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High-resolution mass spectrometry (HRMS) in full scan mode acquires all ions present in the sample of interest offering a lot of qualitative information. This, in combination with the improved performance of the new generation HRMS systems, triggers more (bio) analysts to switch from triple quad MS systems to HRMS for quantitative analysis. Quantitative processing of HRMS data is performed based on narrow mass extraction windows rather than on nominal mass product ion chromatograms (SRM or MRM). Optimal processing of HRMS data requires different considerations and software tools and can have an impact on data processing and final results. The selection of centroid versus continuum/profile data for processing, selection of the optimal narrow mass extraction window, using theoretical versus measured accurate mass for the extraction of the ion chromatograms as well as differences in calculations and data handling residing in the different vendor software packages are tackled in the presented manuscript. These differences are illustrated on HRMS data acquired for the same plasma samples on three different platforms, i.e., a Sciex QToF, a Waters QToF, and a Thermo Orbitrap system, and processed in four different software packages, i.e., Sciex Analyst® TF, Waters Masslynx, Waters Unifi, and Thermo Xcalibur. The impact of these differences on quantitative HRMS performance was evaluated on calibration curves of eight small molecule compounds in plasma using four different ways of processing. Simple guidelines are provided for the selection of an optimal mass extraction window for continuum and centroided data. Graphical Abstract.

Sensitivity is often a critical parameter in quantitative bioanalyses in drug development. For liquid-chromatography-based methods, sensitivity can be improved by reducing the column diameter, but practical sensitivity gains are limited by the reduced sample loading capacity on small internal diameter (I.D.) columns. We developed a set-up that has overcome these limitations in sample loading capacity. The set-up uses 4 columns with gradually decreasing column diameters along the flow-path (2.1 → 1 → 0.5 → 0.15 mm). Samples are pre-concentrated on-line on a 2.1 mm I.D. trapping column and back flushed to a 1 mm I.D. UHPLC analytical column and separated. The peak(s) of interest are transferred using heartcutting to a second trapping column (0.5 mm I.D.), which is back-flushed to a 0.15 mm I.D. micro-UHPLC analytical column for orthogonal separation. The proof of concept of the set-up was demonstrated by the simultaneous analysis of midazolam and 1'-hydroxy midazolam in plasma by injection of 80 μL of protein precipitated plasma. The 4-column funnel set-up proved to be robust and resulted in a 10-50 times better sensitivity compared to a trap-elute approach and 250-500 fold better compared to direct micro-UHPLC analysis. A lower limit of quantification of 100 fg/mL in plasma was obtained for both probe compounds.

Background: Peptides represent a growing class of potential drugs. Information on metabolic clearance can be valuable for peptide drug development but different challenges are encountered with the identification of peptide metabolites in comparison to the process used for small-molecule therapeutics. Results: Enfuvirtide was selected as a test compound and dosed intravenously at 2 mg/kg to rats. Plasma samples were collected and analyzed on two different quadrupole-TOF instruments in positive and negative ion modes. Different post-acquisition processing tools were evaluated to identify the metabolites of a peptide drug in the presence of an in vivo matrix. Charge state filtering and ion mobility extraction were applied to reduce the matrix background and combined with more comprehensive software tools generally used for large molecule analyses as well as tools designed for small-molecule metabolite identification work. Conclusion: Both ion mobility spectrometry and charge state filtration proved to be successful in extracting peptide ions and significantly reducing background signals. Both small- and large-molecule software tools contain specific capabilities that could be usefully combined in a single package for peptide metabolite identification.

Background: With an increased interest in peptides and proteins as potential new drug candidates, new approaches for sensitive and selective quantitative analysis are required. LC–MS/MS analysis provides a good alternative to immunoassays with reduced method development times and increased specificity. Results: We have evaluated two state-of-the-art triple quadrupole and high-resolution TOF mass spectrometers with respect to their performance for quantification of six peptides (glufibrinopeptide B, somatostatin, enfuvirtide, TRI1144, C34 and exenatide). The peptides were spiked into protein-precipitated plasma supernatant. Triple quadrupole quantification was performed in SRM mode, and in high-resolution, MS narrow-width extracted chromatograms were generated for quantification. Specificity, accuracy, reproducibility and robustness were found to be comparable between the two instruments. The triple quadrupole instrument is still the most sensitive instrument for quantification of peptides with a median factor of about four-times higher sensitivity (based on LLOQ evaluation). Conclusion: Based on sensitivity, the newest generation triple quadrupole MS systems are still the preferred technology for quantification of peptides. Since the sensitivity difference between triple quadrupole instruments and the new-generation high-resolution TOF-MS instruments is minor, the latter offer a useful alternative whenever additional selectivity is preferred or the use of a generic approach not requiring method optimization is advantageous.

Background: Amyloid peptides are established biomarkers for Alzheimer’s disease but their analysis presents major challenges. Results: In this article, we describe the use of ultra high-performance LC and API4000 triple quadrupole instrumentation for the quantification of amyloid peptides (Aβ1-38 and Aβ1-42) in cerebrospinal fluid (CSF), using electrospray ionization with negative ion multiple reaction monitoring transitions. Sample preparation was simplified by the addition of acetonitrile and ammonium hydroxide. Although excellent sensitivity and precision was demonstrated, we observed differences in matrix suppression effects when using artificial CSF versus canine CSF for calibration curves and quality control samples. Conclusion: A case study shows that the method can be used to determine the relative levels of two key peptides (Aβ1-38 and Aβ1-42) compared with their predose values (a screening assay) in support of preclinical studies.