Data Mining at U.S. Food and Drug Administration (FDA)
This article summarizes past and current data mining activities at FDA. We address data miners in all sectors, anyone interested in the safety of products regulated by FDA (predominantly medical products, food, veterinary products and nutrition, and tobacco products), and those interested in FDA activities. Topics include routine and developmental data mining activities, short descriptions of the mined FDA data, advantages and challenges of data mining at FDA, and future directions of data mining at FDA
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Authors: Hesha J. Duggirala, Joseph M. Tonning, Ella Smith, Roselie A. Bright, John D. Baker, Robert Ball, Carlos Bell, Khaled Bouri, Susan J. Bright-Ponte, Taxiarchis Botsis, Ma rc Boyer, Keith Burkhart, G. Steven Condrey, James J. Chen, Stuart Chirtel, Ross W. Filice, Henry Francis, Hongying Jiang, Jonathan Levine, David Martin, Taiye Oladipo, Rene O’ Neill, Lee Anne M. Palmer, Antonio Paredes, George Rochester, Deborah Sholtes, Hui- Lee Wong, Zhiheng Xu, Ana Szarfman, Taha Kass -Hout
Publication year:
2015
Language: English (EN)
Level of knowledge: Intermediate: able to
Usage rights: Attribution + ShareAlike - CC-BY-SA
Unless otherwise stated, all materials created by the FOSTER consortium are licensed under a CREATIVE COMMONS
ATTRIBUTION 4.0 INTERNATIONAL LICENSE.
This project has received funding from the European Union’s Seventh Framework Programme for research,
technological development and demonstration under grant agreement no 612425.