Modeling The Population Dynamics Of Erythrocytes To Identify Optimal Drug Dosages For The Treatment Of Hepatitis C Virus Infection

Abstract

The current treatment for hepatitis C virus (HCV) infection – combination therapy with pegylated interferon and ribavirin – elicits sustained responses in only ~50% of the patients treated. Greater cumulative exposure to ribavirin increases response to interferon-ribavirin combination therapy. A key limitation, however, is the toxic sideeffect of ribavirin, hemolytic anemia, which often necessitates a reduction of ribavirin dosage and compromises treatment response. Maximizing treatment response thus requires striking a balance between the antiviral and hemolytic activities of ribavirin. Current models of viral kinetics describe the enhancement of treatment response due to ribavirin. Ribavirin-induced anemia, however, remains poorly understood and precludes rational optimization of combination therapy. Here, we develop a new mathematical model of the population dynamics of erythrocytes that quantitatively describes ribavirin-induced anemia in HCV patients. Based on the assumption that ribavirin accumulation decreases erythrocyte lifespan in a dose-dependent manner, model predictions capture several independent experimental observations of the accumulation of ribavirin in erythrocytes and the resulting decline of hemoglobin in HCV patients undergoing combination therapy, estimate the reduced erythrocyte lifespan in patients and describe inter-patient variations in the severity of ribavirin-induced anemia. Further, model predictions estimate the threshold ribavirin exposure beyond which anemia becomes intolerable and suggest guidelines for the usage of growth hormones. A small fraction of the population (~30%) with polymorphisms in the ITPA gene shows protection from ribavirin-induced anemia. The optimum dosage of ribavirin that can be tolerated is then dependent on the ITPA polymorphisms. Coupled with a previous population pharmacokinetic study, our model yields a facile formula for estimating the optimum dosage given a patient’s weight, creatinine clearance, pretreatment hemoglobin levels, and ITPA polymorphism. The reduced lifespan we predict is in agreement with independent measurements from breath tests as well as estimates derived from in vitro studies of ATP depletion. The latter estimates also agree with the extent of ATP depletion due to ribavirin that we predict from a detailed analysis of the nucleoside metabolism in erythrocytes. Our model thus facilitates in conjunction with models of viral kinetics the rational identification of treatment protocols. Our formula for optimum dose presents an avenue for personalizing ribavirin dosage. By keeping anemia tolerable, the predicted optimal dosage may improve adherence, reduce the need for drug monitoring, and increase response rates.