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Using Viral Dynamics to Connect Clinical Markers of Disease Progression to Sequence Evolution for HIV-1
HIV-1 remains a global health challenge, with over 35 million people infected. The high rates of turnover and evolutionary adaptability exhibited by HIV-1 pose a particular challenge to the use of antiretrovirals, as well as the development of a vaccine. Our focus is to understand the dynamics of two of the most commonly tracked clinical markers of an HIV-1 infection: CD4+ T cells/mm3 (CD4 count) and HIV-1 RNA/ml (viral load). We are developing a dynamic mathematical model of HIV-1 infection that uses equilibration, adaptation, and inheritance to model the initial infection by a founding virus as well as successive generations of viral lineages. We have calibrated our model to match viral load set points and rates of CD4 decline from 91 HIV-infected individuals studied longitudinally during early stages of the disease. We plan to incorporate sustained tissue damage and antiretroviral treatment to study how drug resistance could develop.
Faculty Supervisor:
Alexander Rutherford
Student:
Partner:
Merck Canada Inc (Vancouver, BC);Providence Health Care;IBM Canada Ltd (Burnaby, BC)
Discipline:
Mathematics
Sector:
Manufacturing
University:
Simon Fraser University
Program:
Accelerate
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Mitacs is funded by the Government of Canada, the Government of Alberta, the Government of British Columbia, Research Manitoba, the Government of New Brunswick, the Government of Newfoundland and Labrador, the Government of Nova Scotia, the Government of Ontario, Innovation PEI, the Government of Quebec, the Government of Saskatchewan, and the Government of Yukon.