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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/18723

Title: Using transcriptomics to guide lead optimization in drug discovery projects: Lessons learned from the QSTAR project
Authors: Verbist, Bie
Klambauer, Günter
Vervoort, Liesbet
Thas, Olivier
Bender, Andreas
Göhlmann, Hinrich W. H.
Hochreiter, Sepp
Issue Date: 2015
Citation: DRUG DISCOVERY TODAY, 20 (5), p. 505-513.
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.
Notes: 1 Department of Mathematical Modeling, Statistics and Bioinformatics, Ghent University, Coupure Links 653, B-9000 Gent, Belgium 2 Institute of Bioinformatics, Johannes Kepler University, Linz, Austria 3 Johnson & Johnson Pharmaceutical Research & Development, Division of Janssen Pharmaceutica, Beerse, Belgium 4 Institute for Biostatistics and Statistical Bioinformatics, Hasselt University, Hasselt, Belgium 5 Unilever Centre for Molecular Science Informatics, Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge CB2 1EW, United Kingdom 6 Wolfson Research Institute, Durham University, Durham, UK 7 OpenAnalytics, Jupiterstraat 20, 2600 Antwerp, Belgium 8 Department of Biostatistics and Computational Biology, University of Rochester, Rochester, NY 14611, United States of America 9 CMAST, Eikenlaan11, 9150 Bazel, Belgium
URI: http://hdl.handle.net/1942/18723
DOI: 10.1016/j.drudis.2014.12.014
ISI #: 000355714600003
ISSN: 1359-6446
Category: A1
Type: Journal Contribution
Validation: ecoom, 2016
Appears in Collections: Research publications

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