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Abstract:
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The design of clinical trials is increasingly moving towards innovation such as adaptive design (AD). ADs create new challenges for the statistical analyst, including the processing of trial simulations necessary for creating an optimal design. Optimization of the randomization algorithm and estimation of the operating characteristics of the trial are achieved through thousands of simulation iterations. At each iteration, virtual clinical data are generated at patient, simulation, and scenario levels. These data are complex, copious, and often uninformative in their raw state. I will share lessons learned on how to summarize and present this output effectively, including documentation of output and the utilization of re-usable code for future simulations. I will also discuss the anticipation of timeline and table/figure/listing changes associated with an AD trial.
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