Clinical Research Directory

MIND-AMD Study: a Multidisciplinary Investigation of Neuroretinal Damage in Age-related Macular Degeneration.

Age-related macular degeneration (AMD) is the major cause of legal blindness in developed countries. Intermediate AMD represents the most frequent stage. However, it often evolves towards complicated stages, namely neovascular AMD or geographic atrophy (GA). Despite the available treatments, the visual outcome is highly heterogeneous. The scientific interest is growing regarding the assessment of neuroretinal changes in AMD. Although AMD is mainly considered an outer retinal disease, recent evidence suggests a major involvement of retinal glia and neurons, i.e. an involvement of the inner retina. This damage may remarkably affect the morphological and functional AMD outcome, subverting retinal signal transmission cascade and more clearly explaining the outcome of the disease. The main goal of this study is to perform a multidisciplinary, multicenter, both prospective and retrospective evaluation of neuroretinal degeneration in different AMD stages in preclinical and clinical models.

Ocular Proteomics Testing In Chronic Atrophy

Study to evaluate the safety of routine diagnostic anterior chamber paracentesis (ACP) for proteomic profiling in patients with geographic atrophy (GA)

Real-World Evaluation of AI Enabled Multi-Spectral Imaging (MSI) for AMD Biomarker Detection

The goal of this observational clinical study is to learn if DeepMSI AI detects age-related macular degeneration (AMD) biomarkers with sensitivity and specificity equivalent to experienced clinicians in adults over 40 years old. The main questions it aims to answer are: * Does DeepMSI AI detect AMD biomarkers with sensitivity equivalent to experienced clinicians? * Does DeepMSI AI detect AMD biomarkers with specificity equivalent to experienced clinicians? Participants' eyes will be imaged by MSI-120 and their images will be analyzed for AMD biomarkers by both DeepMSI AI and retina specialists independently. Researchers will compare retina image analysis from DeepMSI AI with ground truth (clinicians' interpretations) to see if AI achieves equivalency in sensitivity and specificity.