Quantitative mass spectrometry imaging of drugs and metabolites: a multiplatform comparison
Mass spectrometry imaging (MSI) provides insight into the molecular distribution of a broad range of compounds and, therefore, is frequently applied in the pharmaceutical industry. Pharmacokinetic and toxicological studies deploy MSI to localize potential drugs and their metabolites in biological ti...
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Veröffentlicht in: | Analytical and bioanalytical chemistry 2021-04, Vol.413 (10), p.2779-2791 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | Mass spectrometry imaging (MSI) provides insight into the molecular distribution of a broad range of compounds and, therefore, is frequently applied in the pharmaceutical industry. Pharmacokinetic and toxicological studies deploy MSI to localize potential drugs and their metabolites in biological tissues but currently require other analytical tools to quantify these pharmaceutical compounds in the same tissues. Quantitative mass spectrometry imaging (Q-MSI) is a field with challenges due to the high biological variability in samples combined with the limited sample cleanup and separation strategies available prior to MSI. In consequence, more selectivity in MSI instruments is required. This can be provided by multiple reaction monitoring (MRM) which uses specific precursor ion-product ion transitions. This targeted approach is in particular suitable for pharmaceutical compounds because their molecular identity is known prior to analysis. In this work, we compared different analytical platforms to assess the performance of MRM detection compared to other MS instruments/MS modes used in a Q-MSI workflow for two drug candidates (A and B). Limit of detection (LOD), linearity, and precision and accuracy of high and low quality control (QC) samples were compared between MS instruments/modes. MRM mode on a triple quadrupole mass spectrometer (QqQ) provided the best overall performance with the following results for compounds A and B: LOD 35.5 and 2.5 μg/g tissue,
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0.97 and 0.98 linearity, relative standard deviation QC |
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ISSN: | 1618-2642 1618-2650 |
DOI: | 10.1007/s00216-021-03210-0 |