Rapid characterization of adeno-associated virus (AAV) capsid proteins using microchip ZipChip CE-MS.

Adeno-associated viruses (AAVs) are viral vectors used as delivery systems for gene therapies. Intact protein characterization of AAV viral capsid proteins (VPs) and their post-translational modifications is critical to ensuring product quality. In this study, microchip-based ZipChip capillary electrophoresis-mass spectrometry (CE-MS) was applied for the rapid characterization of AAV intact VPs, specifically full and empty viral capsids of serotypes AAV6, AAV8 and AAV9, which was accomplished using 5 min of analysis time. Low levels of dimethyl sulfoxide (4%) in the background electrolyte (BGE) improved MS signal quality and component detection. A sensitivity evaluation revealed consistent detection of VP proteoforms when as little as 2.64 × 106 viral particles (≈26.4 picograms) were injected. Besides the traditional VP proteoforms used for serotype identification, multiple VP3 variants were detected, including truncated VP3 variants most likely generated by leaky scanning as well as unacetylated and un-cleaved VP3 proteoforms. Phosphorylation, known to impact AAV transduction efficiency, was also seen in all serotypes analysed. Additionally, low abundant fragments originating from either N- or C-terminus truncation were detected. As the aforementioned VP components can impact product quality and efficacy, the ZipChip's ability to rapidly characterize them illustrates its strength in monitoring product quality during AAV production.

Multi-Attribute Method (MAM) Analytical Workflow for Biotherapeutic Protein Characterization from Process Development to QC.

The multi-attribute method (MAM) has emerged significantly in recent years to support biotherapeutic protein characterization from process development to the QC environment. MAM is a liquid chromatography mass spectrometry (LC-MS) based peptide mapping approach, which combines the benefits from liquid chromatography coupled to high resolution accurate mass mass spectrometry (LC-HRAM MS), enabling direct assessment of protein sequence and product quality attributes with site specificity. These product quality attributes may impact efficacy, safety, stability, and process robustness. MAM is intended to replace conventional analytical approaches as it offers a more streamlined strategy for parallel monitoring of multiple attributes in a single analysis with high sensitivity and confidence, and ultimately supports more robust Quality by Design (QbD) approaches and faster decision cycles for biotherapeutic development. MAM consists of three main stages. The first stage is sample digestion, which typically entails proteolytic digestion of the protein. The second stage is reversed-phase chromatographic separation of the generated peptides and detection by HRAM MS in two phases. During MAM Phase I (discovery phase), data-dependent acquisition (DDA) MS/MS is performed to enable confident identification of peaks and development of a peptide workbook. During MAM Phase II (monitoring phase), full MS acquisition is only carried out for the monitoring of predefined product quality attributes (PQAs). The third stage is data processing, which entails analysis and reporting for each of the two phases including evaluation of sequence coverage, assessment of PQAs and peptide workbook creation during phase I, and targeted monitoring of predefined product attributes and new peak detection (NPD) during phase II. The latter is a comparative analysis that uses a base peak alignment algorithm to determine any non-monitored differences between the LC-MS chromatograms of a test sample and a reference standard. © 2023 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: In-solution sample digestion Alternate Protocol: Automated sample digestion Basic Protocol 2: Reversed-phase chromatographic separation and detection by HRAM-MS (RPLC-HRAM MS) Basic Protocol 3: Data processing and reporting.

Exploring Charge-Detection Mass Spectrometry on Chromatographic Time Scales.

Charge-detection mass spectrometry (CDMS) enables direct measurement of the charge of an ion alongside its mass-to-charge ratio. CDMS offers unique capabilities for the analysis of samples where isotopic resolution or the separation of charge states cannot be achieved, i.e., heterogeneous macromolecules or highly complex mixtures. CDMS is usually performed using static nano-electrospray ionization-based direct infusion with acquisition times in the range of several tens of minutes to hours. Whether CDMS analysis is also attainable on shorter time scales, e.g., comparable to chromatographic peak widths, has not yet been extensively investigated. In this contribution, we probed the compatibility of CDMS with online liquid chromatography interfacing. Size exclusion chromatography was coupled to CDMS for separation and mass determination of a mixture of transferrin and ß-galactosidase. Molecular masses obtained were compared to results from mass spectrometry based on ion ensembles. A relationship between the number of CDMS spectra acquired and the achievable mass accuracy was established. Both proteins were found to be confidently identified using CDMS spectra obtained from a single chromatographic run when peak widths in the range of 1.4-2.5 min, translating to 140-180 spectra per protein were achieved. After demonstration of the proof of concept, the approach was tested for the characterization of the highly complex glycoprotein α-1-acid glycoprotein and the Fc-fusion protein etanercept. With chromatographic peak widths of approximately 3 min, translating to ∼200 spectra, both proteins were successfully identified, demonstrating applicability for samples of high inherent molecular complexity.

