Published Paper Details:

The blood-brain barrier (BBB) is a highly selective structural and functional interface that tightly regulates molecular transport between the bloodstream and the central nervous system, making brain drug delivery a major challenge. This review discusses the anatomy of the BBB, its cellular components--endothelial cells, astrocytes, pericytes, the basement membrane, and microglia--and the junctional complexes that restrict paracellular permeability. Conventional drug delivery approaches remain limited due to restricted permeability, active efflux mechanisms, and a mismatch between in-vitro and in-vivo models. Advances in artificial intelligence (AI) have transformed drug discovery and BBB transport research through improved target identification, molecular screening, de novo drug design, and drug repurposing. AI-driven models, including machine learning and deep learning, enhance the prediction of BBB permeability, optimize nanoparticle-based delivery systems, and integrate In-silico, in-vitro, and in-vivo datasets for better translational accuracy. Additionally, molecular dynamics simulations and computational nanotoxicology provide insight into nanoparticle interactions with BBB membranes, aiding the rational design of nanocarriers capable of crossing the BBB. Despite these advancements, limitations remain due to biological complexity, dataset scarcity, and reduced interpretability of AI algorithms. Overall, integrating AI with experimental BBB models offers a promising path toward more efficient CNS drug development and targeted therapeutic delivery.