The acquisition of high-quality quantitative dataset is the prerequisite for large-scale targeted metabolomics. However, the goal is usually dampened by the complexity of the biological matrices in terms of structural diversity, concentration span, and polarity range. We attempted herein to propose an analytical approach being able to circumvent these technical obstacles, and medicinal bile was employed as a proof of concept. In the liquid chromatography (LC) domain, reversed phase LC and hydrophilic liquid interaction chromatography were coupled in series, namely RPLC-HILIC, to yield appropriate chromatographic behavior for each component regardless of the polarity. In-depth chemical characterization and widely quantitative analysis were successively conducted in the mass spectrometry (MS) domain. Hybrid ion trap-time of flight MS was jointly deployed with hybrid triple quadrupole-linear ion trap MS for metabolite searching because of their orthogonal natures. Afterwards, a tailored MRM strategy that integrated online parameter optimization, ion intensity tailoring, and scheduled monitoring, was subsequently constructed to accomplish comprehensive quantitation although authentic compounds weren't involved and concentration span was quite large. Calibration curve was constructed for each detected identity by preparing and serially diluting the universal metabolome standard (UMS) solution that merged chemical information from all bile samples. Quasi-contents of 164 components including bile acids, sterols, eicosanoids, amino acids, lipids, flavonoids, and so forth, were gained by applying those regressive calibration curves and replaced the role of peak areas to serve as the variables for multivariate statistical analysis. In particular, the concentration ratio between tauroursodeoxycholic acid (TUDCA) and taurohyodeoxycholic acid (THDCA) that were exactly co-eluted as a single peak was calculated from the intensity specific value of m/z 498 > 80 over 498 > 124. Different metabolome occurred among various animal bile samples, and significant variations were also observed for different batches of bear bile powders. Bile acids acted as the indicative components in either discrimination. Overall, RPLC-HILIC–tailored MRM enabled quantitative metabolome profiling of medicinal bile and was thereby a promising analytical tool for large-scale targeted metabolomics.