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AI-driven strategies for advancing corneal cell therapy: a promising frontier
Mahsa Fallah Tafti1, Masoud Khorrami-Nejad2,3, Masoud Arabfard4
1Vision Health Research Center, Semnan University of Medical Science, Semnan, Iran.
Abstract:
Cell-based therapies offer an alternative to corneal transplantation for the management of corneal diseases. However, these approaches require a deeper understanding of the principles of cell therapy, and the ability to predict and diagnose outcomes pre- and post-operatively is highly desirable. Recently, the development of innovative techniques that leverage predefined data from multiple cohorts with corneal diseases has received considerable attention. Approaches using artificial intelligence (AI) can address major concerns in corneal cell therapy, including the identification of novel biomarkers, improvements in cell delivery processes, and the acceleration of personalized treatments. This review summarizes real-world examples of AI applications from preclinical through clinical studies, with a focus on corneal cell-based therapies.
Insights
Artificial intelligence (AI) enhances corneal cell therapy by identifying biomarkers and personalizing treatments. This review explores AI
Area of Science:
- Ophthalmology and Regenerative Medicine
- Biotechnology and Biomedical Engineering
Background:
- Corneal diseases pose significant challenges, with transplantation having limitations.
- Cell-based therapies offer promising alternatives but require advanced understanding and outcome prediction.
- Current methods lack robust pre- and post-operative diagnostic capabilities.
Purpose of the Study:
- To review the application of artificial intelligence (AI) in corneal cell-based therapies.
- To highlight AI's role in addressing key challenges in the field.
- To showcase real-world examples from preclinical to clinical stages.
Main Methods:
- Literature review of AI applications in corneal cell therapy.
- Analysis of AI's impact on biomarker discovery, cell delivery, and personalized treatment.
- Synthesis of data from preclinical and clinical studies.
Main Results:
- AI facilitates the identification of novel biomarkers for corneal diseases.
- AI improves cell delivery processes and enhances treatment personalization.
- AI applications span from preclinical research to clinical trials in corneal cell therapy.
Conclusions:
- AI is a transformative technology for advancing corneal cell-based therapies.
- AI integration offers significant potential for improved patient outcomes and treatment efficacy.
- Further research and clinical translation of AI in this field are warranted.
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