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The multi-attribute method (MAM) is a liquid chromatography-mass spectrometry based method that is used to directly characterize and monitor many product quality attributes and impurities on biotherapeutics, most commonly at the peptide level. It utilizes high-resolution accurate mass spectral data which are analyzed in an automated fashion. MAM is a promising approach that is intended to replace or supplement several conventional assays with a single LC-MS analysis and can be implemented in a Current Good Manufacturing Practice environment. MAM provides accurate site-specific quantitation information on targeted attributes and the nontargeted new peak detection function allows to detect new peaks as impurities, modifications, or sequence variants when comparing to a reference sample. The high resolution MAM workflow was applied here for three independent case studies. First, to monitor the behavior of monoclonal antibody product quality attributes over the course of a 12-day cell culture experiment providing an insight into the behavior and dynamics of product attributes throughout the process. Second, the workflow was applied to test the purity and identity of a product through analysis of samples spiked with host cell proteins. Third, through the comparison of a drug product and a biosimilar with known sequence variants. The three case studies presented here, clearly demonstrate the robustness and accuracy of the MAM workflow that implies suitability for deployment in the regulated environment.

Liquid phase separation analysis and subsequent quantitation remains a challenging task for protein-derived oligosaccharides due to their inherent structural complexity and diversity. Incomplete resolution or co-detection of multiple glycan species complicates peak area-based quantitation and associated statistical analysis when optical detection methods are used. The approach outlined herein describes the utilization of stable isotope variants of commonly used fluorescent tags that allow for mass-based glycan identification and relative quantitation following separation by liquid chromatography (LC) or capillary electrophoresis (CE). Comparability assessment of glycoprotein-derived oligosaccharides is performed by derivatization with commercially available isotope variants of 2-aminobenzoic acid or aniline and analysis by LC- and CE-mass spectrometry. Quantitative information is attained from the extracted ion chromatogram/electropherogram ratios generated from the light and heavy isotope clusters.

Capillary electrophoresis (CE) offers excellent efficiency and orthogonality to liquid chromatographic (LC) separations for oligosaccharide structural analysis. Combination of CE with high resolution mass spectrometry (MS) for glycan analysis remains a challenging task due to the MS incompatibility of background electrolyte buffers and additives commonly used in offline CE separations. Here, a novel method is presented for the analysis of 2-aminobenzoic acid (2-AA) labelled glycans by capillary electrophoresis coupled to mass spectrometry (CE-MS). To ensure maximum resolution and excellent precision without the requirement for excessive analysis times, CE separation conditions including the concentration and pH of the background electrolyte, the effect of applied pressure on the capillary inlet and the capillary length were evaluated. Using readily available 12/13 C 6 stable isotopologues of 2-AA, the developed method can be applied for quantitative glycan profiling in a twoplex manner based on the generation of extracted ion electropherograms (EIE) for 12 C 6 'light' and 13 C 6 'heavy' 2-AA labelled glycan isotope clusters. The twoplex quantitative CE-MS glycan analysis platform is ideally suited for comparability assessment of biopharmaceuticals, such as monoclonal antibodies, for differential glycomic analysis of clinical material for potential biomarker discovery or for quantitative microheterogeneity analysis of different glycosylation sites within a glycoprotein. Additionally, due to the low injection volume requirements of CE, subsequent LC-MS analysis of the same sample can be performed facilitating the use of orthogonal separation techniques for structural elucidation or verification of quantitative performance.