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Title: Modelling hepatitis C therapy—predicting effects of treatment

Abstract

Mathematically modelling changes in HCV RNA levels measured in patients who receive antiviral therapy has yielded many insights into the pathogenesis and effects of treatment on the virus. By determining how rapidly HCV is cleared when viral replication is interrupted by a therapy, one can deduce how rapidly the virus is produced in patients before treatment. This knowledge, coupled with estimates of the HCV mutation rate, enables one to estimate the frequency with which drug resistant variants arise. Modelling HCV also permits the deduction of the effectiveness of an antiviral agent at blocking HCV replication from the magnitude of the initial viral decline. One can also estimate the lifespan of an HCV-infected cell from the slope of the subsequent viral decline and determine the duration of therapy needed to cure infection. The original understanding of HCV RNA decline under interferon-based therapies obtained by modelling needed to be revised in order to interpret the HCV RNA decline kinetics seen when using direct-acting antiviral agents (DAAs). In addition, there also exist unresolved issues involving understanding therapies with combinations of DAAs, such as the presence of detectable HCV RNA at the end of therapy in patients who nonetheless have a sustained virologic response.

Authors:
 [1];  [2]
  1. Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
  2. INSERM, IAME, UMR, Univ. Paris Diderot, Paris (France)
Publication Date:
Research Org.:
Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1236682
Report Number(s):
LA-UR-15-20073
Journal ID: ISSN 1759-5045
Grant/Contract Number:  
AC52-06NA25396
Resource Type:
Journal Article: Accepted Manuscript
Journal Name:
Nature Reviews. Gastroenterology & Hepatology
Additional Journal Information:
Journal Volume: 12; Journal Issue: 8; Journal ID: ISSN 1759-5045
Country of Publication:
United States
Language:
English
Subject:
59 BASIC BIOLOGICAL SCIENCES; Biological Science

Citation Formats

Perelson, Alan S., and Guedj, Jeremie. Modelling hepatitis C therapy—predicting effects of treatment. United States: N. p., 2015. Web. doi:10.1038/nrgastro.2015.97.
Perelson, Alan S., & Guedj, Jeremie. Modelling hepatitis C therapy—predicting effects of treatment. United States. https://doi.org/10.1038/nrgastro.2015.97
Perelson, Alan S., and Guedj, Jeremie. Tue . "Modelling hepatitis C therapy—predicting effects of treatment". United States. https://doi.org/10.1038/nrgastro.2015.97. https://www.osti.gov/servlets/purl/1236682.
@article{osti_1236682,
title = {Modelling hepatitis C therapy—predicting effects of treatment},
author = {Perelson, Alan S. and Guedj, Jeremie},
abstractNote = {Mathematically modelling changes in HCV RNA levels measured in patients who receive antiviral therapy has yielded many insights into the pathogenesis and effects of treatment on the virus. By determining how rapidly HCV is cleared when viral replication is interrupted by a therapy, one can deduce how rapidly the virus is produced in patients before treatment. This knowledge, coupled with estimates of the HCV mutation rate, enables one to estimate the frequency with which drug resistant variants arise. Modelling HCV also permits the deduction of the effectiveness of an antiviral agent at blocking HCV replication from the magnitude of the initial viral decline. One can also estimate the lifespan of an HCV-infected cell from the slope of the subsequent viral decline and determine the duration of therapy needed to cure infection. The original understanding of HCV RNA decline under interferon-based therapies obtained by modelling needed to be revised in order to interpret the HCV RNA decline kinetics seen when using direct-acting antiviral agents (DAAs). In addition, there also exist unresolved issues involving understanding therapies with combinations of DAAs, such as the presence of detectable HCV RNA at the end of therapy in patients who nonetheless have a sustained virologic response.},
doi = {10.1038/nrgastro.2015.97},
url = {https://www.osti.gov/biblio/1236682}, journal = {Nature Reviews. Gastroenterology & Hepatology},
issn = {1759-5045},
number = 8,
volume = 12,
place = {United States},
year = {2015},
month = {6}
}

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Cited by: 14 works
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    Works referencing / citing this record:

    Mathematical modeling of within-host Zika virus dynamics
    journal, August 2018


    Development of a Comprehensive Dataset of Hepatitis C Patients and Examination of Disease Epidemiology in the United States, 2013–2016
    journal, June 2018


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    journal, August 2018


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    Interferon at the cellular, individual, and population level in hepatitis C virus infection: Its role in the interferon-free treatment era
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