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Abstract:
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Rare disease or pediatric clinical development programs often include trials with small sample sizes due to practicability issues. Such small sample trials not only introduce challenges in trial designs, but also call for novel tools in data analysis. Bayesian framework naturally borrows strength from other data sources, and updates the model and results with newly collected data, while takes into account of the differences in various data sources. Hence, it is a rather suitable methodology for analyzing data collected from small sample trials. This presentation will explore the application of Bayesian framework in clinical trials with small sample sizes and illustrate some real trial cases.
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