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Updated: Apr 27, 2026

An R-Based Landscape Validation of a Competing Risk Model
Published on: September 16, 2022
Quantifying the probability of clinical trial success from scientific articles
Vineet Joshi1, Francesca Milletti1
1Roche Innovation Center New York, Pharma Research and Early Development Informatics, East 29th Street, New York, NY 10016, USA.
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.
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