CuraGen Corporation, New Haven, CT, USA

Expression pharmacogenomics applies genome/proteome scale differential expression technologies to both in vivo and in vitro models of drug response to identify candidate markers correlative with and predictive of drug toxicity and efficacy. It is anticipated to streamline drug development by triaging towards lead compounds and clinical candidates that maximize efficacy while minimizing safety risks. As the majority of expression pharmacogenomics will be performed on preclinical therapeutic candidates, compatibility with favored preclinical animal model systems will be essential. This review will address expression pharmacogenomics in the context of those animal model systems commonly used for pharmacokinetic, pharmacodynamic and toxicologic analyses. Specific discussions will cover: (A) relative robustness of genomic and proteomic technology platforms used to generate drug response data in critical model systems; (B) animal handling, treatment and other experimental design optimizations; (C) data analysis strategies for extracting and validating candidate pharmacogenomic markers; and (D) overarching limitations in applying expression pharmacogenomics to animal model systems. The Pharmacogenomics Journal (2001) 1, 48-58.

expression pharmacogenomics; toxicogenomics; animal models; differential expression profiling

DGE, differential gene expression; UTHS, ultra-high-throughput screening; IND, investigational new drug; RYQ-PCR, real-time quantitative polymerase chain reaction; EST, expressed sequence tag; DD, differential display; SAGE, serial analysis of gene expression; RDA, representational difference analysis; TOGA, total gene expression analysis; 2DE, two-dimensional gene electrophoresis; SSRI, selective serotonin uptake inhibitor; ANOVA, analysis of variance; PCA, principle components analysis; GO, gene ontology; SHR, spontaneously hypertensive; WKY, Wistar-Kyoto