Artificial Intelligence/Machine Learning and 62304


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Because SaMD and Artificial Intelligence/Machine Learning software is different, I'm looking for recommendations to implement 62304 across our AL/ML software team and integrate with our QMS. Any recommendations are appreciated.
All the best,

Ed Panek

QA RA Small Med Dev Company
Super Moderator
We are in the middle of an AI submission. As Ronen states is the network continuously learning or are there controlled updates? You can use either one and FDA allows changes without new notifications within your ACP Algorithm Change Protocol.

I think FDA is borrowing ideas from the now-dead Pre Cert program where instead of discrete device approvals FDA Uses a trust in manufacturers' score ideas using audit results, complaints etc to "Pre-approve" changes in the field.


Starting to get Involved
We worked on AI SaMD solutions but we used the frozen algorithm approach to the AI/ML. The software around the AI was built in a classical manner. The AI was architecturally separated from the rest of the system. Then the AI was trained to achieve certain clinical performance. The whole software development followed the IEC62304 while the AI model was tested with the specified input/output configuration of the test data (of the clinical source). The product was released from Software Development Life Cycle (SDLC) level with the AI achieving specific clinical performance, which was equivalent to state of the art. On the PLC level, it has been confirmed with the clinical evaluation. So AI is equal to or slightly better than the current clinical practice. The New AI model needs to repeat the process, hotfixes in the non-AI part do not impact the clinical performance.


IEC 62304 is a great standard for ML-like development. One unique thing is that you would need to put under configuration management the data and ML models. The FDA wants to see that your company is able to reproducibly validate your model and have traceability across the Total Product Life Cycle.
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