Toxicology Data Curation, Integration and Analysis for ToxCast Datasets

Matthew Martin, Richard Judson, and David Dix, US EPA, USA

The EPA ToxCast research program uses a high-throughput screening (HTS) approach for predicting the toxicity of large numbers of chemicals. Phase-I tested 309 well-characterized chemicals (mostly pesticides) in over 500 assays of different molecular targets, cellular responses and cell-states. Phase-II is testing another roughly 700 chemicals and, in addition to the original assay set, will be testing the full chemical library in new assay technologies. In coordination with ToxCast, a large scale toxicology data curation project has provided the key reference toxicity information for predictive modeling exercises in a relational database called ToxRefDB. As part of the data curation process, standardized vocabularies have been developed across systemic, cancer, developmental, and reproductive studies ensuring data comparability across studies. As an example of the entire analysis process, including in vivo data curation, in vitro data workflow and analysis, and integrated modeling approaches, a predictive model of reproductive toxicity is presented. The resulting model is capable of externally predicting rodent reproductive toxicity, as observed in rat multigeneration toxicity tests, with over 75% accuracy. This abstract does not necessarily reflect U.S. EPA policy.