AI-Driven Drug Delivery System Design and Optimization

Artificial Intelligence (AI) is revolutionizing pharmaceutical sciences by enabling rapid, accurate, and cost-effective drug delivery system (DDS) design and optimization. Conventional formulation development relies heavily on trial-and-error experimentation, which is time-consuming and resource-intensive. AI technologies such as machine learning (ML), deep learning (DL), artificial neural networks (ANN), and predictive analytics are transforming formulation development by predicting drug behavior, optimizing excipient selection, improving drug targeting, and enhancing therapeutic outcomes. AI-driven approaches are widely applied in nanotechnology-based drug delivery, personalized medicine, controlled release systems, and smart drug delivery platforms. This review discusses the role of AI in DDS design, optimization strategies, current applications, advantages, challenges, and future perspectives in pharmaceutics. Recent studies indicate that AI significantly accelerates pharmaceutical innovation while reducing development costs and experimental failures.