Degradation of polysorbate investigated by a high-performance liquid chromatography multi-detector system with charged aerosol and mass detection.

Polysorbate 80 is widely used as a formulation component in biopharmaceutical drug products. Recent studies have shown that polysorbate 80 is readily degraded either through direct or indirect means. The degradation of polysorbate 80 causes a concern for the long-term stability of biopharmaceutical drug product, as the breakdown products of polysorbate 80 have been shown to cause adverse effects, such as formation of sub-visible and visible particles and mAb aggregation. Understanding the path and extent of degradation is of a paramount importance for the formulator during formulation development. A multi-detector HPLC system using charged aerosol and mass detection was developed and optimized for the characterization of polysorbate 80 standards. The system included a post-column make-up flow, i.e. an inverse gradient, that enabled constant eluent composition at the detectors. The inverse gradient eliminated the main source of variability for the charged aerosol detector response, thereby enabling the calculation of the mass balance between polysorbate components with different degrees of esterification. Extracted ion chromatograms of the mass detector combined with their respective retention times were used to qualitatively characterize the polysorbate samples down to the individual components. The system was applied to study the degradation of several polysorbate standards which occurred by enzymatic digestion or long-term storage. The system provided detailed information on the mechanism of degradation without the need for additional orthogonal analytical techniques.

Multi-Attribute Method (MAM): An Emerging Analytical Workflow for Biopharmaceutical Characterization, Batch Release and cGMP Purity Testing at the Peptide and Intact Protein Level.

The rapid growth of biotherapeutic industry, with more and more complex molecules entering the market, forces the need for advanced analytical platforms that can quickly and accurately identify and quantify product quality attributes. Mass spectrometry has the potential to provide more detailed information about the quality attributes of complex products, and MS methods are more sensitive than UV methods for detection of impurities. The multi-attribute method (MAM), a liquid chromatography-mass spectrometry based analytical approach is an emerging platform which supports biotherapeutic characterization and cGMP testing. The main advantage lies in the ability to monitor multiple quality attributes in a single assay, both at the peptide and the intact level, facilitating streamlined biopharmaceutical production, from research and development to the QC environment. This review highlights the current landscape of the MAM approach with special attention given to increased analytical throughput, general requirements for QC in terms of instrumentation and software, regulatory requirements, and industry acceptance of the MAM platform.

Exploring proteoforms of the IgG2 monoclonal antibody panitumumab using microchip capillary electrophoresis-mass spectrometry.

The IgG2 type monoclonal antibody panitumumab is an anti-epidermal growth factor receptor (EGFR) drug used for the treatment of EGFR-expressing, chemotherapy resistant, metastatic colorectal carcinoma. In this study, panitumumab drug product was first analysed using size exclusion chromatography coupled to mass spectrometry for rapid identity testing. The experimental data led to the identification of two panitumumab isoforms with several prominent forms remaining unidentified, despite apparently low sample complexity. Microchip capillary electrophoresis-mass spectrometry (CE-MS) was subsequently utilised for a more detailed characterization. It was observed that panitumumab is subject to partial N-terminal pyroglutamate formation. Incomplete conversion is uncharacteristic for N-terminally exposed glutamines and in case of panitumumab gives rise to forms which show successive mass offsets of 17 Da, respectively. If not separated before mass spectrometric analysis, e.g. by capillary electrophoresis, such near isobaric species coalesce into single MS peaks, which subsequently hampers or prevents their assignment. With a total of 42 panitumumab isoforms assigned by CE-MS, these observations highlight a potential pitfall of commonly applied rapid identity testing workflows and demonstrate that even low complexity biopharmaceuticals can require separation strategies which offer high separation selectivity for species close in mass.

