A video recording of a similar talk from Dr. Arup Chakraborty is available online here.
Infectious disease-causing germs are a threat that has plagued humanity since antiquity. Vaccination has often protected against these threats, and saved more lives than any other medical procedure. But, vaccines designed using the empirical paradigms pioneered by Pasteur and Jenner have failed against some pathogens. HIV, a highly mutable virus, is a prominent example. By bringing together theory/computation (rooted in statistical physics and machine learning) with basic and clinical immunology we translated data on HIV protein sequences to knowledge of the HIV fitness landscape – i.e., how the virus’ ability to propagate infection depends on its sequence. Predictions emerging from the fitness landscape were tested positively against in vitro and clinical data. I will discuss how a T cell-based vaccine was designed based on these findings and tested in pre-clinical studies in Macaques. I will then discuss work focused on understanding fundamental aspects of affinity maturation, and how affinity maturation may be manipulated by proper choice of antigens and vaccination protocols to elicit broadly neutralizing antibodies against highly mutable pathogens, such as HIV and influenza.
Jian Qin, Assistant Professor of Chemical Engineering, Stanford University
Pre-Seminar April 28th, 2020 at 4:00 PM over ZOOM