Predicting where photoreceptors will fail in inherited retinal diseases
Photoreceptor Disease in Inherited Retinal Degenerations
This project uses AI to predict which small areas of the retina will lose photoreceptors over the next two years for people with RHO-related retinitis pigmentosa or ABCA4-related Stargardt disease.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of Pennsylvania NIH-funded |
| Lab location | 1 site (Philadelphia, United States) |
| Project ID | NIH-11262928 on NIH RePORTER |
What this research studies
From a patient perspective, researchers will train artificial-intelligence models on retinal images, genetic data, and clinical measures from people with two inherited retinal diseases (RHO-ADRP and ABCA4-STGD). The AI will generate individualized maps of retinal locations most likely to show fast photoreceptor loss over a two-year period. Those predictions will be compared with follow-up imaging and functional tests so investigators can see if the predicted spots actually change faster. The goal is to create reliable, patient-specific targets that clinicians and trials can monitor to detect treatment effects sooner.
Who could benefit from this research
Good fit: People with a confirmed genetic diagnosis of RHO-linked autosomal dominant retinitis pigmentosa or ABCA4-related Stargardt disease who can undergo retinal imaging and periodic follow-up visits are the best candidates.
Not a fit: People without these specific inherited retinal diseases, those with unrelated eye conditions, or those with very advanced, widespread photoreceptor loss are unlikely to benefit from this work.
Why it matters
Potential benefit: If successful, this could make clinical trials and care more efficient by focusing monitoring on the retinal spots most likely to change, helping detect real treatment benefits sooner.
How similar studies have performed: Previous studies have mapped average progression patterns in these diseases, but using individualized AI predictions of vulnerable photoreceptor locations is a newer approach with limited clinical validation so far.
Where this research is happening
Philadelphia, United States
- University of Pennsylvania — Philadelphia, United States (Active)
Researchers
- Principal investigator: Cideciyan, Artur V — University of Pennsylvania
- Study coordinator: Cideciyan, Artur V
About this research
- This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
- Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
- For full project details, budget, and progress reports, visit the official NIH RePORTER page below.