The Effective Statistician - in association with PSI
Early Development and The Dose Selection in the Immune-oncology
Dec 16, 2024
Teppo Huttunen, a Finnish statistician and founder of Eskimage, delves into the complexities of dose selection in immune-oncology. He discusses the challenges of traditional 3+3 design and advocates for the more flexible BOIN design. Teppo emphasizes the balance between safety and efficacy, exploring the crucial role statisticians play in oncology research. He also highlights the importance of industry trends, FDA guidance, and practical challenges in optimizing dose design, making this conversation essential for anyone interested in advancing oncology treatment.
21:59
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Quick takeaways
- Understanding dose selection in immune-oncology requires a shift from traditional methods to more adaptive approaches like the BOIN design.
- The evolving landscape of oncology research underscores the need for optimizing doses to enhance trial outcomes and resource efficiency.
Deep dives
The Shift from Maximum Tolerated Dose to Optimal Biological Dose
In oncology drug development, especially in immuno-oncology, the traditional approach of focusing on the maximum tolerated dose (MTD) is becoming less relevant. It is recognized that the MTD may not always correlate with the most effective dosage, prompting the need to consider the optimal biological dose instead. This shift challenges practitioners to rethink their strategies and promote a more nuanced understanding of dosage effects, particularly with new immuno-oncology therapies. Emphasizing flexibility, the Bayesian Optimal Interval Design (BOIN) model offers a framework that accommodates diverse dosing scenarios and better addresses these evolving needs.
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