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

Implementation of a LC-MS based multi-attribute method (MAM) and intact multi-attribute method (iMAM) workflow for the characterisation of a GLP-Fc fusion protein

Over the past few years, the implementation of mass spectrometry (MS) in QC laboratories has become a more common occurrence. The multi-attribute method (MAM), and emerging intact multi-attribute method (iMAM), are powerful analytical tools utilising liquid chromatography-mass spectrometry (LC-MS) methods that enable the monitoring of critical quality attributes (CQAs) in biotherapeutic proteins in compliant settings. Both MAM and iMAM are intended to replace or supplement several conventional assays with a single LC-MS method utilising MS data in combination with robust, semi-automated data processing workflows. MAM and iMAM workflows can also be implemented into current Good Manufacturing Practices environments due to the availability of CFR 11 compliant chromatography data system software. In this study, MAM and iMAM are employed for the analysis of 4 batches of a glucagon-like peptide-Fc fusion protein. MAM approach involved a first the discovery phase for the identification of CQAs and second, the target monitoring phase of the selected CQAs in other samples. New peak detection was performed on the data set to determine the appearance, absence or change of any peak. For native iMAM workflow both size exclusion and strong cation exchange chromatography were optimized for the identification and monitoring of CQAs at the intact level.

A native SEC-MS workflow and validation for analyzing drug-to-antibody ratio and drug load distribution in cysteine-linked antibody-drug conjugates

The development and optimization of Antibody-Drug Conjugates (ADCs) hinge on enhanced analytical and bioanalytical characterization, particularly in assessing critical quality attributes (CQAs). The ADC's potency is largely determined by the average number of drugs attached to the monoclonal antibody (mAb), known as the drug-to-antibody ratio (DAR). Furthermore, the drug load distribution (DLD) influences the therapeutic window of the ADC, defining the range of dosages effective in treating diseases without causing toxic effects. Among CQAs, DAR and DLD are vital; their control is essential for ensuring manufacturing consistency and product quality. Typically, hydrophobic interaction chromatography (HIC) or reversed-phase liquid chromatography (RPLC) with UV detector have been used to quantitate DAR and DLD in quality control (QC) environment. Recently, Native size-exclusion chromatography-mass spectrometry (nSEC-MS) proves the potential as a platformable quantitative method for characterizing DAR and DLD across various cysteine-linked ADCs in research or early preclinical development. In this work, we established and assessed a streamlined nSEC-MS workflow with a benchtop LC-MS platform, to quantitatively monitor DAR and DLD of different chemotype and drug load level cysteine-linked ADCs. Moreover, to deploy this workflow in QC environment, complete method validation was conducted in three independent laboratories, adhering to the International Council for Harmonization of Technical Requirements for Pharmaceuticals for Human Use (ICH) Q2(R1) guidelines. The results met the predefined analytical target profile (ATP) and performance criteria, encompassing specificity/selectivity, accuracy, precision, linearity, range, quantification/detection limit, and robustness. Finally, the method validation design offers a reference for other nSEC-MS methods that are potentially used to determine the DAR and DLD on cysteine-linker ADCs. To the best of our knowledge, this study is the first reported systematic validation of the nSEC-MS method for detecting DAR and DLD. The results indicated that the co-validated nSEC-MS workflow is suitable for DAR and DLD routine analysis in ADC quality control, release, and stability testing.

Monitoring mAb proteoforms in mouse plasma using an automated immunocapture combined with top-down and middle-down mass spectrometry

Monoclonal antibodies (mAbs) have established themselves as the leading biopharmaceutical therapeutic modality. Once the developability of a mAb drug candidate has been assessed, an important step is to check its in vivo stability through pharmacokinetics (PK) studies. The gold standard is ligand-binding assay (LBA) and liquid chromatography-mass spectrometry (LC-MS) performed at the peptide level (bottom-up approach). However, these analytical techniques do not allow to address the different mAb proteoforms that can arise from biotransformation. In recent years, top-down and middle-down mass spectrometry approaches have gained popularity to characterize proteins at the proteoform level but are not yet widely used for PK studies. We propose here a workflow based on an automated immunocapture followed by top-down and middle-down liquid chromatography-tandem mass spectrometry (LC-MS/MS) approaches to characterize mAb proteoforms spiked in mouse plasma. We demonstrate the applicability of our workflow on a large concentration range using pembrolizumab as a model. We also compare the performance of two state-of-the-art Orbitrap platforms (Tribrid Eclipse and Exploris 480) for these studies. The added value of our workflow for an accurate and sensitive characterization of mAb proteoforms in mouse plasma is highlighted.

