15 Computational approaches for predicting drug solubility and permeability in pharmaceutical formulation

This study explores pharmacokinetic interactions among drugs, elucidating instances where one drug influences the absorption, transportation, distribution, metabolism, or excretion of another within the body. The development of pharmaceutical drugs is a complex, multidisciplinary endeavor, requiring a deep understanding of factors influencing drug efficacy and bioavailability, with a focus on the impact of chemical and physical properties on drug solubility and permeability. The likelihood of drug interactions increases for highly soluble drugs, manifesting through competitive binding to transporters or enzymes, or by modifying the solubility of coadministered drugs. Targeted drug delivery systems play a vital role in enhancing drug permeability and targeting, particularly in addressing central nervous system disorders, where drugs must possess specific physical properties and employ targeted transport mechanisms or strategies to cross the blood-brain barrier. Physical properties also wield influence over drug clearance and metabolism, further underscoring their significance in pharmaceutical development. The integration of computational approaches, specifically those leveraging artificial intelligence, has emerged as a transformative force in predicting drug solubility and permeability, gaining substantial popularity in drug discovery and development. In the realm of drug development, drug solubility and permeability stand as essential factors directly shaping a drug candidate’s success or failure. This abstract provides a comprehensive overview of the intricate dynamics of pharmacokinetic interactions, the impact of chemical and physical properties, targeted drug delivery, and the transformative role of computational approaches in pharmaceutical research and development.