Evidence map›Paper›PMID 25101902›Full record

ArticlePLoS computational biology2014

A hepatitis C virus infection model with time-varying drug effectiveness: solution and analysis.

Jessica M Conway, Alan S Perelson

Abstract read
In one paragraph

Article in PLoS computational biology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed.

  1. Trial
  2. Review
  3. Review
  4. Article
  5. Article
  6. Article
  7. Review
  8. Modelling hepatitis C therapy--predicting effects of treatment.Nature reviews. Gastroenterology & hepatology · 2015
    Review
  9. HCV Kinetic Models and Their Implications in Drug Development.CPT: pharmacometrics & systems pharmacology · 2015
    Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Jessica M ConwayTheoretical Biology and Biophysics, Los Alamos National Laboratory, Los Alamos, New Mexico, United States of America.
Alan S PerelsonTheoretical Biology and Biophysics, Los Alamos National Laboratory, Los Alamos, New Mexico, United States of America.

Funding

Collaborative Integration of HCV Molecular Virology and Mathematical ModelingR01AI078881 · NIAID · UNIVERSITY OF ILLINOIS AT CHICAGO · PI PERELSON, ALAN S, UPRICHARD, SUSAN L. · 2011 to 2025
$7.5M
Modeling Viral and T Lymphocyte DynamicsR01OD011095 · OD · TRIAD NATIONAL SECURITY, LLC · PI PERELSON, ALAN S · 2012 to 2024
$5.0M
COBRE Center for Evolutionary and Theoretical ImmunologyP20GM103452 · NIGMS · UNIVERSITY OF NEW MEXICO · PI LOKER, ERIC SAMUEL · 2012 to 2013
$4.2M
Immune System Modeling/HIVR01AI028433 · NIAID · UNIVERSITY OF CALIF-LOS ALAMOS NAT LAB · PI PERELSON, ALAN S · 1990 to 2021
$3.7M
Viral kinetic models of HCV clearance in hemophiliacs treated with telaprevirR34HL109334 · NHLBI · UNIVERSITY OF CINCINNATI · PI SHERMAN, KENNETH E · 2012 to 2013
$713k
Collaborative Integration of HCV Molecular Virology and Mathematical ModelingR56AI078881 · NIAID · UNIVERSITY OF ILLINOIS AT CHICAGO · PI PERELSON, ALAN S, UPRICHARD, SUSAN L. · 2010 to 2010
$421k
NHLBI NIH HHS R34 HL109334NHLBI NIH HHS R34-HL109334NIAID NIH HHS R01 AI028433NIAID NIH HHS R01-AI028433NIAID NIH HHS R01 AI078881NIAID NIH HHS R01-AI078881NIAID NIH HHS R56 AI078881NIGMS NIH HHS P20 GM103452NIGMS NIH HHS P20-GM103452NIH HHS R01 OD011095NIH HHS R01-OD011095
6 · The paper itself

Abstract

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.

Indexed as

Models, BiologicalAntiviral AgentsComputational BiologyHepacivirusHepatitis CHumansViral LoadAntiviral Agents

Identifiers

PMID25101902
PMCPMC4125050

What OpenQuestion holds

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Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.