FDA on Modifying AI

Recently the FDA released a discussion paper on a Proposed Regulatory Framework for Modifications to Artificial Intelligence/Machine Learning (AI/ML)-Based Software as a Medical Device (SaMD). For starters this paper captures several familiar themes. One is that standalone software can be a medical device (SaMD) and therefore subject to FDA regulation. In the Clinical Decision Support space of standalone software this captures systems that are built by machine learning (ML), as opposed to systems that are rule-based, or more algorithmic. One way to appreciate this distinction is that for algorithmic systems the user can in principle access and therefore check the logic that the system uses to reach its conclusions. Whether such checking actually will occur is a separate matter. On the other hand ML based systems are in general derived from the automated review of large data sets in order to produce a mostly "black box" process of patient data in and answer (diagnosis, advice, suggestion, etc) out. There is essentially no underlying knowledge here (making "learning" perhaps the wrong word) and nothing that can be reasonably duplicated by the user. Once an ML product is cleared or approved by the FDA it may become necessary for the vendor to revise the system either because of errors or because new data is available. Regulatory issues associated with modifying a medical device are well known with the appropriate degree of further regulatory scrutiny depending in part on ...
Source: Medical Connectivity Consulting - Category: Information Technology Authors: Tags: Standards & Regulatory Source Type: blogs