March 3, 2022 | 10:00am EST
Phase 1 clinical trials aim to determine the maximum tolerated dose (MTD) of a new molecule with the goal of identifying a recommended Phase 2 dose (RP2D), often the MTD itself. Ideally, the RP2D would have adequate therapeutic effect to demonstrate preliminary signs of efficacy in Phase 2, but many Phase 2 trials fail to detect a preliminary efficacy signal, prolonging the development program and increasing costs.
A common reason Phase 2 trials fail is because the RP2D selected from the Phase 1 trial was a sub-therapeutic dose. The risk of selecting a sub-therapeutic dose as the RP2D is a key limitation of the traditional 3+3 dose-escalation design in Phase 1.
In this webinar, the panelists will discuss this issue and its broader implications and highlight alternate Bayesian model-based dose escalation designs that offer a higher chance of selecting an effective therapeutic dose as the RP2D, while also providing greater efficiency than the traditional 3+3 rules-based design and increasing the speed to determining the MTD.
Abie Ekangaki, PhD, Vice President, Statistical Consulting and Andreas Schreiner, M.D., Vice President, Medical Affairs Neuroscience & Analgesia