This Principal Investigator proposes to develop models and statistical inferential tools for HIV-1 dynamics in vivo. The following specific aims are proposed: (1) to develop HIV-1 dynamic models which are applicable to virological data from AIDS clinical trials; (2) to develop statistical inferential tools for HIV-1 dynamics; (3) to develop statistical methods for assessing the virological response and activities of anti-HIV drugs and treatments using HIV-1 dynamics; (4) to model virological failure and drug-resistance to provide information for treatment and strategies; and (5) to study host-specific factors for viral dynamics. The techniques of approximation and reparameterization of biological compartment models will be used to achieve the first goal. To achieve the second goal, hierarchical nonlinear mixed-effect models will be used. To assess the response to antiviral drugs and treatments, the connection between the HIV-1 dynamic parameters and the drug efficacy will be established and statistical tools for the comparison of treatments based on dynamic parameters will be developed. To achieve the 4th goal, the developed HIV-1 dynamic models will be modified so as to consider the virological failure due to drug resistance and other factors. The covariate selection procedures for nonlinear mixed-effect models will be developed and studied, and then will be used to study host-specific factors for viral dynamics to achieve the last goal. The developed models in vivo and statistical inferential tools for HIV-1 dynamics may be used to accelerate AIDS clinical trials and the development of antiviral drugs. Also, treatment strategies may be studied using HIV-1 dynamic models. Thus, the proposed HIV-1 dynamic models in vivo and statistical inferential methodology will provide a powerful tool to understand the pathogenesis of HIV and to search for a cure for AIDS.
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