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Activity Number: 37 - Statistical Issues Specific the Therapeutic Areas - 1
Type: Contributed
Date/Time: Sunday, July 29, 2018 : 2:00 PM to 3:50 PM
Sponsor: Biopharmaceutical Section
Abstract #329970 Presentation
Title: A Case Study on Model Based Meta-Analysis (MBMA) for Drug Development Decisions
Author(s): Guohui Liu* and Zhaoyang Teng and Zhaowei Hua and Neeraj Gupta and Richard Labotka
Companies: Takeda Pharmaceuticals Inc and Takeda pharmaceuticals international, Co and Takeda Pharmaceuticals International Co. and Takeda pharmaceuticals international, Co and Takeda pharmaceuticals international, Co
Keywords: oncology; meta analysis; bayesian ; decison-making; clinical trial

The discrepancy on endpoints in early development and late development may contribute significantly to high failure rate in oncology pivotal studies. On the other hand, aggregate study reports are available from multiple studies in the same indication in a hypercompetitive market. We developed a model-based meta-analysis (MBMA) framework to quantitatively predict the probability of technical success on time to event endpoint from pivotal studies based on response rate from early studies. Both frequentist approach and Bayesian approach were used to build an objective information decision-making approach by determining the threshold in an early study to achieve a target in a pivotal study. To represent application of the framework, a case study will be presented using data from 7 phase III studies in relapsed/refractory multiple myeloma (RRMM).

Authors who are presenting talks have a * after their name.

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