Cation exchange chromatography on a monodisperse 3 µm particle enables extensive analytical similarity assessment of biosimilars.

Biosimilarity assessment requires extensive characterization and comparability exercises to investigate product quality attributes of an originator product and its potential biosimilar(s) and to highlight any differences between them. Performing a thorough comparison allows a shortened approval path, which also eliminates lengthy and expensive clinical trials, ensuring comparable product quality and efficacy but at lower drug prices. The wide variety of analytical methods available for biosimilar assessment ranges from biological to analytical assays, each providing orthogonal information to fully characterize biosimilar candidates. Intact native mass spectrometry (MS) has been shown to be an excellent tool for detection and monitoring of important quality attributes such as N-glycosylation, deamidation, sequence truncation and higher order structures. When combined with efficient upfront separation methods, simplification of the proteoform heterogeneity and associated complexity prior to MS analysis can be achieved. Native mass spectrometry can provide robust and accurate results within short analysis times and requires minimal sample preparation. In this study we report the use of a monodisperse strong cation exchange chromatography phase hyphenated with Orbitrap mass spectrometry (SCX-MS) to compare the best-selling biopharmaceutical product Humira® with 7 commercially approved biosimilar products. SCX-MS analysis allowed for the identification of previously described as well as so far unreported proteoforms and their relative quantitation across all samples, revealing differences in N-glycosylation and lysine truncation, as well as unique features for some products such as sialylation and N-terminal clipping. SCX-MS analysis, powered by a highly efficient separation column, enabled deep and efficient analytical comparison of biosimilar products.

Multi-attribute method (MAM) to assess analytical comparability of adalimumab biosimilars.

Adalimumab drug product (Humira ®), the first fully human monoclonal antibody (mAb) approved by FDA in 2002, led the top ten list of best-selling mAbs in 2018 and has been the most profitable drug in the world. With the expiration of patent protection in Europe in 2018 and in United States by 2023, the landscape is changing as up to 10 adalimumab biosimilars are expected to enter the market in the US. Biosimilars offer the potential to lower costs on health care systems and increase patient accessibility. The analytical similarity of seven different adalimumab biosimilars was accomplished in the present study using the multi-attribute method (MAM), a LC-MS based peptide mapping technique that allows for primary sequence assessment and evaluation of multiple quality attributes including deamidation, oxidation, succinimide formation, N- and C- terminal composition and detailed N-glycosylation analysis. In the first step, characterization of the most relevant post-translational modifications of a reference product was attained during the discovery phase of MAM. During the second step, as part of the MAM targeted monitoring phase, adalimumab batch-to batch variability was evaluated to define statistical intervals for the establishment of similarity ranges. The third step describes biosimilarity evaluation of predefined quality attributes and new peak detection for the assessment of any new or modified peak compared to the reference product. This study highlights a new perspective of the MAM approach and its underlying power for biotherapeutic comparability exercises in addition to analytical characterization. MAM offers a streamlined comparability assessment workflow based on high-confidence quality attribute analysis using high-resolution accurate mass mass spectrometry (HRAM MS) and the capability to detect any new or modified peak compared to the reference product.

Comprehensive multi-attribute method workflow for biotherapeutic characterization and current good manufacturing practices testing.

The multi-attribute method (MAM) is a liquid chromatography-mass spectrometry (LC-MS)-based method that is used to directly characterize and monitor numerous product quality attributes (PQAs) at the amino acid level of a biopharmaceutical product. MAM enables identity testing based on primary sequence verification, detection and quantitation of post-translational modifications and impurities. This ability to simultaneously and directly determine PQAs of therapeutic proteins makes MAM a more informative, streamlined and productive workflow than conventional chromatographic and electrophoretic assays. MAM relies on proteolytic digestion of the sample followed by reversed-phase chromatographic separation and high-resolution LC-MS analysis in two phases. First, a discovery study to determine quality attributes for monitoring is followed by the creation of a targeted library based on high-resolution retention time plus accurate mass analysis. The second aspect of MAM is the monitoring phase based on the target peptide library and new peak detection using differential analysis of the data to determine the presence, absence or change of any species that might affect the activity or stability of the biotherapeutic. The sample preparation process takes between 90 and 120 min, whereas the time spent on instrumental and data analyses might vary from one to several days for different sample sizes, depending on the complexity of the molecule, the number of attributes to be monitored and the information to be detailed in the final report. MAM is developed to be used throughout the product life cycle, from process development through upstream and downstream processes to quality control release or under current good manufacturing practices regulations enforced by regulatory agencies.

