Advances in In Vitro and In Silico Tools for Toxicokinetic Dose Modeling and Predictive Toxicology (WC10)
Citation:
Wetmore, B. Advances in In Vitro and In Silico Tools for Toxicokinetic Dose Modeling and Predictive Toxicology (WC10). World Congress on Alternatives and Animal Use in the Life Sciences, WA, Seattle, August 20 - 24, 2017.
Impact/Purpose:
This talk will provide an update to an international audience on the state of science being conducted within the EPA’s Office of Research and Development to develop and refine approaches that estimate internal chemical concentrations following a given exposure, known as toxicokinetics. Toxicokinetic approaches hold great potential in their ability to link in vitro activities or toxicities identified during high-throughput screening with a quantitative external exposure metric that could be used in risk-based prioritization. This talk will provide greater visibility to these efforts and update the audience on recent progress in refining these approaches to address specific chemical groups of interest along with strategies to facilitate their adoption to a particular decision context.
Description:
Recent advances in vitro assays, in silico tools, and systems biology approaches provide opportunities for refined mechanistic understanding for chemical safety assessment that will ultimately lead to reduced reliance on animal-based methods. With the U.S. commercial chemical landscape encompassing thousands of chemicals with limited data, safety assessment strategies that reliably predict in vivo systemic exposures and subsequent in vivo effects efficiently are a priority. Quantitative in vitro-in vivo extrapolation (QIVIVE) is a methodology that facilitates the explicit and quantitative application of in vitro experimental data and in silico modeling to predict in vivo system behaviors and can be applied to predict chemical toxicokinetics, toxicodynamics and also population variability. Tiered strategies that incorporate sufficient information to reliably inform the relevant decision context will facilitate acceptance of these alternative data streams for safety assessments. This abstract does not necessarily reflect U.S. EPA policy.
