Use of data mining at the food and drug administration

Hesha J. Duggirala; Joseph M. Tonning; Ella Smith; Roselie A. Bright; John D. Baker; Robert Ball; Carlos Bell; Susan J. Bright-Ponte; Taxiarchis Botsis; Khaled Bouri; Marc 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; Ana Szarfman; Hui Lee Wong; Zhiheng Xu; Taha Kass-Hout

doi:10.1093/jamia/ocv063

Use of data mining at the food and drug administration

Hesha J. Duggirala, Joseph M. Tonning, Ella Smith, Roselie A. Bright, John D. Baker, Robert Ball, Carlos Bell, Susan J. Bright-Ponte, Taxiarchis Botsis, Khaled Bouri, Marc Boyer, Keith Burkhart, G. Steven Condrey, James J. Chen, Stuart Chirtel, Ross W. Filice, Henry Francis, Hongying Jiang, Jonathan Levine, David MartinTaiye Oladipo, Rene O'Neill, Lee Anne M. Palmer, Antonio Paredes, George Rochester, Deborah Sholtes, Ana Szarfman, Hui Lee Wong, Zhiheng Xu, Taha Kass-Hout

Research output: Contribution to journal › Article › peer-review

46 Scopus citations

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.

Original language	English (US)
Pages (from-to)	428-434
Number of pages	7
Journal	Journal of the American Medical Informatics Association
Volume	23
Issue number	2
DOIs	https://doi.org/10.1093/jamia/ocv063
State	Published - Mar 1 2016
Externally published	Yes

Keywords

Data mining
Disproportionality analysis
Pharmacovigilance

ASJC Scopus subject areas

Health Informatics

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10.1093/jamia/ocv063

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Duggirala, H. J., Tonning, J. M., Smith, E., Bright, R. A., Baker, J. D., Ball, R., Bell, C., Bright-Ponte, S. J., Botsis, T., Bouri, K., Boyer, M., Burkhart, K., Steven Condrey, G., Chen, J. J., Chirtel, S., Filice, R. W., Francis, H., Jiang, H., Levine, J., ... Kass-Hout, T. (2016). Use of data mining at the food and drug administration. Journal of the American Medical Informatics Association, 23(2), 428-434. https://doi.org/10.1093/jamia/ocv063

Duggirala, HJ, Tonning, JM, Smith, E, Bright, RA, Baker, JD, Ball, R, Bell, C, Bright-Ponte, SJ, Botsis, T, Bouri, K, Boyer, M, Burkhart, K, Steven Condrey, G, Chen, JJ, Chirtel, S, Filice, RW, Francis, H, Jiang, H, Levine, J, Martin, D, Oladipo, T, O'Neill, R, Palmer, LAM, Paredes, A, Rochester, G, Sholtes, D, Szarfman, A, Wong, HL, Xu, Z & Kass-Hout, T 2016, 'Use of data mining at the food and drug administration', Journal of the American Medical Informatics Association, vol. 23, no. 2, pp. 428-434. https://doi.org/10.1093/jamia/ocv063

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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.",

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AU - Duggirala, Hesha J.

AU - Tonning, Joseph M.

AU - Smith, Ella

AU - Bright, Roselie A.

AU - Baker, John D.

AU - Ball, Robert

AU - Bell, Carlos

AU - Bright-Ponte, Susan J.

AU - Botsis, Taxiarchis

AU - Bouri, Khaled

AU - Boyer, Marc

AU - Burkhart, Keith

AU - Steven Condrey, G.

AU - Chen, James J.

AU - Chirtel, Stuart

AU - Filice, Ross W.

AU - Francis, Henry

AU - Jiang, Hongying

AU - Levine, Jonathan

AU - Martin, David

AU - Oladipo, Taiye

AU - O'Neill, Rene

AU - Palmer, Lee Anne M.

AU - Paredes, Antonio

AU - Rochester, George

AU - Sholtes, Deborah

AU - Szarfman, Ana

AU - Wong, Hui Lee

AU - Xu, Zhiheng

AU - Kass-Hout, Taha

PY - 2016/3/1

Y1 - 2016/3/1

N2 - 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.

AB - 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.

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KW - Disproportionality analysis

KW - Pharmacovigilance

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Use of data mining at the food and drug administration

Abstract

Keywords

ASJC Scopus subject areas

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