{
  "node_id": "us-fda-good-machine-learning-practice-2021",
  "title": "FDA / Health Canada / UK MHRA - Good Machine Learning Practice for Medical Device Development - 10 Guiding Principles (October 27, 2021)",
  "domain": "AI Governance & Law",
  "version": "1.0.0",
  "last_updated": "2026-06-13",
  "bluf": "On October 27, 2021 the US Food and Drug Administration jointly with Health Canada and the United Kingdom Medicines and Healthcare products Regulatory Agency (MHRA) published the Good Machine Learning Practice (GMLP) for Medical Device Development - 10 Guiding Principles. The Principles establish a tri-national agreed-upon baseline for the development of AI and machine learning medical devices throughout the product lifecycle. The 10 Principles are: (1) Multi-disciplinary expertise is leveraged throughout the total product life cycle; (2) Good software engineering and security practices are implemented; (3) Clinical study participants and data sets are representative of the intended patient population; (4) Training data sets are independent of test sets; (5) Selected reference datasets are based upon best available methods; (6) Model design is tailored to the available data and reflects the intended use of the device; (7) Focus is placed on the performance of the human-AI team; (8) Testing demonstrates device performance during clinically relevant conditions; (9) Users are provided clear, essential information; (10) Deployed models are monitored for performance and re-training risks are managed. The Principles are voluntary international baseline and are operationalised by FDA SaMD action plans, Health Canada AI/ML medical device guidance, and UK MHRA software and AI medical device pre-market guidance. GMLP underpins the FDA Predetermined Change Control Plan (PCCP) framework for AI/ML SaMD.",
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  "crosswalks": {
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  "dependencies": [
    "fda-ai-ml-samd-action-plan",
    "us-fda-aiml-samd-pccp-final-guidance-2024",
    "fda-samd-action-plan-2022"
  ],
  "primary_citations_count": 12
}