Optimal scheduling of drug treatment for HIV infection: Continuous dose control and receding horizon control

Hyungbo Shim, Seung Ju Han, Choo Chung Chung, Sang Won Nam, Jin Heon Seo

Research output: Contribution to journalArticle

61 Citations (Scopus)

Abstract

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 infection. 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 horizon 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 optimality. We also demonstrate the obtained open-loop optimal control is vulnerable to parameter variation of the model and measurement noise. To overcome this difficulty, we finally present nonlinear receding horizon control to incorporate feedback in the drug treatment.

Original languageEnglish
Pages (from-to)282-288
Number of pages7
JournalInternational Journal of Control, Automation and Systems
Volume1
Issue number3
StatePublished - 2003 Sep 1

Fingerprint

Drug therapy
Viruses
Scheduling
Control theory
Cells
Feedback

Keywords

  • Chemotherapy
  • HIV
  • Optimal control
  • Receding horizon control

Cite this

@article{9333748f877340e49b0237e5636ec8ff,
title = "Optimal scheduling of drug treatment for HIV infection: Continuous dose control and receding horizon control",
abstract = "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 infection. 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 horizon 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 optimality. We also demonstrate the obtained open-loop optimal control is vulnerable to parameter variation of the model and measurement noise. To overcome this difficulty, we finally present nonlinear receding horizon control to incorporate feedback in the drug treatment.",
keywords = "Chemotherapy, HIV, Optimal control, Receding horizon control",
author = "Hyungbo Shim and Han, {Seung Ju} and Chung, {Choo Chung} and Nam, {Sang Won} and Seo, {Jin Heon}",
year = "2003",
month = "9",
day = "1",
language = "English",
volume = "1",
pages = "282--288",
journal = "International Journal of Control, Automation and Systems",
issn = "1598-6446",
number = "3",

}

Optimal scheduling of drug treatment for HIV infection : Continuous dose control and receding horizon control. / Shim, Hyungbo; Han, Seung Ju; Chung, Choo Chung; Nam, Sang Won; Seo, Jin Heon.

In: International Journal of Control, Automation and Systems, Vol. 1, No. 3, 01.09.2003, p. 282-288.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Optimal scheduling of drug treatment for HIV infection

T2 - Continuous dose control and receding horizon control

AU - Shim, Hyungbo

AU - Han, Seung Ju

AU - Chung, Choo Chung

AU - Nam, Sang Won

AU - Seo, Jin Heon

PY - 2003/9/1

Y1 - 2003/9/1

N2 - 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 infection. 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 horizon 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 optimality. We also demonstrate the obtained open-loop optimal control is vulnerable to parameter variation of the model and measurement noise. To overcome this difficulty, we finally present nonlinear receding horizon control to incorporate feedback in the drug treatment.

AB - 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 infection. 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 horizon 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 optimality. We also demonstrate the obtained open-loop optimal control is vulnerable to parameter variation of the model and measurement noise. To overcome this difficulty, we finally present nonlinear receding horizon control to incorporate feedback in the drug treatment.

KW - Chemotherapy

KW - HIV

KW - Optimal control

KW - Receding horizon control

UR - http://www.scopus.com/inward/record.url?scp=4544281118&partnerID=8YFLogxK

M3 - Article

AN - SCOPUS:4544281118

VL - 1

SP - 282

EP - 288

JO - International Journal of Control, Automation and Systems

JF - International Journal of Control, Automation and Systems

SN - 1598-6446

IS - 3

ER -