A team coordinated by Jay Chhablani, MD, Vice Chair of Clinical Trials and Professor of Ophthalmology at the UPMC Vision Institute, has won a Thome Foundation two-year $500K grant for his project, “Personalized Assembloid Platform for Drug Discovery and Modelling of Age-Related Macular Degeneration.”
The team includes Dr. Ethan Rossi, PhD, a specialist in high-resolution cellular imaging; Dr. Susana da Silva, PhD, who specializes in developmental biology; Dr. Jonathan Vande Geest, PhD, Professor of Bioengineering at the University of Pittsburgh; and Dr. José-Alain Sahel, MD, Chair of the Department and a retina specialist.
“This research brings us closer to new ways to protect vision and improve eye health,” Dr. Chhablani said.
Age-related macular degeneration (AMD) is a major cause of vision loss, but scientists still do not fully understand how it progresses. The project aims to create a lab-grown retina model that mimics how key layers of the eye (retina, pigment cells, and blood vessels) interact in AMD. Using patient cells and advanced imaging, the team will study disease changes and test potential treatments. “This model could help doctors predict how AMD progresses and find better, more personalized treatments,” Dr. Chhablani added.
Using clinical images, the innovative AI-powered tool for segmenting geographic atrophy (GA) and ellipsoid zone (EZ) loss enables precise AI-driven segmentation while allowing manual correction, ensuring users can validate each scan for EZ loss and hypertransmission with confidence.
GA is an advanced form of AMD that primarily affects older adults, typically those over 60 years of age. It leads to progressive loss of retinal cells, causing blind spots in central vision. People with a family history of AMD, smoking habits, or certain genetic factors are at higher risk. EZ is a key retinal layer representing healthy photoreceptor function. EZ loss is often seen in GA patients and is an important imaging biomarker for tracking disease progression.
Understanding GA and EZ loss helps doctors predict vision decline and monitor how well treatments are working. “Imaging biomarkers like EZ loss can guide early diagnosis, personalized treatment plans, and clinical trial development,” Dr. Chhablani said. “As new therapies emerge, these biomarkers will be crucial for selecting the right patients and measuring treatment effectiveness.”
While no cure currently exists for GA, research into biomarkers, AI-driven imaging analysis from clinical images, and personalized medicine will pave the way for earlier detection and better interventions. Using these assembloid models, formed from normal and diseased patients’ cells, a 3D model of the human retina will benefit from the expertise of Dr. da Silva in developmental biology and the team of Dr. Vande Geest on extracellular matrix. High resolution imaging will be adapted by Dr. Rossi’s team.
“Studies like ours, which develop realistic lab models of AMD from our patients, help test new drugs and improve our understanding of how to slow or stop vision loss,” Dr. Chhablani said. “The future of AMD care lies in precision medicine and innovative research – bringing hope for better treatments and improved quality of life for patients.”