Online Program Home
  My Program

All Times EDT

Abstract Details

Activity Number: 570 - Addressing the Unique Analytic Challenges of Drug Development in Rare Diseases with the Use of Innovative Designs and Real World Evidence in Clinical Trials
Type: Topic Contributed
Date/Time: Thursday, August 6, 2020 : 3:00 PM to 4:50 PM
Sponsor: ENAR
Abstract #309832
Title: Clinical Data Augmentation Strategy via Propensity-Score-Based Bayesian Analysis
Author(s): Junjing Lin* and Margaret Gamalo-Siebers and Ram Tiwari
Companies: Takeda and Eli Lilly & Co and FDA
Keywords: real world evidence; innovative design; propensity scores; historical control; Bayesian

In rare disease drug development, difficulty in enrollment can make the conduct of randomized controlled trials (RCTs) infeasible because of their size, duration, cost, patient preference, or in some cases ethical constraints. One way to mitigate recruitment challenges and inadequate sample size issue is to introduce data-driven priors when borrowing data from external sources, that is, to apply Bayesian methodology. A crucial consideration when we apply data-driven priors vs. objective priors is that we need some assurance of the consistency, objectivity and comprehensiveness of the synthesized data. To achieve this, propensity score matching methods can be used to control for confounding by matching experimental subjects and control subjects on a set of pre-treatment characteristics. In this talk, applications based on real clinical trial data will be discussed.

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

Back to the full JSM 2020 program