Generalized multiple internal standard method for quantitative liquid chromatography mass spectrometry

In this contribution, a multiplicative effects model for generalized multiple-internal-standard method (MEMGMIS) was proposed to solve the signal instability problem of LC-MS over time. MEMGMIS model seamlessly integrates the multiple-internal-standard strategy with multivariate calibration method, and takes full use of all the information carried by multiple internal standards during the quantification of target analytes. Unlike the existing methods based on multiple internal standards, MEMGMIS does not require selecting an optimal internal standard for the quantification of a specific analyte from multiple internal standards used. MEMGMIS was applied to a proof-of-concept model system: the simultaneous quantitative analysis of five edible artificial colorants in two kinds of cocktail drinks. Experimental results demonstrated that MEMGMIS models established on LC-MS data of calibration samples prepared with ultrapure water could provide quite satisfactory concentration predictions for colorants in cocktail samples from their LC-MS data measured 10 days after the LC-MS analysis of the calibration samples. The average relative prediction errors of MEMGMIS models did not exceed 6.0%, considerably better than the corresponding values of commonly used univariate calibration models combined with multiple internal standards. The advantages of good performance and simple implementation render MEMGMIS model a promising alternative tool in quantitative LC-MS assays.