Artificial intelligence (AI) has emerged as a transformative technology in pharmaceutical sciences, enabling improvements in drug discovery, clinical trials, personalized medicine, and pharmaceutical manufacturing. The integration of machine learning (ML), deep learning (DL), natural language processing (NLP), and predictive analytics has accelerated research and development (R&D) processes while reducing operational costs and improving therapeutic outcomes. Recent advances in computational pharmaceutics, digital twins, and agent-based systems have further expanded the capabilities of AI in healthcare. This review article provides a comprehensive overview of AI methodologies, applications in pharmaceutical sciences, regulatory considerations, ethical challenges, and future trends. The manuscript aims to provide a structured and publication-ready review suitable for academic journals in pharmaceutical sciences.
Nidhi Chauhan1*, Parekh Prerna Jigneshbhai2*, Vijay Oza3, Siddik Ugharatdar4, Patel Bhavani5, Patel Brijesh6 (Wed,) studied this question.