Researchers at the University of Michigan have received a $1.5 million grant to demonstrate how adaptive clinical trial design can improve the speed, efficiency and safety of clinical research. As part of the three-year project, the researchers also will identify barriers to widespread adoption of these innovative trial designs in academic research.
The grant was awarded through a joint program sponsored by the National Institutes of Health (NIH) and the U.S. Food and Drug Administration (FDA), which was developed to support the use of new scientific tools and technologies that can help the FDA evaluate new treatments in a better and faster way.
By showing what can be gained from adaptive clinical trials and understanding the obstacles to adoption, the researchers hope their work will promote greater understanding of adaptive designs among academic researchers. “The current process for the design, review and funding of NIH-funded clinical trials has historically not fostered the incorporation of adaptive designs,” said William G. Barsan, M.D., professor and chair of the University of Michigan Department of Emergency Medicine, who will lead the project. “Pharmaceutical and device manufacturers have increasingly turned to such designs as ways to identify promising treatments more quickly—and also to move away from treatments which are not working.”
In addition to Barsan, other team members for the project include Donald A. Berry, Ph.D, founder of Berry Consultants and a biostatistician at M.D. Anderson Cancer Center in Houston, Texas; Roger J. Lewis, M.D., Ph.D., professor of the Department of Emergency Medicine at Harbor-UCLA Medical Center in Los Angeles; and William J. Meurer, M.D., M.S., assistant professor of the Department of Emergency Medicine at the University of Michigan.
The researchers believe that adaptive designs, which allow adjustments to a clinical trial using information accumulated as patients are enrolled, can improve the conduct of trials. “Adaptive clinical trials offer a way to increase the efficiency and likelihood of success in the treatment process, by allowing the trial design to be modified, in pre-specified ways, in response to information arising from within the trial itself,” said Barsan. “The upfront work required to simulate and evaluate trial performance for the various situations that could arise as a trial progresses is substantial, but it is essential to verify trial performance and to achieve increased efficiency.”
This approach, according to Barsan, also can improve safety for clinical trial participants. “Adaptive designs essentially allow the statisticians to continuously reanalyze the data over the entire study and we can end up changing how patients are assigned within the study if it really looks like it’s working,” he said. “We believe this is one way to avoid getting false negatives and it’s better protection for patients, which is really important.”
The researchers will test this strategy by optimizing the design of four phase III trials being conducted in an existing neurological trials network. “We will use four trials from that pipeline, currently at various stages in the development process, and investigate the efficiency gained from incorporating various adaptive techniques including frequent interim analyses, probability-based decision rules, longitudinal modeling of unknown outcomes and response-adaptive randomization,” said Barsan. “Hopefully it will lead to considerable savings in the research process and allow us to more accurately and rapidly identify treatments which improve patient outcomes.”
Barsan said his team hopes that regulators can use the results of their research to provide additional guidance on adaptive clinical trial design, particularly for later-phase studies. “Most of the previous experience has been in early-phase trials—we hope to demonstrate that these designs can be very helpful in adequate and well-controlled phase III trials as well,” said Barsan. “This is a unique opportunity to help transform the way clinical trials occur. Given our limited resources, both in clinical trial volunteers and in the financial expense of trial conduct, it is imperative that we capitalize on the state-of-the-art statistical design to find effective treatments for serious health problems.”