Navigating regulatory and policy challenges for AI enabled combination devices
Abstract
Artificial Intelligence (AI) has made it possible for traditional Combination Devices (CDs) to innovate in the healthcare industry by combining the technology and healthcare sectors in recent years. Nonetheless, the difficulties, such as dependence on predicate devices, are highlighted in the US Food and Drug Administration's (FDA) 510(k) process, particularly for AI that is constantly evolving. Even though software and AI are included by the European Union's (EU) new Medical Device Regulations, it is still challenging to incorporate adaptive algorithms into conformance evaluations. It is underlined how urgently frameworks aware of AI concerns such as model deterioration and data biases are needed. Manufacturers' difficulties with regulations are clarified by case studies and insights from recalled equipment. Proposed are flexible policy frameworks that provide a balance between quick innovation and patient protections. In order to facilitate the safe, efficient, and egalitarian deployment of AI, recommendations are made to regulators and policymakers, promoting worldwide standards.
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References
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3570129
2. Khalid N, Qayyum A, Bilal M, Al-Fuqaha A, Qadir J. Privacy-preserving artificial intelligence in healthcare: Techniques and applications. Computers in Biology and Medicine. sciencedirect [Internet]. 2023 [cited 2025 Jan 6];158(1):106848 Available from:
https://www.sciencedirect.com/science/article/pii/S001048252300313X
3. Gasimova C. Privacy and Transparency in an AI-driven World: Does Algorithmic Transparency Fit on Data Privacy Under GDPR? [Internet]. SSRNR: NY; 2023 [cited 2024 Nov 16]. Available from:
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4482889
4. Künzle B, Kolbe M, Grote G. Ensuring patient safety through effective leadership behaviour: A literature review. Safety Science [Internet]. 2010 Jan 04 [cited 2025 Jan 3];48(1):1–17. Available from:
https://www.sciencedirect.com/science/article/abs/pii/S0925753509001143
5. Center for Devices and Radiological Health. Artificial Intelligence and Machine Learning in Software [Internet]. US:USFDA; 2019 Jan 4 [cited 2025 Jan 28]. Available from:
https://www.fda.gov/medical-devices/software-medical-device-samd/artificial-intelligence-and-machine-learning-software-medical-device
6. Santra S, Kukreja P, Saxena K, Gandhi S, Singh OV. Navigating regulatory and policy challenges for AI enabled combination devices. Frontiers in Medical Technology [Internet]. EU: health.ec.europa; 2024 Nov 28 [cited 2025];6:1473350. Available from:
https://health.ec.europa.eu/medical-devices-sector_en
7. Premarket Notification 510(k) [Internet]. US: USFDA;2025 [cited 2025 Jan 24]. Available from:
https://www.fda.gov/medical-devices/premarket-submissions-selecting-and-preparing-correct-submission/premarket-notification-510k
8. Health C for D and R. Artificial Intelligence and Machine Learning (AI/ML)-Enabled Medical Devices. [Internet]. US: USFDA;2024 Jul 18 [cited 2025 Jan 22]. Available from:
https://www.fda.gov/medical-devices/software-medical-device-samd/artificial-intelligence-and-machine-learning-aiml-enabled-medical-devices
9. Muehlematter U, Daniore P, Vokinger K. Approval of artificial intelligence and machine learning-based medical devices in the USA and Europe (2015–20): A comparative analysis. The Lancet Digital Health. sciencedirect [Internet]. 2021 Mar 1[cited 2025 Feb 4];3(3):e195–203 Available from:https://www.sciencedirect.com/science/article/pii/S2589750020302922
10. Center for Devices and Radiological Health. Artificial Intelligence and Machine Learning in Software [Internet]. USFDA:US; 2019 [cited 2025 Jan 21]. Available from:
https://www.fda.gov/medical-devices/software-medical-device-samd/artificial-intelligence-and-machine-learning-software-medical-device
11. Center. Emerging Drug Safety Technology Meeting (EDSTM) Program [Internet]. US:USFDA; 2024 [cited 2025 Feb 14]. Available from:
