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Activity Number:
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112
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Type:
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Contributed
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Date/Time:
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Monday, August 7, 2006 : 8:30 AM to 10:20 AM
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Sponsor:
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Biopharmaceutical Section
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| Abstract - #307199 |
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Title:
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Bayesian Adaptive Dose Selection
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Author(s):
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Melissa Spann and David Manner*+ and John W. Seaman
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Companies:
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Eli Lilly and Company and Eli Lilly and Company and Baylor University
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Address:
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Lilly Corporate Center, Indianapolis, IN, 46285,
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Keywords:
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Bayesian ; adaptive ; dose selection ; SAS ; WinBUGS
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Abstract:
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We will present a Bayesian adaptive approach to dose selection that uses effect sizes of doses relative to placebo to select the most efficacious dose. We assume a parallel design with multiple treatment arms including a placebo arm and a continuous outcome measure. The proposed design removes treatment arms if their performance relative to placebo or other treatment arms is undesirable. A linear or quadratic function is used to determine the rate (slow or fast) at which treatment arms can be removed. This allows the investigator flexibility by presetting the criteria of acceptable performance for a treatment arm for a given trial. We will present simulation results based on programming executed in SAS and WinBugs.
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