Targeted CQA analytical control strategy for commercial antibody products: Replacing ion-exchange chromatography methods for charge heterogeneity with multi-attribute monitoring

Peptide mapping with mass spectrometry (MS) is an important tool for protein characterization in the biopharmaceutical industry. Historically, peptide mapping monitors post-translational modifications (PTMs) of protein products and process intermediates during development. Multi-attribute monitoring (MAM) methods have been used previously in commercial release and stability testing panels to ensure control of selected critical quality attributes (CQAs). Our goal is to use MAM methods as part of an overall analytical testing strategy specifically focused on CQAs, while removing or replacing historical separation methods that do not effectively distinguish CQAs from non-CQAs due to co-elution. For example, in this study, we developed a strategy to replace a profile-based ion-exchange chromatography (IEC) method using a MAM method in combination with traditional purity methods to ensure control of charge variant CQAs for a commercial antibody (mAb) drug product (DP). To support this change in commercial testing strategy, the charge variant CQAs were identified and characterized during development by high-resolution LC-MS and LC-MS/MS. The charge variant CQAs included PTMs, high molecular weight species, and low molecular weight species. Thus, removal of the IEC method from the DP specification was achieved using a validated LC-MS MAM method on a QDa system to directly measure the charge variant PTM CQAs in combination with size exclusion chromatography (SE-HPLC) and capillary electrophoresis (CE-SDS) to measure the non-PTM charge variant CQAs. Bridging data between the MAM, IEC, and SE-HPLC methods were included in the commercial marketing application to justify removing IEC from the DP specification. We have also used this MAM method as a test for identity to reduce the number of QC assays. This strategy has received approvals from several health authorities.

Compliance and regulatory considerations for the implementation of the multi-attribute-method by mass spectrometry in a quality control laboratory

Multi-attribute methods employing mass spectrometry are applied throughout the biopharmaceutical industry for product and process characterization purposes but are not yet widely accepted as a method for batch release and stability testing under the good manufacturing practice (GMP) regime, due to limited experience and level of comfort with the technical, compliance and regulatory aspects of its implementation at quality control (QC) laboratories. This article is the second part of a two-tiered publication aiming at providing guidance for implementation of the multi-attribute method by peptide mapping liquid chromatography mass spectrometry (MAM) in a QC laboratory. The first part [1] focuses on technical considerations, while this second part provides considerations related to GMP compliance and regulatory aspects. This publication has been prepared by a group of industry experts representing 14 globally acting major biotechnology companies under the umbrella of the European Federation of Pharmaceutical Industries and Associations (EFPIA) Manufacturing & Quality Expert Group (MQEG).

Recent applications of quantitative mass spectrometry in biopharmaceutical process development and manufacturing

Biopharmaceutical products have seen rapid growth over the past few decades and continue to dominate the global pharmaceutical market. Aligning with the quality by design (QbD) framework and realization, recent advances in liquid chromatography-mass spectrometry (LC-MS) instrumentation and related techniques have enhanced biopharmaceutical characterization capabilities and have supported an increased development of biopharmaceutical products. Beyond its routine qualitative characterization, the quantitative feature of LC-MS has unique applications in biopharmaceutical process development and manufacturing. This review describes the recent applications and implications of the advancement of quantitative MS methods in biopharmaceutical process development, and characterization of biopharmaceutical product, product-related variants, and process-related impurities. We also provide insights on the emerging applications of quantitative MS in the lifecycle of biopharmaceutical product development including quality control in the Good Manufacturing Practice (GMP) environment and process analytical technology (PAT) practices during process development and manufacturing. Through collaboration with instrument and software vendors and regulatory agencies, we envision broader adoption of phase-appropriate quantitative MS-based methods for the analysis of biopharmaceutical products, which in turn has the potential to enable manufacture of higher quality products for patients.

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.

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.

