AI Medical Device Regulatory Strategy and Clinical Evaluation Training

Turn an AI concept into a credible medical device development strategy.

This practical masterclass helps AI start-ups, medical device manufacturers and development teams determine when software qualifies as a medical device, plan EU market access, build proportionate quality and technical documentation, and define the clinical evidence needed to support intended purpose, claims, safety, performance and clinical benefit.

Learning Outcomes / Benefits

• Determine whether an AI software product qualifies as medical device software under the EU MDR or IVDR.
• Understand how intended purpose, claims, user context and patient impact influence qualification and classification.
• Build a regulatory and market-access strategy from early development through CE marking and post-market activities.
• Identify the quality management system and technical documentation needed for an AI medical device start-up.
• Recognise AI-specific risks related to data quality, bias, transparency, model drift, cybersecurity, privacy and human oversight.
• Understand the clinical evaluation process and select an appropriate clinical evaluation strategy for the device and risk class.
• Understand the principles for establishing clinical benefit, performance and safety claims that are measurable, clinically relevant and supported by appropriate evidence.
• Recognise the clinical and non-clinical evidence requirements for AI-enabled MDSW, including validation datasets, literature, clinical investigations and post-market clinical follow-up.
• Apply the learning to draft an intended purpose and determine a preliminary software qualification and classification.

As a participant, you will also receive a personalised one-page report outlining the basic qualification and classification of your product.

Course Content

• Module 1: When AI software becomes a medical device – Apply MDR, IVDR and MDCG principles to distinguish MDSW from non-medical software and understand the role of intended purpose.
• Module 2: Qualification and classification – Work through medical device and IVD software classification, including MDR Rule 11 and the consequences of clinical context and patient impact.
• Module 3: Regulatory strategy and EU market access – Connect development planning, conformity assessment, notified body involvement, CE marking and post-market obligations.
• Module 4: Quality management for AI start-ups – Understand proportionate QMS expectations under MDR, IVDR and ISO 13485, with links to software, information security and AI management standards.
• Module 5: Technical documentation and AI-specific risk – Structure core documentation and address data quality, representativeness, bias, explainability, model drift, security, privacy, validation and change management.
• Module 6: Clinical evaluation fundamentals – Follow the clinical evaluation lifecycle from planning and literature review to appraisal, analysis, reporting and PMCF.
• Module 7: Intended purpose, clinical benefit and claims – Create a consistent evidence backbone and translate claims into measurable outcomes and acceptance criteria.
• Module 8: Clinical evidence for AI MDSW – Evaluate valid clinical association, technical performance and clinical performance, and consider the relevance, quality and sufficiency of training, validation and test data.
• Practical exercise – Draft an intended purpose for an AI product and determine its preliminary qualification and classification.

Target Audience

Who should attend: This course is ideal for founders and employees in AI and MedTech start-ups, regulatory affairs and quality assurance professionals, clinical and medical affairs specialists, software and machine-learning developers, product managers, R&D leaders, clinical development teams and consultants who need to bring AI-enabled medical device software from concept toward compliant EU market access.

Prerequisites

• Basic familiarity with medical devices, software development, clinical development or regulated product development is recommended.
• No advanced prior knowledge of clinical evaluation is required.
• Participants are encouraged to bring an AI product concept or use case for the practical exercise.

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