Looking ahead, an area that deserves more attention is the development of AI-driven decision support tools in ophthalmology. While AI has been widely explored for image analysis, the real challenge—and opportunity—is integrating AI into clinical workflows to support diagnosis, prognosis and treatment planning in a way that is reliable, explainable and equitable.

Vita-Salute San Raffaele University, Milan, Italy

Vissum (Miranza Group)/Universidad Miguel Hernández Medical School, Alicante, Spain

I’m particularly excited about the advances in long-acting drug delivery systems (Susvimo) and gene therapy. With new clinical data expected later this year, we may soon have better tools to reduce treatment burden for chronic retinal diseases like AMD and DME. At the same time, AI integration into electronic health records is becoming a reality, which could streamline workflows, flag high-risk patients, and guide personalized treatment, all within a real-world clinical environment. I am also particularly enthusiastic about robot-assisted retina surgery, though I believe it will still take a couple of years to become commercially available in our field.

  Universidade Federal de São Paulo, Brazil