Optimal Scheduling of Drug Treatment for HIV Infection : Continuous Dose Control and Receding Horizon Control

It is known that HIV (Human Immunodeficiency Virus) infection, which causes AIDS after some latent period, is a dynamic process that can be modeled mathematically. Effects of available anti-viral drugs, which prevent HIV from infecting healthy cells, can also be included in the model. In this paper we illustrate control theory can be applied to a model of HIV infec- tion. In particular, the drug dose is regarded as control input and the goal is to excite an immune response so that the symptom of infected patient should not be developed into AIDS. Finite hori- zon optimal control is employed to obtain the optimal schedule of drug dose since the model is highly nonlinear and we want maximum performance for enhancing the immune response. From the simulation studies, we found that gradual reduction of drug dose is important for the optimal- ity. We also demonstrate the obtained open-loop optimal control is vulnerable to parameter varia- tion of the model and measurement noise. To overcome this difficulty, we finally present nonlin- ear receding horizon control to incorporate feedback in the drug treatment.

[1]  Martin A Nowak,et al.  Mathematical models of HIV pathogenesis and treatment. , 2002, BioEssays : news and reviews in molecular, cellular and developmental biology.

[2]  H. Schattler,et al.  On optimal controls for a general mathematical model for chemotherapy of HIV , 2002, Proceedings of the 2002 American Control Conference (IEEE Cat. No.CH37301).

[3]  D. Kirschner,et al.  Optimal control of the chemotherapy of HIV , 1997, Journal of mathematical biology.

[4]  V. Jansen,et al.  Effector cytotoxic T lymphocyte numbers induced by vaccination should exceed levels in chronic infection for protection from HIV. , 2001, Vaccine.

[5]  Alan S. Perelson,et al.  Mathematical Analysis of HIV-1 Dynamics in Vivo , 1999, SIAM Rev..

[6]  David Q. Mayne,et al.  Constrained model predictive control: Stability and optimality , 2000, Autom..

[7]  Ki Chang Kim,et al.  Study of an In-order SMT Architecture and Grouping Schemes , 2003 .

[8]  M. Martin-Landrove,et al.  A model for continuously mutant HIV-1 , 2000, Proceedings of the 22nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (Cat. No.00CH37143).

[9]  S. E. Tuna,et al.  Model predictive control when a local control Lyapunov function is not available , 2003, Proceedings of the 2003 American Control Conference, 2003..

[10]  M. Nowak,et al.  Specific therapy regimes could lead to long-term immunological control of HIV. , 1999, Proceedings of the National Academy of Sciences of the United States of America.

[11]  Guanrong Chen,et al.  Feedback control of a biodynamical model of HIV-1 , 2001, IEEE Transactions on Biomedical Engineering.

[12]  Robert F. Stengel,et al.  Optimal control of a viral disease , 2001, Proceedings of the 2001 American Control Conference. (Cat. No.01CH37148).

[13]  R. Stephenson A and V , 1962, The British journal of ophthalmology.

[14]  J.A.M. Felippe de Souza,et al.  Optimal control theory applied to the anti-viral treatment of AIDS , 2000, Proceedings of the 39th IEEE Conference on Decision and Control (Cat. No.00CH37187).

[15]  D. Wodarz,et al.  Helper-dependent vs. helper-independent CTL responses in HIV infection: implications for drug therapy and resistance. , 2001, Journal of theoretical biology.

[16]  Sang-Hui Park,et al.  A Rotation Invariant Image Retrieval with Local Features , 2003 .

[17]  M. Nowak,et al.  Dynamic multidrug therapies for HIV: a control theoretic approach. , 2015, Journal of theoretical biology.

[18]  Samuel E. Moskowitz Controlled Inquiry Rates of Clinical Interviews in Telehomecare , 2003 .

[19]  Andrew R. Teel,et al.  Enhancing immune response to HIV infection using MPC-based treatment scheduling , 2003, Proceedings of the 2003 American Control Conference, 2003..

[20]  Pini Gurfil,et al.  Optimal control of HIV infection with a continuously-mutating viral population , 2002, Proceedings of the 2002 American Control Conference (IEEE Cat. No.CH37301).

[21]  Rachel Levy,et al.  Modeling control of HIV infection through structured treatment interruptions with recommendations for experimental protocol , 2001 .