[5440]

I'm a regulatory consultant for AI software and submit several AI/ML FDA submissions per week. Overall, I've submitted 100+ AI/ML submissions to date. Generally, FDA has been really focused on locked algorithms even though there has been some guidance lately stating the the new Good Machine Learning Practice (GMLP) will provide some allowance for iterations without submitting new 510ks. I will say that a number of companies are slightly tuning their algorithms without FDA resubmission within the confines of the FDA Guidance "https://www.fda.gov/regulatory-information/search-fda-guidan...". That said, most companies most companies are just leaving their specifications at sensitivity/specificity of 80% which gives them some leeway to improve above those limits. In truth most companies are above 97%-99%. While most of the submissions I work on are MRI/CT image related, I'm starting to get a lot more in the predictive space centered around ovarian (CA125), breast or PSA cancer scores. Lately pathology AI is escalating rapidly.

[brundolf]

Thanks for the informed and informative answer! I love how common it is on HN to hear from someone with first-hand knowledge of a topic