Artificial intelligence is transforming pharmaceutical science by changing how data are analysed, predictions are generated, and decisions are supported throughout the medicine-development pathway. AI in Pharmaceutical Sciences: From Drug Discovery to Clinical Practice examines these changes within the scientific, technological, and professional framework of modern pharmacy.The book covers AI applications from drug discovery and molecular research to formulation, pharmaceutical analysis, quality evaluation, manufacturing, safety assessment, and clinical practice. It explains how machine learning and related computational approaches assist pattern recognition, outcome prediction, multidimensional data integration, and evidence-based decision support.The book emphasises not only what AI can achieve but also how to interpret its outputs in terms of data quality, model validation, biological plausibility, analytical reliability, patient relevance, and regulatory expectations. This approach connects computational innovation with established pharmaceutical principles rather than treating AI as an isolated technology. Written for pharmacy students, teachers, researchers, and pharmaceutical professionals, the book provides a structured foundation for understanding the current and emerging role of AI across pharmaceutical research, development, and clinical application.