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A Hepatitis C Virus Infection Model with Time-Varying Drug Effectiveness: Solution and Analysis
Simple models of therapy for viral diseases such as hepatitis C virus (HCV) or human immunodeficiency virus assume that, once therapy is started, the drug has a constant effectiveness. More realistic models have assumed either that the drug effectiveness depends on the drug concentration or that the...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4125050/ https://www.ncbi.nlm.nih.gov/pubmed/25101902 http://dx.doi.org/10.1371/journal.pcbi.1003769 |
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author | Conway, Jessica M. Perelson, Alan S. |
author_facet | Conway, Jessica M. Perelson, Alan S. |
author_sort | Conway, Jessica M. |
collection | PubMed |
description | Simple models of therapy for viral diseases such as hepatitis C virus (HCV) or human immunodeficiency virus assume that, once therapy is started, the drug has a constant effectiveness. More realistic models have assumed either that the drug effectiveness depends on the drug concentration or that the effectiveness varies over time. Here a previously introduced varying-effectiveness (VE) model is studied mathematically in the context of HCV infection. We show that while the model is linear, it has no closed-form solution due to the time-varying nature of the effectiveness. We then show that the model can be transformed into a Bessel equation and derive an analytic solution in terms of modified Bessel functions, which are defined as infinite series, with time-varying arguments. Fitting the solution to data from HCV infected patients under therapy has yielded values for the parameters in the model. We show that for biologically realistic parameters, the predicted viral decay on therapy is generally biphasic and resembles that predicted by constant-effectiveness (CE) models. We introduce a general method for determining the time at which the transition between decay phases occurs based on calculating the point of maximum curvature of the viral decay curve. For the parameter regimes of interest, we also find approximate solutions for the VE model and establish the asymptotic behavior of the system. We show that the rate of second phase decay is determined by the death rate of infected cells multiplied by the maximum effectiveness of therapy, whereas the rate of first phase decline depends on multiple parameters including the rate of increase of drug effectiveness with time. |
format | Online Article Text |
id | pubmed-4125050 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-41250502014-08-12 A Hepatitis C Virus Infection Model with Time-Varying Drug Effectiveness: Solution and Analysis Conway, Jessica M. Perelson, Alan S. PLoS Comput Biol Research Article Simple models of therapy for viral diseases such as hepatitis C virus (HCV) or human immunodeficiency virus assume that, once therapy is started, the drug has a constant effectiveness. More realistic models have assumed either that the drug effectiveness depends on the drug concentration or that the effectiveness varies over time. Here a previously introduced varying-effectiveness (VE) model is studied mathematically in the context of HCV infection. We show that while the model is linear, it has no closed-form solution due to the time-varying nature of the effectiveness. We then show that the model can be transformed into a Bessel equation and derive an analytic solution in terms of modified Bessel functions, which are defined as infinite series, with time-varying arguments. Fitting the solution to data from HCV infected patients under therapy has yielded values for the parameters in the model. We show that for biologically realistic parameters, the predicted viral decay on therapy is generally biphasic and resembles that predicted by constant-effectiveness (CE) models. We introduce a general method for determining the time at which the transition between decay phases occurs based on calculating the point of maximum curvature of the viral decay curve. For the parameter regimes of interest, we also find approximate solutions for the VE model and establish the asymptotic behavior of the system. We show that the rate of second phase decay is determined by the death rate of infected cells multiplied by the maximum effectiveness of therapy, whereas the rate of first phase decline depends on multiple parameters including the rate of increase of drug effectiveness with time. Public Library of Science 2014-08-07 /pmc/articles/PMC4125050/ /pubmed/25101902 http://dx.doi.org/10.1371/journal.pcbi.1003769 Text en https://creativecommons.org/publicdomain/zero/1.0/ This is an open-access article distributed under the terms of the Creative Commons Public Domain declaration, which stipulates that, once placed in the public domain, this work may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. |
spellingShingle | Research Article Conway, Jessica M. Perelson, Alan S. A Hepatitis C Virus Infection Model with Time-Varying Drug Effectiveness: Solution and Analysis |
title | A Hepatitis C Virus Infection Model with Time-Varying Drug Effectiveness: Solution and Analysis |
title_full | A Hepatitis C Virus Infection Model with Time-Varying Drug Effectiveness: Solution and Analysis |
title_fullStr | A Hepatitis C Virus Infection Model with Time-Varying Drug Effectiveness: Solution and Analysis |
title_full_unstemmed | A Hepatitis C Virus Infection Model with Time-Varying Drug Effectiveness: Solution and Analysis |
title_short | A Hepatitis C Virus Infection Model with Time-Varying Drug Effectiveness: Solution and Analysis |
title_sort | hepatitis c virus infection model with time-varying drug effectiveness: solution and analysis |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4125050/ https://www.ncbi.nlm.nih.gov/pubmed/25101902 http://dx.doi.org/10.1371/journal.pcbi.1003769 |
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