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Medical device regulation is undergoing structural revolution as regulatory systems increasingly converge around lifecycle evidence, quality management systems, and international standards.

Modern Medical Device Regulation, Volume 6: Regulatory Convergence and Future Systems serve as the capstone volume of the series, synthesizing the analytical frameworks developed across the earlier volumes and examining the institutional transition now reshaping global regulatory systems.

These transitions include the increasing centrality of lifecycle evidence governance, the expansion of operational oversight across the Total Product Lifecycle (TPLC), and structural regulatory shifts such as the transition from the Quality System Regulation (QSR) to the Quality Management System Regulation (QMSR). Together, these developments reflect a broader evolution in how regulatory institutions, manufacturers, and healthcare systems govern medical technologies.
Drawing on a comparative case study of AI/ML medical device regulation across six jurisdictions, the volume identifies the emergence of a trimodal global governance structure built upon shared lifecycle oversight principles. This perspective informs the second chapter, which examines how ongoing institutional transitions--including changes in regulatory authority, lifecycle evidence governance, quality system frameworks, and the expanding roles of the personnel responsible for generating and managing lifecycle evidence--may reshape medical device regulation by 2035.

As a structural response to these developments, the book introduces the Lifecycle Governance Architecture (LGA), which integrates the CERT-CHIA cost framework, the SIRTIA interpretation layer, and the ATOR governance decision rule. Together, these elements organize lifecycle evidence across differing regulatory governance models while maintaining consistent evidence accountability across the TPLC.

This premium hardcover edition expands the application of LGA in chapter 3, with added emphasis on how lifecycle evidence should move through the QMS and across the manufacturer-healthcare delivery organization interface. The expanded discussion clarifies how cost signals, complaints, CAPA, service records, clinical observations, and post-market data can support earlier visibility of emerging risk rather that leaving failures to become apparent only in healthcare delivery environments.

By structuring lifecycle evidence within a common governance framework, LGA supports more accountable decision-making across regulatory, manufacturing, and clinical contexts.

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