By John Balser, PhD, President, Mark Chang, PhD, Senior Vice President, and Robin Bliss, PhD, Director
The Food and Drug Administration (FDA) has started encouraging the use of adaptive designs for clinical studies. In essence, adaptive designs allow prospectively planned modifications to a clinical trial based on interim data, provided scientific validity (the ability to draw sound inferences) and data integrity (credibility and reproducibility) are preserved.
After issuing draft guidance in 2010, the agency’s Center for Devices and Radiological Health and Center for Biologics Evaluation and Research released a final guidance on the topic in 2016.
Their intent was to clarify how best to plan and carry out adaptive design for clinical trials (particularly in medical device development) and to boost the approach’s uptake among companies. But despite the FDA’s embrace of the design method, how do you know whether adaptive designs would be beneficial, practical or appropriate to implement?
As with most methodologies, pros and cons vary based on the type of trial needed, the patient population, resources and appropriate data management strategies, and many other factors. However, there are some key issues that bear consideration to help you figure out if the design merits a serious look for your upcoming studies.
Pros and Cons of Adaptive Clinical Trial Design
Advantages of adaptive design include:
- Patient welfare can be maximized by reducing exposure to ineffective or dangerous treatments at the earliest possible point.
- Resource requirements can be reduced for a clinical trial series.
- Chances for success improve due to the opportunity for mid-stream adjustments.
- Drug and Medical devices may get to market faster.
- Waste of resources and time can be minimized if devices or treatments are ineffective.
- Most disadvantages can be avoided or accommodated with careful advance planning.
Although the pros of adaptive design sound very promising, the approach is not without its challenges.
Potential drawbacks to adaptive clinical trials include:
- Mid-study changes in treatments or population allotment can lead to Type I error inflation or operational bias.
- For group sequential designs and sample size re-estimation design approaches, study subjects included in interim analysis are also included in the final data analysis, violating the “one person one vote” rule that would ensure independence of estimates.
- “Pick-the-winner” designs result in greater likelihood of receiving a more effective treatment for subjects who enroll later in a study, which can imbalance randomization efforts.
- Statistical significance (alpha) penalties apply whenever adaptations are made and p-values can be challenging to define and compute
- Analysis that reports pooled efficacy rather than sub-group findings can make it hard to interpret the true value of a treatment if some groups have significantly different results from others.
Evaluating the Value of Adaptive Design for Your Trials
Here are some additional details to consider to help you decide whether this creative approach to clinical trials interests you:
- Adaptive design requires very thorough and methodical advanced planning. This can add time to the planning and paperwork process upfront but can save on time to market longer-term. The primary goal of advanced planning is to avoid bias or perception of bias by establishing decision points and options for adaptation a priori.
- An independent data analysis team or data monitoring committee can be invaluable for preserving scientific validity and data integrity, conducting interim computations and maintaining a blinded sponsor during adaptive decision-making, especially for phase-3 trials
- Clinical trial simulations help identify opportunities for design optimization, the potential impact of failure scenarios, possible trial results with strict Type I error control, ideal and possible samples sizes and power estimations, dynamic trial experiences from recruitment to completion, and many other scenarios in advance. This can improve your ability to plan for success and can highlight whether or not adaptive trial designs are superior to conventional designs for your needs.
- Earlier and more intense interaction with the FDA is critical to the development of an acceptable design with appropriate safeguards and sufficient decision parameters specified in advance of trial initiation. These interactions can be very fruitful but may result in significant redirection during initial preparatory stages.
With proper planning, collaboration with the FDA, data management and simulation work, adaptive design can offer a unique way to streamline your clinical trial process experience. As the field of adaptive design continues to develop, Veristat will continue to offer expert solutions and services targeted toward optimizing the planning and implementation of clinical trials.
Learn More
Read more about the FDA’s guidance on adaptive clinical trials in our publication on the topic:
- “Interpreting the Regulatory Perspective on Adaptive Designs,” published in Statistics in Biopharmaceutical Research in 2018.
- How to select and execute a biomarker driven clinical trial design
- 3 Tips to Knowing When Adaptive Design Is Right for Your Clinical Trials