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Thursday, June 18 • 5:00pm - 6:00pm
#562 OD: ON DEMAND - Utilization of Bayesian Statistics in Clinical Trials

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Component Type: Session
Level: Intermediate

Bayesian statistics have gained much traction over the last decade in clinical development. It can be attributed to the advancement in Bayesian modeling that is more tailored for clinical trial designs as well as the expansion of technologies that allow for much faster simulations. On the other hand, even with the inertia from both regulatory and industry to conduct traditional randomized controlled trials, it is indisputable that innovative trial designs need to be considered in the current competitive environment. Bayesian statistics provides a natural and systematic approach for trialists to leverage strength from existing data and knowledge at the design stage. It has proven to be much more efficient and just as rigorous, if not more, than traditional designs. Utilization of Bayesian statistics in clinical trials has gained much wider acceptance in clinical development, varying from pre-clinical studies to post-marketing researches, including registrational trials. Similar to other statistical tools, Bayesian statistics can be used in different designs, at different stages for different purposes. This session will have speakers from both industry and regulatory discussing various ways of using Bayesian statistics in clinical trials, introducing new Bayesian models, and assessing advantages and caveats as well as providing guidance and lessons learned.

Learning Objectives

Describe utilization of Bayesian statistics in clinical development; Discuss how Bayesian statistics can provide a more efficient trial design; Identify advantages and caveats of using Bayesian statistics in clinical trial designs, as well as regulatory guidance.


Freda W. Cooner, PhD


Overview and Optimization of an Adaptive Bayesian Two-Stage “Drop-the-Losers” Trial Design
Alex Karanevich, PhD

Pediatric Drug Development and Bayesian Method
Hengrui Sun, DrPH, MD

Design of a Single Arm Trial in a Rare, Progressive Disease Using Natural Histories and a Disease Progression Model
Joe Marion, PhD

avatar for Freda Cooner

Freda Cooner

Senior Director - Statistics, Eli Lilly and Company, United States
Dr. Freda Cooner is currently a Senior Director in Eli Lilly and Company. Prior to that, she is a Statistics Director in Amgen, leading the prostate cancer statistics program and exploration of innovative designs for several oncology and non-oncology products, including master protocols... Read More →
avatar for Alex Karanevich

Alex Karanevich

Biostatistician, EMB Statistical Solutions
Completed an MS in mathematics at the University of Wyoming, and PhD in biostatistics at the University of Kansas Medical Center. Specialized in Bayesian statistics/ adaptive trial designs, with applications to amyotrophic lateral sclerosis (ALS). Became an industry biostatistician... Read More →
avatar for Joe Marion

Joe Marion

Statistical Scientist, Berry Consultants
Joe Marion is a Statistical Scientist for Berry Consultants where he specializes in the design of innovative Bayesian adaptive clinical trials. His work at Berry includes the design and simulation of platform trials, the use of Bayesian primary analysis in phase 3 trials, and disease... Read More →
avatar for Hengrui Sun

Hengrui Sun

Statistician, OB, OTS, CDER, FDA, United States
Dr. Sun is currently a statistical reviewer in the Anti-viral team, Division IV, Office of Biostatistics, CDER, FDA. She is also a member in the FDA Office of Biostat Pediatric Subcommittee and ASA Biopharm Section pediatric working group. Before joining FDA, Dr. Sun served as Senior... Read More →

Thursday June 18, 2020 5:00pm - 6:00pm EDT
TBD Virtual Event Horsham, PA 19044
  11: Statistics, Session