https://www.fda.gov/drugs/cder-emerging-drug-safety-technology-program-edstp/emerging-drug-safety-technology-meeting-edstm-program
12. EUR-Lex - Official Journal of the European Union [Internet]. Europa.eu:eu; 2025 [cited 2025 Feb 14]. Available from:
https://eur-lex.europa.eu/legal-content/EN/TXT/PDF/?uri=CELEX:32017R0745
13. EUR-Lex - Official Journal of the European Union [Internet]. Europa:eu; 2025 [cited 2025 Feb 11]. Available from:
https://eur-lex.europa.eu/legal-content/EN/TXT/PDF/?uri=CELEX:32017R0745
14. Medical Device [Internet]. EU: health.ec.europa; 2025 [cited 2025 Jan 5]. Available from:
https://health.ec.europa.eu/system/files/2020-09/md_mdcg_2019_11_guidance_qualification_classification_software_en_0.pdf
15. European Union. EUR-Lex - 32016R0679 - EN - EUR-Lex [Internet]. EU:Europa.eu; 2016 [cited 2025 Jan 5]. Available from:
https://eur-lex.europa.eu/eli/reg/2016/679/oj/eng
16. Health C for D and R. 510(k) Clearances [Internet]. US:USFDA; 2025[cited 2025 Jan 22]. Available from:
https://www.fda.gov/medical-devices/device-approvals-and-clearances/510k-clearances
17. HeartFlow FFRCT Analysis - Non-Invasive Cardiac Test www.heartflow.com [Internet]. US:heartflow;2024 [Cited 2025 Jan 15]. Available from:
https://www.heartflow.com/heartflow-ffrct-analysis/
18. IDx-DR [Internet].US:Healthvisors; 2024 [Cited 2025 Feb 4]. Available from:
https://www.healthvisors.com/en/idx-dr/
19. Aidence [Internet]. Aidence; 2024 [cited 2025 Feb 04]. Available from:
https://www.aidence.com/
20. EUR-Lex - 32017R0745 - EN - EUR-Lex [Internet]. EU: europa.eu; 2025 [cited 2025 Jan 03]. Available from:
https://eur-lex.europa.eu/eli/reg/2017/745/oj/eng
21. Center for Devices and Radiological Health. Artificial Intelligence and Machine Learning in Software [Internet]. US:USFDA;2025 [cited 2025 Jan 02]. Available from:
https://www.fda.gov/medical-devices/software-medical-device-samd/artificial-intelligence-and-machine-learning-software-medical-device
22. Health C for D and R. Digital Health Software Precertification (Pre-Cert) Pilot Program [Internet]: US: USFDA; 2022 [cited 2025 Jan 20]. Available from:
https://www.fda.gov/medical-devices/digital-health-center-excellence/digital-health-software-precertification-pre-cert-pilot-program
23. European Commission. Ethics Guidelines for Trustworthy AI [Internet]. EU:ec.europa; 2025 [cited 2025 Jan 03]. Available from:
https://ec.europa.eu/futurium/en/ai-alliance-consultation.1.html
24. Oren Y, Keromytis A. A Attacking the Internet using Broadcast Digital Television [Internet]. cs.columbia; 2014 Apr [cited 2025 Jan 01]; 46(4):1–37. Available from:
http://www.cs.columbia.edu/nsl/papers/2015/aether.tissec.pdf
25. Learning under Concept Drift: A Review [Internet]. US:Dntb.gov.; 2018 [cited 2025 Feb 14]. Available from: https://ouci.dntb.gov.ua/en/works/9JoQAQ17/
26. Santra S, Kukreja P, Saxena K, Gandhi S, Singh OV. Navigating regulatory and policy challenges for AI enabled combination devices. Front Med Technol. 2024 Nov 28;6:1473350. doi: 10.3389/fmedt.2024.1473350.
27. Liao, Q.V., Gruen, D., & Miller, S. Questioning the AI: Informing Design Practices for Explainable AI User Experiences. Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems; 2020.
28. Walsh KE, Marsolo KA, Davis C, Todd T, Martineau B, Arbaugh C, Verly F, Samson C, Margolis P. Accuracy of the medication list in the electronic health record-implications for care, research, and improvement. J Am Med Inform Assoc. 2018 Jul 1;25(7):909-912.
doi: 10.1093/jamia/ocy027.
29. Zou J, Schiebinger L. AI can be sexist and racist — it’s time to make it fair. Nature [Internet].nature; 2025 [cited 2025 Jan 18]; 559(7714):324–6. Available from:
https://www.nature.com/articles/d41586-018-05707-8
30. Briganti G, Moine OL. Artificial Intelligence in Medicine: Today and Tomorrow. Frontiers in Medicine [Internet]. Frontiersin; 2020 Feb 01[cited 2025 Feb 2];7(27). Available from:
https://www.frontiersin.org/articles/10.3389/fmed.2020.00027/full
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