What is An Adaptive Design and Why Choose it?
If the data collected in your study does not mimic the initial assumptions, an adaptive design would provide an opportunity for course correction. For example, if the initial assumptions were too conservative, and the product is performing better than expected, an adaptive design may allow for a study to stop early due to overwhelming efficacy. On the other hand, if the results were trending in the right direction, but not as strongly as originally predicted, an adaptive design could allow for an increase in sample size to increase the power of the study. Adaptive designs are particularly useful when there is uncertainty regarding the initial assumptions for the trial.
Adaptive vs Fixed Trial
A trial with a fixed design should have a fixed number of patients, a fixed patient population, and a fixed primary endpoint. All patients will be enrolled, treated and followed through the primary endpoint prior to any data being analyzed. They tend to have a shorter planning phase but may run longer than necessary.
A trial with an adaptive design allows for more flexibility. There would be at least one interim analysis to allow investigators to see how the trial is doing and make pre-specified changes to the study design. For example, the adaptation could involve changing the number of patients to enroll or the patient population.
An example of the difference in enrollment and submission timing is shown below for a study with a maximum planned enrollment of 600 subjects and interim analyses planned to test for efficacy with a chance to stop the trial early after 300, 400 and 500 subjects are enrolled.
Should My Trial Be Adaptive?
The advantage of having an adaptive study design is that it is more robust and flexible than a fixed trial design. Although it can be more efficient, a disadvantage would be that adaptive designs are more complex and require more extensive planning. For example, in addition to determining the number of subjects needed, the length of follow-up and defining the endpoints, you also need to determine what type of adaptive design you are doing, and plan the associated interim analyses. These interim analyses need to be pre-specified and statistically sound. You want to make sure that by taking this initial peek at the data that you are going to minimize any bias that may inadvertently be introduced into the trial. There are also statistical considerations to make sure that you don’t increase the chance of a false positive – i.e., determining that your product is safe and effective when it truly is not.
Adaptive designs are beneficial when there are uncertainties in the study design that can be addressed with planned opportunities to change the course of the trial. These designs are not always advantageous, especially in trials where enrollment is expected to be quick or there is a relatively short time to observation of the primary endpoint.
A fixed design is the traditional approach to running a clinical trial and tends to be more straightforward. However, it relies heavily on initial assumptions and does not provide an opportunity for correction if the study veers off course.
An adaptive design, on the other hand, is more complex and requires extensive planning. There are additional operational and statistical considerations. However, these designs tend to be more flexible. They allow for course correction, can provide early information for interested parties (like investors) and can ultimately be cost effective and speed time to submission.
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