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Machine learning (ML), a subset of artificial intelligence, has become integral across software in all industries, and the medical and life science spaces are no exceptions. ML can help medical systems improve the identification and diagnosis of disease, create personalized medicine, and help with drug discovery and manufacturing (just to name a few areas). Current guidance and regulations require validation of the final version of the software prior to a release\u2014so what does this mean for Software as a Medical Device (SaMD)<\/a> systems that incorporate ML and \u2018continual\u2019 algorithms designed to accumulate and improve knowledge after a system\u2019s release in the market?<\/p>\n The FDA and other regulatory agencies currently lack the guidance needed for medical device manufacturers<\/a> to include continual algorithms that adjust and improve post-market submissions. A changed algorithm would require a premarket review for each minor adjustment due to the potential impact on patient care.<\/p>\n There are many medical ML products on the market today, which currently use the DeNovo and 510(k) process, but the process is locked. Otherwise, the ML product would violate regulatory control. With this limitation, the FDA has been listening to input from the industry to help inform potential guidance and regulatory change.<\/p>\n In April 2019, the FDA released a paper called \u201cProposed Regulatory Framework for Modifications to Artificial Intelligence\/ Machine Learning (AI\/ML) Based Software as a Medical Device (SaMD).\u201d<\/a>\u00a0The paper describes and outlines a possible approach to a premarket review for artificial intelligence and machine learning-driven software modifications.<\/p>\n The proposed framework includes elements from the FDA\u2019s current premarket programs including:<\/p>\n One of the key proposed expectations from the FDA would be a commitment from manufacturers to be transparent with the constant monitoring of artificial intelligence and machine-learning-based software providing periodic updates, including any changes to algorithm protocols.<\/p>\n The proposed framework received positive feedback from the industry, and the FDA has now decided to implement the discussion paper with guidance. It is expected to be released sometime in 2021. The intended premarket approval process will allow a trusted manufacturer (see below for definition) to make pre-approved post-release changes only if the manufacturer follows a predetermined change control plan.<\/p>\n So what does the FDA mean by a trusted manufacturer?<\/p>\n Firstly, a trusted manufacturer should ensure they have an efficient and proactive quality system in place. Some of the key quality-related areas to focus on are:<\/p>\n Several other considerations are critical in becoming a \u2018trusted manufacturer\u2019 under the anticipated guidance, some of which include:<\/p>\n This is an exciting time for medical and life science companies embarking on or continuing their ML product\u2019s journey. Connect with us<\/a> to find out how Jama can help!<\/p>\n <\/p>\nThe Current Situation<\/h3>\n
Future FDA Regulatory Process<\/h3>\n
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What is a Trusted Manufacturer?<\/h3>\n
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