Intact multi-attribute method (iMAM): A flexible tool for the analysis of monoclonal antibodies.

The availability of rapid methods that can accurately define and quantify biopharmaceutical critical quality attributes has been the driving force for the implementation of mass spectrometry techniques throughout the development and production pipeline. While the multi-attribute method (MAM) has become widely adopted and developed, some critical information cannot be monitored through this workflow, such as correct chain assembly or the presence of fragments or aggregates. In this study, we combine intact protein mass spectrometry and the multi-attribute method to create an intact multi-attribute method - or iMAM. Using a CFR Part 11 compliant data system, we evaluated the proposed workflow using several intact analysis approaches under both denaturing and native conditions. As for the standard MAM approach, iMAM involves the generation of an intact protein target workbook which is created from the analysis of a reference sample, with ID confirmation obtained from deconvolution results and chromatographic retention times, while quantitation is obtained from the intensities of the m/z of most abundant charge states. The created processing method is then applied to the analysis of subsequent samples. New peak detection can also be performed, monitoring the number of components revealed after each analysis. The entire data process can be automated to generate a report within the chromatography data system software. Three case studies presented herein show the potential of iMAM for implementation at different stages of the production pipeline, from product development to stability testing and batch release.

Inline electrochemical reduction of NISTmAb for middle-up subunit liquid chromatography-mass spectrometry analysis.

Disulfide bond reduction within antibody mass spectrometry workflows is typically carried out using chemical reducing agents to produce antibody subunits for middle-down and middle-up analysis. In this contribution we offer an online electrochemical reduction method for the reduction of antibodies coupled with liquid chromatography (LC) and mass spectrometry (MS), reducing the disulfide bonds present in the antibody without the need for chemical reducing agents. An electrochemical cell placed before the analytical column and mass spectrometer facilitated complete reduction of NISTmAb inter- and intrachain disulfide bonds. Reduction and analysis were carried out under optimal solvent conditions using a trapping column and switching valve to facilitate solvent exchange during analysis. The level of reduction was shown to be affected by electrochemical potential, temperature and solvent organic content, but with optimization, complete disulfide bond cleavage was achieved. The use of an inline electrochemical cell offers a simple, rapid, workflow solution for liquid chromatography mass spectrometry analysis of antibody subunits.

Native LC-MS for capturing quality attributes of biopharmaceuticals on the intact protein level.

Intact protein analysis by means of mass spectrometry has become a well-established method for the characterization of biotherapeutics. However, due to the highly complex nature of recombinant proteins, prior chromatographic separation is inevitable for a comprehensive analysis. In recent years, progress in coupling a variety of liquid chromatography-based native separation modes such as size exclusion, ion exchange and hydrophobic interaction chromatography to mass spectrometry (native LC-MS) has been reported, therefore allowing for rapid assessment of molecular mass and deep characterization of the heterogeneity of complex, recombinantly produced therapeutic proteins. Here we provide a comprehensive overview of recent advances in the development and application of native LC-MS for biopharmaceutical characterization.

A rapid, simple and sensitive microfluidic chip electrophoresis mass spectrometry method for monitoring amino acids in cell culture media.

The development and optimization of cell culture media for biotech applications is a fundamental step of process development. The composition of cell culture media requires an ideal blend of amino acids, vitamins, nucleosides, lipids, carbohydrates, trace elements and other components. The ability to monitor these constituents is required to ensure that cells receive sufficient nutrients to facilitate growth, viability and productivity. Analysis of cell culture media is challenging due to the range and diversity of compounds contained in this matrix and normally requires time consuming methods. A rapid, simple and sensitive microfluidic chip CE-MS method is described to monitor amino acids in chemically defined cell culture media from a Chinese hamster ovary cell line cultured over a period of 10 days. The described platform enabled the separation of 16 amino acids in less than 2 minutes and without the requirement for extensive sample preparation. The analytical parameters evaluated were precision, linearity, limit of detection and limit of quantification. The majority of essential amino acids were present in cell culture growth in high concentrations compared to non-essential amino acids. Over the course of the 10 days cell culture the concentration of certain amino acids declined by up to 100%. Microfluidic chip based CE-MS methods can be used effectively to obtain the consumption rates of amino acids in cell culture media during cell growth and to perform at-line monitoring and screening of cell culture status.

