title: Deductive genomics: a functional approach to identify innovative drug targets in the post-genome era.
abstract: The sequencing of the human genome has generated a drug discovery process that is based on sequence analysis and hypothesis-driven (inductive) prediction of gene function. This approach, which we term inductive genomics, is currently dominating the efforts of the pharmaceutical industry to identify new drug targets. According to recent studies, this sequence-driven discovery process is paradoxically increasing the average cost of drug development, thus falling short of the promise of the Human Genome Project to simplify the creation of much needed novel therapeutics. In the early stages of discovery, the flurry of new gene sequences makes it difficult to pick and prioritize the most promising product candidates for product development, as with existing technologies important decisions have to be based on circumstantial evidence that does not strongly predict therapeutic potential. This is because the physiological function of a potential target cannot be predicted by gene sequence analysis and in vitro technologies alone. In contrast, deductive genomics, or large-scale forward genetics, bridges the gap between sequence and function by providing a function-driven in vivo screen of a highly orthologous mammalian model genome for medically relevant physiological functions and drug targets. This approach allows drug discovery to move beyond the focus on sequence-driven identification of new members of classical drug-able protein families towards the biology-driven identification of innovative targets and biological pathways.
authors.affiliation: Ingenium Pharmaceuticals AG, Martinsried, Germany. gabriele.stumm@ingenium-ag.com
authors.forename: Gabriele
authors.initials: G
authors.lastname: Stumm
authors.forename: Andreas
authors.initials: A
authors.lastname: Russ
authors.forename: Michael
authors.initials: M
authors.lastname: Nehls
mesh_terms: D000818:Animals; D016503:Drug Delivery Systems / Q000379:methods* / Q000639:trends; D016678:Genome; D015894:Genome, Human; D023281:Genomics / Q000379:methods* / Q000639:trends; D006801:Humans