Understanding drug resistance for monotherapy treatment of HIV infection
type: Item
instance of: scholarly article
title: Understanding drug resistance for monotherapy treatment of HIV infection
zbMATH Open document ID: 0922.92011
DOI: 10.1007/BF02458429
author: Denise E. Kirschner
author: Glenn Webb
published in: Bulletin of Mathematical Biology
publication date: 1999-10-19T00:00:00Z
review text: A deterministic mathematical model is developed to investigate monotherapy treatment strategies of HIV patients in the presence of drug-resistant mutant HIV strains. The model is a nonlinear system of differential equations for the following five variables: the infected \(\text{CD}4^+\) \(T\) cells \(T(t)\), the wild-type virus and the mutant virus infected \(T\) cells \(T^s(t)\) and \(T^r(t)\), and the wild-type and the mutant viral load \(V_s(t)\) and \(V_r(t)\), respectively. Model features allow infection of \(T\) cells by both sensitive and resistant strains, release of newly produced virion, growth, mutation, clearance of virion, and \(T\) cell proliferation. Monotherapy is modeled for a variable time window by reduction of viral infectivity. This is implemented by multiplying the infection rate of \(T\) cells by free virus \(V_s\) and by multiplying with a treatment effectiveness parameter \(P_1\). A similar parameter \(P_2\) is applied to the external lymphoid system. A total of 27 model parameters -- 9 time dependent - are specified from clinical data. A numerical simulation study is performed to model the above described five variables for different treatment schedules on an individual basis. The results are compared qualitatively with clinical \(\text{CD4}^+T\) cell courses from 6 key AIDS studies performed between 1990 and 1995. Treatment benefit is based on increase or retention of \(\text{CD4}^+T\) cell counts and on low viral titer. Best monotherapy treatment effect is suggested by this model when the treatment starts in a middle region of \(250/\text{mm}^3\) to \(400/\text{mm}^3\) of \(\text{CD}4^+\) cell count and when a careful balance beteen mutant and wild-type HIV strains is achieved.
reviewed by: Lutz Edler
Mathematics Subject Classification ID: 92C50
Mathematics Subject Classification ID: 92B05
zbMATH DE Number: 1053267
zbMATH Keywords: AIDS model drug resistance
zbMATH Keywords: HIV infection treatment
zbMATH Keywords: deterministic model
MaRDI profile type: Publication
cites work: A model for treatment strategy in the chemotherapy of AIDS
cites work: A Mathematical Model of Combined Drug Therapy of HIV Infection
cites work: Dynamics of HIV infection of CD4\(^ +\) T cells
Wikidata QID: Q44348252
Recommended article: Emergence of HIV-1 drug resistance during antiretroviral treatment
Recommended article: HIV drug resistance: insights from mathematical modelling
Recommended article: Q3533221
Recommended article: Emergence of drug-resistance in HIV dynamics under distinct HAART regimes
Recommended article: Dynamic treatment model to examine the association between phenotypic drug resistance and duration of HIV viral suppression
Recommended article: Q4624278
Recommended article: Resistance to protease inhibitors in a model of HIV-1 infection with impulsive drug effects
Recommended article: Effects of combined drug therapy on HIV-1 infection dynamics
Recommended article: An optimal strategy for HIV multitherapy
Recommended article: Optimal treatment strategies derived from a HIV model with drug-resistant mutants
description: scientific article; zbMATH DE number 1053267