Subcategory: Chemical/Bimolecular/Process Engineering
Room: Exhibit Hall
Phineas Nyang’oro - North Carolina Central University
Co-Author(s): Henrik Pinholt, Massachusetts Institute of Technology, Cambridge, MAArup K. Chakraborty, Massachusetts Institute of Technology, Cambridge, MA
Traditional vaccines and immunization prevent millions of deaths from virus borne diseases annually across the globe. However, there exist highly mutable viruses such as HIV and SARS-CoV-19 that undergo many mutations within a host’s body, precluding traditional vaccines from providing protection against disease. To remedy this issue, the Arup K Chakraborty Lab for Computational Immunology has proposed methods for computationally predicting optimal vaccination protocols based on innate immunity. This required several simulations modeling the population dynamics of viruses and B-Cells and their interplay. The focus of the project was on creating models for viral population growth and decay by employing use of a series of Master Equations, a method by which one can quantify the rates of change between states within an environment. The realization of the project goals involved an analysis of model dynamics containing multiple strains of a virus due to its interactions with broadly neutralizing antibodies (bnAbs). This resulted in a new understanding of the parameter values that minimize viral populations. The mutation regimes that lead viruses to become susceptible to bnAbs were observed, showing low mutation rates and high mutation rates with high coverage result in almost to complete extinction, while moderate values lead to the proliferation of disease.
Funder Acknowledgement(s): I would like to thank the MIT Summer Research Program for funding my internship. I would also like to thank to my professor and PI, Dr.Arup K. Chakraborty, for providing me with the opportunity to work in his lab this summer and pairing me with my mentor, Henrik Pinholt, who helped me advance my project. Finally, I would like to thank all the members of the Chakraborty Lab for Computational Immunology for their assistance.
Faculty Advisor: Dr. Arup K. Chakraborty, Arupc@mit.edu
Role: Several simulations modeling the population dynamics of viruses and B-Cells and their interplay. The focus of the project was on creating models for viral population growth and decay by employing use of a series of Master Equations, a method by which one can quantify the rates of change between states within an environment.