FDA Developing Regulatory Framework for AI-Related Medical Devices
By HospiMedica International staff writers Posted on 16 Apr 2019 |
The US Food and Drug Administration {Silver Spring, MD, USA (FDA)} is considering a new regulatory framework specifically tailored to promote the development of safe and effective medical devices that use advanced artificial intelligence (AI) algorithms.
AI algorithms are already being used to aid in the screening for diseases and providing treatment recommendations. Until now, the FDA has granted clearance and marketing authorization to AI technologies, also called “locked” algorithms, which do not continually adapt or learn every time the algorithm is used. Manufacturers modify these locked algorithms at intervals such as “training” the algorithm using new data, followed by manual verification and validation of the updated algorithm. In the case of traditional software as a medical device, a sponsor is required to make a submission demonstrating the safety and effectiveness of the modifications.
However, machine learning algorithms that continually evolve, often called “adaptive” or “continuously learning” algorithms, do not require manual modification to incorporate learning or updates as they can learn from new user data presented to them through real-world use. For instance, an algorithm that detects breast cancer lesions on mammograms can learn to improve the confidence with which it identifies lesions as cancerous or could learn to identify specific sub-types of breast cancer by continually learning from real-world use and feedback.
The FDA is now exploring a framework that would allow for the modifications to algorithms to be made from real-world learning and adaptation, while simultaneously ensuring that the safety and effectiveness of the software as a medical device is maintained. The FDA is considering how an approach that enables the evaluation and monitoring of a software product from its pre-market development to post-market performance could provide reasonable assurance of safety and effectiveness and allow the agency’s regulatory oversight to embrace the iterative nature of these AI products while ensuring that its standards for safety and effectiveness are maintained.
“We’re taking the first step toward developing a novel and tailored approach to help developers bring artificial intelligence devices to market by releasing a discussion paper. Other steps in the future will include issuing draft guidance that will be informed by the input we receive. Our approach will focus on the continually evolving nature of these promising technologies. We plan to apply our current authorities in new ways to keep up with the rapid pace of innovation and ensure the safety of these devices,” said the FDA in its press release.
Related Links:
US Food and Drug Administration
AI algorithms are already being used to aid in the screening for diseases and providing treatment recommendations. Until now, the FDA has granted clearance and marketing authorization to AI technologies, also called “locked” algorithms, which do not continually adapt or learn every time the algorithm is used. Manufacturers modify these locked algorithms at intervals such as “training” the algorithm using new data, followed by manual verification and validation of the updated algorithm. In the case of traditional software as a medical device, a sponsor is required to make a submission demonstrating the safety and effectiveness of the modifications.
However, machine learning algorithms that continually evolve, often called “adaptive” or “continuously learning” algorithms, do not require manual modification to incorporate learning or updates as they can learn from new user data presented to them through real-world use. For instance, an algorithm that detects breast cancer lesions on mammograms can learn to improve the confidence with which it identifies lesions as cancerous or could learn to identify specific sub-types of breast cancer by continually learning from real-world use and feedback.
The FDA is now exploring a framework that would allow for the modifications to algorithms to be made from real-world learning and adaptation, while simultaneously ensuring that the safety and effectiveness of the software as a medical device is maintained. The FDA is considering how an approach that enables the evaluation and monitoring of a software product from its pre-market development to post-market performance could provide reasonable assurance of safety and effectiveness and allow the agency’s regulatory oversight to embrace the iterative nature of these AI products while ensuring that its standards for safety and effectiveness are maintained.
“We’re taking the first step toward developing a novel and tailored approach to help developers bring artificial intelligence devices to market by releasing a discussion paper. Other steps in the future will include issuing draft guidance that will be informed by the input we receive. Our approach will focus on the continually evolving nature of these promising technologies. We plan to apply our current authorities in new ways to keep up with the rapid pace of innovation and ensure the safety of these devices,” said the FDA in its press release.
Related Links:
US Food and Drug Administration
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