Key to research success: designing better studies
Key to research success: designing better studies
Adaptive trials is one new model
Clinical research experts largely agree on the clinical research industry's problems. It's more difficult to find a consensus on potential solutions. However, one strategy often mentioned these days is for the industry to design better clinical trials.
"We're closer to designing better trials, and the technology has been available for a while," says Dave Handelsman, senior industry consultant at SAS Health and Life Sciences in Cary, NC.
"What's lacking is the will to change," he adds.
The industry's problems of patent and revenue concerns and poor performance are growing and soon will be unmanageable.
"When you're in the pharma industry and revenues are growing, efficiency is less important," Handelsman says. "But when revenues are not growing and when Lipitor® and many other drugs and billions of dollars will disappear from the top pharma revenue stream, it's time to look at different business models."
One way is to design and apply smarter clinical trials, he adds.
"It takes too long to get a drug through the approval process, and late phase III failures are huge cost problems," Handelsman says. "A lot of trials don't meet their endpoints for a variety of reasons."
Better study design also could solve some of these problems.
Sponsors could use data and information technology tools to better assess the likelihood of a clinical trial's success. They could use this information, as well as simulations of different study designs, to design a trial for optimal demonstration of safety or efficacy, Handelsman says.
For instance, one new study design strategy involves adaptive design clinical trials. These work differently than conventional clinical trials by including a prospectively planned opportunity for modification on a specified aspect of the study design, based on analysis of interim data, according to the U.S. Food and Drug Administration's "Guidance for Industry, Adaptive Design Clinical Trials for Drugs and Biologics," a 50-page draft guidance published at www.fda.gov in February, 2010.
"You design it to make changes in the protocol, like adding a dosing arm or removing a dosing arm," Handelsman says. "There are prespecified changes along the way with the goal of having a more effective research program."
Adaptive trials are not the same as studies that are changed as a result of information obtained from outside study results or other external data and events.
There have been case studies on how adaptive trials help improve clinical research, but they are difficult to implement, Handelsman says.
"The math is complicated, and there's an operational piece that doesn't necessarily fit pharma companies' style," he says.
It's challenging for sponsors to get the drug to different sites in different doses than what was originally planned. Also, clinical trial sites have to get data in quickly so the protocol can be adapted, and that's difficult to accomplish, Handelsman says.
Plus it takes longer to get a complex, adaptive trial approved by institutional review boards and other committees, he adds.
"But there is a lot of opportunity there," Handelsman says.
Pharmaceutical sponsors have had the most interest in adaptive trials, according to the FDA's draft guidance.
Some of the possible study design modifications that can be planned in an adaptive trial include these listed in the FDA guidance:
- Study eligibility criteria for either subsequent enrollment or for a subset selection of an analytic population
- Randomization procedure
- Treatment regimens of the different study groups, including dose level, schedule, and duration
- Total sample size of the study, including early termination
- Concomitant treatments used
- Planned schedule of patient evaluations for data collection, such as the number of intermediate time points, timing of last patient observation and duration of patient study participation
- Primary endpoint, including outcome assessments, time point of assessment, use of unitary versus composite endpoint, or the components included in a composite endpoint
- Selection and/or order of secondary endpoints
- Analytic methods to evaluate the endpoints, including covariates of final analysis, statistical methodology, and type I error control.
Other ways studies might be designed better involves gathering more data in clinical trials for the purpose of identifying genetic bases for diseases and finding subpopulations that have responded well to treatment even when the general study population does not have positive findings, suggests Ken Getz, MBA, senior research fellow and assistant professor at the Tufts Center for the Study of Drug Development at Tufts University in Boston, MA.
"There is a lot of talk now about stratified medicines," Getz adds.
Stratified medicine research is where investigators use biomarkers to identify patients who are more likely to benefit from a particular drug or who are most likely to experience an adverse event. Clinicians could match patients with therapies with this type of information, and some trials are collecting these data.
"We're still at a critical place where companies are looking to gather more data, identify biomarkers, validate biomarkers, and collect genetic tissue to help them identify genetic bases for diseases," Getz explains.
These types of studies can lead to treatment breakthroughs and are beginning to transform early stage innovation through integrated partnerships with academic organizations for the purpose of identifying new and promising drug candidates, he adds.
"The sponsor will provide data on failed compounds and let scientists at the university cull through the data to see if they can find a subpopulation that might have responded well to the treatment," Getz says.
Clinical research experts largely agree on the clinical research industry's problems. It's more difficult to find a consensus on potential solutions. However, one strategy often mentioned these days is for the industry to design better clinical trials.Subscribe Now for Access
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