Mathematical modeling of HIV -1 infection and drug therapy
Abstract
Significant contributions have been made to our understanding of HIV-1 dynamics by use of mathematical modeling and experimental data analysis. This thesis begins with a brief review of some basic models used to study virus infection and to estimate important parameters that govern viral production and viral clearance. Then some recent developments in the modeling of HIV-1 dynamics and antiretroviral response are presented. The main focus of this thesis is on the impact of various classes of antiretroviral drugs that target different stages of the viral replication cycle. Age-structured models are developed to study the influence of drug therapy on the within-host virus dynamics. The effectiveness of different drug combinations is compared. Two-strain models are also developed to study the mechanisms underlying the emergence of drug resistance during therapy. The influence of time-varying drug efficacy due to dosing schedule and suboptimal adherence on antiviral responses is investigated. Finally, the eclipse stage of HIV-1 infection is incorporated into mathematical models to study the evolution of drug resistant viral strains with consideration of trade-offs between viral enzyme function and drug susceptibility. Findings of these modeling studies would provide more insights into HIV-1 pathogenesis and help us improve the current treatment.
Degree
Ph.D.
Advisors
Feng, Purdue University.
Subject Area
Mathematics|Virology
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