Using Mathematical-Statistical Modeling to Inform the Design of HIV Treatment Strategies and Clinical Trials
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H. Thomas Banks, North Carolina State Universtiy  *Marie Davidian, North Carolina State University  Eric S Rosenberg, Massachusetts General Hospital 

Keywords: Adaptive treatment stratetgy, HIV dynamics, Simulation, Structured treatment interruption

Much progress has been made in management of HIV infection using highly active antiretroviral (ARV) therapies, but continuous treatment involves significant cost, burden, toxicities, drug resistance, and adherence problems. This has led to interest in "structured treatment interruption" (STI) strategies involving cycles of ARV withdrawal and initiation; however, studies of STI have been inconclusive, in part because the strategies evaluated may not have been the most advantageous to study. The speaker is part of a team (statistician, immunologist, mathematicians, control theorists) using HIV dynamic models for simulation-based design of HIV treatment strategies and clinical trials to study them. A clinical trial so designed is collecting extensive data that will be used to refine the models and design better strategies. We describe this multidisciplinary disease modeling approach.