LuxIA, an AI algorithm co-developed by RetinAI US and non-profit organisation Fundación Ver Salud (FVS), has achieved CE-MDR certification as a Class IIb medical device in the European Union (EU) for diabetic retinopathy (DR) screening.
Granted under the EU Medical Device Regulation (EU MDR 2017/745), the certification was facilitated through RetinAI’s parent company Ikerian.
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LuxIA is tailored for screening diabetic adult patients for more-than-mild diabetic retinopathy (mtmDR), supporting ophthalmologists, trained healthcare professionals and general practitioners.
Its use is critical in achieving earlier diagnosis of mtmDR, a condition that threatens vision if left unchecked.
The certification underscores the joint commitment of the companies to offer AI-driven solutions that adhere to regulatory standards and improve clinical outcomes and patient management.
The device is compatible with digital 45° colour fundus images from Topcon cameras such as NW200 and NW400, facilitating integration into current clinical workflows.
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By GlobalDataLuxIA enhances RetinAI’s current portfolio of optical coherence tomography (OCT) analysis solutions, which are based on AI, contributing to a collection of clinically validated AI modules that are CE-certified for ophthalmology.
RetinAI co-founder and CEO Dr Carlos Ciller said: “Receiving CE-MDR certification for LuxIA underscores our shared commitment with FVS to advance leading-edge ophthalmic care to patients through reliable and impactful AI technology.
“This milestone is pivotal, enabling healthcare providers to improve patient management and outcomes for diabetic retinopathy across Europe, reinforcing our joint mission of transforming vision care through innovation.”
Ikerian and RetinAI US focus on developing software solutions that utilise machine learning and computer vision to expedite research, pharma, and clinical workflows globally.
Their focus spans ophthalmology, vascular conditions, rare, and neurodegenerative conditions. RetinAI’s tools are designed to collect, organise, and analyse ocular health data, aiding healthcare professionals in making timely decisions.
