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:

<<Return to PCC Home>>