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Computational Toxicology Research

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EPA evaluates the potential risks of the manufacture and use of thousands of chemicals. To assist with this evaluation, EPA scientists developed a rapid, automated (high-throughput) model using off the shelf technology that predicts exposures for thousands of chemicals. These predictions are being used to prioritize the order in which chemicals should be evaluated further. EPA refers to this research effort as ExpoCast.

EPA Research Action

ExpoCast incorporated a new concept in exposure estimations, rapid and cost efficient high throughput exposure prioritization. As a proof of concept, ExpoCast evaluated 1,763 chemicals using off-the-shelf models for estimating exposure due to industrial environmental releases (USEtox and RAIDAR) and a simple indicator of consumer product use. New models are being evaluated to refine predictions and include new routes of exposure.

Results and Impact

This research demonstrated that the ExpoCast approach can be used to make high throughput exposure predictions for human exposures to chemicals and to understand where additional information is required to improve these estimates. Currently, ExpoCast predicts the contribution from environmental release to overall exposure rapidly and efficiently. However, more research is needed to improve predictions for exposures resulting from indoor and consumer use since both are large determinants of exposure. Combining ExpoCast exposure predictions with the hazard predictions from ToxCast provides the capability to develop rapid risk-based prioritization for chemicals. This prioritization will identify those chemicals most in need of additional testing to adequately assess their potential risks.

EPA scientists will continue to research how to develop high throughput models for exposure from consumer use and indoor environment. This research will progress quickly as more and more consumer use data becomes available.

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