Dynamic multidrug therapies for HIV: a control theoretic approach.

Motivated by the inability of current drug treatment to provide long-term benefit to HIV-infected individuals, we derive HIV therapeutic strategies by formulating and analyzing a mathematical control problem. The model tracks the dynamics of uninfected and infected CD4+ cells and free plasma virus, and allows the virus to mutate into various strains. At each point in time, several different therapeutic options are available, where each option corresponds to a combination of reverse transcriptase inhibitors. The controller observes the individual's current status and chooses among the therapeutic options in a dynamic fashion in order to minimize the total viral load. Our initial numerical results suggest that dynamic therapies have the potential to significantly outperform the static protocols that are currently in use; by anticipating and responding to the disease progression, the dynamic strategy reduces the total free virus, increases the uninfected CD4+ count, and delays the emergence of drug-resistant strains.