on the Critical Path Opportunities List calls for “modernizing predictive toxicology,” described as follows:
Identifying preclinical biomarkers that predict human liver or kidney toxicity would speed innovation for many different types of therapeutics. Activities to develop genomic biomarkers for the mechanistic interpretation of toxicological observations—complementary to but independent of these classic toxicological observations—could begin to create the data foundation for qualification of new safety biomarkers. Collaborations among sponsors to share what is known about existing safety assays could be a first step toward the goal of safer medical products. (FDA, 2006:9)
Halbert explained that the fundamental underlying principle of toxicogenomics is that compounds with similar mechanisms of toxicity and efficacy will have similar gene expression profiles. Thus information about how various compounds affect gene expression—in the context of other knowledge about those compounds—can lead to a better understanding of both the compounds’ mechanisms of action and their toxicity. One of the goals of toxicogenomics is to identify biomarkers—generally sets of genes or RNA—from data collected on known drugs and toxicants, and use these biomarkers to predict mechanisms of action or toxicity in new compounds.
To be effective, toxicogenomics requires the collection and analysis of large amounts of data. These data must be highly diverse, in terms of not only the types of drugs and compounds that should be represented in the database, but also the types of data collected. For example, gene expression data should be collected in addition to traditional toxicology end points such as clinical chemistry and histopathology. The data should be organized in a well-curated database, and their interpretation requires novel methods of analyzing patterns and predicting outcomes.
Toxicogenomics is currently being used in a variety of ways in drug discovery and development. It is being applied
to rescue at-risk programs at the preclinical or early clinical stages by gaining additional insight into a compound’s mechanism of action and how it is causing toxicity;
to screen and evaluate leads at different stages proactively by predicting toxicities and mechanisms of action so that candidate compounds can be eliminated from the development pipeline as early as possible; and
to develop preclinical biomarkers of drug response and toxicity.
Toxicogenomics offers a number of advantages. Gene expression can be predictive and can be more sensitive than traditional approaches. It