Core Computational Toxicology Research

Computational toxicology is the integration of modern computing and information technology with molecular biology and chemistry to improve EPA's prioritization of data requirements and risk assessments for toxic chemicals. The goal of EPA's research program on computational toxicology is to better understand the relationships between sources of environmental pollutant exposure and adverse outcomes.

As a result of this new research initiative, research has begun on the "Linkage of Exposure and Effects Using Genomics, Proteomics, and Metabonomics in Small Fish Models". This three phase approach incorporates a combination of whole organism endpoints, genomic, proteomic, and metabonomic approaches, and computational modeling to:

• identify new molecular biomarkers of exposure to endocrine disrupting compounds (EDCs) representing several modes/mechanisms of action (MOA)
• link those biomarkers to effects that are relevant for both diagnostic and predictive risk assessments using small fish models (fathead minnow and zebrafish).

Related Link: EPA's Computational Toxicology Research Program

This research will assist in prediction of environmental transformation and chemical effects based on structural characteristics, and enhance quantitative risk assessments, including areas of uncertainty such as a basis for extrapolation of effects of endocrine disrupting chemicals, interspecies extrapolation, complex chemical mixtures and dose-response assessment.

2005 Computational Toxicology Workshop