What is an adaptive design in a clinical trial, and what is a typical oncological example?

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Adaptive designs use interim data to make pre-planned changes to aspects of a trial—such as dose, sample size, or how participants are randomized—without compromising the study’s validity and integrity. In oncology, a typical example is a seamless Phase II/III or multi-arm, multi-stage trial where interim analyses assess efficacy. If an arm isn’t performing well, that arm can be dropped and patients redistributed to more promising arms, potentially accelerating development and reducing exposure to ineffective treatments. This approach relies on pre-specified rules and statistical methods to control error rates, ensuring conclusions remain reliable.

Fixed designs lock all decisions at the start, which is why option one isn’t adaptive. Changing endpoints after data collection or completion isn’t what adaptive designs are about, and while adaptive designs can adjust sample size, they don’t require every trial to double the size mid-trial—adjustments are driven by prespecified rules and the interim data.