Toxicogenomic predictive modeling: Emerging opportunities for more efficient drug discovery and development

Abstract

Drug discovery companies are coming under increasing pressure to prove the long-term safety of their products more precisely, and to provide more data on them. As highlighted by Vioxx, for many drugs, the existence of adverse drug reactions (ADRs) becomes apparent once the compound has been extensively prescribed and a population base of considerable size has been exposed to the therapeutic agent. The ability to make decisions regarding termination of clinical development of a non-viable drug candidate as early as possible will have a large financial impact for a pharmaceutical company. Knowledge regarding the interactions of chemicals, genes, and cell function can improve chemical risk analyses. These efforts will be aided by continued improvement and expansion of predictive toxicology in combination with a range of mutually supportive technologies to develop strategies to facilitate better and more focused decision-making throughout the drug discovery process. Failure to implement such an approach causes companies to withdraw drugs from development or the market. This not only presents human health consequences but also has a negative economic impact on the industry. As such, one of the major challenges in drug discovery is to accurately predict which new drugs will be associated with a significant incidence of ADRs. The ability to produce information on potential toxicity early in the discovery phase will become the basis for judging whether a drug candidate merits further development.