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In Vitro-In Vivo Extrapolation of Thyroid-Related Endpoints with Higher Throughput Pregnancy PBPK Modeling
Citation:
Truong, K., D. Kapraun, S. Davidson-Fritz, J. Wambaugh, S. Degitz, J. Olker, M. Hornung, R. Judson, AND K. Friedman. In Vitro-In Vivo Extrapolation of Thyroid-Related Endpoints with Higher Throughput Pregnancy PBPK Modeling. Quantitative Systems Pharmacology (QSP) Summit Cambridge 2024, Cambridge, MA, May 01, 2024. https://doi.org/10.23645/epacomptox.25765788
Impact/Purpose:
To cause developmental toxicity, chemical exposures must cause bioactive concentrations in key tissues during susceptible lifestages, including during early fetal development. Next generation chemical risk assessment (NGRA) aims to replace and enhance traditional toxicity testing via in vitro new approach methodologies (NAMs). Translating in vitro bioactivity-based points of departure (PODs) from NAMs to an in vivo dose context requires in vitro-in vivo extrapolation (IVIVE) based upon toxicokinetics. Higher throughput toxicokinetic (HTTK) methods are needed for IVIVE involving large chemical screening libraries and many potential PODs from multiple models of toxicities such as developmental toxicity. The open-source software package “httk” has recently added a high throughput human gestational toxicokinetic model. When combined with a modified adult model to capture early pregnancy (prior to 13 weeks of gestation), these tools can be used for IVIVE based on maternal-fetal exposures for the entire duration of human pregnancy. A case study will be presented using maternal-fetal IVIVE to determine the most potent chemicals for thyroid disruption as indicated by in vitro high-throughput screening characterizing thyroid-relevant molecular initiating events . This presentation will delineate assumptions to building a full model of pregnancy for addition to “httk.” IVIVE-derived human equivalent doses are generally higher when based on internal tissue concentrations and susceptible life stages of the individual, which is important to inform potential margins of exposure and priority for obtaining additional thyroid bioactivity and/or developmental exposure information. This abstract does not reflect EPA policy.
Description:
To cause developmental toxicity, chemical exposures must cause bioactive concentrations in key tissues during susceptible lifestages, including during early fetal development. Next generation chemical risk assessment (NGRA) aims to replace and enhance traditional toxicity testing via in vitro new approach methodologies (NAMs). Translating in vitro bioactivity-based points of departure (PODs) from NAMs to an in vivo dose context requires in vitro-in vivo extrapolation (IVIVE) based upon toxicokinetics. Higher throughput toxicokinetic (HTTK) methods are needed for IVIVE involving large chemical screening libraries and many potential PODs from multiple models of toxicities such as developmental toxicity. The open-source software package “httk” has recently added a high throughput human gestational toxicokinetic model. When combined with a modified adult model to capture early pregnancy (prior to 13 weeks of gestation), these tools can be used for IVIVE based on maternal-fetal exposures for the entire duration of human pregnancy. A case study will be presented using maternal-fetal IVIVE to determine the most potent chemicals for thyroid disruption as indicated by in vitro high-throughput screening characterizing thyroid-relevant molecular initiating events . This presentation will delineate assumptions to building a full model of pregnancy for addition to “httk.” IVIVE-derived human equivalent doses are generally higher when based on internal tissue concentrations and susceptible life stages of the individual, which is important to inform potential margins of exposure and priority for obtaining additional thyroid bioactivity and/or developmental exposure information. This abstract does not reflect EPA policy.
URLs/Downloads:
DOI: In Vitro-In Vivo Extrapolation of Thyroid-Related Endpoints with Higher Throughput Pregnancy PBPK Modeling
QSP_SUMMIT_2024_TRUONG.PDF (PDF, NA pp, 1884.666 KB, about PDF)