The evaluation of chemical alternatives in the context of substitution decisions includes the need to integrate data from multiple disparate data streams across a range of hazard criteria in order to make decisions considering tradeoffs. Such decisions rely on specialized knowledge regarding the various data domains and reflect user priorities concerning specific hazard criteria. The Toxicological Prioritization Index (ToxPiTM) was developed as a visualization tool to support this challenging data environment. The tool was designed to enable the consideration of multiple sources of evidence (e.g., exposure, hazard, social determinations of health), and transformed into transparent rankings to facilitate decision making and stakeholder communication efforts.
Join us for the first webinar organized by SETAC's new Interest Group, the Advancement and Application of Alternatives Assessment (SETAC A4 IG), and learn more about the functionality and utility of ToxPi to support evaluations of alternatives and substitution decisions. The webinar will feature David Reif, one of the original developers of ToxPi and current Chief of the Predictive Toxicology Branch in the Division of Translational Toxicology at the National Institute of Environmental Health Sciences (NIEHS). Reif will provide an overview of ToxPi, then explore its utility with a substitution case example. He will also describe recent functionality upgrades, plus forthcoming updates including AI-assisted modeling that will be launched later this year.
Chief of the Predictive Toxicology Branch, National Institute of Environmental Health Sciences
Chief of the Predictive Toxicology Branch, National Institute of Environmental Health Sciences
David M. Reif, Ph.D., has been Chief of the Predictive Toxicology Branch in the Division of Translational Toxicology at the National Institute of Environmental Health Sciences (NIEHS). In this role, he leverages expertise of the branch in artificial intelligence and machine learning, data science, toxicogenomics, spatiotemporal exposures and toxicology, computational methods development and new approach methods to advance predictive toxicology applications with partners across NIEHS, the interagency Tox21 Program and the Interagency Coordinating Committee on the Validation of Alternative Methods.
Prior to joining NIEHS in 2022, Reif was a professor of bioinformatics at North Carolina State University, in the Department of Biological Sciences. He has also served as a principal investigator with the U.S. EPA's National Center for Computational Toxicology and has been been recognized with several honors, including the Presidential Early Career Award for Scientists and Engineers, awarded by The White House as the highest honor bestowed by the United States government on science and engineering professionals in the early stages of their independent research careers.