ANN ARBOR, Mich., Oct. 7 /PRNewswire-USNewswire/ -- Clinical trials in which participants are randomly assigned to different treatments by design are the cornerstone of clinical research. When conducted correctly, it's widely accepted by the research community that the results are valid and can be trusted.
But researchers at the University of Michigan hope to improve the process for bringing therapies and medical devices to patients by investigating the impact of a class of innovative trial designs known as adaptive clinical trials – which make adjustments to the trial using information accumulated as patients are enrolled – in hopes of improving the efficiency of clinical trials as a whole.
"One of the hard and firm rules of randomized clinical trials, and for good reason, is you can't just go changing your trial to get the results you want," says William Barsan, M.D., chair and director of the U-M Department of Emergency Medicine. "But with adaptive clinical trials, you spend a lot of time up-front asking yourself, 'What if?' so that any changes made throughout the course of the study are all agreed upon at the beginning, written into the study design and only changed throughout the course of the study based on pre-specified rules."
Researchers cannot always predict at what point a specific drug or treatment will show therapeutic results during the course of the study, if at all. Once a standard trial is underway, trial characteristics such as inclusion criteria cannot be modified or changed even if a sufficient amount of data collected before the trials end-date demonstrates that such changes may be necessary.
For example, remaining patients who are randomized to the placebo group cannot benefit from the therapeutic effect of the treatment, and money will continue to be spent until the trial ends. Current trials often include periodic review of data to search for early benefit or early harm but changes are usually only triggered when an overwhelming effect is seen.
Adaptive clinical trials can more seamlessly make use of accumulating information using Bayesian statistics – which allow data analysts to predict trial success based on early patient responses and other accumulating information.
"Adaptive design essentially allows 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," says Barsan, who is also principal investigator of the clinical trials coordinating center of the Neurological Emergencies Treatment Trials Network. "We believe this is one way to avoid getting false negatives and it's better protection for patients which is really important."
The three-year project, "Accelerating Drug and Device Evaluation through Innovative Clinical Trial Design," is one of four recipients of a $9.4 million award by the National Institutes of Health-Food and Drug Administration Joint Leadership Council to spearhead collaborative activities to stimulate a new research in regulatory science.
The project is led by Barsan, Donald A. Berry, Ph.D., senior statistical scientist and founder of Berry Consultants, and Roger J. Lewis, M.D., Ph.D., co-chair of the Regulatory and Ethics Knowledge and Research Program and professor of emergency medicine at the University of California –Los Angeles.
The objective of the grant is to "optimize the design of four large, neurological emergency trials at various stages of development," Barsan says. "We'll use modeling and mathematical simulation to really kick the tires on a number of potential adaptive designs with the hope of gaining efficiency in the ultimate trial design. 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."
|SOURCE University of Michigan Health System|
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