Chronic hepatitis caused by the hepatitis C virus (HCV) is a serious global health problem. More than 170 million people around the world are currently HCV infected. A minority of patients spontaneously clears the virus, and the remaining with chronic infection are at risk for disease progression potentially leading to liver cancer and death. Although viral clearance can be achieved in a large number of chronically infected patients through current treatment with combination therapy, some viruses are more treatment resilient than others leaving many patients without treatment options. Encouraging new trials are leading to the approval of new drugs, however fast resistance development has already been found as their major drawback. This is because, as with HIV, the population of closely related hepatitis C viruses in the patient, also known as quasispecies, evolves rapidly in response to drug selective pressure. The first clinical trials have shown potential mutation patterns causing resistance, but much is still to be learned. This project thus aims to first develop and optimize techniques useful for mapping drug resistance mutations in routine clinical practice. The optimized techniques can then be applied to better characterize and understand the mutational patterns responsible for emerging in vivo drug resistance, and to ultimately develop, if needed, a resistance interpretation algorithm for optimizing individual patients’ treatment. The results of this project can be readily implemented in the management of HCV infected patients, giving clinicians additional tools to tailor treatment strategies for individual HCV patients.