Although adaptive designs produce numerous benefits for clinical trials, there are also a number of risks associated with it. Below, Advanced Clinical outlines some of the key risks when conducting adaptive designs as well as ways people mitigate them. Also are some FDA-accepted designs, including the more well known Bayesian approach.
What are the big, key risks?
One major concern is the effect of adaptive designs on statistical measures. Though addressed broadly, the issue of preservation of type I error rate remains a key issue in adaptive design. Also, changes in sample size, hypotheses, and other statistical measures affect the validity of the outcome data in clinical trials. Logistic concerns include methods on how to collect data. With interim decision making, data must be collected rapidly, and with short follow-up times in order for that data to remain relevant to the current state of the study. The main procedural issue to be followed closely relates to data review, careful decision making, and implementation of decisions during adaptive trials while maintaining trial integrity.
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How do you mitigate those risks?
To mitigate risks that come with adaptive design, careful planning pre-clinical trial must take place. The right statistical measures must be in place and through simulation, the right statistical changes must be determined in case interim data suggests changes on statistical procedures. During clinical trials, it is recommended to have a Data Monitoring Committee (DMC) to review interim results and determine whether relative changes can be made. Also during trials, the use of clinical technologies such as EDC, IVRS and IWRS as well as light EDC are highly recommended in order to deal with the logistic concern of quick, responsive data analysis.
Some commonly accepted designs approved by the FDA (click picture for full view!)
Bayesian Adaptive Dose Allocation Approach (click picture for full view!)
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