Course Objectives

Upon completion of this course, participants should be able to:

Examine new evidence for understanding the pathophysiology in nonexudative age-related macular degeneration
Examine new evidence for predicting disease progression in nonexudative age-related macular degeneration
Evaluate the benefits and limitations of different imaging and visual function technologies in the diagnosis and clinical management of macular and retinal diseases
Incorporate the latest advances in artificial intelligence, specifically machine learning, for the diagnosis and treatment of retinal diseases
Evaluate emerging therapies for the treatment of nonexudative age-related macular degeneration and review the real-world outcomes following the use of complement inhibitors in clinical practice to better understand the population most likely to benefit from these drugs
Evaluate therapies targeting novel disease pathways being investigated in early-stage clinical trials for nonexudative age-related macular degeneration
Provide an update on the next generation of anti-VEGF therapies recently approved and currently in development
Evaluate the clinical use of available anti-VEGF drugs for exudative ocular diseases
Evaluate emerging therapies for the treatment of exudative age-related macular degeneration and understand how we might use these new therapies in conjunction with established anti-VEGF drugs and better understand the population most likely to benefit from these new drugs