Modeling Viral Evolutionary Dynamics after Telaprevir-Based Treatment

摘要: For patients infected with hepatitis C virus (HCV), the combination of direct-acting antiviral agent telaprevir, pegylated-interferon alfa (Peg-IFN), and ribavirin (RBV) significantly increases chances sustained virologic response (SVR) over treatment Peg-IFN RBV alone. If do not achieve SVR telaprevir-based treatment, their viral population is often enriched telaprevir-resistant variants at end treatment. We sought to quantify evolutionary dynamics these post-treatment resistant variant populations. Previous estimates were limited by analyzing only sequence data (20% sensitivity, qualitative resistance information) from 388 enrolled in Phase 3 clinical studies. Here we add clonal analysis (5% quantitative) for a subset patients. developed computational model which integrates both quantitative data, forms framework future analyses drug resistance. The was qualified showing that deep-sequence (1% sensitivity) are consistent predictions. When determining median time populations revert 20% patients, predicts 8.3 (95% CI: 7.6, 8.4) months versus 10.7 (9.9, 12.8) estimated using solely genotype 1a, 1.0 (0.0, 1.4) 0.9 2.7) 1b. each individual patient, predicted typically comparable or faster than data. Furthermore, 11.0 2.1 after failure 99% wild-type HCV genotypes 1a 1b, respectively. Our modeling approach provides projecting accurate, assessment set consisting largely information.