Commentary discusses translating eye-derived biomarkers into systemic disease prediction, suggesting implications for clinical pathways.
The idea that the eye offers a window into systemic health is not new, but the scale, resolution and computability of ophthalmic imaging are unprecedented. Optical coherence tomography (OCT) and fundus photography are embedded in eye care, generating high-dimensional data that capture neural, vascular and structural biology in vivo. Linked to indices of systemic health and longitudinal outcomes, and analysed with modern machine learning, these data underpin oculomics: the use of ophthalmic biomarkers to detect, characterise or predict systemic disease [ 1 , 2 ]. This commentary suggests that the UK is uniquely placed to translate oculomics from retrospective association to clinically useful prediction, but success will depend less on algorithmic novelty than on governance, prospective validation, implementation and multidisciplinary, cross-sector collaboration to define its place within clinical pathways.
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Heatley et al. (2026) studied this question.
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