FDA, Health Canada, MHRA Propose Transparency Guidelines for AI in Medical Devices

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Health regulators from the U.S., Canada, and the UK are working together to enhance transparency in machine learning medical devices. In 2021, the FDA, Health Canada, and the MHRA identified ten guiding principles for good machine learning practice (GMLP) to ensure the safe and effective development of AI/ML technologies in medical devices.

Building on GMLP, these agencies are now focusing on developing a regulatory framework for modifications to AI/ML-Based Software as a Medical Device (SaMD) with additional guiding principles specifically for transparency in machine learning-enabled medical devices (MLMDs).

Transparency in MLMDs is essential for clear communication of crucial information such as the device’s purpose, target population, performance, and risks to healthcare professionals, patients, caregivers, and other stakeholders. This transparency promotes patient-centered care, informed decision-making, and safe use of these advanced technologies.

The proposed guiding principles for transparency address key aspects such as providing detailed information about the device’s medical purpose, target population, performance, risks, integration into healthcare workflows, and the logic behind its outputs. Human-centered design principles are fundamental in achieving effective transparency by involving relevant stakeholders throughout the design and development process.

These guiding principles for transparency aim to support safe, effective, and patient-centered use of AI/ML technologies in healthcare by emphasizing the importance of clear communication, timely updates, and comprehensive information. Stakeholder engagement and collaboration will be crucial in refining and implementing these transparency practices in the rapidly evolving field of medical technology.

For more information, you can refer to the MHRA’s full announcement here and the FDA’s docket on the proposals here. The regulators are seeking feedback and engagement to further inform collaborative development in this rapidly evolving field.

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For further inquiries, you may contact Julia Gillert, Jaspreet Takhar, or Elina Angeloudi. Julia Gillert, Of Counsel at Baker McKenzie’s London office, focuses exclusively on regulatory matters affecting the Healthcare & Life Sciences industry. Jaspreet Takhar, a senior associate at Baker McKenzie’s London office, advises leading tech and healthcare companies on digital health issues.

The collaboration between these regulatory agencies signifies a step towards enhancing transparency in AI/ML technologies in medical devices, promoting patient-centered care, informed decision-making, and safe use of these advanced technologies.

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Kunal Joshi
Kunal Joshi
Meet Kunal, our insightful writer and manager for the Machine Learning category. Kunal's expertise in machine learning algorithms and applications allows him to provide a deep understanding of this dynamic field. Through his articles, he explores the latest trends, algorithms, and real-world applications of machine learning, making it accessible to all.

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