You are here:
Evaluating Rapid Models for High-Throughput Exposure Forecasting (SOT)
Citation:
Wambaugh, J. Evaluating Rapid Models for High-Throughput Exposure Forecasting (SOT). Presented at Society of Toxicology Annual Meeting, San Diego, CA, March 22 - 26, 2015. https://doi.org/10.23645/epacomptox.5082769
Impact/Purpose:
This presentation is part of a Symposium/Workshop at the Society of Toxicology Annual meeting in San Diego and will be presented on March 26, 2015. The session is entitled "Exposure Assessment in the 21st Century: Needs and Challenges Facing High-Throughput Exposure Modeling."
Description:
High throughput exposure screening models can provide quantitative predictions for thousands of chemicals; however these predictions must be systematically evaluated for predictive ability. Without the capability to make quantitative, albeit uncertain, forecasts of exposure, the putative risk due to an arbitrary chemical cannot be rapidly evaluated. We use a statistical evaluation framework to evaluate and calibrate predictive models with exposures inferred from monitoring. This evaluation framework provides three important results 1) the calibrations to exposure data assess the predictive ability of the available models, 2) the scatter of the exposure data about the calibrated predictions is an empirical measure of uncertainty, and 3) the calibration and uncertainty can be extrapolated from limited sets of monitoring data (100s of chemicals) to the much larger (1000s) chemical sets with no monitoring data. For 7968 chemicals tested by the U.S. Federal Government Tox21 consortium, we have made exposure forecasts using use information compiled from multiple databases and production volume. A reverse pharmacokinetic model was used to infer multiple chemical exposure combinations that would be consistent with biomarkers measured in urine samples and reported by the Centers for Disease Control (CDC) National Health and Nutrition Examination Survey (NHANES). For thousands of chemicals with no other source of exposure information, these methods predict human exposure for various demographic groups surveyed by NHANES, including women of child-bearing age and children aged 6-11. This abstract does not necessarily reflect U.S. EPA policy.
