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Author Spotlight: Understanding Retinal Vessel Resilience and Disease Progression
Published on: January 12, 2024
Development and Novel Therapeutics in Diabetic Retinopathy
Pravinkumar Ingle1, Nurin Alesya Hamden2, Wai Kei Soh2
1Department of Pharmacy Practice, School of Pharmacy, IMU University, Kuala lumpur, Malaysia.
Diabetic retinopathy (DR) is a growing diabetes complication causing vision loss. Optimizing current treatments and exploring new therapies, including AI, are crucial for better patient outcomes.
Area of Science:
- Ophthalmology
- Endocrinology
- Pharmacology
Background:
- Diabetic retinopathy (DR) is a significant complication of diabetes mellitus, leading to progressive retinal damage and potential vision impairment.
- The increasing global prevalence of DR necessitates advancements in treatment optimization and the development of novel therapeutic strategies.
- Current management includes anti-vascular endothelial growth factor (anti-VEGF) and corticosteroid therapies, but challenges remain.
Purpose of the Study:
- To review the epidemiological trends of diabetic retinopathy.
- To summarize current and emerging therapeutic interventions for DR, including pharmacological and technological advancements.
- To explore challenges in DR treatment development and the potential role of artificial intelligence (AI) in its management.
Main Methods:
- Literature review of epidemiological data on DR prevalence.
- Analysis of current pharmacological treatments (anti-VEGF, corticosteroids) and novel drug therapies in clinical trials.
- Exploration of modern treatments like laser therapy and the integration of AI in DR screening and management.
Main Results:
- DR prevalence is increasing, highlighting the need for improved treatments.
- Several pharmacological therapies are effective in reducing vision impairment risk.
- Novel drug therapies and AI applications show promise for enhanced DR diagnosis and management.
Conclusions:
- Optimizing existing treatments and developing new drugs are essential for managing DR.
- Addressing challenges like healthcare costs and improving mechanistic understanding is critical.
- AI integration offers significant potential for early diagnosis and improved patient care in DR management.
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