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Activity Number: 359 - Contributed Poster Presentations: Biopharmacutical Section
Type: Contributed
Date/Time: Tuesday, July 31, 2018 : 10:30 AM to 12:20 PM
Sponsor: Biopharmaceutical Section
Abstract #327257
Title: A Bayesian Adaptive Model-Based Approach for Dose Selection in a FGF21 2nd Gen Phase 1 Study
Author(s): Yuping Dong*
Keywords: dose selection; Bayesian adaptive; Multiple ascending dose; dose-response

Usually the dose levels for a Single Ascending Dose (SAD) or Multiple Ascending Dose (MAD) Phase 1 clinical study are based on pharmacokinetic (PK) and safety evaluation. But in one SAD/MAD study, we also want the dose levels studied to be able to achieve some degree of response for a PD biomarker, especially the highest dose for the top MAD panel. A Bayesian adaptive model-based approach was developed to achieve this goal. With this approach, the dose-response relationship was predicted/updated dynamically using Emax model based on observed data from the ongoing study combining with prior information from pre-clinical and clinical studies, and further the pre-specified dose for next dose panel was adaptively evaluated and adjusted during this study to achieve desired/target response level. A simulation was done to evaluate the characteristics of two dose selection strategies.

Authors who are presenting talks have a * after their name.

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