RETRACTED: AI-driven Design of Drug Delivery Systems: Strategies and Challenges in Overcoming Biological Barriers

The design of drug delivery systems encounters substantial challenges due to various biological barriers, such as the blood-brain barrier, mucus barrier, and intestinal barrier, which hinder effective drug delivery and targeted therapy. Recent advancements in artificial intelligence (AI) have introduced innovative approaches to overcoming these barriers, particularly by enhancing drug permeability and enabling precision. This review explores the role of AI-driven drug delivery systems in overcoming multiple biological barriers, with a particular focus on innovations targeting the blood-brain barrier, mucus barrier, corneal barrier, and intestinal barrier. By utilizing deep learning, data analytics, and optimized drug carrier designs, AI has made significant strides in improving drug targeting, penetration, and controlled release. Moreover, AI facilitates the development of personalized drug delivery systems, thus enhancing treatment potency while minimizing side effects. The integration of AI with conventional drug delivery platforms has the potential to advance precision medicine. However, despite these promising advancements, the successful clinical translation of AI-optimized drug delivery systems still faces technical and validation hurdles. Future progress in more efficient algorithms and enhanced interdisciplinary collaboration is essential for overcoming biological barriers and advancing personalized treatment, ultimately contributing more significantly to global health. This article explores how artificial intelligence, especially deep learning, advances drug delivery by helping overcome biological barriers like the blood-brain and intestinal barriers for improved therapeutic outcomes.