Global Regulators publish Good Machine Learning Practices (GMLP)

by | Nov 1, 2021 | AI, Analytics, Compliance, Consulting Group, Data, FDA, Guidance, ISO, Medical Devices, MedTech, QMS, Quality, Quality Systems, Regulatory, Requirements, Robotics, SaMD, Standardization, Standards


It is no secret that AI/ML medical devices are under a special spotlight by international regulators this year. With more and more AI/ML SaMD’s being engineered, regulatory authorities like the FDA have been pushing for a more robust regulatory strategy. Last week, the FDA, Health Canada and the UK’s Medicines and Healthcare Products Regulatory Agency (MHRA) jointly published “10 Guiding Principles” for Good Machine Learning Practices (GMLP)[1]. These principles will lay the foundation for the newest branch of GxP’s aimed at developing safe and effective AI/ML medical devices.

Many of the foundational principles rely on good software engineering, such as data quality assurance, cybersecurity practices, data authenticity/integrity, and risk management. Additionally, the principles outline that the model’s intended integration into clinical workflow, and the benefits/risks should be leveraged throughout the total product life cycle. The following are additional principles outlined in the informal guidance:

  • Clinical study participants and data sets are representative of the intended patient population
  • Training data sets are independent of test sets
  • Selected reference datasets are based upon best available methods
  • Model design is tailored to the available data and reflects the intended use of the device
  • Focus is placed on the performance of the Human-AI team
  • Testing demonstrates device performance during clinically relevant conditions
  • Users are provided clear and essential information
  • Deployed models are monitored for performance, similar to post-market surveillance1

If you need assistance developing a medical device integrated with AI/ML, EMMA International’s team of experts can help with everything from a regulatory strategy, to developing software specification documentation, post-market vigilance, and beyond. Give us a call at 248-987-4497 or email to find out more!

[1] FDA (2021) Good Machine Learning Practice for Medical Device Development: Guiding Principles retrieved on 10/31/2021 from:

Madison Green

Madison Green

Director of Technical Operations - Mrs. Green serves as EMMA International’s Director of Technical Operations. She has experience in technical writing, nonconforming product management, issue evaluations, and implementing corrective and preventative actions in the pharmaceuticals and medical device industries. She has experience cross-functionally between R&D, lean manufacturing operations, and RA compliance. Mrs. Green also has academic and work experience with human health-risk engineering controls, physiological biophysics, and clinical research. Mrs. Green holds a Bachelor of Science in Biosystems Engineering with a concentration in Biomedical Engineering from Michigan State University. She is also a Certified Quality Auditor (CQA), and is currently pursuing her M.S. in Quality Management.

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