SESSION H – The Annual Deming Conference on Applied Statistics

TITLE:Statistical Translation of Extrapolation: A Tutorial for Demonstrating Efficacy and Safety of Investigational Medicines in Pediatric Populations
SPEAKERS: James Travis, FDA; Margaret Gamalo, Pfizer Inc; and Jingjing Ye, BeiGene
MODERATOR: Jingjing Ye

Abstract :

Pediatric drug development often faces substantial challenges, including economic, logistical, technical, and ethical barriers, among others. Pediatric drug development lags adult development by about 8 years and often faces infeasibility of trials, resulting in children being a large, underserved population of “therapeutic orphans,” as an estimated 80% of children are treated off-label (Mulugeta et al. in Pediatr Clin 64(6):1185-1196, 2017). Among many efforts to mitigate these feasibility barriers and as an ethical approach to minimizing exposing pediatric patients to the research risks, increased attention has been given to extrapolation; that is, the leveraging of available data from adults or older age groups to draw conclusions for the pediatric population. Recent ICH harmonization on a pediatric extrapolation framework provides a clearer path forward for pediatric drug development programs leveraging some degree of extrapolation despite uncertainties. In this framework, the degree to which extrapolation can be used lies along a continuum representing the uncertainties to be addressed through generation of new pediatric evidence (Gamalo et al. 2021). This tutorial is structured as a combination of pediatric drug development process and statistical methodologies.

Outline of the tutorial:

Part I: Pediatric drug development regulatory history and ICH guidelines, including extrapolation strategy, process, concept, and plan. Regulatory implications and optimize pediatric drug development programs.

Part II: The applicability of Bayesian methodology within the framework of extrapolation and the incorporation of a “validate” approach within process. A discussion on related references is provided, e.g., Gamalo et al. (2017) for a review of Bayesian methods to the extrapolation of adult data to support drug approvals in a pediatric population.

Part III: The extent of development relating to safety and assessment of safety in pediatric patients

Instructors’ Biography:

James Travis is a statistical team leader in the Office of Biostatistics within the Center for Drug Evaluation and Research at the US Food and Drug Administration and leads the team supporting the Division of Pediatric and Maternal Health. James joined the Agency in 2014 following completion of his PhD at the University of Maryland, Baltimore County. He is a representative on the Pediatric Review Committee for the Office of Biostatistics. He has interests in Bayesian methods, particularly the use of informative priors in implementing extrapolation in pediatric clinical trials.

Margaret (Meg) Gamalo, PhD is Head of Statistics –Inflammation and Immunology, Pfizer Innovative Health. She combines expertise in biostatistics, regulatory and adult and pediatric drug development. She recently was a Research Advisor, Global Statistical Sciences at Eli Lilly and Company and prior to that was a Mathematical Statistician at the Food and Drug Administration. Meg leads the Pediatric Innovation Task Force at the Biotechnology Innovation Organization. She also actively contributes to research topics within the European Forum for Good Clinical Practice – Children’s Medicine Working Party. Meg is Editor-in-Chief of the Journal of Biopharmaceutical Statistics and is actively involved in many statistical activities in the American Statistical Association. She received her PhD in Statistics from The University of Pittsburgh and master’s in applied mathematics from the University of the Philippines.

Dr. Jingjing Ye is an executive director and currently leads a global team, Data Science and Operational Excellence (DSOE), with Global Statistics and Data Sciences (GSDS) in BeiGene. She has over 16 years experience in pharmaceutical industry and US FDA, with focus in cancer drug discovery and development. Her statistical and regulatory experience expands full spectrum on patients’ treatment journey from diagnosis, treatment to living with the condition. Before BeiGene, she was most recently a statistics team leader in the Office of Biostatistics in CDER. At CDER, she supervised a team of statistical analysts and reviewers for designing, reviewing and analyzing clinical trials to support drug approvals throughout preIND, IND, NDA/BLA and post-approval studies in oncology and hematology. She was statistical representative within the Oncology Center of Excellence (OCE) Pediatric Review sub-committee, responsible for overseeing all pediatric review operations within the OCE.

She is currently the co-lead on several working groups, including ASA Biopharmaceutical Section (BIOP) Pediatric Working Group (pediatric extrapolation sub-team), ASA BIOP Statistical Considerations in Oncology Pediatric Trials subgroup under ASA BIOP Stats Methods in Oncology working group, and DIA-ASA Master Protocol Patient Engagement Sub-team. She received her PhD degree in statistics from University of California, Davis and B.S. in Applied Mathematics from Peking University in China.