报告题目： Modeling a cancer combination immune-therapy with certainty: an immune checkpoint inhibitor and its synergy with an immunostimulant
报 告 人：Yang Kuang（况阳） 教授（Arizona State University）
负 责 人：王开发
报告时间：2026年05月25日（星期一）上午9:00－10:00
报告地点：数学大楼912报告厅
参加人员：教师、研究生、本科生
摘要：Immune checkpoint inhibitors (ICIs) are a novel cancer therapy that may induce tumor regression across multiple types of cancer. There has recently been interest in combining the ICIs with other forms of treatments, as not all patients benefit from monotherapy. We propose a mathematical model consisting of ordinary differential equations to investigate the combination treatments of the ICI avelumab and the immunostimulant NHS-muIL12. We validated the model using the average tumor volume curves provided in Xu et al. (2017). This mathematical model produce insightful conditions for local stability for both the tumorous and tumor-free steady states. Additionally, we conducted systematic mathematical analysis for the case that both drugs are applied continuously. Numerical simulations suggest that the two drugs act synergistically. Compared to monotherapy, about one-third the dose of both drugs is required in combination for tumor control.
报告人简介：Yang Kuang is a professor of mathematics at Arizona State University (ASU) since 1988. He received his B.Sc from the University of Science and Technology of China in 1984 and his Ph.D degree in mathematics in 1988 from the University of Alberta. He is the author of more than 200 refereed journal publications and 16 books (including 11 special issues) and the founder and editor of Mathematical Biosciences and Engineering. He has directed 28 Ph.D dissertations in mathematical and computational biology and many major multi-disciplinary research projects in US. He is well known for his efforts in developing practical theories to the study of delay differential equation models and models incorporating resource quality in biology and medicine. His recent research interests focus on the formulation and validation of scientifically well-grounded and computationally tractable mathematical models to describe the rich and intriguing dynamics of various within-host diseases and their treatments.
