Data Use Application 011
Lead applicant organisation name
Name of the legal entity that signs the contract to access the data.
Janssen Research & Development, LLC.
Project title
The title of the project/research study request that the applicant is investigating through the use of health data.
Understanding the progression of dry age-related macular degeneration and its impact on visual impairment.
Lay summary
A concise and clear description of the project. This should outline the problem, objective and the expected outcomes in language that is understandable to the general public.
Age-related macular degeneration (AMD) is a leading cause of blindness in patients over the age of 60. There are two forms: a “wet” form, due to growth of abnormal blood vessels underneath the retina, and a “dry" form due to degeneration of retinal cells. While there are successful treatments for wet AMD, there are limited approved treatments for dry AMD and no cure exists. Vision loss from advanced dry AMD is visualised as discrete areas of atrophy. These geographic atrophy (GA) lesions grow over time, resulting in irreversible vision loss. How lesions grow and their impact on vision is still poorly understood.
This research uses imaging data imaging to better understand progression of GA lesions and their effects on vision. Artificial Intelligence tools will help to identify imaging features that may inform how these lesions progress, beginning with establishing baseline features when a patient first presents in clinic and risk factors that are connected to disease progression. The study will then link imaging findings with visual acuity data to understand the relationship between lesions and patient function.
Public benefit statement
A description in plain English of the anticipated outcomes, or impact of project on the general public.
Improved understanding of early eye disease and risk factors that predict disease could prevent unnecessary vision loss through earlier treatment. An algorithm predictive of GA growth would allow estimation of how long it would take for a patient to have visual symptoms from this disease. Better understanding of risk factors and timing of disease progression can allow clinicians to better target future therapies to the individual patients at the right time. The algorithm could also help design better clinical trials, thereby increasing the potential success of finding a treatment for dry AMD, as well as help to personalise the treatment to individual patients.
Latest approval date
The last date the data access request for this project was approved by a data custodian.
2 August 2024
Dataset(s) name
The name of the dataset(s) being accessed.
Moorfields Geographic Atrophy Dataset
Access type
Determines whether the data will be accessed with an Trusted Research Environment (TRE) or via data release.
Data Licence Agreement. Data released to a secure and controlled environment under contract with the research applicant.
Data sensitivity level
The level of identifiability of the data being accessed, as defined by Understanding Patient Data.
Anonymised