Georgia Institute of Technology College of Sciences

Hepatitis C virus (HCV) infects 2.2% of the world's population and is a major cause of liver disease worldwide. There is no vaccine against HCV and current interferon and ribavirin (IFN/RBV) therapy is effective in 50%-60% of patients. Since the interferon therapy is the expansive and painful for the patient process, it is very important to predict its outcome before starting full course of treatment. HCV exists in infected patients as a large viral population of intra-host variants (quasispecies), which form the certain topological structure (sequence space) and may be differentially resistant to interferon treatment. We present a method for measuring differential interferon resistance of HCV quasispecies based on the mathematical modeling and analysis of HCV population dynamics during the first hours of interferon therapy. The analysis of the model allowed us to accurately predict the long-term outcome of the interferon therapy on the test group of patients.