Facts and interpretation stay separate.
auditable readingSource fact
FDA treats AI-enabled medical-device software through device pathways plus AI lifecycle expectations.
iFeed reading
The core operating question is controlled change: what can change, how it is validated, and how users are informed.
Operational meaning
Submission evidence should connect intended use, data, performance, PCCP, transparency, cybersecurity, and real-world monitoring.
Do not overclaim
A PCCP does not allow unlimited model evolution.
The useful question is what work this creates.
iFeed meaningDevice software function
Evidence depends on the clinical function, risk, and role of the software.
AI/ML model development
Training, testing, validation, and data representativeness need source-linked records.
Predetermined Change Control Plan
Planned model changes can be described and governed before implementation.
Transparency
Users need information about intended use, performance, limitations, and updates.
Human factors and oversight
Human interaction with AI output affects risk and evidence needs.
Real-world monitoring
Post-market performance and drift concerns need planned review.
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FDA AI-enabled device lifecycle draft guidance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.