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Activity Number: 26
Type: Topic Contributed
Date/Time: Sunday, July 29, 2012 : 2:00 PM to 3:50 PM
Sponsor: Section on Bayesian Statistical Science
Abstract - #305841
Title: Semiparametric Bayesian Approach for Benefit-Risk Assessments in Dose-Finding Trials
Author(s): Satrajit Roychoudhury*+
Companies: Novartis
Address: 180 Park Ave, Florham Park, NJ, 07932, United States
Keywords: Benefit risk assessment ; Minimum effective dose ; Maximum safe dose ; Adverse event ; Heterogeneity ; Dirichlet process
Abstract:

For most therapeutic areas the traditional dose finding approach for Phase II of a new candidate drug is conducted by designing a small randomized trial with multiple ascending doses. Primary objectives of these studies are looking for differences in safety, pharmacokinetic profile and evidence that the drug has an effect on the disease being studied. Commonly used methods in dose finding are often insufficient to explore the underline dose response and dose toxicity relation information in complete manner. In this article we presented a semiparametric bayesian model based approach of benefit-risk assessment in dose finding trails. Proposed methodology not only takes account monitored efficacy and safety measures but also includes information comes from evolving adverse events happen during trial. This provides a vivid picture of benefit- risk assessment of an investigational drug even in early stage. The proposed model is discussed under both monotonic and non-monotonic order restrictions. The model is Numerical and data examples will be used to illustrate the properties of these approaches.


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