Technical considerations for the implementation of the Multi-Attribute-Method by mass spectrometry in a Quality Control laboratory

Multi-attribute methods employing mass spectrometry are applied throughout the biopharmaceutical industry for product and process characterization purposes but are not yet widely accepted as a method for batch release and stability testing under good manufacturing practice (GMP) due to limited experience and level of comfort with the technical, compliance and regulatory aspects of its implementation at quality control (QC) laboratories. Here, current literature related to the development and application of the multi-attribute method by peptide mapping liquid chromatography mass spectrometry (MAM) is compiled with the aim of providing guidance for the implementation of MAM in a QC laboratory. This article, focusing on technical considerations, is the first part of a two-tiered publication, whereby the second part will focus on GMP compliance and regulatory aspects. This publication has been prepared by a group of industry experts representing 14 globally acting major biotechnology companies under the umbrella of the European Federation of Pharmaceutical Industries and Associations (EFPIA) Manufacturing & Quality Expert Group (MQEG).

A native multi-dimensional monitoring workflow for at-line characterization of mAb titer, size, charge, and glycoform heterogeneities in cell culture supernatant

With growing maturity of the biopharmaceutical industry, new modalities entering the therapeutic design space and increasing complexity of formulations such as combination therapy, the demands and requirements on analytical workflows have also increased. A recent evolution in newer analytical workflows is that of multi-attribute monitoring workflows designed on chromatography-mass spectrometry (LC-MS) platform. In comparison to traditional one attribute per workflow paradigm, multi-attribute workflows are designed to monitor multiple critical quality attributes through a single workflow, thus reducing the overall time to information and increasing efficiency and throughput. While the 1^st generation multi-attribute workflows focused on bottom-up characterization following peptide digestion, the more recent workflows have been focussing on characterization of intact biologics, preferably in native state. So far intact multi-attribute monitoring workflows suitable for comparability, utilizing single dimension chromatography coupled with MS have been published. In this study, we describe a native multi-dimensional multi-attribute monitoring workflow for at-line characterization of monoclonal antibody (mAb) titer, size, charge, and glycoform heterogeneities directly in cell culture supernatant. This has been achieved through coupling ProA in series with size exclusion chromatography in 1^st dimension followed by cation exchange chromatography in the 2^nd dimension. Intact paired glycoform characterization has been achieved through coupling 2D-LC with q-ToF-MS. The workflow with a single heart cut can be completed in 25 mins and utilizes 2D-liquid chromatography (2D-LC) to maximize separation and monitoring of titer, size as well as charge variants.

Intact Mass Analysis–Based Multi-Attribute Methods (iMAMs) for Characterization of Biopharmaceuticals

Multi-attribute methods (MAMs) are becoming increasingly popular for their ability to analyze multiple critical quality attributes (CQA) in a single workflow. This capability becomes particularly attractive for a product class such as monoclonal antibodies, which are large and complex, and have many CQAs that need to be monitored and controlled during their manufacturing so as to deliver consistent product quality. In an earlier installment, we discussed the role of liquid chromatography and mass spectrometry in MAMs. In this article, we focus on intact mass analysis–based multi-attribute methods (iMAMs), a suitable alternative that can complement standard MAMs or be used when there is a need for rapid turnaround and monitoring of only a limited number of CQAs. Multiple case studies are presented to elucidate this concept.

Interlaboratory Evaluation of a User-Friendly Benchtop Mass Spectrometer for Multiple-Attribute Monitoring Studies of a Monoclonal Antibody

In the quest to market increasingly safer and more potent biotherapeutic proteins, the concept of the multi-attribute method (MAM) has emerged from biopharmaceutical companies to boost the quality-by-design process development. MAM strategies rely on state-of-the-art analytical workflows based on liquid chromatography coupled to mass spectrometry (LC-MS) to identify and quantify a selected series of critical quality attributes (CQA) in a single assay. Here, we aimed at evaluating the repeatability and robustness of a benchtop LC-MS platform along with bioinformatics data treatment pipelines for peptide mapping-based MAM studies using standardized LC-MS methods, with the objective to benchmark MAM methods across laboratories, taking nivolumab as a case study. Our results evidence strong interlaboratory consistency across LC-MS platforms for all CQAs (i.e., deamidation, oxidation, lysine clipping and glycosylation). In addition, our work uniquely highlights the crucial role of bioinformatics postprocessing in MAM studies, especially for low-abundant species quantification. Altogether, we believe that MAM has fostered the development of routine, robust, easy-to-use LC-MS platforms for high-throughput determination of major CQAs in a regulated environment.

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.