期刊
DRUG DISCOVERY TODAY
卷 21, 期 11, 页码 1740-1744出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.drudis.2016.07.008
关键词
-
资金
- Roche
The development of cancer drugs is time-consuming and expensive. In particular, failures in late-stage clinical trials are a major cost driver for pharmaceutical companies. This puts a high demand on methods that provide insights into the success chances of new potential medicines. In this study, we systematically analyze publication patterns emerging along the drug discovery process of targeted cancer therapies, starting from basic research to drug approval - or failure. We find clear differences in the patterns of approved drugs compared with those that failed in Phase Feeding these features into a machine learning classifier allows us to predict the approval or failure of a targeted cancer drug significantly better than educated guessing. We believe that these findings could lead to novel measures for supporting decision making in drug development.
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