Ophthalmology and Optometry

Ophthalmology and optometry constitute two interrelated disciplines that together underpin comprehensive eye care. Ophthalmology, as a medical speciality, is devoted to the diagnosis, treatment, and management of ocular diseases using advanced imaging techniques, minimally invasive surgical procedures, and novel therapeutic modalities. In parallel, optometry focuses on the examination of refractive errors, the prescription of corrective lenses, and the delivery of primary eye care. In recent decades, remarkable technological advances such as optical coherence tomography (OCT), high‐intensity focused ultrasound (HIFU), and digital imaging have facilitated more accurate diagnoses and personalised treatment strategies across both fields. The integration of artificial intelligence with traditional imaging modalities has further enabled the early detection of subtle retinal and choroidal changes, thus enhancing outcomes in conditions ranging from glaucoma to diabetic retinopathy. Collaborative efforts between ophthalmologists and optometrists are fostering multidisciplinary approaches that not only refine diagnostic precision but also ensure that therapeutic interventions are tailored to local healthcare settings and patient needs.

Research in Nature Index

Notable progress has been achieved in therapies targeting advanced retinal conditions. For instance, a 2023 study demonstrated that pegcetacoplan significantly slowed the progression of geographic atrophy secondary to AMD over two years, heralding a promising pharmacological avenue with an acceptable safety profile [1]. Other recent work emphasises data-driven approaches to diagnosis and prognosis. A newly developed foundation model employing self-supervised learning on 1.6 million unlabelled retinal images has shown consistent performance across multiple ocular and systemic disease detection tasks, underscoring the capability of artificial intelligence to reduce the reliance on extensive manual labelling [2].

These findings intersect with research on diabetic retinopathy, where a deep learning system was evaluated for predicting disease progression over five years. By analysing sizable datasets totalling hundreds of thousands of fundus images, this model achieved strong predictive accuracy for personalised screening intervals [3]. Additionally, complementary methods such as liquid-biopsy proteomics have broadened our understanding of ocular ageing, showing how specific protein profiles in the aqueous humour can indicate cellular changes in the retina. These novel techniques promise to further elucidate disease onset in conditions like diabetic retinopathy and Parkinson’s-related retinal degeneration [4].

Meanwhile, therapies intended to sustain or improve visual acuity in neovascular AMD have continued to refine treatment frequency and quality-of-life outcomes. Faricimab, a bispecific antibody with extended dosing up to every 16 weeks, demonstrated non-inferiority to established agents, indicating new possibilities for longer treatment intervals and reduced intervention burden [5]. Such extended regimens not only aim to maintain visual acuity but also relieve patient pressures arising from frequent injections, exemplifying the field’s drive for more efficient and personalised care.

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Technical terms

Geographic atrophy (GA): A late-stage form of AMD characterised by progressive loss of the retinal pigment epithelium and overlying photoreceptors.

Self-supervised learning: An artificial intelligence training approach that does not require large, fully annotated datasets, instead leveraging patterns and structures within unlabelled data.

Diabetic retinopathy: A microvascular complication of diabetes affecting the retina, potentially leading to vision loss when untreated.

Bispecific antibody: A specialised therapeutic protein engineered to bind two different molecular targets, often improving treatment efficacy.

References

1. Pegcetacoplan for the treatment of geographic atrophy secondary to age-related macular degeneration (OAKS and DERBY). The Lancet (2023).
2. A foundation model for generalizable disease detection from retinal images. Nature (2023).
3. A deep learning system for predicting time to progression of diabetic retinopathy. Nature Medicine (2024).
4. Liquid-biopsy proteomics combined with AI identifies cellular drivers of eye aging and disease in vivo. Cell (2023).
5. Efficacy, durability, and safety of intravitreal faricimab up to every 16 weeks for neovascular age-related macular degeneration. The Lancet (2022).

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