In silico prediction of novel therapeutic targets using gene–disease association data

BACKGROUND: Target identification and validation is a pressing challenge in the pharmaceutical industry, with many of the programmes that fail for efficacy reasons showing poor association between the drug target and the disease. Computational prediction of successful targets could have a considerable impact on attrition rates in the drug discovery pipeline by significantly reducing the initial search space. Here, we explore whether gene-disease association data from the Open Targets platform is

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ethics.ai (29 August 2017), “In silico prediction of novel therapeutic targets using gene–disease association data,” evidence record 8229, https://ethics.ai/record/8229 (originally published by OpenAlex).

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