Regulatory Affairs for Digital Health & AI Medical Devices

This course contains the use of artificial intelligence.

Digital health can scale quickly. Regulatory strategy cannot be improvised after launch. When software supports diagnosis, prediction, triage, treatment or monitoring, questions around SaMD, AI/ML medical device functions, clinical evidence, cybersecurity, quality systems and model change control become business-critical.

Regulatory Affairs for Digital Health & AI Medical Devices is a practical, internationally focused course for professionals who need to turn complex requirements into defensible decisions. It connects EU MDR/IVDR, the EU AI Act and the US FDA approach with market-entry considerations for China (NMPA) and India (CDSCO).

Whether you work in Regulatory Affairs, Quality Assurance, clinical development, product management, software engineering, data science, cybersecurity, medical affairs or startup leadership, this course will help you understand what regulators expect—and how to build the evidence, documentation and governance needed to support an AI-enabled medical device throughout its lifecycle.

WHAT YOU WILL LEARN

You will learn how to:

• Define intended purpose, intended use, users, populations and claims before choosing a regulatory pathway.

• Distinguish Digital Health, Software as a Medical Device (SaMD), software in a medical device, accessories and Clinical Decision Support (CDS).

• Determine whether software is a medical device using practical qualification logic for the EU and United States.

• Classify medical device software under EU MDR/IVDR, including Rule 11 and the consequences of decisions that may cause serious deterioration.

• Build an EU conformity assessment strategy and understand the role of the Notified Body.

• Integrate EU AI Act high-risk requirements with MDR documentation, risk management, data governance, transparency and human oversight.

• Evaluate FDA pathways for software, CDS and AI-enabled devices, including 510(k), De Novo, Pre-Submission strategy and evidence planning.

• Structure a Predetermined Change Control Plan (PCCP) and govern model updates, retraining, drift and version changes.

• Plan analytical, technical and clinical validation, including subgroup performance, bias, Real-World Evidence and continuous monitoring.

• Apply cybersecurity-by-design, threat modeling, SBOM controls, vulnerability management and secure lifecycle principles.

• Build an audit-ready Quality Management System for regulated software, covering design controls, IEC 62304, ISO 14971, CAPA, complaints, vigilance and post-market surveillance.

• Develop practical market-entry strategies for AI medical devices in China through NMPA and in India through CDSCO.

EU REGULATORY STRATEGY

The European pathway is covered from qualification and classification through conformity assessment and lifecycle compliance. You will work with MDR/IVDR concepts, Rule 11, technical documentation, GSPR mapping, clinical evaluation, risk management, labeling, PMS/PMCF, vigilance and Notified Body expectations.

The course also addresses the EU AI Act as an operational framework—not simply a legal overview. You will learn how data governance, transparency, human oversight, logging, accuracy, robustness and cybersecurity can be mapped into an integrated MDR and QMS evidence architecture without unnecessary duplication.

US FDA STRATEGY

You will examine the FDA boundary between device and non-device CDS, how intended use drives pathway selection, and how to frame a credible regulatory story for 510(k), De Novo or Pre-Submission interaction. Dedicated case material covers software documentation, clinical validation, human factors, cybersecurity, post-market changes, model drift, CAPA and recalls.

EVIDENCE, SAFETY AND SOFTWARE LIFECYCLE

A successful submission requires more than an accurate algorithm. The course separates analytical, technical and clinical validation; connects hazards to risk controls and verification evidence; and shows how performance must be monitored across sites, populations and software versions.

You will also learn how a minimum viable QMS differs between a startup and a mature organization, and how to create disciplined change control, release management, supplier oversight, complaint handling and post-market escalation for continuously evolving software.

GLOBAL MARKET PERSPECTIVE

The China and India deep dives explain why a global dossier cannot simply be copied into every market. You will consider NMPA and CDSCO pathways, local representation, testing and evidence, language and labeling, data and cybersecurity, import considerations and post-market responsibilities.

LEARN BY DOING

This is not a lecture-only course. Your learning experience includes:

• 12 module quizzes and case challenges.

• Four AI-powered regulatory role plays.

• Professional learning toolkits, decision trees, checklists and templates.

• Step-by-step US and EU AI imaging SaMD case studies.

• China NMPA and India CDSCO regulatory playbooks.

• A final global capstone assignment with ten board-level decisions and complete instructor model answers.

In the capstone, you act as Global Regulatory Lead for a fictional AI SaMD. You must align claims, classification, evidence, EU AI Act compliance, FDA strategy, PCCP, cybersecurity, QMS and international launch sequencing into one board-ready regulatory plan.

WHY THIS COURSE IS DIFFERENT

Many regulatory courses stop at definitions or treat every market as a separate checklist. This course follows the real decision chain: intended purpose shapes qualification and classification; classification shapes pathway and evidence; evidence connects to risk controls, labeling and post-market monitoring; and every model update must remain inside a governed lifecycle.

The course is organized around work products and decisions that appear in real programs. You will compare plausible alternatives, identify uncertainty, set regulatory gates and explain why a recommendation is defensible. The role plays test how you respond under pressure, while the capstone requires you to integrate technical, clinical, quality and international considerations for senior decision-makers.

This approach makes the material useful whether you are preparing a first strategy, challenging an existing plan, supporting due diligence, working with a Notified Body, preparing an FDA interaction or coordinating a global launch.

WHO THIS COURSE IS FOR

This course is designed for Regulatory Affairs and Quality professionals, product and clinical leaders, software and ML teams, cybersecurity specialists, consultants, founders and anyone moving from general health technology into regulated medical device software.

No coding experience is required. Basic familiarity with digital health or medical devices is helpful, but the course begins with core qualification concepts and progresses to advanced global strategy.

By the end, you will not only understand the frameworks—you will have practiced how to make, document and defend the decisions that determine whether an AI medical device is ready for regulatory review and responsible market entry.

This course is educational and does not constitute legal advice. Always confirm product-specific requirements with the relevant authority, Notified Body and qualified regulatory or legal professionals.