Artificial Intelligence (AI) is rapidly transforming pharmaceutical sciences and healthcare by introducing data-driven, intelligent approaches across the drug development lifecycle and patient care continuum. From early-stage drug discovery to clinical evaluation, manufacturing, pharmacovigilance, and personalized medicine, AI technologies enable faster decision-making, improved accuracy, and enhanced efficiency. By integrating diverse data sources such as biological datasets, clinical records, real-world evidence, and patient-generated data, AI supports predictive modelling, precision therapeutics, and proactive safety monitoring. Furthermore, patient-centric applications including digital therapeutics, remote monitoring, and virtual health assistants are redefining healthcare delivery by extending care beyond traditional clinical settings. Despite these advancements, ethical concerns, regulatory challenges, data governance issues, and implementation barriers remain critical considerations. This review highlights the evolving role of AI in modern pharmaceutical sciences with a strong emphasis on patient-oriented healthcare, discusses current challenges, and outlines future perspectives toward fully personalized and predictive healthcare models. Responsible and collaborative integration of AI is essential to ensure sustainable innovation, patient safety, and equitable healthcare outcomes.
Neelam Begum1*, Mamilla Pavani2, Kankara Sirisha3, Eedara Vishnu Priya4, Ramala Revanth Reddy5, Ramavath Manikanta Nayak6 (Wed,) studied this question.