A highly sensitive liquid chromatography-tandem mass spectrometry (LC-MS/MS) method was developed and validated for simultaneous determination of daclatasvir (DCV), simeprevir (SMV), sofosbuvir (SOF), and its major metabolite GS-331007 in human plasma using stable-isotope-labeled (SIL) analogs as internal standards (IS) to minimize a possible matrix effect. Liquid-liquid extraction (LLE) of the analytes and IS from human plasma was performed using a commercial extraction kit requiring low sample volume (50 μL). The analytes were eluted under a gradient program with mobile phase A (water + 0.1% formic acid) and mobile phase B (methanol + 0.1% formic acid) at a flow-rate of 0.6 mL/min for 10 min. The detection was performed on a Qtrap 5500 triple quadrupole tandem-mass spectrometer using multiple reaction monitoring (MRM) mode via the positive electrospray ionization interface. The method was validated according to the European Medicine Agency (EMA) guidelines over the clinically relevant concentration range of 15.6-2000 ng/mL. The high reproducibility, the low matrix effect associated with the use of SIL-IS, and the need of small sample amounts make this method particularly suited for high-throughput routine analysis. The proposed method was successfully applied to a retrospective clinical pharmacology study involving 67 HIV/HCV co-infected patients treated with a SOF-based therapy. DCV, SMV, SOF, and GS-331007 plasma levels were measured at week 4 of treatment and compared with the patients' clinical and laboratory characteristics. Higher GS-331007 plasma concentrations were observed in female patients compared to males, which can be explained by different anthropometric characteristics between genders. Importantly, patients with high plasma levels of GS-331007 also showed enhanced concentration of DCV and SMV probably due to a specific metabolic/pathological condition. Altogether, our findings indicate that the proposed method is a reliable and accurate new tool for high-throughput screening of large patient cohorts that could be readily used to optimize treatment modalities and reduce drug-related toxicities.