A high-resolution multi-attribute method for product characterization, process characterization, and quality control of therapeutic proteins

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.

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.

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.

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.

Evolution of Vaccines Formulation to Tackle the Challenge of Anti-Microbial Resistant Pathogens

The increasing diffusion of antimicrobial resistance (AMR) across more and more bacterial species emphasizes the urgency of identifying innovative treatment strategies to counter its diffusion. Pathogen infection prevention is among the most effective strategies to prevent the spread of both disease and AMR. Since their discovery, vaccines have been the strongest prophylactic weapon against infectious diseases, with a multitude of different antigen types and formulative strategies developed over more than a century to protect populations from different pathogens. In this review, we review the main characteristics of vaccine formulations in use and under development against AMR pathogens, focusing on the importance of administering multiple antigens where possible, and the challenges associated with their development and production. The most relevant antigen classes and adjuvant systems are described, highlighting their mechanisms of action and presenting examples of their use in clinical trials against AMR. We also present an overview of the analytical and formulative strategies for multivalent vaccines, in which we discuss the complexities associated with mixing multiple components in a single formulation. This review emphasizes the importance of combining existing knowledge with advanced technologies within a Quality by Design development framework to efficiently develop vaccines against AMR pathogens.

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).

Analytical Performance Evaluation of Identity, Quality-Attribute Monitoring and new Peak Detection in a Platform Multi-Attribute Method Using Lys-C Digestion for Characterization and Quality Control of Therapeutic Monoclonal Antibodies

The use of multi-attribute method (MAM) for identity and purity testing of biopharmaceuticals offers the ability to complement and replace multiple conventional analytical technologies with a single mass spectrometry (MS) method. Phase-appropriate method validation is one major consideration for the implementation of MAM in a current Good Manufacturing Practice (cGMP) environment. We developed a MAM workflow for therapeutic monoclonal antibodies (mAbs) with optimized sample preparation using lysyl endopeptidase (Lys-C) digestion. In this study, we evaluated the assay performances of this platform MAM workflow for identity, product quality attributes (PQAs) monitoring and new peak detection (NPD) for single and coformulated mAbs. An IgG4 mAb-1 and its coformulations were used as model molecules in this study. The assay performance evaluation demonstrated the full potential of the platform MAM approach for its intended use for characterization and quality control of single mAb-1 and mAb-1 in its coformulations. To the best of our knowledge, this is the first performance evaluation of MAM for mAb identity, PQA monitoring, and new peak detection (NPD) in a single assay, featuring 1) the first performance evaluation of MAM for PQA monitoring using Lys-C digestion with a high-resolution MS, 2) a new approach for mAb identity testing capable of distinguishing single mAb from coformulations using MAM, and 3) the performance evaluation of NPD for MAM with Lys-C digestion. The developed platform MAM workflow and the MAM performance evaluation paved the way for its GMP qualification and enabled clinical release of mAb-1 in GMP environment with MAM.

Development and optimization of a LC-MS based multi-attribute method (MAM) workflow for characterization of therapeutic Fc-fusion protein

The growing complexity of novel biopharmaceutical formats, such as Fc-fusion proteins, in increasingly competitive environment has highlighted the need of high-throughput analytical platforms. Multi-attribute method (MAM) is an emerging analytical technology that utilizes liquid chromatography coupled with mass spectrometry to monitor critical quality attributes (CQAs) in biopharmaceuticals. MAM is intended to supplement or replace the conventional chromatographic and electrophoretic approaches used for quality control and drug release purpose. In this investigation, we have developed an agile sample preparation approach for deploying MAM workflow for a complex VEGFR-targeted therapeutic Fc-fusion protein. Initially, a systematic time course evaluation of tryptic digestion step was performed to achieve maximum amino acid sequence coverage of >96.5%, in a short duration of 2 h, with minimum assay artifacts. This approach facilitated precise identification of five sites of N-glycosylation with successful monitoring of other CQAs such as deamidation, oxidation, etc. Subsequently, the developed MAM workflow with suitable tryptic digestion time was qualified according to the International council for harmonisation (i.e. ICH) Q2R1 guidelines for method validation. Post-validation, the analytical workflow was also evaluated for its capability to identify unknown moieties, termed as 'New Peak Detection' (i.e. NPD), and assess fold change between the reference and non-reference samples, in a representative investigation of pH stress study. The study, thus, demonstrated the suitability of the MAM workflow for characterization of heavily glycosylated Fc-fusion proteins. Moreover, its NPD feature could offer an all-encompassing view if applied for forced degradation and stability studies.

High concentration formulation developability approaches and considerations

The growing need for biologics to be administered subcutaneously and ocularly, coupled with certain indications requiring high doses, has resulted in an increase in drug substance (DS) and drug product (DP) protein concentrations. With this increase, more emphasis must be placed on identifying critical physico-chemical liabilities during drug development, including protein aggregation, precipitation, opalescence, particle formation, and high viscosity. Depending on the molecule, liabilities, and administration route, different formulation strategies can be used to overcome these challenges. However, due to the high material requirements, identifying optimal conditions can be slow, costly, and often prevent therapeutics from moving rapidly into the clinic/market. In order to accelerate and derisk development, new experimental and in-silico methods have emerged that can predict high concentration liabilities. Here, we review the challenges in developing high concentration formulations, the advances that have been made in establishing low mass and high-throughput predictive analytics, and advances in in-silico tools and algorithms aimed at identifying risks and understanding high concentration protein behavior.

Attribute Analytics Performance Metrics from the MAM Consortium Interlaboratory Study

The multi-attribute method (MAM) was conceived as a single assay to potentially replace multiple single-attribute assays that have long been used in process development and quality control (QC) for protein therapeutics. MAM is rooted in traditional peptide mapping methods; it leverages mass spectrometry (MS) detection for confident identification and quantitation of many types of protein attributes that may be targeted for monitoring. While MAM has been widely explored across the industry, it has yet to gain a strong foothold within QC laboratories as a replacement method for established orthogonal platforms. Members of the MAM consortium recently undertook an interlaboratory study to evaluate the industry-wide status of MAM. Here we present the results of this study as they pertain to the targeted attribute analytics component of MAM, including investigation into the sources of variability between laboratories and comparison of MAM data to orthogonal methods. These results are made available with an eye toward aiding the community in further optimizing the method to enable its more frequent use in the QC environment.