Bayesian statistics and clinical trial designs for human cells and tissue products for regulatory approval

INTRODUCTION: In order to obtain premarket approval for medical products derived from human cells or tissues in the United States (US), the European Union (EU), and Japan, data from clinical trials are typically required to evaluate product efficacy and safety. Clinical investigators or study sponsors often face challenges when designing clinical trials on human cells and tissue products with the goal of obtaining premarket approval owing to the unique characteristics of products in this category. The methods used to administer, infuse and transplant these products vary more widely than the methods used for pharmaceuticals. In addition, final product quality may vary depending on the product source, i.e., patients or donors. These products are generally intended to treat intractable and rare diseases or injuries; therefore, it may not be possible to collect a sufficient number of cases and enrollment may be a long process. Moreover, since the technology for product development in this category is relatively new, knowledge and experience from previous studies are limited. METHODS: The key elements for the design of clinical trials to determine product efficacy were identified by examining clinical trial designs for approving products. Review reports for approved products from regulatory authorities in the US and Japan as well as the European public assessment reports in the EU were analyzed. RESULTS: For one product approved in the US, Dermagraft(®), Bayesian statistics were used to evaluate product efficacy, instead of traditional (frequentist) statistics. Based on the statistical guidance for clinical trials recently issued by the US Food and Drug Administration, statistical analyses including Bayesian statistics are key elements in the design of clinical trials for products based on human cells and tissues. New regulations regarding human cells and tissue products have recently been implemented in Japan, including conditional and time-limited approval for regenerative medicine products. In these cases, Bayesian statistics are a promising alternative approach to support product development. CONCLUSIONS: Our results emphasize the benefit of considering cogitating statistical methods, such as Bayesian statistics, when designing clinical trials for regulatory purposes.