Good Machine Learning Practices (GMLP) Working Group
Advances practical Good Machine Learning Practices for the responsible development, validation, deployment, and lifecycle management of AI-enabled technologies across medical devices and GxP environments with the ultimate goal of pioneering robust quality assurance frameworks for these innovative technologies. The Working Group is expanding foundational GMLP principles to address emerging capabilities such as Generative AI, large language models (LLMs), and agentic AI, while developing practical guidance that promotes safe, effective, trustworthy, and regulatory-aligned adoption throughout the AI lifecycle.
Working Group Leaders
Contributors:
Pat Baird, Philips
Alex Friedman, Olympus
Lacey Harbour, Pathway for Patient Health
Enes Hosgor, Gesund.ai
Shannon Hoste, Pathway for Patient Health
Anju Kurian, Elekta
Melissa Masters, CMD MedTech
Monica Montanez, NAMSA
Pinalee Nanda, NEC Oncolmmunity AS\
Don Peters, dPeters Consulting
Nithya Rajan, GE Healthcare
Melinda Smith, MH Smith Consulting
Rebecca Walters, Kaleidoscope
Publications:
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