There is an unmet need in patients with geographic atrophy (GA) for treatments that preserve and improve functional vision to maintain their independence and quality of life. The limited number of available treatments for GA have demonstrated structural benefits, but none have consistently shown significant functional outcomes in clinical trials. Currently, best-corrected visual acuity (BCVA) is considered the gold standard functional endpoint in clinical trials; however, in the case of GA, it cannot fully evaluate visual impairment or treatment response, particularly in fovea-sparing GA lesions. In addition, BCVA may not fully capture the functional impact of foveal and parafoveal scotomas. There is emerging evidence for the utility of other functional assessments that may provide a more robust representation of the functional impact of GA; however, the current utilization of these tests in GA clinical trials varies widely. This review aims to evaluate current functional endpoints in GA and their strengths and limitations based on characteristics such as strength of structure-function correlation, practicality and feasibility, and patient perspective. There are many factors to consider when choosing a functional vision assessment when designing a GA clinical trial, and each functional vision assessment has several advantages and disadvantages, which are summarized in this review article.

The eye provides novel insights into general health, as well as pathogenesis and development of systemic diseases. In the past decade, growing evidence has demonstrated that the eye's structure and function mirror multiple systemic health conditions, especially in cardiovascular diseases, neurodegenerative disorders, and kidney impairments. This has given rise to the field of oculomics-the application of ophthalmic biomarkers to understand mechanisms, detect and predict disease. The development of this field has been accelerated by three major advances: 1) the availability and widespread clinical adoption of high-resolution and non-invasive ophthalmic imaging ("hardware"); 2) the availability of large studies to interrogate associations ("big data"); 3) the development of novel analytical methods, including artificial intelligence (AI) ("software"). Oculomics offers an opportunity to enhance our understanding of the interplay between the eye and the body, while supporting development of innovative diagnostic, prognostic, and therapeutic tools. These advances have been further accelerated by developments in AI, coupled with large-scale linkage datasets linking ocular imaging data with systemic health data. Oculomics also enables the detection, screening, diagnosis, and monitoring of many systemic health conditions. Furthermore, oculomics with AI allows prediction of the risk of systemic diseases, enabling risk stratification, opening up new avenues for prevention or individualized risk prediction and prevention, facilitating personalized medicine. In this review, we summarise current concepts and evidence in the field of oculomics, highlighting the progress that has been made, remaining challenges, and the opportunities for future research.