David Crabb
PhD, Professor at City St George’s, University of London (UK)
A leader in multidisciplinary research studies with internationally recognized achievements in developing new approaches to measure vision, presents keynote “Age-related eye disease through the eyes of the patient”

David is Professor in the Department of Optometry and Visual Sciences at City St. George’s, University of London. He gained degrees in Mathematics and Statistics before completing a PhD in Visual Science. He has written more than 200 research papers and has led many multidisciplinary and multicentre research studies over more than 20-year period. Professor Crabb’s research laboratory contains a lively mixture of vision scientists, optometrists, psychologists, mathematicians and computer scientists. The Crabb Lab has attracted an international reputation focusing on measurement in vision, particularly in age-related eye disease. Themes of work include relating different stages of eye disease to patient’s everyday life, ocular imaging and image processing, design of new tests for visual disorders and using ‘big data’ to assesses health service delivery in eye clinics.

Web:: www.staff.city.ac.uk/crabblab  Twitter: @crabblab

Age-related eye disease –  through the eyes of the patient

Successful clinical management of age-related eye diseases such as glaucoma and age-related macular degeneration ought to be about making the right decisions to prevent meaningful loss of vision-related quality of life. Yet we still know relatively little about how different levels of vision loss, at different stages of these diseases, affect a person’s ability to carry out everyday tasks. One approach to addressing this gap is to measure patient performance in controlled laboratory tasks. Another is simply to ask patients themselves. The latter can be especially revealing, helping to demystify assumptions about how people perceive the world with progressive vision loss. Understanding these impacts is vital for both clinical care and clinical trials, where endpoints should reflect what matters to patients—how they read, navigate, drive, and recognize faces—not just small changes on clinical tests.