BACKGROUND: "Complete Extrapolation" of efficacy from adult or other pediatric data, to the pediatric population, is an important scientific tool that reduces the need for pediatric efficacy trials. Dose finding and safety studies in pediatrics are still needed. "No Extrapolation" requires 2 pediatric efficacy trials. "Partial Extrapolation" eliminates the need to conduct 2 pediatric efficacy trials; 1 efficacy or exposure/response study may be sufficient. We examined pediatric extrapolation from 2009 to 2014 evaluating any changes in extrapolation assumptions and the causes for these changes since a prior analysis published in 2011. METHODS: We reviewed all 157 products with 388 pediatric studies submitted to the FDA from 2009 through 2014. We assessed whether efficacy was extrapolated from adult or other pediatric data and categorized extrapolation as Complete, Partial, or No, and identified the reasons for the changes. RESULTS: Partial extrapolation decreased, whereas use of No and Complete extrapolation noticeably increased. Complete, Partial, or No extrapolations changed from 14%, 68%, and 18% in the 2011 study to 34%, 29%, and 37% respectively in the current study. The changes were mostly due to a better understanding of pediatric pathophysiology, why trials have failed, and improved endpoints. CONCLUSIONS: Evolving science and data obtained from clinical trials increases the certainty of extrapolation assumptions and drives decisions to utilize extrapolation. Lessons learned from the conduct of these trials are critical to improving evidence-based medicine. Extrapolation of Efficacy is a powerful scientific tool that streamlines pediatric product development. Increased knowledge and evolving science inform utilization of this tool.
BACKGROUND: "Complete Extrapolation" of efficacy from adult or other pediatric data, to the pediatric population, is an important scientific tool that reduces the need for pediatric efficacy trials. Dose finding and safety studies in pediatrics are still needed. "No Extrapolation" requires 2 pediatric efficacy trials. "Partial Extrapolation" eliminates the need to conduct 2 pediatric efficacy trials; 1 efficacy or exposure/response study may be sufficient. We examined pediatric extrapolation from 2009 to 2014 evaluating any changes in extrapolation assumptions and the causes for these changes since a prior analysis published in 2011. METHODS: We reviewed all 157 products with 388 pediatric studies submitted to the FDA from 2009 through 2014. We assessed whether efficacy was extrapolated from adult or other pediatric data and categorized extrapolation as Complete, Partial, or No, and identified the reasons for the changes. RESULTS: Partial extrapolation decreased, whereas use of No and Complete extrapolation noticeably increased. Complete, Partial, or No extrapolations changed from 14%, 68%, and 18% in the 2011 study to 34%, 29%, and 37% respectively in the current study. The changes were mostly due to a better understanding of pediatric pathophysiology, why trials have failed, and improved endpoints. CONCLUSIONS: Evolving science and data obtained from clinical trials increases the certainty of extrapolation assumptions and drives decisions to utilize extrapolation. Lessons learned from the conduct of these trials are critical to improving evidence-based medicine. Extrapolation of Efficacy is a powerful scientific tool that streamlines pediatric product development. Increased knowledge and evolving science inform utilization of this tool.
Entities:
Keywords:
Drug Development; Extrapolation of Efficacy; Pediatric Efficacy Trial
Authors: Julia Dunne; William J Rodriguez; M Dianne Murphy; B Nhi Beasley; Gilbert J Burckart; Jane D Filie; Linda L Lewis; Hari C Sachs; Philip H Sheridan; Peter Starke; Lynne P Yao Journal: Pediatrics Date: 2011-10-24 Impact factor: 7.124
Authors: Deborah A Elder; Patricia M Herbers; Tammy Weis; Debra Standiford; Jessica G Woo; David A D'Alessio Journal: J Pediatr Date: 2012-01-10 Impact factor: 4.406
Authors: Deborah A Elder; Lindsey N Hornung; Patricia M Herbers; Ron Prigeon; Jessica G Woo; David A D'Alessio Journal: J Pediatr Date: 2014-12-31 Impact factor: 4.406
Authors: Jess T Whitson; John D Roarty; Lingam Vijaya; Alan L Robin; Robert D Gross; Theresa A Landry; Jaime E Dickerson; Sally A Scheib; Haydn Scott; Steven Y Hua; Adrienne M Woodside; Michael V W Bergamini Journal: J AAPOS Date: 2008-03-04 Impact factor: 1.220
Authors: Irin Tanaudommongkon; Shogo John Miyagi; Dionna J Green; Janelle M Burnham; John N van den Anker; Kyunghun Park; Johanna Wu; Susan K McCune; Lynne Yao; Gilbert J Burckart Journal: Clin Pharmacol Ther Date: 2020-06-22 Impact factor: 6.875