Is Adaptive Trial Design the Buzzword of 2018 or the Real Deal?

There is always a degree of uncertainty when designing your clinical trial.  What doses should you test? What is the best population and size of population to study?  Traditionally, clinical trial design includes choosing and sticking to the initial parameters throughout the trial.  These randomized clinical trial designs have contributed immensely to patient care, yet there are a number of shortcomings including the need for large sample sizes and long study duration. 

These potential pitfalls, led to the development of adaptive clinical trial design.  This design type allows flexible components to the major aspects of a trial, like the treatment arms, the allocation to the different treatment arms, the patient population, and the sample size.  Importantly, all potential modifications need to be specified before the start of the trial. 

According to FDA guidelines for industry, an adaptive clinical trial can involve:

  • Interim looks to stop or to adjust patient accrual
  • Interim looks to assess stopping the trial early either for success, futility or harm
  • Reversing the hypothesis of non-inferiority to superiority or vice versa
  • Dropping arms or doses or adjusting doses
  • Modification of the randomization rate to increase the probability that a patient is allocated to the most appropriate arm

Adaptive clinical trial designs, have been recognized for more than a decade as a way to increase trial efficiency by means of shorter duration, fewer participants, and increased probability of demonstrating an effect of the drug if one exists.  But they are still not used as widely as traditional clinical trial design as there are currently few people who have the necessary training and experience in these trial methodologies, including clinicians, researchers, and statisticians. But with calls to enhance clinical trial successes, will we see a sea change this coming year? To take a closer look, here’s a breakdown of the advantages and disadvantages of this design method. 

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Advantages of adaptive design

  1. Increase the likelihood of achieving the study objectives, while yielding an improved understanding of treatment effects (dose-response and subgroup effects).
  2. Yield more informative data than would otherwise be feasible given the constraints on time and resources that are allocated to a traditional clinical trial program.
  3. Reduce study time and resources, and permit exploring a broader range of treatment options or doses while maintaining a small sample size.
  4. Reduce patient exposure to ineffective or toxic treatments, and have the potential to identify subgroups of patients who are more likely to be responders to a certain therapy.


Disadvantages of adaptive design 

  1. The biggest disadvantage is the risk of bias— the systematic tendency for the estimate of treatment effect to deviate from its true value, or for a statistical analysis to lead to an increased rate of error, or false positives. (i.e. adaptive designs may overestimate the true effect of a drug or treatment).
  2. There is a potential to be counterproductive. Even if rigorously controlled with statistical methods to minimize error, there is question that the modifications will produce results that will be difficult to interpret.
  3. Limit the opportunity to reflect on data and result in less thoughtful and less complete programs.
  4. Unexpected results are unlikely to be identified by limited, rapid interim data analyses of adaptive designs, as well as by dropping treatment arms which could lead to safety issues.

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