Site search

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.

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.

In the April issue of RF Quarterly, global experts on software as a medical device (SaMD) address software development and the associated challenges, clinical evaluation of SaMD, safety and security risk management, digital therapeutics, and more.

Regulatory authorities expect that clinical evidence for a software as medical device (SaMD) is generated with a scientific level of rigor that is commensurate with their risk and impact, and provide assurance of safety, effectiveness, and performance. As the range and scale of potential uses of artificial intelligence (AI) and machine learning (ML) for healthcare raises, new issues related for premarket clinical evaluation become apparent. Regulators across the globe focus their efforts on developing robust regulatory frameworks and the unified industry standards for risk classification and evaluation of medical AI, that safeguards against potential risks while balancing innovation.Keywords – AI/ML-based SaMD, clinical evidence, SaMD, software evaluation

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

This article applies to software development and validation and discusses the security and usability engineering aspects of software. It uses the term 'software” for software as a medical device (SaMD) and medical device software (MDSW), including MDSW that is embedded on, drives, or influences the use of a hardware medical device, software accessories, and software components. Keywords – agile development; incremental software; static waterfall