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.

Highlights

  • Chronic hepatitis C virus (HCV) infection affects between 150 and 180 million people world-wide and is a major cause of chronic liver disease, cirrhosis and hepatocellular carcinoma

  • More realistic assumptions are that drug effectiveness either depends directly on the drug concentration or varies over time

  • A previously introduced varying-effectiveness (VE) differential equation model is studied in the context of HCV infection

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Summary

Introduction

Chronic hepatitis C virus (HCV) infection affects between 150 and 180 million people world-wide and is a major cause of chronic liver disease, cirrhosis and hepatocellular carcinoma. Neumann et al [3] showed that if plasma HCV RNA levels were measured frequently after treatment initiation with interferon one observed a biphasic decline after a short delay when the logarithm of HCV RNA/ml was plotted versus time on treatment (Fig. 1). This type of biphasic decline has been observed with many different types of HCV treatments including those employing PegIFN and RBV, and a variety of HCV protease and polymerase inhibitors [4,5,6,7,8,9,10]

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