Modeling HCV kinetics under therapy using PK and PD information

Background: Mathematical models have proven helpful in analyzing the virological response to antiviral therapy in hepatitis C virus (HCV) infected subjects. Objective: To summarize the uses and limitations of different models for analyzing HCV kinetic data under pegylated IFN therapy. Methods: We formulate mathematical models and fit them by nonlinear least square regression to patient data to estimate model parameters. We compare the goodness of fit and parameter values estimated by different models statistically. Results/conclusion: The best model for parameter estimation depends on the availability and the quality of data as well as the therapy used. We also discuss the mathematical models that will be needed to analyze HCV kinetic data from clinical trials with new antiviral drugs.