Real-World Evidence

Real-World Evidence (RWE) and Biocompatibility: Implications of ISO 10993-1:2025 for Medical Device Manufacturers

December 11, 2025
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By Dr. Ebot Eyong

The revised ISO 10993-1 marks a significant shift in biocompatibility assessment by enabling risk-based justifications supported by real-world evidence. This article explores pre-market submissions, manufacturer implications, AI-enabled device challenges, and regulatory pitfalls.

In November 2025, a revised version of ISO 10993-1 was published, marking a significant shift in biocompatibility assessment by formally enabling risk-based justifications, supported by real-world evidence (RWE), rather than relying solely on prescriptive biological testing. This update aligns biocompatibility expectations more closely with modern device development, including software-driven and AI-enabled technologies.

Key Points for pre-Market Submissions

For regulatory submissions (e.g., FDA 510(k), De Novo, PMA, and EU MDR technical documentation), manufacturers may now justify biocompatibility using a structured risk management approach that incorporates existing data, material characterization, clinical experience, post-market surveillance, and RWE. Submissions must clearly document the biological evaluation plan, rationale for omitted tests, data relevance, and residual risk acceptability, all aligned with ISO 14971.

Implications for Manufacturers

The update reduces unnecessary testing, potentially lowering costs and timelines, but increases expectations for scientific rigor and documentation quality. Manufacturers must demonstrate strong data governance, traceability, and lifecycle management, particularly when leveraging RWE across device generations or platforms.

Challenges for AI-Enabled Devices

AI-enabled devices introduce additional complexity, as software-driven changes may alter use conditions, patient interaction, or exposure profiles. Manufacturers must ensure that biocompatibility assumptions remain valid as AI functionality evolves, especially when supported by Predetermined Change Control Plans (PCCPs).

Regulatory Pitfalls

Regulators face challenges assessing the sufficiency, relevance, and bias of RWE, as well as understanding indirect safety impacts from adaptive AI behavior. Ensuring consistency across reviews while supporting innovation remains a key risk.

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