Use of data mining at the Food and Drug Administration. (23rd July 2015)

• Record Type: Journal Article
• Authors: Duggirala, Hesha J; Tonning, Joseph M; Smith, Ella; Bright, Roselie A; Baker, John D; Ball, Robert; Bell, Carlos; Bright-Ponte, Susan J; Botsis, Taxiarchis; Bouri, Khaled; Boyer, Marc; Burkhart, Keith; Steven Condrey, G; Chen, James J; Chirtel, Stuart; Filice, Ross W; Francis, Henry; Jiang, Hongying; Levine, Jonathan; Martin, David; Oladipo, Taiye; O'Neill, Rene; Palmer, Lee Anne M.; Paredes, Antonio; Rochester, George; Sholtes, Deborah; Szarfman, Ana; Wong, Hui-Lee; Xu, Zhiheng; Kass-Hout, Taha
• Is Part Of: Journal of the American Medical Informatics Association. Volume 23:Number 2(2016:Mar.)
• Page Start: 428
• Page End: 434
• Publication Date: 2015-07-23
• Subjects: data mining -- pharmacovigilance -- disproportionality analysis; Medical informatics -- Periodicals; Information Services -- Periodicals; Medical Informatics -- Periodicals; Médecine -- Informatique -- Périodiques; Informatica; Geneeskunde; Informatique médicale; Computer network resources; Electronic journals; 610.285
• DOI: 10.1093/jamia/ocv063
• Languages: English
• ISSNs: 1067-5027

Abstract

Abstract: Objectives This article summarizes past and current data mining activities at the United States Food and Drug Administration (FDA). Target audience We address data miners in all sectors, anyone interested in the safety of products regulated by the FDA (predominantly medical products, food, veterinary products and nutrition, and tobacco products), and those interested in FDA activities. Scope Topics include routine and developmental data mining activities, short descriptions of mined FDA data, advantages and challenges of data mining at the FDA, and future directions of data mining at the FDA.