Tracing production instability in a clonally derived CHO cell line using single-cell transcriptomics.

A variety of mechanisms including transcriptional silencing, gene copy loss, and increased susceptibility to cellular stress have been associated with a sudden or gradual loss of monoclonal antibody (mAb) production in Chinese hamster ovary (CHO) cell lines. In this study, we utilized single-cell RNA-seq (scRNA-seq) to study a clonally derived CHO cell line that underwent production instability leading to a dramatic reduction of the levels of mAb produced. From the scRNA-seq data, we identified subclusters associated with variations in the mAb transgenes and observed that heavy chain gene expression was significantly lower than that of the light chain across the population. Using trajectory inference, the evolution of the cell line was reconstructed and was found to correlate with a reduction in heavy and light chain gene expression. Genes encoding for proteins involved in the response to oxidative stress and apoptosis were found to increase in expression as cells progressed along the trajectory. Future studies of CHO cell lines using this technology have the potential to dramatically enhance our understanding of the characteristics underpinning efficient manufacturing performance as well as product quality.

Tracking the Behavior of Monoclonal Antibody Product Quality Attributes Using a Multi-Attribute Method Workflow.

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.

Detection and quantitation of host cell proteins in monoclonal antibody drug products using automated sample preparation and data-independent acquisition LC-MS/MS.

Ensuring the removal of host cell proteins (HCPs) during downstream processing of recombinant proteins such as monoclonal antibodies (mAbs) remains a challenge. Since residual HCPs might affect product stability or safety, constant monitoring is required to demonstrate their removal to be below the regulatory accepted level of 100 ng/mg. The current standard analytical approach for this procedure is based on ELISA; however, this approach only measures the overall HCP content. Therefore, the use of orthogonal methods, such as liquid chromatography-mass spectrometry (LC-MS), has been established, as it facilitates the quantitation of total HCPs as well as the identification and quantitation of the individual HCPs present. In the present study, a workflow for HCP detection and quantitation using an automated magnetic bead-based sample preparation, in combination with a data-independent acquisition (DIA) LC-MS analysis, was established. Employing the same instrumental setup commonly used for peptide mapping analysis of mAbs allows for its quick and easy implementation into pre-existing workflows, avoiding the need for dedicated instrumentation or personnel. Thereby, quantitation of HCPs over a broad dynamic range was enabled to allow monitoring of problematic HCPs or to track changes upon altered bioprocessing conditions.

Optimisation of the use of sliding window deconvolution for comprehensive characterisation of trastuzumab and adalimumab charge variants by native high resolution mass spectrometry.

The biopharmaceutical industry continues to develop mAb-based biotherapeutics in increasing numbers. Due to their complexity, there are several critical quality attributes (CQAs) that need to be measured and controlled to guarantee product safety and efficacy. Charge variant analysis is a widely used method to monitor changes in product quality during the manufacturing process of monoclonal antibodies (mAbs) and, together with a bottom-up peptide centred approach, acts as a key analytical platform to fulfil regulatory requirements. Native MS measures biomolecules under conditions that preserve most aspects of protein tertiary and quaternary structure, enabling direct characterization of large intact proteins such as mAbs. The resulting native mass spectrum of a mAb is characterized by a narrower charge-state envelope that simplifies the spectra and also condenses the ion signals into fewer peaks, increasing the signal-to-noise ratio. Algorithmic spectral deconvolution is needed for routine accurate and rapid molecular weight determination, and consequently, multiple deconvolution algorithms have evolved over the past decade. Here, we demonstrate the utility of the sliding window algorithm as a robust and powerful deconvolution tool for comprehensive characterisation of charge variant analysis data for mAbs. Optimum performance is evaluated by studying the impact of critical software parameters on detection, identification and relative quantitation of protein isoforms. By combining molecular mass and retention time information, it was possible to identify multiple modifications on adalimumab and trastuzumab, both IgG1 mAbs, including lysine truncation, deamidation and succinimide formation, along with the N-glycan distribution of each of the identified charge variants. Sliding window deconvolution also provides a key benefit of low abundant variant detection in a single analysis and the ability to detect co-eluting components with different relative abundances. The studied mAbs demonstrate the algoritms applicability for efficient data processing of both simple and complex mAbs analysed using pH gradient cation exchange chromatography coupled to native mass spectrometry.

