InferTrust FDA Enforcement: Cryptographic Proof for AI/ML Medical Devices
When FDA issues a 483 or orders a recall of your AI device, can you prove what every inference did? InferTrust seals the record at the point of computation so your evidence is ready before the inspector arrives.
What InferTrust FDA Enforcement Does
InferTrust FDA Enforcement creates cryptographically signed decision records for every inference made by AI/ML-based medical devices. This covers SaMD clinical decision support under FDA scrutiny, AI-enabled diagnostic device recall defense, Predetermined Change Control Plan (PCCP) compliance, post-market surveillance monitoring, 510(k) and De Novo submission evidence, and Good Machine Learning Practice (GMLP) documentation.
Key Pain Points Addressed
- FDA 483 observations citing inadequate AI device documentation and version control
- Class I or Class II recalls requiring proof of which model version produced each diagnostic output
- PCCP submissions needing sealed evidence of every model update and retraining event
- Post-market surveillance requiring provable performance records across patient populations
- Edge AI medical devices operating at the point of care with no network connectivity
Decision Actions Captured
- FDA_COMPLIANT: Decision within cleared indications for use and approved operational parameters
- FDA_FLAG: Output triggers a performance or safety concern requiring clinical review
- FDA_NONCONFORMANCE: Decision outside approved parameters with sealed deviation record
- FDA_ESCALATE: Confidence below threshold, routed to qualified clinician per device labeling
- FDA_HOLD: Insufficient input data quality or pending validation checkpoint
Regulatory Frameworks Supported
- FDA 21 CFR Part 820: Quality System Regulation for Medical Devices
- FDA SaMD PCCP: Predetermined Change Control Plan for AI/ML Devices
- GMLP: Good Machine Learning Practice Principles
- IEC 62304: Medical Device Software Lifecycle
- ISO 13485: Medical Device Quality Management Systems
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