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Cellular Automata Model of Drug Therapy for
HIV Infection
Peter Sloot
1
, Fan Chen
1
, and Charles Boucher
2
1
Faculty of Sciences, Section Computational Science, University of Amsterdam
The Netherlands.
{
sloot, fanchen
}
@science.uva.nl
2
Department of Virology, University Hospital Utrecht, Utrecht University
The Netherlands.
C.Boucher@azu.nl
Abstract.
In this study, we employ non-uniform Cellular Automata
(CA) to simulate drugtreatment of HIV infection, where each computa-
tional domain may contain different CA rules, in contrast to normal uni-
form CA models. Ordinary (or partial) differential equation models are
insu
*
cient to describe the two extreme time scales involved in HIV infec-
tion (days and decades), as well as the implicit spatial heterogeneity [4,3,
10]. R.M.Zorzenon dos Santose [13] (2001) reported a cellular automata
approach to simulate three-phase patterns of human immunodeficiency
virus (HIV) infection consistingof primary response, clinical latency and
onset of acquired immunodeficiency syndrome (AIDS), Here we report
a related model. We developed a non-uniform CA model to study the
dynamics of drugtherapy of HIV infection, which simulates four- phases
(acute, chronic, drugtreatment responds and onset of AIDS). Our results
indicate that both simulations (with and without treatments) evolve to
the relatively same steady state (characteristic of Wolfram's class II be-
haviour). Three different drugtherapies (mono-therapy, combined drug
therapy and highly active antiretroviral therapy HAART) can also be
simulated in our model. Our model for prediction of the temporal be-
haviour of the immune system to drugtherapy qualitatively corresponds
to clinical data.
1
Introduction
1.1
Biological Background of HIV Infection
The infection of human immunodeficiency virus (HIV), causing AIDS (acquired
immunodeficiency syndrome), is almost invariably a progressive, lethal disease
with insidious time course. Currently, clinicians identified two common labo-
ratory markers for detection of disease progression (the amount of virus (HIV-
RNA) and the number of T helper cells (CD4 T cells) in blood. Immune response
for typical virus infection varies from days to weeks, but HIV infection typically
follows a three-phase pattern (See also Fig. 1).
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