11420E500100 工學院英文書報討論／Seminar

主題 TOPIC
▸　Novel Approaches and Applications of AI in Drug Discovery

❝　This presentation summarizes the application of artificial intelligence (AI) in drug discovery, focusing on its integration with traditional computer-aided drug design (CADD) methods such as docking, QSAR, and molecular dynamics. While conventional approaches support structure- and ligand-based design, they are often limited by scalability and efficiency. AI, including machine learning and deep learning, enhances drug development by enabling high-throughput analysis, predictive modeling, and generative design. It is applied across key stages, including target identification, hit discovery, lead optimization, and pharmacokinetics prediction. In small molecules, AI improves virtual screening and de novo design; in biologics, it supports antibody optimization and stability prediction; and in nucleic acid drugs, it enables sequence design and off-target analysis. Case studies demonstrate accelerated development timelines and improved success rates, even with limited datasets. However, challenges remain, including data quality, integration, expertise gaps, and ethical concerns such as bias. Overall, AI-driven approaches are transforming drug discovery into a more efficient and data-driven process, accelerating therapeutic development and advancing precision medicine. 　❞

講者 SPEAKER
▸　柯屹又副組長 Deputy Division Director Yi-Yu Ke
▸　工業技術研究院 生醫與醫材研究所生醫大數據組 Big Data Division, Biomedical Technology and Device Research Laboratories, Industrial Technology Research Institute (ITRI)

時間 TIME
▸　2026/04/28 (TUE) 13:00 ~ 14:30

地點 VENUE
▸　工程一館201教室 Classroom 201, Engineering Building 1