OBJECTIVES: Rapid Virologic Response (RVR) is currently used as the best predictor of Sustained Virologic Response (SVR) with dual therapy (DT) in genotype-1 chronic hepatitis C (G1-CHC), to optimize the adoption of the triple therapy (TT) with direct-acting antivirals (boceprevir: BOC and telaprevir: TVR). Bio-mathematical modelling of viral dynamics during DT has potentially higher accuracy than RVR in the identification of SVR patients. The objective of this study was to analyse the cost-effectiveness profile of a personalized anti-HCV therapy in F0-F2 G1-CHC based on a bio-mathematical model (model-guided strategy: MG) rather than on the RVR (guideline-guided strategy: GG). METHODS: A deterministic bio-mathematical model of the infected cell dynamics was validated in a cohort of 135 G1-CHC patients treated with DT at the University Hospital in Pisa, Italy. A lifetime health economic (HE) model was then developed to compare MG and GG strategies in the perspective of the Italian National Health Service. The model was alimented with observed data in the validation cohort, clinical variables and economic data available in the literature. A 3.5% discount rate was applied to outcomes and costs. One-way and probabilistic sensitivity analyses were run. RESULTS: the outcomes with MG- and GG-strategy were 19.1-19.4 and 18.9-19.3 quality-adjusted-life-years (QALY). Total per-patient lifetime costs were €25,200-€26,000 with MG-strategy and €28,800-€29,900 with GG-strategy. When comparing MG- with GG-strategy the former resulted more effective and less costly, being defined as dominant. CONCLUSIONS: The adoption of a SVR predictive criterion based on a bio-mathematical model, has the potential to improve the cost-effectiveness of a personalized anti-HCV therapy, allowing a more accurate identification of patients who can be effectively treated with DT and reserving high-cost BOC- and TVR-based TT for those who really need it.