In an era where medical innovation is more critical than ever, artificial intelligence (AI) offers unprecedented opportunities in the realm of healthcare, particularly in drug discovery and development. Harnessing AI for drug repurposing represents a frontier in accelerating the identification of new therapeutic uses for existing drugs, reducing time and costs associated with traditional drug development.
In this talk, we will explore the transformative potential of computational drug repurposing in the era of AI. We will delve into the applications of deep learning for drug-target prediction and drug sensitivity prediction, as well as the utilization of knowledge graphs to uncover hidden relationships between drugs and biological entities. Additionally, we will introduce the large language model (LLM) and discuss its potential in processing vast amounts of biomedical literature and clinical trial data to inform drug repurposing efforts. By highlighting real-world examples and case studies, this talk aims to provide a comprehensive overview of the opportunities and challenges that lie ahead in the field of AI-driven drug repurposing.
Join us to delve into how computational drug repurposing, powered by AI, can become a pivotal tool in swiftly and effectively responding to future healthcare challenges.
Now included in the IEEE Computer Society Chapters Featured Events Region 1 and Region 2 Coordinator;
Also included in IEEE Region 1 Professional Activities Webinars.
Speaker(s): Nansu Zong,
Virtual: https://events.vtools.ieee.org/m/389460