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Abstract Details
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Activity Number:
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660
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Type:
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Contributed
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Date/Time:
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Thursday, August 2, 2012 : 10:30 AM to 12:20 PM
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Sponsor:
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Biopharmaceutical Section
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| Abstract - #304908 |
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Title:
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Go/No-Go Decisions Based on Probability of Success
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Author(s):
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Kaihong Jiang*+ and Yan Zheng
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Companies:
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Sanofi and Sanofi
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Address:
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Mail Code: 55C-335A, Bridgewater, NJ, 08807, United States
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Keywords:
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Probability of Success ;
Go/No-go Decisions ;
Bayesian ;
Bionomial ;
POC
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Abstract:
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Post phase II go/no-go decisions typically reply on data summary statistics that are observed in the phase II trials such as p-values, observed effects, and their corresponding confidence intervals, etc. However, these statistics can be ambiguous for decision making as they do not inform directly about the risk of failure or probability of success of the subsequent phase III trials. Proper quantitative assessment of the probability of success (POS) is critical to the risk-informed decision making process. A POS function has been previously developed for the normally distributed data in a combined Bayesian-frequentist framework. In this paper, we extend the previous work to derive the POS function for the outcome data that follow a binomial distribution. Examples are provided to show how the POS is applied to go/no-go decisions as well as its use in sample size planning for the subsequent
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