USA Law and Practice Contributed by: Nadia de la Houssaye, Andy Lee, Jason Loring and Graham Ryan, Jones Walker LLP
ing through federal agencies may affect investor sentiment. • Market consolidation and acquisition activity: Large healthcare technology companies increasingly acquire specialised AI start-ups to integrate inno - vative capabilities into comprehensive healthcare platforms. These acquisitions accelerate technol - ogy deployment while providing start-ups with the resources necessary for large-scale implementa - tion and regulatory compliance. 2. Legal Framework for Healthcare AI 2.1 Regulatory Definition and Classification of Healthcare AI The United States lacks a single, comprehensive def - inition of healthcare AI across regulatory agencies. Instead, different federal bodies provide context-spe - cific definitions tailored to their respective jurisdictions The FDA regulates healthcare AI primarily under exist - ing medical device frameworks, classifying AI-enabled software as “software as a medical device” (SaMD) when it meets specific criteria for medical purposes. The FDA’s traditional paradigm of medical device regulation was not designed for adaptive AI and ML technologies. This creates unique challenges for con - tinuously learning algorithms that may evolve after ini - tial market authorisation. In January 2021, the FDA issued the AI/ML-based SaMD Action Plan, which outlined the following five actions based on the total product life cycle (TPLC) approach for the oversight of AI-enabled medical devices: and regulatory frameworks. FDA Classification Approach • tailoring the regulatory framework with the issu - ance of draft guidance on predetermined change control plans (PCCPs); • harmonising good machine learning practices (GMLPs); • developing a patient-centric approach, including ensuring transparency of devices for users; • supporting methods for the elimination of ML algo - rithm bias and algorithm improvement; and
• working with stakeholders piloting real-world per - formance monitoring. Regulatory Categories by Function Healthcare AI systems receive different regulatory treatment in the United States based on their intended functions and clinical applications: • diagnostic AI systems undergo medical device regulation when they analyse patient data to pro - vide diagnostic information or recommendations; • therapeutic AI systems directly influence treatment decisions or provide therapeutic interventions, and therefore face the most stringent regulatory requirements; and • administrative AI systems used for non-clinical purposes such as scheduling, billing or operational management generally fall outside FDA medical device regulation but may be subject to other pri - vacy and security requirements. Emerging Classification Challenges As of late 2023, the FDA had not approved any devic - es that rely on a purely generative AI (genAI) architec - ture. genAI technologies can create synthetic content, including medical images or clinical text, which may require new regulatory approaches. The distinction between clinical decision support tools and medical devices remains an ongoing area of regu - latory clarification. Software that provides information to healthcare providers for clinical decision-making may or may not constitute a medical device depend - ing on the specific functionality and level of interpreta - tion provided. The Federal Food, Drug, and Cosmetic Act (FFDCA) provides the foundational legal framework governing healthcare AI systems that meet medical device cri - teria. In 2021, the Health Information Technology for Economic and Clinical Health Act (the “HITECH Act”) was amended to require the Health and Human Ser - vices (HHS) Secretary to further encourage regulated entities to bolster their cybersecurity practices. The 21st Century Cures Act clarified FDA authority over certain software functions while exempting specific 2.2 Key Laws and Regulations Federal Medical Device Regulation
127 CHAMBERS.COM
Powered by FlippingBook