Global approval and certification of ophthalmic AI devices: a comparative regulatory perspective

Grzybowski, Andrzej and Liu, T. Y. Alvin and Popovic, Marko M. and Zhao, Ally and Miyake, Masahiro and Takahashi, Hidenori and Kawasaki, Ryo and He, Mingguang and Gong, Xia and Göktaş, Polat and Jin, Kai (2026) Global approval and certification of ophthalmic AI devices: a comparative regulatory perspective. Asia-Pacific Journal of Ophthalmology, 15 (3). ISSN 2162-0989

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Abstract

Artificial intelligence (AI) tools are rapidly reshaping ophthalmology by improving screening and diagnosis for diabetic retinopathy, age-related macular degeneration, glaucoma, and increasingly retina-based systemic risk assessment. This narrative review provides a comparative assessment of regulatory pathways governing ophthalmic AI and software as a medical device (SaMD) across the United States, European Union, United Kingdom, Australia, China, Japan, Canada, India, and selected emerging jurisdictions. We used a structured search of public regulator databases, guidance documents, manufacturer disclosures, and peer-reviewed literature to assemble a representative sample of marketed or authorized devices through August 2025; the device inventory is illustrative rather than exhaustive. Key differences persist in device classification, evidence expectations, change management for adaptive algorithms, and post-market oversight. Examples such as LumineticsCore, EyeArt, DrNoon for CVD, CLAiR, and EyeWisdom illustrate how risk-based approaches vary across jurisdictions. These inconsistencies can delay multi-region deployment and complicate implementation, supporting the need for lifecycle-focused and internationally aligned standards for safe, transparent, and equitable use of ophthalmic AI.
Item Type: Article
Additional Information: This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
Uncontrolled Keywords: Artificial Intelligence; Certification; Medical device legislation; Ophthalmology
Divisions: Faculty of Engineering and Natural Sciences
Depositing User: Polat Göktaş
Date Deposited: 03 Jun 2026 12:34
Last Modified: 03 Jun 2026 12:34
URI: https://research.sabanciuniv.edu/id/eprint/54129

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