Drug Repositioning by Mining Adverse Event Data in ClinicalTrials.gov

Eric Wen Su

doi:10.1007/978-1-4939-8955-3_4

Drug Repositioning by Mining Adverse Event Data in ClinicalTrials.gov

Methods Mol Biol. 2019:1903:61-72. doi: 10.1007/978-1-4939-8955-3_4.

Author

Eric Wen Su¹

Affiliation

¹ Advanced Analytics Hub, Eli Lilly and Company, Indianapolis, IN, USA. ewsu@lilly.com.

PMID: 30547436
DOI: 10.1007/978-1-4939-8955-3_4

Abstract

The protocol below describes an in silico method for drug repositioning (drug repurposing). The data source is ClinicalTrials.gov , which contains about a quarter of a million clinical studies. Mining such rich and clean clinical summary data could be helpful to many health-related researches. Described here is a method that utilizes serious adverse event data to identify potential new uses of drugs and dietary supplements (repositioning).

Keywords: Adverse event; ClinicalTrials.gov; Drug repositioning; Drug repurposing; I2E; Indication discovery; PolyAnalyst; Text mining.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Algorithms
Computational Biology* / methods
Data Mining* / methods
Databases, Factual
Drug Repositioning* / methods
Drug-Related Side Effects and Adverse Reactions*
Humans
Software
User-Computer Interface