New Approach Methodologies for Exposure from EPA’s ExpoCast Project (SACATM Meeting invited talk)

Exposure is a key component of evaluating the risks posed by anthropogenic chemicals. Exposure is the degree or contact between a chemical and human and ecological target populations. EPA's Exposure Forecaster (ExpoCast) project is charged with the development of new datasets and predictive models that provide exposure information for thousands of chemicals to support agency decision-making. ExpoCast datasets enable the development of cheminformatic machine learning models that fill critical gaps for data-poor chemicals and parameterize new mechanistic models for human, ecological, and occupational exposure pathways. These pathway models can be statistically integrated with available monitoring data to produce consensus exposure predictions and estimates of uncertainty. New high-throughput analytical approaches are also being developed that will expand the chemical space monitored in human and ecological media. Finally, new high-throughput toxicokinetic data and models are used to link ExpoCast exposure predictions to in vitro hazard data. These ExpoCast tools, which can be considered New Approach Methodologies for exposure, are suitable for dealing with the thousands of chemicals in commerce with limited sources of chemical exposure information.