The ToxCast Program for Prioritizing Toxicity Testing of Environmental Chemicals

• Published in: Toxicological sciences Vol. 95; no. 1; pp. 5 - 12
• Main Authors: Dix, David J., Houck, Keith A., Martin, Matthew T., Richard, Ann M., Setzer, R. Woodrow, Kavlock, Robert J.
• Format: Journal Article
• Language: English
• Published: United States Oxford University Press 01.01.2007
• Subjects: Animals; bioinformatics; Biomarkers - metabolism; chemoinformatics; Computational Biology; Environmental Pollutants - toxicity; Gene Expression Regulation - drug effects; Genomics; high-throughput screening; Humans; Proteomics; Risk Assessment; Systems Integration; Toxicity Tests - methods; toxicogenomics; Toxicology - methods; United States; United States Environmental Protection Agency; United States; chemoinformatics; toxicogenomics; high-throughput screening; bioinformatics
• ISSN: 1096-6080; 1096-0929
• DOI: 10.1093/toxsci/kfl103

The U.S. Environmental Protection Agency (EPA) is developing methods for utilizing computational chemistry, high-throughput screening (HTS), and various toxicogenomic technologies to predict potential for toxicity and prioritize limited testing resources toward chemicals that likely represent the greatest hazard to human health and the environment. This chemical prioritization research program, entitled “ToxCast,” is being initiated with the purpose of developing the ability to forecast toxicity based on bioactivity profiling. The proof-of-concept phase of ToxCast will focus upon chemicals with an existing, rich toxicological database in order to provide an interpretive context for the ToxCast data. This set of several hundred reference chemicals will represent numerous structural classes and phenotypic outcomes, including tumorigens, developmental and reproductive toxicants, neurotoxicants, and immunotoxicants. The ToxCast program will evaluate chemical properties and bioactivity profiles across a broad spectrum of data domains: physical-chemical, predicted biological activities based on existing structure-activity models, biochemical properties based on HTS assays, cell-based phenotypic assays, and genomic and metabolomic analyses of cells. These data will be generated through a series of external contracts, along with collaborations across EPA, with the National Toxicology Program, and with the National Institutes of Health Chemical Genomics Center. The resulting multidimensional data set provides an informatics challenge requiring appropriate computational methods for integrating various chemical, biological, and toxicological data into profiles and models predicting toxicity.