Innovative and Future Trends in Personalized Medicine for Retinal Diseases

A special issue of Journal of Personalized Medicine (ISSN 2075-4426). This special issue belongs to the section "Personalized Therapy and Drug Delivery".

Deadline for manuscript submissions: closed (31 December 2025) | Viewed by 881

Special Issue Editor


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Guest Editor
Department of General and Pediatric Ophthalmology, Medical University of Lublin, 20-093 Lublin, Poland
Interests: retinal diseases; macular diseases; age-related macular degeneration (AMD); intravitreal injections; retinal surgery

Special Issue Information

Dear Colleagues,

Personalized medicine is rapidly transforming the landscape of retinal disease management, offering the potential for tailored treatments based on an individual's unique genetic and molecular profile. This approach moves beyond the traditional one-size-fits-all model, taking into account the complexities of individual variations in genes, environment, and lifestyle. By integrating genomic, epigenomic, and proteomic data, clinicians can gain a deeper understanding of disease mechanisms and tailor therapeutic strategies to an individual's specific needs. Personalized medicine is revolutionizing healthcare by employing advances in understanding the genetic factors and biological mechanisms behind disease, coupled with individual patient considerations, to make healthcare safer and more effective. The scope of personalized medicine extends beyond therapeutic interventions to encompass preventative strategies, identifying individuals at risk, and implementing preemptive measures to mitigate disease onset or progression. Recent advancements in areas such as imaging technologies, DNA sequencing, gene therapy, and stem cell biology have propelled clinical trials and rapidly changed the therapeutic outlook for retinal diseases.

For this Special Issue, we invite authors to contribute manuscripts that focus on notable advancements in the combined use of cutting-edge diagnostic techniques and targeted treatment strategies for retinal disorders. Through this Special Issue, we aim to enhance our understanding of the complexities associated with personalized medicine in this challenging field.

Dr. Joanna Dolar-Szczasny
Guest Editor

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Keywords

  • retinal disease
  • age-related macular degeneration
  • diabetic retinopathy
  • gene therapy
  • retinal biomarker
  • personalized medicine
  • retinal imaging
  • molecular profile
  • artificial intelligence in ophthalmology
  • inherited retinal diseases

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Published Papers (1 paper)

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17 pages, 1001 KB  
Systematic Review
The Role of Artificial Intelligence in Imaging-Based Diagnosis of Retinal Dystrophy and Evaluation of Gene Therapy Efficacy
by Weronika Chuchmacz, Barbara Bobowska, Alicja Forma, Eliasz Dzierżyński, Damian Puźniak, Barbara Teresińska, Jacek Baj and Joanna Dolar-Szczasny
J. Pers. Med. 2025, 15(12), 605; https://doi.org/10.3390/jpm15120605 - 5 Dec 2025
Cited by 1 | Viewed by 628
Abstract
Introduction: Inherited retinal dystrophies (IRDs) are genetically determined conditions leading to progressive vision loss. Developments in gene therapy are creating new treatment options for IRD, but require precise imaging diagnosis and monitoring. According to recent studies, artificial intelligence, especially deep neural networks, could [...] Read more.
Introduction: Inherited retinal dystrophies (IRDs) are genetically determined conditions leading to progressive vision loss. Developments in gene therapy are creating new treatment options for IRD, but require precise imaging diagnosis and monitoring. According to recent studies, artificial intelligence, especially deep neural networks, could become an important tool for analyzing imaging data. Material and Methods: A systematic literature review was conducted in accordance with PRISMA guidelines, using PubMed, Scopus, and Web of Science databases to identify publications from 2015 to 2025 on the application of artificial intelligence in diagnosing inherited retinal dystrophies and monitoring the effects of gene therapy. The included articles passed a two-stage selection process and met the methodological quality criteria. Results: Among all the included studies it can be noticed that the use of artificial intelligence in diagnostics and therapy of IRDs is rather effective. The most common method was deep learning with its subtype convolutional neural networks (CNNs). However, there is still a place for improvement due to various limitations occurring in the studies. Conclusions: The review points to the growing potential of AI models in optimizing the diagnostic and therapeutic pathway in IRDs, while noting current limitations such as low data availability, the need for clinical validation, and the interpretability of the models. AI may play a key role in personalized ophthalmic medicine in the near future, supporting both clinical decisions and interventional study design. Full article
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