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The U.S. Food and Drug Administration today issued guidance on Bayesian statistical methods in the design and analysis of medical device clinical trials that could result in less costly and more efficient patient studies.
The Bayesian statistical method applies an algorithm that makes it possible for companies to combine data collected in previous studies with data collected in a current trial. The combined data may provide sufficient justification for smaller or shorter clinical studies.
“This final guidance on the use of Bayesian statistics is consistent with the FDA’s commitment to streamline clinical trials, when possible, in order to get safe and effective products to market faster,” said FDA Commissioner Margaret A. Hamburg, M.D. “This is a terrific example of regulatory science in practice at FDA.”

The U.S. Food and Drug Administration today issued guidance on Bayesian statistical methods in the design and analysis of medical device clinical trials that could result in less costly and more efficient patient studies.

The Bayesian statistical method applies an algorithm that makes it possible for companies to combine data collected in previous studies with data collected in a current trial. The combined data may provide sufficient justification for smaller or shorter clinical studies.

“This final guidance on the use of Bayesian statistics is consistent with the FDA’s commitment to streamline clinical trials, when possible, in order to get safe and effective products to market faster,” said FDA Commissioner Margaret A. Hamburg, M.D. “This is a terrific example of regulatory science in practice at FDA.”

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