title: Using transcriptomics to guide lead optimization in drug discovery projects: Lessons learned from the QSTAR project.
abstract: The pharmaceutical industry is faced with steadily declining R&D efficiency which results in fewer drugs reaching the market despite increased investment. A major cause for this low efficiency is the failure of drug candidates in late-stage development owing to safety issues or previously undiscovered side-effects. We analyzed to what extent gene expression data can help to de-risk drug development in early phases by detecting the biological effects of compounds across disease areas, targets and scaffolds. For eight drug discovery projects within a global pharmaceutical company, gene expression data were informative and able to support go/no-go decisions. Our studies show that gene expression profiling can detect adverse effects of compounds, and is a valuable tool in early-stage drug discovery decision making.
authors.affiliation: Department of Mathematical Modeling, Statistics and Bioinformatics, Ghent University, Coupure Links 653, B-9000 Gent, Belgium.
authors.forename: Bie
authors.initials: B
authors.lastname: Verbist
authors.affiliation: Institute of Bioinformatics, Johannes Kepler University, Linz, Austria.
authors.forename: Günter
authors.initials: G
authors.lastname: Klambauer
authors.affiliation: Johnson & Johnson Pharmaceutical Research & Development, Division of Janssen Pharmaceutica, Beerse, Belgium.
authors.forename: Liesbet
authors.initials: L
authors.lastname: Vervoort
authors.affiliation: Johnson & Johnson Pharmaceutical Research & Development, Division of Janssen Pharmaceutica, Beerse, Belgium.
authors.forename: Willem
authors.initials: W
authors.lastname: Talloen
authors.affiliation: Institute for Biostatistics and Statistical Bioinformatics, Hasselt University, Hasselt, Belgium.
authors.forename: Ziv
authors.initials: Z
authors.lastname: Shkedy
authors.affiliation: Department of Mathematical Modeling, Statistics and Bioinformatics, Ghent University, Coupure Links 653, B-9000 Gent, Belgium.
authors.forename: Olivier
authors.initials: O
authors.lastname: Thas
authors.affiliation: Centre for Molecular Science Informatics, Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge CB2 1EW, UK.
authors.forename: Andreas
authors.initials: A
authors.lastname: Bender
authors.affiliation: Johnson & Johnson Pharmaceutical Research & Development, Division of Janssen Pharmaceutica, Beerse, Belgium.
authors.forename: Hinrich W H
authors.initials: HW
authors.lastname: Göhlmann
authors.affiliation: Institute of Bioinformatics, Johannes Kepler University, Linz, Austria. Electronic address: hochreit@bioinf.jku.at.
authors.forename: Sepp
authors.initials: S
authors.lastname: Hochreiter
mesh_terms: D000818:Animals; D030541:Databases, Genetic; D003661:Decision Support Techniques; D017277:Drug Approval; D055808:Drug Discovery / Q000379:methods*; D064420:Drug-Related Side Effects and Adverse Reactions / Q000235:genetics*; D020869:Gene Expression Profiling; D005786:Gene Expression Regulation / Q000187:drug effects; D006801:Humans; D015394:Molecular Structure; D015397:Program Evaluation; D021281:Quantitative Structure-Activity Relationship; D018570:Risk Assessment; D014158:Transcription, Genetic / Q000187:drug effects*