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Cited by 318Pharmaceutical studies and practicesStatistical Methods in Clinical TrialsPharmaceutical Economics and Policy

Extrapolation of Adult Data and Other Data in Pediatric Drug-Development Programs

Dunne, Julia, Rodriguez, William J., Murphy, M. Dianne, Beasley, B. Nhi, Burckart, Gilbert J., Filie, Jane D., Lewis, Linda L., Sachs, Hari C. +3 more·2011·Pediatrics
DOI 10.1542/peds.2010-3487
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Abstract

OBJECTIVES: In 1994, the US Food and Drug Administration (FDA) proposed an approach, based on extrapolation of efficacy findings from adults to the pediatric population, to maximize the use of adult data and other data when designing pediatric drug-development programs. We examined the experience of the FDA in using extrapolation to evaluate how and when it was used and any changes in scientific assumptions over time. METHODS: We reviewed 370 pediatric studies submitted to the FDA between 1998 and 2008 in response to 159 written requests (166 products) issued under the Pediatric Exclusivity Provision. We identified cases in which efficacy was extrapolated from adult data or other data, we categorized the type of pediatric data required to support extrapolation, and we determined whether the data resulted in new pediatric labeling. RESULTS: Extrapolation of efficacy from adult data occurred for 82.5% of the drug products (137 of 166). Extrapolation was defined as complete for 14.5% of the products (24 of 166) and partial for 68% of them (113 of 166). Approaches to extrapolation changed over time for 19% of the therapeutic indications studied (13 of 67). When extrapolation was used, 61% of the drug products (84 of 137) obtained a new pediatric indication or extension into a new age group; this number decreased to 34% (10 of 29) when there was no extrapolation. CONCLUSIONS: Extrapolating efficacy from adult data or other data to the pediatric population can streamline pediatric drug development and help to increase the number of approvals for pediatric use.

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Crossref · 10.1542/peds.2010-3487

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  • Historical FDA regulatory decisions have been interpreted and applied in categorical terms (full, partial, none).

    “historical FDA regulatory decisions have, in practice, been interpreted and applied in categorical terms: sponsors often receive labeling feedback that effectively falls into coarse bins such as full , partial , or none in terms of extrapolation acceptability. [9].”

    From PED-X-Bench: A Benchmark of Adult-to-Pediatric Extrapolation Decisions in FDA Drug Labels (2025) · cites this paper as [9]

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Authors
Dunne, J., Rodriguez, W. J., Murphy, M. D., Beasley, B. N., Burckart, G. J., Filie, J. D., Lewis, L. L., Sachs, H. C., Sheridan, P. H., Starke, P., & Yao, L. P.
Affiliations
  • Office of Pediatric Therapeutics, Office of the Commissioner,
  • Divisions of Cardiorenal Products,
  • United States Food and Drug Administration (US)
  • Anesthesia, Analgesia, and Rheumatology Products,
  • Sarepta Therapeutics (United States) (US)
  • Pediatric and Maternal Health Staff,
  • Neurology Products,
  • Pulmonary and Allergy Associates (US)
  • Gastroenterology Products, and
Corresponding author
Dunne, Julia
ORCID
Venue
Pediatrics
Publisher
American Academy of Pediatrics (AAP)
Published
2011-11-01
Volume
128
Issue
5
Pages
e1242-e1249
ISSN
  • 0031-4005 (ISSN-L)
  • 1098-4275
DOI
10.1542/peds.2010-3487
OpenAlex
W2123246083
Cited by
318
References
10
Citations by year
2026: 7 · 2025: 14 · 2024: 20 · 2023: 16 · 2022: 30 · 2021: 26 · 2020: 27 · 2019: 36 · 2018: 31 · 2017: 30 · 2016: 25 · 2015: 22 · 2014: 14 · 2013: 15 · 2012: 5
FWCI
10.04
Type
journal article
Language
en
Open access
closed
Locations
  • PEDIATRICS (publishedVersion)
  • PubMed (publishedVersion)
Topics
  • Health Sciences › Medicine › Pediatrics, Perinatology and Child Health › Pharmaceutical studies and practices
  • Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
  • Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Pharmaceutical Economics and Policy
Keywords
pediatric drug development, FDA regulatory policy
MeSH terms
Adult, Age Factors, Child, Child, Preschool, Data Interpretation, Statistical, Drug Therapy, Pharmaceutical Preparations, Female, Humans, Infant, Male, Pediatrics, Quality Control, Retrospective Studies, United States, United States Food and Drug Administration, Drug Design, Cohort Studies, Program Development, Drug Dosage Calculations, Drug-Related Side Effects and Adverse Reactions

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