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Abstract:
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Ever since the establishment of Best Pharmaceuticals for Children Act (BPCA) in 2002 and Pediatric Research Equity Act (PREA) in 2003, there have been a steady increase in the number of pediatric clinical development programs initiated. However, these programs often include small sample trials due to practicability issues besides the other clinical issues in pediatric patients. Such issues not only introduce challenges in trial designs, but also call for novel tools in data analysis. The Bayesian framework allows for borrowing of information from other data sources and could potentially result in updates to the model and analysis results based on accumulating data, while taking into account differences in various data sources. It may therefore have utility as a methodology for analyzing data collected from small sample trials. Pediatric studies often have the natural prior data source from adult trials. Bayesian methodology can systematically borrow information from these data if appropriate and also calibrate the rate of borrowing to minimize the uncertainty incurred from using adult data. This presentation will explore the application of Bayesian method in pediatric trials.
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