Observational Study on Personalized Monitoring of Non-foveal, Non-vision Compromising Atrophic Age-Related Macular Degeneration Using Artificial Intelligence Tracking Disease Progression Over Two Years

What this Trial Is About

Researchers are conducting a prospective, multinational, multicenter observational study to assess and predict how non-foveal, non-vision compromising atrophic age-related macular degeneration AMD progresses in individual patients over two years. The study aims to measure the rate of progression, identify changes in the retina related to the disease, and evaluate the use of approved artificial intelligence AI algorithms to monitor AMD progression. This research is important as no treatment is currently approved in Europe for this condition. Participants will be followed for 24 months with check-ins every 6 months. During these visits, routine eye imaging tests will be performed, including Scanning Laser Fundus Photography, Color Fundus Photography, Optical Coherence Tomography, and Optical Coherence Tomography Angiography. Patients medical histories will be reviewed, and standard eye exams plus questionnaires about visual function will be completed. No specific treatment will be given as part of the study however, if a treatment becomes approved in the EU during the study, patients may receive it following standard care outside the study. Participants will undergo regular assessments focusing on imaging to characterize and quantify retinal changes linked to geographic atrophy progression. Researchers will use these images and AI tools to identify patients at risk for faster disease progression. Safety monitoring will continue throughout the 2-year period, and the study will collect data on disease progression biomarkers and AI monitoring effectiveness. This observational approach will help improve understanding of AMD progression without altering patient care during the study.

Personalized Monitoring of Non-foveal, Non-vision Compromising Atrophic Age-related Macular Degeneration With Artificial Intelligence and Identification of Disease Progression