Eye2Gene 1.0
Research type
Research Study
Full title
Eye2Gene: accelerating the diagnosis of inherited retinal diseases
IRAS ID
242050
Contact name
Nikolas Pontikos
Contact email
Sponsor organisation
University College London
Clinicaltrials.gov Identifier
Z6364106/2021/11/67, Data Protection reference number
Duration of Study in the UK
3 years, 0 months, 1 days
Research summary
Inherited retinal disease (IRDs) are a leading cause of visual impairment in the working age population. Mutations in over 300 genes are associated with IRDs and a genetic diagnosis, which involves identifying the affected gene in a patient, is the first step towards care and management of the patient. However, genetics diagnosis is currently slow, expensive and not widely accessible:
- Average time to diagnosis is over 5 years and costs £10,000 per patient.
- More than 40% of patients are undiagnosed (>10,000 individuals).The aim is to address the evidence gap in IRD diagnosis with an AI algorithm, Eye2Gene, to accelerate and democratise the IRD diagnosis service.
Currently Eye2Gene predicts the gene causing the disease from a retinal scan, with a top-5 accuracy of 88% on our internal dataset.
Using the data from this study, the Eye2Gene algorithm will be developed as a software medical device by:
1)Validating Eye2Gene on independent datasets from two external sites (Oxford University Hospital and Liverpool University Hospital)
2)Providing explainability by identifying specific abnormalities (IRD-specific features) in retinal scans.REC name
Wales REC 5
REC reference
22/WA/0049
Date of REC Opinion
29 Mar 2022
REC opinion
Further Information Favourable Opinion