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Posted 06 August 2021 | By Vatsal Chhaya, MSc, and Kapil Khambholja, PhD
FDA discussion paper
In April 2019, the FDA published a discussion paper on AI-ML‒based SaMD,1 describing the agency’s plan to regulate premarket review for AI- and ML-driven software modifications. As the part of its proposed framework, agency put forward a “predetermined change control plan” in premarket submissions, which included SaMD prespecifications and algorithm change protocol to enhance the mechanism of safeguarding the patients. The traditional regulatory pathway includes premarket approval, 510k notifications (premarket clearance), and de novo classification.
The software modifications can involve changes to the algorithm architecture and can be performed regarding performance and inputs (without changing intended use) and related to SaMD’s intended uses.
FDA proposed the application of the total product lifecycle (TPLC) regulatory approach to AI-ML‒based SaMD. The TPLC approach allows evaluation and monitoring of the product from the premarketing application stage to the postmarketing surveillance stage to ensure quality, safety, and effectiveness. The TPLC approach is based on the following principles:
Given the announcement of marketing authorization of a breakthrough device – cardiac ultrasound software – through de novo regulatory pathway since February 2020, there has been immense interest in the innovation of AI-based SaMD using the proposed framework. The authorization trend for similar devices continued thereafter.5 Thus, the FDA’s Digital Health Center of Excellence6 has delineated an action plan with operational guidance for both SaMD and software in a medical device, or SiMD.
In January 2021, the FDA published an action plan on AI-ML‒based SaMD.7 The paper was published in response to the feedback on the FDA discussion paper on proposed regulatory framework for AI in SaMD. The paper summarized the feedback and briefly described a plan containing five major actions.
Tags: EU, MDSW, SaMD, US
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