San Francisco, California, U.S., October 8, 2026
Verana Health and Bitfount have announced a collaboration to simplify and accelerate patient prescreening for ophthalmology clinical trials by combining artificial intelligence (AI), ophthalmic imaging and electronic health record (EHR) data. The collaboration aims to help clinical research teams identify potentially eligible participants more efficiently and accurately, supporting faster trial recruitment and reducing the burden of manual screening. The joint approach integrates AI-based analysis of existing eye images with relevant clinical information and compares these findings against each study’s eligibility criteria. The solution was recently clinically validated in a study conducted with Moorfields Eye Hospital, highlighting the potential of multimodal data analysis to support clinical research. By connecting imaging results with real-world clinical data, the companies aim to provide research sites with a more structured, pre-validated pool of potential participants while maintaining established privacy processes and existing imaging infrastructure.
AI Combines Eye Imaging and Electronic Health Records
The collaboration brings together Verana Health’s real-world data capabilities and Bitfount’s on-premise federated AI analysis platform. Under the approach, participating clinical research sites can assess potential eligibility using information from patients’ electronic health records alongside ophthalmic images, including optical coherence tomography (OCT) scans and fundus photographs. Bitfount’s AI analyzes existing images locally and generates an imaging eligibility flag for each patient. This flag appears alongside EHR-derived eligibility criteria, helping research teams assess whether individuals may qualify for a particular study. OCT and fundus imaging are widely used in ophthalmology to examine structures of the eye and support the diagnosis and monitoring of conditions such as diabetic retinopathy, glaucoma and macular degeneration. These images can provide clinically relevant information that may not be fully captured in structured medical records alone. Combining imaging with clinical data may therefore offer a more comprehensive way to prescreen patients for studies that require specific retinal findings, disease characteristics or other eligibility requirements. The integrated workflow compares available patient information with each clinical trial’s protocol-defined inclusion and exclusion criteria. This can help research teams identify candidates before undertaking more resource-intensive screening procedures. Final eligibility decisions still depend on the study protocol and the required clinical assessments; AI-assisted prescreening is intended to support, rather than replace, clinical research teams.
Verana Trial Connect Supports Research Site Workflows
The prescreening results are available through Verana Trial Connect (VTC), a HIPAA-compliant platform designed to support clinical trial recruitment, as well as through Bitfount’s on-premise application. VTC provides participating research sites with a pre-validated list of potential patients, including their imaging qualification status and relevant EHR-derived criteria. By organizing these results in a shared workflow, the companies aim to reduce manual chart review, improve screening efficiency and help minimize screen failures. Screen failures occur when individuals initially considered for a trial do not ultimately meet all eligibility requirements. Reducing unnecessary screening activity may help research teams use their resources more effectively and limit avoidable delays in enrollment. The companies also emphasize that the approach is designed to work with existing imaging infrastructure and established data privacy processes. Bitfount’s on-premise analysis model allows image analysis to take place locally, supporting a workflow in which sensitive clinical information can be assessed without requiring all underlying data to be centralized. The collaboration is intended to combine the benefits of AI-enabled analysis with practical requirements for healthcare data governance.
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Real-World Ophthalmology Data Could Support Faster Trials
Verana Health has access to real-world data from the American Academy of Ophthalmology’s IRIS Registry (Intelligent Research in Sight), which contains longitudinal, de-identified information covering more than 90 million patients from over 15,000 contributing clinicians. The company uses physician expertise and AI-driven analytics to support clinical research and the generation of real-world evidence. Bitfount contributes AI tools for ophthalmic image analysis, while Verana Health provides clinical data capabilities and the Verana Trial Connect workflow. Together, the companies aim to make patient identification more efficient and help clinical studies better reflect the characteristics of real-world patient populations. The collaboration reflects a broader effort to apply AI and real-world data to clinical trial recruitment, an area where delays in identifying suitable participants can affect study timelines and operational costs. The companies expect the combined approach to help research teams create more targeted patient pipelines and support ophthalmic research. The announcement does not establish that every trial will recruit faster or that the technology will eliminate screening failures. Its impact will depend on the study requirements, available data and implementation at participating sites. Nevertheless, integrating eye imaging with EHR information represents a practical approach to improving the prescreening process for ophthalmology studies and supporting the development of future treatments.
Source: Verana Health, Bitfount press release
