GCI Seminar Series May 2024: How information technologies can aid the rational design of variant-proof vaccines and drugs
Presenter: Professor Matthew McKay, Department of Electrical and Electronic Engineering, University of Melbourne
Date and Time: Wednesday 15 May 2024, 12 - 1pm
Venue: Hybrid Event
- Room B120 (Theatre 2), Building 379 (207-221 Bouverie Street, Parkville 3010)
- or via Zoom Link - Meeting ID: 811 3463 1055, Password: 876985
ABSTRACT:
Complex dynamics and high genetic diversity of RNA viruses pose major challenges to vaccine and drug development. Intelligent models built using techniques from statistical physics, information theory, and machine learning, applied together with immunological and virological data, offer novel approaches to confront these challenges. This talk will introduce models for HIV, HCV and COVID-19 and will describe their use in predicting genomic “weak spots” that can guide vaccine and drug designs that seek to corner the viruses with targeted immune or therapeutic responses. A preclinical vaccine trial for HIV (in monkeys) designed based on these models will be described. Generally, the talk will demonstrate how concepts in data science and engineering, coupled with programmable biotechnology innovations (e.g., mRNA technologies, used in the Pfizer/BioNTech and Moderna COVID-19 vaccines) can aid the rational design of future-generation vaccines and therapies.
ABOUT THE PRESENTER:
Matthew McKay is an ARC Future Fellow and Professor in the Department of Electrical and Electronic Engineering at the University of Melbourne. He holds honorary appointments in the Department of Microbiology and Immunology and the Victorian Infectious Diseases Reference Laboratory (VIDRL) in the Doherty Institute. Matthew was previously a Professor at the Hong Kong University of Science & Technology. He has been a Research Scientist with the Institute for Medical Engineering & Science (IMES) at MIT and with the Department of Statistics at Stanford. He received his Ph.D. from the University of Sydney, is a Fellow of the IEEE, and has served as a Young Scientist of the World Economic Forum and the World Laureates Forum. In 2021, he was awarded the Australia-China Alumni Award for Research and Science by the Australia-China Alumni Association. Matthew’s areas of interest include machine learning and signal processing, infectious diseases and vaccines.