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This article provides a detailed examination of the evolution of the framework for predetermined change control plans (PCCPs) in the US from concept to implementation and its emergence as a potential global standard. Building on perspectives shared by regulatory, legal, and technical experts, it analyzes key elements of two recent US Food and Drug Administration (FDA) guidance documents for PCCPs for artificial intelligence-enabled device software functions and for all medical devices. The article further explores best practices for drafting and maintaining PCCPs across the total product lifecycle and considers their strategic implications for manufacturers and regulators.

Global regulatory harmonization in the medical device sector is essential for ensuring timely patient access to safe and effective technologies while reducing redundant regulatory burdens. This article explores the evolving landscape of harmonization efforts, focusing on the convergence of regulatory frameworks across key markets such as the EU, US, and Asia-Pacific region. It highlights the role of international initiatives such as the International Medical Device Regulators Forum (IMDRF), reliance models, and mutual recognition agreements in shaping a more unified global approach. Furthermore, the article examines how regulatory reliance, streamlined documentation, and shared clinical evidence are being leveraged to accelerate approvals and maintain compliance. It also addresses the challenges of aligning diverse regulatory expectations, particularly in postmarket surveillance (PMS), labeling, and quality system requirements. The discussion underscores the importance of cross-functional collaboration, digital transformation, and proactive engagement with notified bodies and competent authorities, emphasizing the importance of a strategic, risk-based approach to global regulatory operations that balances innovation, patient safety, and market agility.

While FDA experience is highly valued in the private industry, transitioning from the agency to private-sector employment requires new skills and a shift in mindset. This article provides resources for regulatory professionals with FDA experience seeking careers in the private sector. The article explores common career pathways in the medical device space, addresses key differences between the FDA and industry roles, and provides strategies for leveraging FDA experience outside the agency. The insights are based on the authors' experiences after departing from the FDA. The article is divided into two sections – the first outlining career pathways and the second offering advice on job hunting.

Digital health has revolutionized the healthcare sector. Artificial intelligence (AI) and machine learning (ML) have gained widespread recognition because of their promising benefits in enhancing diagnosis, decision making, and treatment capabilities. A robust regulatory framework is essential for Al/ML-enabled medical devices to balance innovation while safeguarding public health. This article provides an overview of the global regulatory landscape for AI/ML-enabled medical devices, focusing on the framework in the US, EU, Canada, UK, Singapore, China, Hong Kong, Brazil, South Korea, Australia, and the International Medical Device Regulators Forum (IMDRF).

Artificial intelligence as medical devices (AIaMDs) have the power to learn from real-world performance and over time and may provide a different output compared with that initially cleared for a given set of inputs. However, regulatory frameworks have remained relatively unchanged and are largely focused on approaches around traditional hardware-based medical devices. In this article, the authors explain the US Food and Drug Administration's (FDA's) current thinking on enabling a total product lifecycle (TPLC) approach for AIaMDs, with a specific focus on predetermined change control plans (PCCP). They also briefly discuss approaches in other regulatory jurisdictions.

The FDA's Quality Management System Regulation (QMSR) proposal, paired with the International Organization for Standardization's ISO 13485:2016, is expected to deliver cost savings to medtech organizations that adhere to both requirements. This article covers the differences between QMSR, ISO 13485:2016, and the Medical Device Single Audit Program (MDSAP) so leaders can prepare for the upcoming changes.

This article provides an overview of the quality system requirements concerning software as a medical device (SaMD), with an emphasis on learnings and considerations for implementing an agile or hybrid-based development process. The authors further expand upon topics unique to SaMD development, specifically the importance of dataset integrity during development, considerations for proactive postmarket surveillance and the interplay between cybersecurity and risk management. Keywords – agile, dataset integrity for AI/ML, cybersecurity, software as a medical device, SaMD, software development