Artificial Intelligence in Precision Drug Design, Volume 2: Advanced Applications explores the transformative role of AI in modern drug discovery and development, presenting cutting-edge research and methodologies that integrate machine learning, network pharmacology, and computational modeling to accelerate therapeutic innovation. It covers a wide range of applications, including AI-driven drug repurposing, combination therapies, cancer immunotherapy, neuroscience, vaccine development, and molecular dynamics, but also delves into emerging technologies such as quantum computing, large language models, and graph neural networks. Designed for academics, this volume provides researchers, clinicians, and graduate students with a resource on the latest AI methodologies in precision medicine. Users will find this to be a great resource that supports evidence-based innovation, fosters interdisciplinary collaboration, and equips them with insights to advance personalized healthcare solutions. Presents state-of-the-art research on AI-driven drug repurposing, combination therapies, vaccine development, and molecular modeling, offering a comprehensive view of current innovations - Covers cutting-edge AI applications across drug discovery - Combines machine learning, network pharmacology, quantum computing, and large language models to address complex biomedical challenges with precision and scalability - Equips scholars, clinicians, and graduate students with practical insights and frameworks to accelerate personalized medicine and foster interdisciplinary collaboration Empowers researchers with cutting-edge AI tools to accelerate precision medicine and revolutionize therapeutic discovery Advanced Applications of Bioinformatics in Precision Drug Design: Volume 2: Advanced Applications explores the transformative role of AI in modern drug discovery and development. This volume presents cutting-edge research and methodologies that integrate machine learning, network pharmacology, and computational modeling to accelerate therapeutic innovation. The book covers a wide range of applications, including AI-driven drug repurposing, combination therapies, cancer immunotherapy, neuroscience, vaccine development, and molecular dynamics. It also delves into emerging technologies such as quantum computing, large language models, and graph neural networks, offering a comprehensive view of how AI reshapes biomedical research. Designed for an academic audience, this volume provides researchers, clinicians, and graduate students with a rich resource to understand the latest AI methodologies in precision medicine. It supports evidence-based innovation, fosters interdisciplinary collaboration, and equips readers with insights to advance personalized healthcare solutions. Dr. Khalid Raza is an Associate Professor at the Department of Computer Science, Jamia Millia Islamia, New Delhi, India, and an Adjunct Professor at UCSI University, Malaysia. He has over 14 years of teaching and research experience and previously served as an ICCR Chair Visiting Professor at Ain Shams University, Egypt. Dr. Raza has published more than 160 peer-reviewed papers and authored/edited over 15 books with Springer, Elsevier, and CRC Press. He serves as Academic Editor of PLoS ONE, BMC Artificial Intelligence, and Guest Editor of npj Precision Oncology, JoVE, and several other journals. Recipient of Clarivate’s (Web of Science) India Excellence Research Citation Award 2025, Dr. Raza is consistently featured in the World’s Top 2% Scientists list (2022–2025). His research focuses on AI, bioinformatics, and health informatics