Aston2018 - Dynamics of Hepatitis C Infection

  public model
Model Identifier
Short description
Related Publication
  • A New Model for the Dynamics of Hepatitis C Infection: Derivation, Analysis and Implications.
  • Aston PJ
  • Viruses , 4/ 2018 , Volume 10 , Issue 4 , PubMed ID: 29652855
  • Department of Mathematics, University of Surrey, Guildford, Surrey GU2 7XH, UK.
  • We review various existing models of hepatitis C virus (HCV) infection and show that there are inconsistencies between the models and known behaviour of the infection. A new model for HCV infection is proposed, based on various dynamical processes that occur during the infection that are described in the literature. This new model is analysed, and three steady state branches of solutions are found when there is no stem cell generation of hepatocytes. Unusually, the branch of infected solutions that connects the uninfected branch and the pure infection branch can be found analytically and always includes a limit point, subject to a few conditions on the parameters. When the action of stem cells is included, the bifurcation between the pure infection and infected branches unfolds, leaving a single branch of infected solutions. It is shown that this model can generate various viral load profiles that have been described in the literature, which is confirmed by fitting the model to four viral load datasets. Suggestions for possible changes in treatment are made based on the model.
Submitter of the first revision: Sarubini Kananathan
Submitter of this revision: Sarubini Kananathan
Modellers: Sarubini Kananathan

Metadata information

is (3 statements)
BioModels Database MODEL1808280002
BioModels Database MODEL1808280002
BioModels Database BIOMD0000000713

isDescribedBy (1 statement)
PubMed 29652855

hasTaxon (2 statements)
Taxonomy Homo sapiens
Taxonomy Hepacivirus C

hasProperty (2 statements)
Mathematical Modelling Ontology Ordinary differential equation model
Experimental Factor Ontology hepatitis C infection

Curation status


Connected external resources

SBGN view in Newt Editor

Name Description Size Actions

Model files

PVR.xml SBML L2V4 representation of Aston2018 - Dynamics of Hepatitis C Infection 36.00 KB Preview | Download

Additional files

Breakthrough.cps Copasi file for Breakthrough 62.41 KB Preview | Download
NullResponse.cps Copasi file for Null Response 62.29 KB Preview | Download
PVR.cps Copasi file for PVR 62.18 KB Preview | Download
Triphasic.cps Copasi file for Triphasic 62.21 KB Preview | Download

  • Model originally submitted by : Sarubini Kananathan
  • Submitted: Sep 6, 2018 3:20:58 PM
  • Last Modified: Oct 16, 2018 3:47:24 PM
  • Version: 8 public model Download this version
    • Submitted on: Oct 16, 2018 3:47:24 PM
    • Submitted by: Sarubini Kananathan
    • With comment: Automatically added model identifier BIOMD0000000713
  • Version: 5 public model Download this version
    • Submitted on: Sep 6, 2018 3:20:58 PM
    • Submitted by: Sarubini Kananathan
    • With comment: Model revised without commit message

(*) You might be seeing discontinuous revisions as only public revisions are displayed here. Any private revisions unpublished model revision of this model will only be shown to the submitter and their collaborators.

: Variable used inside SBML models

Species Initial Concentration/Amount

3.3246 mol

infected cell ; hepatocyte
417520.0 mol

Hepacivirus C
4450000.0 mol
Reactions Rate Parameters
T + V => I compartment*beta*T*V beta = 8.3376E-9
=> T; I compartment*r_T_Tmax*T/(T+I) r_T_Tmax = 10645.0
I => compartment*1/(1+R)*r_T_d*I R = 30.078; r_T_d = 0.0019927
T => compartment*r_T_d*T r_T_d = 0.0019927
V => compartment*c*V c = 17.908
=> I; T compartment*1/(1+R)*r_T_Tmax*I/(T+I) R = 30.078; r_T_Tmax = 10645.0
=> V; I compartment*pstar*I pstar = 203.96
Curator's comment:
(added: 16 Oct 2018, 15:44:17, updated: 16 Oct 2018, 15:44:17)
Figure 12 of the reference publication has been reproduced. The model file and figure attached is for the partial virologic response (PVR) of the viral load. Initial conditions were taken from the publication. The model was simulated using Copasi 4.22 and the figure was generated using Python 2.7.