Detection and quantitation of host cell proteins in monoclonal antibody drug products using automated sample preparation and data-independent acquisition LC-MS/MS / 药物分析学报

Ensuring the removal of host cell proteins (HCPs) during downstream processing of recombinant pro-teins such as monoclonal antibodies (mAbs) remains a challenge.Since residual HCPs might affect product stability or safety,constant monitoring is required to demonstrate their removal to be below the regulatory accepted level of 100 ng/mg.The current standard analytical approach for this procedure is based on ELISA;however,this approach only measures the overall HCP content.Therefore,the use of orthogonal methods,such as liquid chromatography-mass spectrometry (LC-MS),has been established,as it facilitates the quantitation of total HCPs as well as the identification and quantitation of the indi-vidual HCPs present.In the present study,a workflow for HCP detection and quantitation using an automated magnetic bead-based sample preparation,in combination with a data-independent acquisi-tion (DIA) LC-MS analysis,was established.Employing the same instrumental setup commonly used for peptide mapping analysis of mAbs allows for its quick and easy implementation into pre-existing workflows,avoiding the need for dedicated instrumentation or personnel.Thereby,quantitation of HCPs over a broad dynamic range was enabled to allow monitoring of problematic HCPs or to track changes upon altered bioprocessing conditions.

Inter-laboratory study of an optimised peptide mapping workflow using automated trypsin digestion for monitoring monoclonal antibody product quality attributes.

Peptide mapping analysis is a regulatory expectation to verify the primary structure of a recombinant product sequence and to monitor post-translational modifications (PTMs). Although proteolytic digestion has been used for decades, it remains a labour-intensive procedure that can be challenging to accurately reproduce. Here, we describe a fast and reproducible protocol for protease digestion that is automated using immobilised trypsin on magnetic beads, which has been incorporated into an optimised peptide mapping workflow to show method transferability across laboratories. The complete workflow has the potential for use within a multi-attribute method (MAM) approach in drug development, production and QC laboratories. The sample preparation workflow is simple, ideally suited to inexperienced operators and has been extensively studied to show global applicability and robustness for mAbs by performing sample digestion and LC-MS analysis at four independent sites in Europe. LC-MS/MS along with database searching was used to characterise the protein and determine relevant product quality attributes (PQAs) for further testing. A list of relevant critical quality attributes (CQAs) was then established by creating a peptide workbook containing the specific mass-to-charge (m/z) ratios of the modified and unmodified peptides of the selected CQAs, to be monitored in a subsequent test using LC-MS analysis. Data is provided that shows robust digestion efficiency and low levels of protocol induced PTMs. Graphical abstract.

In-depth analysis of monoclonal antibodies using microfluidic capillary electrophoresis and native mass spectrometry.

Charge variant profiling of therapeutic proteins is required by the International Council for Harmonisation guidelines and is traditionally performed by capillary electrophoresis or ion exchange chromatography. Recently, improvements in the hyphenation of capillary electrophoresis with mass spectrometry and the introduction of mass spectrometry compatible background electrolytes has allowed the implementation of native mass spectrometric determination of the charge variant profile obtained from the electrophoretic separation. The low flow operation of the microfluidic electrophoretic platform significantly boosts mass spectrometric sensitivity and increases the dynamic range, even when using sample amounts as low as 1 ng in capillary. In the current study, rituximab, trastuzumab and bevacizumab drug products were analysed using the ZipChip microfluidic CE-ESI-MS platform that facilitated confident identification of proteoforms with an average mass accuracy of <15 ppm. Up to 52 proteoforms were identified for trastuzumab drug product, while rituximab sample revealed the presence of fragments and sialylated N-glycans. Overall, the CE-ESI-MS platform proved to be a fast and robust tool for therapeutic protein charge variant profiling and facilitated efficient coupling with native mass spectrometry for the generation of highly informative characterisation data.