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Thursday, June 18 • 8:00am - 9:00am
#410 SL: Statistical Considerations for Using External Controls in Clinical Trials

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Component Type: Session
Level: Advanced
CE: ACPE 1.00 Knowledge UAN: 0286-0000-20-747-L04-P; CME 1.00; IACET 1.00; RN 1.00

A synthetic control arm (SCA) has been suggested as possibly advantageous as an external control to aid in the interpretation of clinical trials where a randomized concurrent control is clinically unethical, practically infeasible, or unacceptable to patients. Because the SCA is made up of patient level data from the real world or from historical clinical trials, there is opportunity to match the patient composition of the SCA to that of the experimentally treated group in baseline demographics and disease specific characteristics. This may be a considerable advantage over traditional external controls such as benchmarking with static results from medical literature or clinical intuition with populations that may not be sufficiently similar to the experimentally treated group. Speakers will provide a brief introduction to SCA and will discuss a variety of statistical approaches for the creation and use of SCAs. Discussion may include the use of clinical trials data and real-world data for construction of SCAs, various statistical matching and weighting methods for creation of the SCA, the possible impact of unobserved or unavailable historical information on the balancing process and the treatment effect, and others.

Learning Objectives

Define a synthetic control arm (SCA) and the proposal for use of SCA in indications where a concurrent randomized control is not ethical or not feasible; Discuss the advantages and disadvantages of real world data and clinical trials data in a SCA; Describe a variety of statistical methods associated with construction and use of SCAs.


Jennifer Clark, PhD


Synthetic Control Arms as External Controls in Evaluation of Treatment Effects in Drug Development
Ruthie Davi, PhD, MS

Treatment Effect and Variability When Using External Comparators in RCTs: A Statistical Epistemological Approach
Luis Rojas, PhD, MS

Industry Perspective
Andrew E. Mulberg, MD

avatar for Andrew Mulberg

Andrew Mulberg

Head, Senior Vice President, Global Regulatory Affairs, Amicus Therapeutics
He is responsible for directing global regulatory strategies for all Amicus programs to bring multiple therapies to patients with rare and devastating diseases. Dr. Mulberg is a pediatric gastroenterologist who has spent the past 6 years working at the U.S. Food and Drug Administration... Read More →
avatar for Luis Rojas

Luis Rojas

Senior Principal Statistician, Parexel
Luis holds a PhD in Statitics and has over 30 years of experience that expands to the pharmaceutical, CRO, academia and medical device industry. He is currently a Senior Principal Statistician at Parexel and the former Head of Study Designs / Adaptive Design unit within Advisory Service... Read More →
avatar for Jennifer Clark

Jennifer Clark

Mathematical Statistician, OB, OTS, CDER, FDA, United States
Jennifer Clark is a statistical reviewer for the FDA's Center for Drug Evaluation and Research. Her current work is in cardiology and nephrology with research interests in clinical outcome assessments and Bayesian methodology. Her past research interests include work in high dimensional... Read More →
avatar for Ruthie Davi

Ruthie Davi

Vice President, Data Science and Statistician, Medidata, a Dassault Systèmes company, United States
Ruthie Davi is a Statistician and Vice President, Data Science at Acorn AI by Medidata (a Dassault Systèmes Company) and has a background in pharmaceutical clinical trials with more than 20 years working as a Statistical Reviewer, Team Leader, and Deputy Division Director in the... Read More →

Thursday June 18, 2020 8:00am - 9:00am EDT
TBD Virtual Event Horsham, PA 19044
  11: Statistics, Session