title: Toxicogenomics in the pharmaceutical industry: hollow promises or real benefit?
abstract: Almost 10 years ago, microarray technology was established as a new powerful tool for large-scale analysis of gene expression. Soon thereafter the new technology was discovered by toxicologists for the purpose of deciphering the molecular events underlying toxicity, and the term "Toxicogenomics" appeared in scientific literature. Ever since, the toxicology community was fascinated by the multiplicity of sophisticated possibilities toxicogenomics seems to offer: genome-wide analysis of toxicant-induced expression profiles may provide a means for prediction of toxicity prior to classical toxicological endpoints such as histopathology or clinical chemistry. Some researchers even speculated of the classical methods being superfluous before long. It was assumed that by using toxicogenomics it would be possible to classify compounds early in drug development and consequently save animals, time, and money in pre-clinical toxicity studies. Moreover, it seemed within reach to unravel the molecular mechanisms underlying toxicity. The feasibility of bridging data derived from in vitro and in vivo systems, identifying new biomarkers, and comparing toxicological responses "across-species" was also excessively praised. After several years of intensive application of microarray technology in the field of toxicology, not only by the pharmaceutical industry, it is now time to survey its achievements and to question how many of these wishes and promises have really come true.
authors.affiliation: F. Hoffmann-La Roche Ltd., Non-Clinical Drug Safety, 4070 Basel, Switzerland. anke.luehe@roche.com
authors.forename: Anke
authors.initials: A
authors.lastname: Lühe
authors.forename: Laura
authors.initials: L
authors.lastname: Suter
authors.forename: Stefan
authors.initials: S
authors.lastname: Ruepp
authors.forename: Thomas
authors.initials: T
authors.lastname: Singer
authors.forename: Thomas
authors.initials: T
authors.lastname: Weiser
authors.forename: Silvio
authors.initials: S
authors.lastname: Albertini
mesh_terms: D000818:Animals; D015415:Biomarkers; D016208:Databases, Factual; D015195:Drug Design; D004345:Drug Industry / Q000191:economics / Q000639:trends*; D004347:Drug Interactions; D020869:Gene Expression Profiling; D023281:Genomics; D006801:Humans; D020411:Oligonucleotide Array Sequence Analysis; D013045:Species Specificity; D043922:Toxicogenetics / Q000191:economics / Q000639:trends*
chemical_list: D015415:Biomarkers