Alternative Designs to Traditional 3+3 Design in Phase 1 Dose Escalation Studies

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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. Presenters: Abie Ekangaki, Ph.D., Vice President, Statistical Consulting, Premier Research Andreas Schreiner, M.D., Vice President, Medical Affairs Neuroscience & Analgesia, Premier Research
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Premier Research is a clinical research company, dedicated to helping biotech, specialty pharma, and device innovators transform life-changing ideas and breakthrough science into new medical treatments. As a global company, Premier specializes in the use of innovative technologies for smart study design and trial management to deliver clean, conclusive data to sponsors. Whether it’s developing product lifecycle strategies, reducing clinical development cycle times, securing access to patients, navigating global regulations, maximizing the impact of limited rare disease data, or providing expertise in specific therapeutic areas, Premier is committed to helping its customers answer the unmet needs of patients across a broad range of medical conditions.