title: Systematic drug repositioning through mining adverse event data in ClinicalTrials.gov.
abstract: Drug repositioning (i.e., drug repurposing) is the process of discovering new uses for marketed drugs. Historically, such discoveries were serendipitous. However, the rapid growth in electronic clinical data and text mining tools makes it feasible to systematically identify drugs with the potential to be repurposed. Described here is a novel method of drug repositioning by mining ClinicalTrials.gov. The text mining tools I2E (Linguamatics) and PolyAnalyst (Megaputer) were utilized. An I2E query extracts "Serious Adverse Events" (SAE) data from randomized trials in ClinicalTrials.gov. Through a statistical algorithm, a PolyAnalyst workflow ranks the drugs where the treatment arm has fewer predefined SAEs than the control arm, indicating that potentially the drug is reducing the level of SAE. Hypotheses could then be generated for the new use of these drugs based on the predefined SAE that is indicative of disease (for example, cancer).
authors.affiliation: Advanced Analytics Hub, Eli Lilly and Company , Indianapolis , IN , United States of America.
authors.forename: Eric Wen
authors.initials: EW
authors.lastname: Su
authors.affiliation: Advanced Analytics Hub, Eli Lilly and Company , Indianapolis , IN , United States of America.
authors.forename: Todd M
authors.initials: TM
authors.lastname: Sanger
keywords: ClinicalTrials.gov; Drug repositioning; Drug repurposing; Indication discovery; Text mining