Assessment of monoclonal antibody glycosylation: a comparative study using HRMS, NMR, and HILIC-FLD.

Monoclonal antibodies (mAbs) represent the largest class of therapeutic protein drug products. mAb glycosylation produces a heterogeneous, analytically challenging distribution of glycoforms that typically should be adequately characterized because glycosylation-based product quality attributes (PQAs) can impact product quality, immunogenicity, and efficacy. In this study, two products were compared using a panel of analytical methods. Two high-resolution mass spectrometry (HRMS) workflows were used to analyze N-glycans, while nuclear magnetic resonance (NMR) was used to generate monosaccharide fingerprints. These state-of-the-art techniques were compared to conventional analysis using hydrophilic interaction chromatography (HILIC) coupled with fluorescence detection (FLD). The advantages and disadvantages of each method are discussed along with a comparison of the identified glycan distributions. The results demonstrated agreement across all methods for major glycoforms, demonstrating how confidence in glycan characterization is increased by combining orthogonal analytical methodologies. The full panel of methods used represents a diverse toolbox that can be selected from based on the needs for a specific product or analysis.

An Integrated Analysis of Metabolites, Peptides, and Inflammation Biomarkers for Assessment of Preanalytical Variability of Human Plasma.

Discrepancies in blood sample collection and processing could have a significant impact on levels of metabolites, peptides, and protein biomarkers of inflammation in the blood; thus, sample quality control is critical for successful biomarker identification and validation. In this study, we analyzed the effects of several preanalytical processing conditions, including different storage times and temperatures for blood or plasma samples and different centrifugation forces on the levels of metabolites, peptides, and inflammation biomarkers in human plasma samples using ethylenediaminetetraacetic acid (EDTA) as an anticoagulant. Temperature was found to be the major factor for metabolite variation, and both time and temperature were identified as major factors for peptide variation. For inflammation biomarkers, temperature played different roles depending on the sample type (blood or plasma). Low temperature affected inflammation biomarkers in blood, while room temperature impacted inflammation biomarkers in plasma.

Stability of the Human Plasma Proteome to Pre-analytical Variability as Assessed by an Aptamer-Based Approach.

Variable processing and storage of whole blood and/or plasma are potential confounders in biomarker development and clinical assays. The goal of the study was to investigate how pre-analytical variables impact the human plasma proteome. Whole blood obtained from 16 apparently healthy individuals was collected in six EDTA tubes and processed randomly under six pre-analytical variable conditions including blood storage at 0 °C or RT for 6 h (B6h0C or B6hRT) before processing to plasma, plasma storage at 4 °C or RT for 24 h (P24h4C or P24hRT), low centrifugal force at 1300 × g, (Low×g), and immediate processing to plasma under 2500 × g (control) followed by plasma storage at -80 °C. An aptamer-based proteomic assay was performed to identify significantly changed proteins (fold change ≥1.2, P < 0.05, and false discovery rate < 0.05) relative to the control from a total of 1305 proteins assayed. Pre-analytical conditions Low×g and B6h0C resulted in the most plasma proteome changes with 200 and 148 proteins significantly changed, respectively. Only 36 proteins were changed under B6hRT. Conditions P24h4C and P24hRT yielded changes of 28 and 75 proteins, respectively. The complement system was activated in vitro under the conditions B6hRT, P24h4C, and P24hRT. The results suggest that particular pre-analytical variables should be controlled for clinical measurement of specific biomarkers.

Multi-Attribute Method for Quality Control of Therapeutic Proteins.

Recent advances in high resolution mass spectrometry (MS) instrumentation and semi-automated software have led to a push toward the use of MS-based methods for quality control (QC) testing of therapeutic proteins in a cGMP environment. The approach that is most commonly being proposed for this purpose is known as the multi-attribute method (MAM). MAM is a promising approach that provides some distinct benefits compared to conventional methods currently used for QC testing of protein therapeutics, such as CEX, HILIC, and CE-SDS. Because MS-based methods have not been regularly used in this context in the past, new scientific and regulatory questions should be addressed prior to the final stages of implementation. We have categorized these questions into four major aspects for MAM implementation in a cGMP environment for both new and existing products: risk assessment, method validation, capabilities and specificities of the New Peak Detection (NPD) feature, and comparisons to conventional methods. This perspective outlines considerations for each of these main points and suggests approaches to help address potential issues.

