title: Quantifying the probability of clinical trial success from scientific articles.
abstract: We sought to analyze how the number and quality of publications predict clinical trial success for a set of gene-disease associations. Limiting the scope of our analysis to genes in the protein kinase family and to oncology indications, we extracted gene-disease relationships from more than 12 million article titles and abstracts published between 1992 and 2012. We integrated these data with clinical trial information for FDA-approved kinase inhibitors and kinase inhibitors that failed owing to lack of efficacy. We found that, up until the year when a compound enters clinical trials, the cumulative number of publications about a gene-disease relationship corresponding to the compound's mechanism of action is, at the median, 30 for approved compounds but only four for failed compounds.
authors: Roche Innovation Center New York, Pharma Research and Early Development Informatics, East 29th Street, New York, NY 10016, USA.
authors: Vineet
authors: V
authors: Joshi
authors: Roche Innovation Center New York, Pharma Research and Early Development Informatics, East 29th Street, New York, NY 10016, USA. Electronic address: francesca.milletti@roche.com.
authors: Francesca
authors: F
authors: Milletti
mesh_terms: D002986:Clinical Trials as Topic / Q000706:statistics & numerical data*; D017277:Drug Approval / Q000706:statistics & numerical data*; D056726:Genetic Association Studies; D006801:Humans; D010506:Periodicals as Topic / Q000706:statistics & numerical data*; D011336:Probability; D039781:PubMed