A review on artificial intelligence in pharmaceutical sciences: opportunities and challenges

SIGNIFICANCE: The review aims to systematically explore the transformative impact of artificial intelligence (AI) on pharmaceutical sciences. It addresses key research questions regarding how AI accelerates drug development, enhances clinical trial design, optimizes manufacturing, and drives advances in personalized and precision medicine. METHODS: A comprehensive literature review was conducted. It synthesized recent studies, industry reports, and regulatory guidelines on AI adoption. Covered drug discovery, clinical trials, pharmacovigilance, manufacturing, supply chain management, and pharmacy education. It also critically examined barriers such as data quality, privacy, explainability, and the evolving regulatory landscape. RESULTS: AI accelerates pharmaceutical R&D, identification, lead optimization, ADMET (absorption, distribution, metabolism, excretion, toxicity) prediction, drug repurposing, and clinical trial analytics. It enables faster and more cost-effective development. Advancements in personalized medicine and individualized patient data are driving better patient outcomes. The students still ace continuing challenges in data interpretation, privacy, and regulatory issues. CONCLUSIONS: Ongoing AI advancements and evolving regulations are set to revolutionize pharmaceutical science. They will enable efficient, predictive, and patient-centered healthcare. Success will depend on integrating multi-omics, adopting explainable AI, and fostering collaboration among all stakeholders. Ultimately, AI promises safer, faster, and more precise drug delivery system. It benefits clinicians, researchers, and students.