The role of mass spectrometry in the characterization of biologic protein products.

INTRODUCTION: Mass spectrometry (MS) is widely used in the characterization of biomolecules including peptide and protein therapeutics. These biotechnology products have seen rapid growth over the past few decades and continue to dominate the global pharmaceutical market. Advances in MS instrumentation and techniques have enhanced protein characterization capabilities and supported an increased development of biopharmaceutical products. Areas covered: This review describes recent developments in MS-based biotherapeutic analysis including sequence determination, post-translational modifications (PTMs) and higher order structure (HOS) analysis along with improvements in ionization and dissociation methods. An outlook of emerging applications of MS in the lifecycle of product development such as comparability, biosimilarity and quality control practices is also presented. Expert commentary: MS-based methods have established their utility in the analysis of new biotechnology products and their lifecycle appropriate implementation. In the future, MS will likely continue to grow as one of the leading protein identification and characterization techniques in the biopharmaceutical industry landscape.

Modern analytics for synthetically derived complex drug substances: NMR, AFFF-MALS, and MS tests for glatiramer acetate.

Glatiramer acetate (GA) is a mixture of synthetic copolymers consisting of four amino acids (glutamic acid, lysine, alanine, and tyrosine) with a labeled molecular weight range of 5000 to 9000 Da. GA is marketed as Copaxone™ by Teva for the treatment of multiple sclerosis. Here, the agency has evaluated the structure and composition of GA and a commercially available comparator, Copolymer-1. Modern analytical technologies which can characterize these complex mixtures are desirable for analysis of their comparability and structural "sameness." In the studies herein, a molecular fingerprinting approach is taken using mass-accurate mass spectrometry (MS) analysis, nuclear magnetic resonance (NMR) (1D-(1)H-NMR, 1D-(13)C-NMR, and 2D NMR), and asymmetric field flow fractionation (AFFF) coupled with multi-angle light scattering (MALS) for an in-depth characterization of three lots of the marketplace drug and a formulated sample of the comparator. Statistical analyses were applied to the MS and AFFF-MALS data to assess these methods' ability to detect analytical differences in the mixtures. The combination of multiple orthogonal measurements by liquid chromatography coupled with MS (LC-MS), AFFF-MALS, and NMR on the same sample set was found to be fit for the intended purpose of distinguishing analytical differences between these complex mixtures of peptide chains.

Improved precision of proteomic measurements in immunoprecipitation based purifications using relative quantitation.

Mass spectrometry coupled immunoprecipitation (MS-IP) studies are useful in identifying and quantitating potential binding partners of a target protein. However, they are often conducted without appropriate loading controls. Western blots are often used to analyze loading controls, yet there are limitations to their usefulness as analytical tools. One remedy for this is the use of selected reaction monitoring (SRM), where the areas under the curve (AUCs) of peptides from a protein of interest can be normalized to those from the constant regions of the immunoglobulins used for the IP. Using this normalization method, significant changes in relative peptide abundance were observed between samples when there appeared to be an unequal load based on immunoglobulin peptide abundance.

Method validation and new peak detection for the liquid chromatography-mass spectrometry multi-attribute method.

