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Optimizing Small Clinical Trials with Simulation-Guided Design: A Case Study

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Smaller clinical trials can be optimized in significant ways using simulation-guided design. A small biotech studying chronic pain had a one-year trial it planned to implement, but wondered if it could be shortened. Let’s take a closer look at how Cytel helped this sponsor reduce their trial time without sacrificing power.

The need for a well-timed interim analysis

An interim analysis generates evidence to forecast probability of success and efficacy, allowing sponsors to make informed decisions about early stopping. And the timing of an interim analysis can significantly affect its ability to help sponsor teams achieve trial design goals. The earlier the interim look, the less data there will be on how well the trial is going. The later the look, the fewer patients who may be spared from potentially underperforming treatments. A well-timed interim look, however, can provide opportunities for strategic decisions and enable sponsors to manage resources in the face of uncertainty.

Chronic pain clinical trial design challenge

In this case, a small biotech was developing a Phase III study to assess the efficacy of a new treatment for patients with chronic pain. The sponsor had been considering a sample size re-estimation design with an interim look at 50% enrollment, wanting to maintain at least 85% power, and reached out to Cytel to help find the optimal design. With Solara®, Cytel’s strategic consultants identified a design with two interim analyses that not only maintained power at 90%, but also shaved off 15% of the trial time.

Download our case study to learn more about how Solara enabled this team to identify the best possible design to achieve their goals:


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The Winter Weekends Reads series features complimentary publications on a variety of topics on clinical trial design and data science. Subscribe to our weekly newsletter below and never miss a post!

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