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Background <p>Artificial intelligence is emerging as a transformative force in pharmaceutical sciences by enabling data-driven decision-making, automation, and predictive modeling. In ocular drug delivery, where therapeutic efficacy is hindered by complex anatomical and physiological barriers, AI presents significant opportunities to overcome these challenges. Its ability to optimize drug combinations, design smart delivery systems, and personalize therapies underscores its relevance in advancing ophthalmic care.</p> Area Covered <p>This review explores the intersection of AI and ophthalmic therapeutics, highlighting its role in formulation design, disease prediction, patient-specific treatment strategies, and smart delivery platforms, and outlines future research directions to bridge current gaps. Machine learning is advancing ocular drug delivery by optimizing nano-formulations, predicting release kinetics, and modeling pharmacokinetics. Alongside AI-powered diagnostics and integration with biosensors, contact lenses, and implants, these innovations are driving real-time monitoring and truly personalized ocular therapy and early detection and monitoring ocular diseases such as glaucoma, diabetic retinopathy, and macular degeneration. Challenges including limited clinical validation, model interpretability, data security, and regulatory complexities are highlighted. Furthermore, current gaps such as the lack of comprehensive studies on AI-assisted stimuli-responsive carriers and integration with patient-specific data are identified. Future directions emphasize explainable AI, smart biomaterials, and robust ethical-regulatory frameworks for clinical translation.</p> Expert Opinion <p>AI integration in ocular therapeutics marks a paradigm shift toward precision drug delivery and personalized care. Despite progress, challenges in explainability, regulation, and validation remain, yet innovations in AI-driven nanocarriers, smart systems, and real-time monitoring hold the potential to revolutionize ocular pharmacology overcoming limitations of conventional therapies.</p> Graphical Abstract <p></p>

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Artificial Intelligence in Ocular Drug Delivery: Precision Drug Delivery's New Horizon

  • 期刊论文

  • 发表日期：

    2025年12月12日

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  • Vaibhavi Srivastava,
  • Pragya Yadav,
  • Abhishek Yadav,
  • Poonam Parashar

摘要

Background

Artificial intelligence is emerging as a transformative force in pharmaceutical sciences by enabling data-driven decision-making, automation, and predictive modeling. In ocular drug delivery, where therapeutic efficacy is hindered by complex anatomical and physiological barriers, AI presents significant opportunities to overcome these challenges. Its ability to optimize drug combinations, design smart delivery systems, and personalize therapies underscores its relevance in advancing ophthalmic care.

Area Covered

This review explores the intersection of AI and ophthalmic therapeutics, highlighting its role in formulation design, disease prediction, patient-specific treatment strategies, and smart delivery platforms, and outlines future research directions to bridge current gaps. Machine learning is advancing ocular drug delivery by optimizing nano-formulations, predicting release kinetics, and modeling pharmacokinetics. Alongside AI-powered diagnostics and integration with biosensors, contact lenses, and implants, these innovations are driving real-time monitoring and truly personalized ocular therapy and early detection and monitoring ocular diseases such as glaucoma, diabetic retinopathy, and macular degeneration. Challenges including limited clinical validation, model interpretability, data security, and regulatory complexities are highlighted. Furthermore, current gaps such as the lack of comprehensive studies on AI-assisted stimuli-responsive carriers and integration with patient-specific data are identified. Future directions emphasize explainable AI, smart biomaterials, and robust ethical-regulatory frameworks for clinical translation.

Expert Opinion

AI integration in ocular therapeutics marks a paradigm shift toward precision drug delivery and personalized care. Despite progress, challenges in explainability, regulation, and validation remain, yet innovations in AI-driven nanocarriers, smart systems, and real-time monitoring hold the potential to revolutionize ocular pharmacology overcoming limitations of conventional therapies.

Graphical Abstract