Switching Strategies to Mitigate HIV Mutation

Author

Hernandez-Vargas, Esteban Abelardo ; Colaneri, Patrizio ; Middleton, R.H.

Author_Institution

Dept. of Syst. Immunology, Helmholtz Centre for Infection Res., Braunschweig, Germany

Volume

22

Issue

4

fYear

2014

fDate

Jul-14

Firstpage

1623

Lastpage

1628

Abstract

HIV mutates rapidly and may develop resistance to specific drug therapies. There is no general agreement on how to optimally schedule the available treatments for mitigating the effects of mutations. With a switched positive linear system, we examined different control strategies applied to a higher order nonlinear mutation model. Simulation results suggest that model predictive control could outperform the common clinical treatment recommendations. This brief is a step forward to develop further tools for helping the practitioners to find the optimal treatment schedule.

Keywords

diseases; drugs; linear systems; medical control systems; microorganisms; optimal control; patient treatment; predictive control; time-varying systems; HIV mutation mitigation; clinical treatment recommendation; control strategies; drug therapies; higher order nonlinear mutation model; optimal treatment schedule; predictive control; resistance development; switched positive linear system; switching strategies; treatment optimal scheduling; Drugs; Human immunodeficiency virus; Immune system; Load modeling; Observers; Switches; HIV; model predictive control (MPC); mutation; positive systems; positive systems.;

fLanguage

English

Journal_Title

Control Systems Technology, IEEE Transactions on

Publisher

ieee

ISSN

1063-6536

Type

jour

DOI

10.1109/TCST.2013.2280920

Filename

6606820