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.
| Original language | English |
|---|---|
| Pages (from-to) | 505-513 |
| Number of pages | 9 |
| Journal | Drug Discovery Today |
| Volume | 20 |
| Issue number | 5 |
| DOIs | |
| Publication status | Published - 2015 |
Fields of science
- 303 Health Sciences
- 304 Medical Biotechnology
- 304003 Genetic engineering
- 305 Other Human Medicine, Health Sciences
- 101004 Biomathematics
- 101018 Statistics
- 102 Computer Sciences
- 102001 Artificial intelligence
- 102004 Bioinformatics
- 102010 Database systems
- 102015 Information systems
- 102019 Machine learning
- 106023 Molecular biology
- 106002 Biochemistry
- 106005 Bioinformatics
- 106007 Biostatistics
- 106041 Structural biology
- 301 Medical-Theoretical Sciences, Pharmacy
- 302 Clinical Medicine
JKU Focus areas
- Computation in Informatics and Mathematics
- Nano-, Bio- and Polymer-Systems: From Structure to Function
- Medical Sciences (in general)
- Health System Research
- Clinical Research on Aging
