Modeling the emergence of drug-resistant mutants: Implications for treatment strategies for HIV-1 infection (Immune deficiency)

It is widely known that antiviral-drug treatment of human immunodeficiency virus type 1 (HIV-1) often fails as a result of the emergence of drug-resistant mutant viruses. The long-term feasibility of currently recommended combination therapy with potent antiviral-drugs may be questioned. Total eradication of the virus may not occur. Serious side effects and patient non-adherence to the therapy may dramatically increase the risk of drug-resistant mutations. Therefore, it is now recognized that careful therapeutic strategies must be developed to minimize the likelihood of developing drug-resistant mutants. One area of recent clinical research has focused on the possibility of strengthening the HIV-1 specific immune response to further suppress the viral load during anti-viral drug treatment. Several clinical trials are currently planned and being conducted to evaluate the effects of immunotherapy with combinations of antiviral-drug treatments.; In this dissertation, we evaluate different treatment strategies with antiviral-drugs and explore how host immune response affects the success of antiviral treatment strategies. We provide a new mathematical model which describes the deterministic growth dynamics of drug-resistant mutants in the effects of HIV-1 specific immune response. We also present a simple approach incorporating stochastic processes into the proposed deterministic model. Our stochastic model describes the random evolution of drug-resistant mutants during antiviral-drug treatments.; Monte-Carlo studies are finally conducted to evaluate the success of treatment strategies in minimizing the likelihood of the emergence of drug-resistant mutants.