A University of Surrey research professor has developed a mathematical model based on earlier models, for monitoring HCV progression and treatment response.
Philip J. Aston, PhD
A researcher from the University of Surrey, Guildford, UK, has developed a new mathematical model for gaining insight into the progression of the hepatitis C virus (HCV) as well as the effects treatment has on HCV infection in individual patients.
Mathematically modelling infections may give researchers more insight into the dynamics of infection prior to and following therapy, Philip J. Aston, PhD, a research professor at the University of Surrey told MD Magazine. It could also make more feasible longer-term predictions.
“In particular, variables that cannot be quantified experimentally, such as the healthy and infected hepatocytes in the HCV model, are included in the model and so the model can give insight into the behavior of these variables,” Aston said.
To form the new model, the study researcher, Aston performed a review of existing mathematical models of HCV infection. In this review, Aston examined the Neumann Model, which adapted models of HIV and hepatitis B (HBV) infections to HCV infections.
The first Dahari Model, which demonstrated that solutions can show a decline in viral load in response to treatment, was also examined. Additionally, the second Dahari Model was included in the review, with this model also possessing the ability to show the impact treatment has on viral load.
In the new mathematical model of HCV infection, Aston includes various components involved in infection and treatment, such as mathematical formulas for cell regeneration, stem cells, and infection of hepatocytes. Overall, the new mathematical model includes the concentration of healthy and infected hepatocytes and virions as well as components of the first Neumann and Dahari models.
Aston expressed interest in seeing whether his new mathematical model for HCV infections could be converted or adapted for other viral infections — considering the Neumann HCV model included in the new formula was initially adapted from HIV and HBV infections to HCV infections. Also, further study may be necessary to determine whether this model could effectively monitor viral load data of an HCV-infected patient receiving treatment, subsequently helping in monitoring prognosis and facilitating subsequent therapy optimization.
“A new model of HCV infection has been proposed by incorporating recent biological knowledge of HCV infection from which recommendations for changes to treatment are provided,” Aston said. “The new model has given rise to 3 recommendations for changes in the treatment of HCV.”
One of these recommendations involves the use of lower medication doses for effectively eliminating infection, particularly if the infection is detected and treated in its early stages. Additionally, the continuation of a low-level drug treatment for keeping a patient’s infection at a manageable level may be necessary if the virus level in the patient’s blood increases following treatment.
Also, as treatment progresses, the drug dose should be reduced as this would reduce the cost of treatment “as well as providing a reduction in side effects for the patient.”
“Further research which tests out each of the above 3 recommendations in a clinical setting would help to translate this research into clinical practice,” Aston concluded.
The study, "A New Model for the Dynamics of Hepatitis C Infection: Derivation, Analysis and Implications," was published online in the journal Viruses.