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Activity Number:
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378
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Type:
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Contributed
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Date/Time:
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Wednesday, August 1, 2007 : 8:30 AM to 10:20 AM
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Sponsor:
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Biopharmaceutical Section
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| Abstract - #308444 |
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Title:
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A Bayesian Approach to Utilizing Prior Data in New Drug Development
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Author(s):
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Todd Coffey*+ and Larry Z. Shen and Wei Deng
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Companies:
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Amylin Pharmaceuticals, Inc. and Amylin Pharmaceuticals, Inc. and Amylin Pharmaceuticals, Inc.
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Address:
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9360 Towne Centre Drive, San Diego, CA, 92121,
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Keywords:
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clinical trials ; event rate ; patient-year observation ; Poisson distribution ; relative risk ; safety analysis
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Abstract:
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We propose a Bayesian method to combine safety data collected from two drug development programs using the same active drug substance but for different indications, formulations, or patient populations. The key concept of our method is to use data from the previous program to construct a posterior distribution that will in turn serve as a prior distribution for the new program. This updated prior down weights data from the previous program to emphasize the new program. We have tested this approach using data from a Phase 2 study that was conducted for a new indication of an approved drug. The results indicate that the estimated safety risk level was affected both by the observed event rates and the extent of exposure. This approach appropriately characterizes the safety profile across the two development programs and properly contextualizes new safety signals from the new program.
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