Collaborative Integration of HCV Molecular Virology and Mathematical Modeling

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Hepatitis C virus (HCV) is a hepatotropic virus that establishes chronic infection in ~70% of those exposed. As a result, currently more than 71 million people worldwide are infected and at increased risk of developing liver disease and hepatocellular carcinoma. While effective interferon (IFN)-free direct acting antiviral (DAA) therapeutic combinations are highly potent, the promise of DAAs has not yet put us on track to achieve the WHO goal of elimination by 2030. Reaching this goal will require a scaling-up of HCV screening, linkage-to-care, and reduction of treatment cost. Additionally, this will require understanding HCV spread, specifically how to prevent the spread of viral antiviral resistance variants within individuals such that these drug resistance viruses are not transmitted to the population. Importantly, viral cell-to-cell spread has been implicated in antiviral escape, immune escape, and persistence of viruses in general. Thus, the insights gained through the study of HCV should broadly inform future antiviral strategies. Mathematical modeling of HCV in the serum of infected patients during therapy has driven our understanding of HCV infection dynamics, the effect of IFN treatment, and led to methods for the quantitative evaluation of HCV treatment efficacy. Since FDA-approval of HCV DAAs, we have pioneered the development of multiscale models of DAA treatment response in vitro and in patients. This work revealed the dual mechanism of action of NS5A inhibitors and has demonstrated that viral kinetic modeling might allow for a reduction in the duration of DAA therapy in the majority of patients. These clinical insights have been informed by our modeling of HCV infection in cell culture where we are able to directly measure both intracellular and extracellular viral and cellular parameters. Applying both cell culture experimentation and in vivo patient data, we have recently obtained evidence that viral entry/spread plays a major role in the maintenance of steady state infection having broad implications regarding viral spread as an antiviral drug target and how spread impacts antiviral treatment response in terms of drug efficacy, viral escape, and drug synergy. Because these new models have raised important biological questions about HCV spread and antiviral drug strategies, the objective of this cross disciplinary R01 renewal is to enable the improvement of the treatment for HCV and other viruses by formulating and testing mathematical models of HCV infection and treatment response in vivo and in vitro. The specific aims are: 1) Refine and validate time to cure predictions using in vivo and in silico trials; 2) Elucidate quantitative details about the HCV life cycle and the role of hepatocytes in HCV clearance; 3) Expand and optimize mathematical models of HCV cell-to-cell spread; and 4) Determine the importance of cell-to-cell spread as an antiviral drug target.