Pharmacoinformatics in Drug–Excipient Interactions

Drug-excipient interaction studies are critical in formulation development as they directly influence the stability and biopharmaceutical performance. Understanding these interactions aids in selecting compatible excipients to ensure optimal product development. In the evolving landscape of drug development, traditional experimental approaches are increasingly being complemented by advanced computational methods. Pharmacoinformatics is an interdisciplinary field that combines quantum chemical methods, molecular modeling, and artificial intelligence (AI) to advance drug development and formulation design. Particularly in studying drug-excipient interactions, it offers significant advantages in streamlining the formulation development process by enabling the understanding of molecular behavior and underlying interaction mechanisms. Quantum chemical calculations provide electronic/atomic-level insights into excipient complexes, while molecular modeling enables the visualization and simulation of dynamic behavior. AI models enhance the screening of excipients by learning recurring patterns from both experimentally and computationally estimated molecular descriptors. Many recent studies have demonstrated the applicability of computational tools in preformulation studies, screening, or prediction of drug-excipient complexes, understanding their properties that impact biopharmaceutical performance, and insights into their stability. This perspective highlights the role of pharmacoinformatics in drug-excipient interaction studies, discussing key advancements and future directions in pharmaceutical research.