The multi-attribute method (MAM) is a liquid chromatography-mass spectrometry (LC-MS) peptide mapping technique that has been proposed as a replacement for several conventional quality control (QC) methods for therapeutic proteins. In addition to quantification of multiple product quality attributes (PQAs), MAM can also monitor impurities using a new peak detection (NPD) feature. Here, results are provided from method validation and NPD studies of an MAM approach applied to rituximab as a model monoclonal antibody (mAb). Twenty-one rituximab PQAs were monitored, including oxidation, pyroglutamination, deamidation, lysine clipping, and glycosylation. The PQA monitoring aspect of the method was validated according to ICH Guidance. Accuracy, precision, specificity, detection and quantitation limits, linearity, range, and robustness were demonstrated for this MAM approach with minimal issues. All PQAs were successfully validated except for several oxidation sites, which did not pass intermediate precision criteria. The variability found in oxidation measurements was attributed to artificial oxidation during sample preparation and could likely be alleviated through several approaches. The NPD aspect of the method was also evaluated. A spike-in approach was used to assess the limits of detection and quantitation (LOD/LOQ) of the NPD feature of MAM. For NPD, the peak intensity threshold was found to be the most critical parameter for accurate detection of impurities since a low threshold can result in false positives while a high threshold can obscure the detection of true peaks. Overall, the MAM approach presented and validated here has been demonstrated to be suitable for both targeted monitoring of rituximab PQAs and non-targeted detection of new peaks that represent impurities.

The Use of Mass Spectrometry in Therapeutic Protein Biologics License Applications: A Retrospective Review Revisited.

Biologic license applications (BLAs) for 93 therapeutic proteins approved between 2016 and 2020 were analyzed for use of mass spectrometry (MS) as a follow up to a previous study that assessed MS use in BLAs from 2000 to 2015. Thirty percent of these BLAs were biosimilars, while only one biosimilar BLA was approved prior to 2016. This analysis evaluated the use of a variety of MS techniques and instrumentation. Results were further interpreted based on the relationship of MS use over time, between drug types, and between new drugs and biosimilars. MS data were included in 93 BLAs examined. The top eight quality attributes most assessed by MS in rank order were amino acid sequence, molecular mass, oxidation, disulfide bonds, deamidation, glycosylation, N-terminal sequence variants, and C-terminal sequence variants. These attributes were the same top attributes seen previously from BLAs approved between 2000 and 2015, and the use of MS to analyze them generally continued to increase across the new time frame. The average number of attributes analyzed by MS per BLA also continued to increase over the extended time frame of 21 years. High-resolution, accurate mass instrumentation such as the Orbitrap and time-of-flight (TOF) usage increased over time for all assessed attributes, while matrix-assisted laser desorption/ionization (MALDI)-TOF/(TOF) usage decreased. From highest to lowest rank, the top 11 attributes were antibody drug conjugate (ADC) characterization (i.e., drug load distribution/drug to antibody ratio (DAR), ADC and linkage site, and synthetic linker), isomerization, folding/higher-order structure (HOS), truncation, host cell proteins (HCPs), sequence variants (amino acid substitutions), succinimidation, glycation, PEGylation, charge variants, and oxidation.

An etanercept O-glycovariant with enhanced potency.

Most therapeutic proteins are glycosylated with N-glycans and/or O-glycans. N-glycans on therapeutic proteins have been extensively studied for their control strategy and impact on drug product quality. However, knowledge of O-glycosylation in therapeutic protein production and its impact on product quality remains elusive. To address this gap, we generated an O-glycoengineered Chinese Hamster Ovary (CHO) cell line platform to modulate O-glycosylation of therapeutic proteins and investigated the impact of O-glycans on the physicochemical and biological properties of etanercept. Our results demonstrate that this CHO cell line platform produces controlled O-glycosylation profiles containing either truncated O-glycans (sialylTn and/or Tn), or sialylCore 3 alone, or sialylCore 1 with sialylTn or sialylCore 3 O-glycans on endogenous and recombinant proteins. Moreover, the platform demonstrated exclusive modulation of O-glycosylation without affecting N-glycosylation. Importantly, certain O-glycans on etanercept enhanced tumor necrosis factor-α binding affinity and consequent potency. This is the first report that describes the systematic establishment of an O-glycoengineered CHO cell line platform with direct evidence that supports the applicability of the platform in the production of engineered proteins with desired O-glycans. This platform is valuable for identifying O-glycosylation as a critical quality attribute of biotherapeutics using the quality by design principle.