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Pediatrics. 2020 Feb;145(2). pii: e20190562. doi: 10.1542/peds.2019-0562. Epub 2020 Jan 14.

Big Data in the Assessment of Pediatric Medication Safety.

Author information

1
Office of Pediatric Therapeutics, US Food and Drug Administration, Rockville, Maryland; afunkhou2001@yahoo.com.
2
Departments of Pediatrics and Health Policy, Vanderbilt University Medical Center, Nashville, Tennessee.
3
Population Medicine, Harvard Medical School and Harvard Pilgrim Healthcare Insititute, Boston, Massachusetts.
4
Division of Translational Therapeutics, Department of Pediatrics, Faculty of Medicine, University of British Columbia, Vancouver, Canada.
5
Paulson School of Engineering and Applied Sciences, Harvard University, Boston, Massachusetts.
6
Departments of Biomedical Informatics, Pediatrics, and.
7
Divisions of Pediatric Infectious Diseases and Clinical Parmacology, Department of Pediatrics, and.
8
Departments of Biomedical Informatics, Pediatrics, and Emergency Medicine, School of Medicine, Emory University, Atlanta, Georgia.
9
Office of Vaccines and Blood Products and.
10
Office of New Drug IV, Pharmaceuticals and Medical Devices Agency, Tokyo, Japan.
11
Department of Epidemiology, Julius Center Research Program Cardiovascular Edpidemiology, Utrecht University Medical Center, Utrecht, Netherlands.
12
Institute of Translational Medicine, University of Liverpool, Liverpool, United Kingdom; and.
13
Division of Cardiology, Department of Internal Medicine, School of Medicine, Center for Health Science, Duke Clinical Research Institute, Duke University, Durham, North Carolina.

Abstract

Big data (BD) in pediatric medication safety research provides many opportunities to improve the safety and health of children. The number of pediatric medication and device trials has increased in part because of the past 20 years of US legislation requiring and incentivizing study of the effects of medical products in children (Food and Drug Administration Modernization Act of 1997, Pediatric Rule in 1998, Best Pharmaceuticals for Children Act of 2002, and Pediatric Research Equity Act of 2003). There are some limitations of traditional approaches to studying medication safety in children. Randomized clinical trials within the regulatory context may not enroll patients who are representative of the general pediatric population, provide the power to detect rare safety signals, or provide long-term safety data. BD sources may have these capabilities. In recent years, medical records have become digitized, and cell phones and personal devices have proliferated. In this process, the field of biomedical science has progressively used BD from those records coupled with other data sources, both digital and traditional. Additionally, large distributed databases that include pediatric-specific outcome variables are available. A workshop entitled "Advancing the Development of Pediatric Therapeutics: Application of 'Big Data' to Pediatric Safety Studies" held September 18 to 19, 2017, in Silver Spring, Maryland, formed the basis of many of the ideas outlined in this article, which are intended to identify key examples, critical issues, and future directions in this early phase of an anticipated dramatic change in the availability and use of BD.

PMID:
31937606
DOI:
10.1542/peds.2019-0562

Conflict of interest statement

POTENTIAL CONFLICT OF INTEREST: The authors have indicated they have no potential conflicts of interest to disclose.

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