Artificial intelligence applications rely on diverse datasets to make informed decisions. As datasets grow, algorithms improve in sensitivity and specificity. The challenge remains, how to handle this from a regulatory perspective without hindering innovation and delaying products into the market?
The FDA is considering modifications to the Software as a Medical Device Pre-Specifications (SaMD) that would allow for changes to be made because of learning and adaptation. The FDA’s goal is to ensure that the safety and effectiveness of the software as a medical device is maintained.
In this discussion, Shawnnah will lead an overview of the Software as a Medical Device Pre-Specifications (SaMD) guidance(s) and how the proposed FDA framework allows for iterative improvements of artificial intelligence and machine learning-based software as a medical device, while assuring patient safety.
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