Authors: Kovuru. Rasi
Abstract: Artificial Intelligence (AI) is transforming the pharmaceutical industry by introducing advanced computational approaches for formulation design, drug delivery optimization, and personalized medicine. Conventional pharmaceutical development methods are often time-consuming, expensive, and dependent on repeated experimental trials. AI-based technologies such as machine learning, deep learning, artificial neural networks, and predictive analytics provide innovative solutions by analyzing large datasets, predicting formulation behavior, and optimizing drug delivery systems with improved precision and efficiency. AI assists researchers in identifying critical formulation variables, predicting drug–excipient interactions, enhancing stability, and improving bioavailability while reducing development time and manufacturing costs. In drug delivery optimization, AI supports the development of targeted, controlled, and patient-specific delivery systems including nanoparticles, liposomes, transdermal systems, and smart drug carriers. Furthermore, AI-driven models facilitate quality-by-design approaches, real-time monitoring, and automated decision-making during pharmaceutical manufacturing. The integration of AI with pharmaceutical sciences also promotes personalized therapeutics by enabling dose optimization according to patient-specific factors such as genetics, age, disease condition, and metabolic profile. Despite its significant advantages, challenges including data reliability, regulatory concerns, ethical issues, and the need for interdisciplinary expertise remain barriers to widespread implementation. This review highlights recent advancements, applications, benefits, challenges, and future prospects of AI in pharmaceutical formulation development and drug delivery optimization, emphasizing its potential to revolutionize modern pharmaceutics and improve healthcare outcomes.
DOI: http://doi.org/10.5281/zenodo.20696741
