Innovative Screening Strategies for Cyclodextrin Interactions: AI, Computational Models, and Experimental Approaches

Poor solubility remains one of the most persistent and costly challenges in pharmaceutical drug development. Inside this eBook you'll find peer-reviewed research and expert perspectives on how AI, machine learning, and molecular dynamics simulations are transforming cyclodextrin-based drug formulation. From a novel nomenclature system that enables AI-driven structural optimization to a landmark case study examining remdesivir's interactions with sulfobutylether-β-cyclodextrins, readers will gain actionable insight into predictive modeling strategies that reduce API waste, accelerate development timelines, and improve the odds of getting complex small molecules to patients.