In the Interim…
In the Interim...
Podcast Description
A podcast on statistical science and clinical trials.
Explore the intricacies of Bayesian statistics and adaptive clinical trials. Uncover methods that push beyond conventional paradigms, ushering in data-driven insights that enhance trial outcomes while ensuring safety and efficacy. Join us as we dive into complex medical challenges and regulatory landscapes, offering innovative solutions tailored for pharma pioneers. Featuring expertise from industry leaders, each episode is crafted to provide clarity, foster debate, and challenge mainstream perspectives, ensuring you remain at the forefront of clinical trial excellence.
Podcast Insights
Content Themes
Explores Bayesian statistics, adaptive clinical trial designs, and innovative methodologies to tackle medical challenges, with episodes featuring in-depth discussions such as the transformative impact of platform trials during the COVID pandemic and regulatory navigation in adaptive trials.
A podcast on statistical science and clinical trials.
Explore the intricacies of Bayesian statistics and adaptive clinical trials. Uncover methods that push beyond conventional paradigms, ushering in data-driven insights that enhance trial outcomes while ensuring safety and efficacy. Join us as we dive into complex medical challenges and regulatory landscapes, offering innovative solutions tailored for pharma pioneers. Featuring expertise from industry leaders, each episode is crafted to provide clarity, foster debate, and challenge mainstream perspectives, ensuring you remain at the forefront of clinical trial excellence.
In this episode of “In the Interim…” we revisit the ground-breaking seamless phase 2/3 clinical trial for the GLP-1 agonist, dulaglutide—better known as Trulicity. We discuss the intricacies of the adaptive trial design, and the unique features that helped expedite development by 12-18 months. Listeners will gain insight into how Bayesian algorithms and innovative statistical methods were pivotal in navigating a complex trial design, benefiting Eli Lilly’s pipeline and changing the landscape of diabetes treatment.
Key Highlights:
- Outline of the trial design and the barriers faced during its inception in 2007-2008.
- Explanation of the Clinical Utility Index and its role in adaptive randomization.
- The DSMB’s role and interaction with Bayesian decision-making models.
- Simulation-based design to optimize development efficiencies.
- Insights into the predictive power of the trial on weight loss outcomes in subsequent trials.
Quotes:
- “The trial was run entirely by Bayesian algorithms.” – Scott Berry
- “They believed this utility function was absolutely the right way to go forward.” – Scott Berry
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