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A Tutorial on Modern Bayesian Methods in Clinical Trials

Clinical trials continue to be the gold standard for evaluating new medical technologies. New advancements in modern computation power have led to increasing interest in Bayesian methods.

Despite the multiple benefits of Bayesian approaches, application to clinical trials has been limited. Based on insights from the survey of clinical researchers in drug development conducted by the Drug Information Association Bayesian Scientific Working Group (DIA BSWG), insufficient knowledge of Bayesian approaches was ranked as the most important perceived barrier to implementing Bayesian methods. Results of the same survey indicate that clinical researchers may find the interpretation of results from a Bayesian analysis to be more useful than conventional interpretations.

In the paper “A Tutorial on Modern Bayesian Methods in Clinical Trials” published in Therapeutic Innovation & Regulatory Science (volume 57, pages 402–416 (2023)), Rajat Mukherjee worked with Natalia Muehlemann, Tianjian Zhou, Munshi Imran Hossain, Satrajit Roychoudhury and Estelle Russek-Cohen to illustrate key concepts tied to Bayesian methods, starting with familiar concepts widely used in clinical practice before advancing in complexity, and use practical illustrations from clinical development.

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