According to the guidance on adaptive design for medical device clinical studies, “adaptive designs may optimize the treatment of subjects enrolled in the study and safeguard their welfare from ineffective or unsafe treatments and interventions at the earliest possible stage.”
The guidance also addresses data integrity issues, stressing that manufacturers update infrastructure, from monitoring and data management systems, to how they work with institutional review boards (IRBs).
For example, manufacturers are encouraged to use purpose-built clinical trial management systems to handle data more securely. Additionally, if manufacturers use an adaptive design, they are required to use statistical software that can perform Bayesian analyses.
“Adaptive designs give patients the best chance of being on the right treatment and participating in a safe and secure trial,” said Vicki Anastasi, Vice President and Global Head, Medical Devices & Diagnostics Research at Icon, whose ADDPLAN software has been validated for adaptive designs and licensed by the FDA, EMA, and PMDA for analyzing data from adaptive studies.
“The guidance clearly encourages industry to understand the utility of adaptive trials to address the inefficiencies in current study designs,” Anastasi told Outsourcing-Pharma.com. “It provides an overview of how to incorporate adaptive elements into protocols submitted to the FDA.”
However, adaptive design is not a new concept. The Center for Devices and Radiological Health (CDRH), a branch of the FDA, has been evaluating adaptive designs for more ten years. From 2007 to 2012 the center received 120 submissions including adaptive elements.
“This guidance makes it clear that regulators support the approach and should lead to rapid change in how manufacturers design studies across their portfolio,” said Anastasi.
The benefits of adaptive design
In addition to providing benefits to patients, from a commercial point of view, Anastasi explained the value of adaptive design is achieved at a portfolio level, “namely by mitigating the risk that errant trial parameters could cause an effective device to fail or suffer delays and by augmenting opportunities to ensure that limited resources are directed to the most productive products,” she said.
“Since adaptive designs reduce white space between trials, stop trials early when a device demonstrates efficacy, and mitigate the risk of unnecessary setbacks during the clinical development process, manufacturers can deliver more innovations to market in a much shorter time span,” Anastasi added.
“This acceleration of cycle times allows manufacturers to beat competitors to market and maximize the revenue potential from any device brought to market.”
Anastasi’s list of adaptive designs that manufacturers should assess:
- Early stopping for effectiveness, which accelerates time-to-market, or futility, which can preserve millions of dollars that would otherwise be spent on the trial.
- Sample size reassessment to mitigate the costs and delays associated with overpowered trials and unnecessary recruitment, as well as the potential risk that an underpowered study could undermine a product’s viability.
- Seamless designs to alter a study’s hypothesis, in a prospectively planned manner, such that a late phase pilot study may continue into a pivotal study, thereby reducing white space and efficiently carrying over existing sites and patients. With an adaptive design, Manufacturers can also test superiority and inferiority hypotheses in the same study. If the device does not meet its superiority criteria, the trial can still demonstrate non-inferiority, increasing the chance for success and the opportunity to demonstrate the strongest claim possible.
- Adaptive enrichment designs that adjust trial inclusion/exclusion criteria for devices that may work better in a particular subgroup, allowing demonstration of a success claim in a responder group and prevention of failure or underperformance due to the dilution effect of irrelevant patient subpopulations.
In order to achieve these benefits, Anastasi explained that checkpoints should be set early in the product lifecycle to assess the relevancy of various adaptive designs for its clinical development program.
Yet, not all trials are appropriate for adaptive design.
“For example, fast-enrolling trials that last only a few weeks would logistically preclude an interim analysis,” said Anastasi. “Most device trials would benefit from simulations to identify risks that may arise over the course of a trial and development of designs that optimally addresses those risks.”
However, Anastasi explained that this review process requires a time investment and access to statisticians with experience in device-relevant adaptive trials, as the strategies and processes used in pharmaceuticals don’t always translate to benefits in device development.
“This investment, however, is offset by adaptations that, for example, compress study duration through combined pilot and pivotal studies, adjust the sample size to preserve statistical significance, or prevent an overpowered design from continuing to recruit unnecessary subjects,” added Anastasi.
“Overall, adaptive designs remove risk from a portfolio in ways that benefit patients, regulators, and manufacturers alike.”