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June 1, 2026
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Episode 64, “Fighting Time in Adaptive Trials”

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In this episode of "In the Interim…", Dr. Scott Berry explores the challenge of protracted endpoint timelines in adaptive clinical trials and the statistical strategies used to increase the rate of actionable information gain.

On the latest episode of "In the Interim…", Dr. Scott Berry breaks down the critical challenge in adaptive trials: fighting time to accelerate learning.

In traditional fixed trials, you wait months or years for primary endpoint data before making any decisions. There is no concern or need to model long-term endpoints. Adaptive trials promise smarter, more efficient designs, but only if you can learn quickly enough to make meaningful adaptations.

Scott walks through real examples:

● I-SPY 2's longitudinal modeling predicted 60% response rates with just one completed patient

● BAN 2401's Alzheimer's trial used early cognitive measures to guide dose allocation

● Lilly's AWARD-5 trial strategically controlled enrollment speed to maximize learning efficiency with predictive modeling of 12-month outcomes

The key insight is that early timepoint data combined with Bayesian modeling can forecast final outcomes to improve the trial adaptations.

To hear how longitudinal models improves learning in adaptive designs tune in today:
https://www.berryconsultants.com/resource/64-fighting-time-in-adaptive-trials

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