene databases; ICE AEDHuman predictions were mainly concordant with the USEPA PBPK PODs quantitatively. Low fold-differences between PBPK POD and ICE AEDHuman predictions indicated that the ICE models are health-protective. HTTK-Pop age-refinements were within 10-fold of the USEPA PBPK PODs.
Conclusions: CompTox tools were used to identify assay targets in the MOA and identify potential molecular initiating targets in the adverse outcome pathway for potential use in risk assessment.
Keywords: ToxCast/Tox21; atrazine; integrated chemical environment; population-based high throughput toxicokinetics; propazine; risk assessment; simazine.
© 2022 Wiley Periodicals LLC.
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