Use of computational toxicology models to predict toxicological points of departure: A case study with triazine herbicides.

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.

Use of computational toxicology tools to predict in vivo endpoints associated with Mode of Action and the endocannabinoid system: A case study with chlorpyrifos, chlorpyrifos-oxon and Δ9Tetrahydrocannabinol.

Currently, there is a lack of knowledge about the effects of co-exposures of cannabis, contaminated with pesticides like chlorpyrifos (CPF) and the toxic metabolite CPF-oxon (CPFO). CPF/CPFO residues, and Δ9Tetrahydrocannabinol (Δ9THC), the main component in cannabis, are known to disrupt the endocannabinoid system (eCBS) resulting in neurodevelopmental defects. Although there are in vivo data characterizing CPF/CPFO and Δ9THC, there are mechanistic data gaps and deficiencies. In this study, an investigation of open access CompTox tools and ToxCast/Tox21 data was performed to determine targets relating to the modes of action (MOA) for these compounds and, given the available biological targets, predict points of departure (POD). The main findings were as follows: 1) In vivo PODs for each chemical were from open literature, 2) Concordance between ToxCast/Tox21 assay targets and known targets in the metabolic and eCBS pathways was evaluated, 3) Human Equivalent Administered Dose (EADHuman) PODs showed the High throughput toxicokinetic (HTTK) 3 compartment model (3COMP) was more predictive of in vivo PODs than the PBTK model for CPF, CPFO and Δ9THC, 4) Age-adjusted 3COMP HTTK-Pop EADHuman, with CPF and CPFO ToxCast/Tox21 AC50 values as inputs were predictive for ages 0-4 when but not Δ9THC compared to in vivo PODs. 5) Age-related refinements for CPF/CPFO were primarily from ToxCast/Tox21 active hit-calls for nuclear receptors, CYP2B6 and AChE inhibition (CPFO only) associated with the metabolic pathway. Only one assay target (arylhydrocarbon hydroxylase receptor) was common between CPF/CPFO and Δ9THC. While computational refinements may select some sensitive events involved in the metabolic pathways; this is highly dependent on the cytotoxicity limits, availability of metabolic activity in the ToxCast/Tox21 assays and reliability of assay performance. Some uncertainties and data gaps for Δ9THC might be addressed with assays specific to the eCBS. For CPF, assays with appropriate metabolic activation could better represent the toxic pathway.