AI changes the evidence pattern, not the need for control.
AI MedTech / SaMDTraining and validation data
Data provenance, representativeness, and clinical relevance are core evidence.
Performance monitoring
Model drift and real-world performance need planned review.
Transparency
Users need limits, intended use, updates, and performance information.
Cybersecurity and software lifecycle
AI governance sits inside secure, controlled software lifecycle work.
AI governance must connect to existing regulated systems.
not isolatedIntended-use and clinical workflow map
Connect this evidence to QMS, clinical, software, supplier, data, or lifecycle governance where applicable.
Software function description
Connect this evidence to QMS, clinical, software, supplier, data, or lifecycle governance where applicable.
Training/validation data summary
Connect this evidence to QMS, clinical, software, supplier, data, or lifecycle governance where applicable.
Performance evaluation report
Connect this evidence to QMS, clinical, software, supplier, data, or lifecycle governance where applicable.
Human factors/oversight rationale
Connect this evidence to QMS, clinical, software, supplier, data, or lifecycle governance where applicable.
PCCP description
Connect this evidence to QMS, clinical, software, supplier, data, or lifecycle governance where applicable.
Current public sources for AI MedTech / SaMD.
official firstThese links are the public source anchors for this workspace. Interpretation, checklists, and future assets should point back here before being reused outside iFeed.
FDA AI Software as a Medical Device page
Current · FDA landing page for AI-enabled software as a medical device.
FDA PCCP guidance for AI-enabled device software functions
2024-12-04 · Guidance on marketing submission recommendations for predetermined change control plans.
FDA AI-enabled device lifecycle draft guidance
2025-01 · Draft lifecycle management and marketing submission guidance. Treat as draft/watch item.
FDA/Health Canada/MHRA GMLP principles
2021-10-27 · Ten guiding principles for machine-learning-enabled medical device development.