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

作者：Verbist Bie^*; Klambauer Guenter; Vervoort Lie**et; Talloen Willem; Shkedy Ziv; Thas Olivier; Bender Andreas; Goehlmann Hinrich W H; Hochreiter Sepp

来源：Drug Discovery Today, 2015, 20(5): 505-513.

DOI：10.1016/j.drudis.2014.12.014

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.

• 出版日期2015-5