Abstract
In recent decades, mass spectrometry techniques, particularly when combined with separation methods such as high-performance liquid chromatography, have become increasingly important in pharmaceutical, bio-analytical, environmental, and food science applications because they afford high selectivity and sensitivity. However, mass spectrometry has limitations due to the matrix effects (ME), which can be particularly marked in complex mixes, when the analyte co-elutes together with other molecules, altering analysis results quantitatively. This may be detrimental during method validation, negatively affecting reproducibility, linearity, selectivity, accuracy, and sensitivity. Starting from literature and own experience, this review intends to provide a simple guideline for selecting the best operative conditions to overcome matrix effects in LC-MS techniques, to obtain the best result in the shortest time. The proposed methodology can be of benefit in different sectors, such as pharmaceutical, bio-analytical, environmental, and food sciences. Depending on the required sensitivity, analysts may minimize or compensate for ME. When sensitivity is crucial, analysis must try to minimize ME by adjusting MS parameters, chromatographic conditions, or optimizing clean-up. On the contrary, to compensate for ME analysts should have recourse to calibration approaches depending on the availability of blank matrix. When blank matrices are available, calibration can occur through isotope labeled internal standards and matrix matched calibration standards; conversely, when blank matrices are not available, calibration can be performed through isotope labeled internal standards, background subtraction, or surrogate matrices. In any case, an adjusting of MS parameters, chromatographic conditions, or a clean-up are necessary.
Highlights
Typical examples of “relative” matrix effects (ME) are encountered during the analysis of such biological fluids as urine or blood, in which the presence and concentration of sample interferences depend on factors such as patient variability, time points after dosing, diet, renal function, and metabolism [3,46,47]
Most authors do not discriminate between these two phenomena, and the lot variability is faced with the “classic,” approach used for most general absolute MEs, that is, to overcome MEs by taking care in sample preparation and pre-treatment, chromatographic conditions, and mass-spectrometric sources
The author reported that if the coefficient of variation (CV%) of their standard line slopes does not exceed 3–4%, the relative MEs can be considered negligible, and concluded that the comparison of the CV% values of standard line slopes of these five different lots with the analogous values obtained by repeated analysis (n = 5) in a single lot may serve as an excellent measure of relative MEs
Summary
Liquid chromatography-mass spectrometry techniques figure among the most powerful and useful analytical instruments for quantification of organic components in complex mixtures in environmental studies [1], food quality and composition research [2], and bioanalytical and pharmaceutical fields [3,4].Because of their sensitivity and specificity, especially in tandem mass mode, they are the techniquesMolecules 2020, 25, 3047; doi:10.3390/molecules25133047 www.mdpi.com/journal/moleculesMolecules 2020, 25, 3047 of choice in most private and government quality control laboratories [5,6], that apply validated analytical methods.Despite the advanced features of HPLC-MS technology, the validation process is not performed, especially because of its susceptibility to matrix effects (MEs) [7]. Liquid chromatography-mass spectrometry techniques figure among the most powerful and useful analytical instruments for quantification of organic components in complex mixtures in environmental studies [1], food quality and composition research [2], and bioanalytical and pharmaceutical fields [3,4] Because of their sensitivity and specificity, especially in tandem mass mode, they are the techniques. When a mass spectrometer is used for quantitation, especially with atmospheric pressure ionization (API) interfaces, the interference species can alter the ionization efficiency in the source, when they co-elute with the target analyte These effects may cause ionization suppression or ionization enhancement [9]. Very time-consuming [23,67,68]
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