Federal Register #FDA-2026-N-10165

FDA Request for Information on Statistical Considerations for Rare Disease Clinical Investigations

The Food and Drug Administration (FDA), under the Department of Health and Human Services, is seeking public input on statistical considerations for clinical investigations in rare diseases. - Government Buyer: - Food and Drug Administration (FDA) - Department of Health and Human Services - Purpose: - Collect feedback on statistical approaches for clinical trials involving rare disease drugs, biologics, and medical devices - Issued in conjunction with the Rare disease Innovation, Science, and Exploration (RISE) Workshop - Participants: - Medical product developers - Disease advocates - Researchers - Products/Services Requested: - No specific products or services are being procured - Request for information and comments on pre-read documents and workshop content - Unique/Notable Requirements: - Focus on challenges such as small patient populations, statistical power, endpoint selection, and efficiency-enhancing strategies - Input sought on tailored statistical review approaches, including randomized designs, sequential analyses, and use of external data sources - Emphasis on improving regulatory science and facilitating drug development for rare diseases - OEMs and Vendors: - No OEMs or vendors are mentioned, as this is a request for information rather than a procurement opportunity

Description

The Food and Drug Administration (FDA) is establishing a public docket to collect feedback on statistical considerations for rare disease clinical investigations. This initiative is in conjunction with a Rare disease Innovation, Science, and Exploration (RISE) Workshop focused on the same topic. The FDA seeks input on pre-read documents related to clinical trials of rare disease drugs, biologics, and medical devices, as well as feedback on the workshop content. The goal is to improve regulatory science and facilitate drug development for rare diseases by addressing challenges such as small patient populations and statistical complexities.

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