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Using transcriptomics to guide lead optimization in drug discovery projects : lessons learned from the QSTAR project

(2015) DRUG DISCOVERY TODAY. 20(5). p.505-513
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Bioinformatics: from nucleotids to networks (N2N)
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.
Keywords
GENE-EXPRESSION SIGNATURES, RECEPTOR, TRIGLYCERIDE TRANSFER PROTEIN, TYROSINE KINASE INHIBITORS, EPIDERMAL-GROWTH-FACTOR, IN-VITRO, CANCER, MICROARRAY DATA, CHOLESTEROL, SUPPORT

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Citation

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Chicago
Verbist, Bie, Günter Klambauer, Liesbet Vervoort, Willem Talloen, Ziv Shkedy, Olivier Thas, Andreas Bender, et al. 2015. “Using Transcriptomics to Guide Lead Optimization in Drug Discovery Projects : Lessons Learned from the QSTAR Project.” Drug Discovery Today 20 (5): 505–513.
APA
Verbist, Bie, Klambauer, G., Vervoort, L., Talloen, W., Shkedy, Z., Thas, O., Bender, A., et al. (2015). Using transcriptomics to guide lead optimization in drug discovery projects : lessons learned from the QSTAR project. DRUG DISCOVERY TODAY, 20(5), 505–513.
Vancouver
1.
Verbist B, Klambauer G, Vervoort L, Talloen W, Shkedy Z, Thas O, et al. Using transcriptomics to guide lead optimization in drug discovery projects : lessons learned from the QSTAR project. DRUG DISCOVERY TODAY. 2015;20(5):505–13.
MLA
Verbist, Bie, Günter Klambauer, Liesbet Vervoort, et al. “Using Transcriptomics to Guide Lead Optimization in Drug Discovery Projects : Lessons Learned from the QSTAR Project.” DRUG DISCOVERY TODAY 20.5 (2015): 505–513. Print.
@article{5814401,
  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.},
  author       = {Verbist, Bie and Klambauer, G{\"u}nter and Vervoort, Liesbet and Talloen, Willem and Shkedy, Ziv and Thas, Olivier and Bender, Andreas and G{\"o}hlmann, Hinrich WH and Hochreiter, Sepp and QSTAR Consortium, the and Clement, Lieven},
  issn         = {1359-6446},
  journal      = {DRUG DISCOVERY TODAY},
  keyword      = {GENE-EXPRESSION SIGNATURES,RECEPTOR,TRIGLYCERIDE TRANSFER PROTEIN,TYROSINE KINASE INHIBITORS,EPIDERMAL-GROWTH-FACTOR,IN-VITRO,CANCER,MICROARRAY DATA,CHOLESTEROL,SUPPORT},
  language     = {eng},
  number       = {5},
  pages        = {505--513},
  title        = {Using transcriptomics to guide lead optimization in drug discovery projects : lessons learned from the QSTAR project},
  url          = {http://dx.doi.org/10.1016/j.drudis.2014.12.014},
  volume       = {20},
  year         = {2015},
}

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