Development of a comprehensive approach for performance evaluation of a quantitative multi-attribute method as a quality control method.

The multi-attribute method has been recognized as an elegant quantification tool for post-translational modifications (PTMs) of therapeutic proteins, since it can evaluate several attributes spontaneously and site-specifically. Here, the abundance of PTMs calculated by three different types of formula were compared and there was little difference among the results. For the method evaluation, two different kinds of peptides were used as internal standards (ISs) and one of the IS was used as the "standard peak" to define the signal strength of MS. They are also used for system suitability testing to verify whether the condition or sensitivity of mass spectrometry are high enough to evaluate the minor components by confirming the recovery rate of one IS to the another. This system is beneficial that since we have defined the limit of quantification as a certain ratio to IS, consistent MS intensity is applied as the threshold across all detected peaks.

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

During the manufacturing of therapeutic proteins, Critical Quality Attributes (CQAs) have been monitored by conventional methods, such as cation exchange chromatography (CEX), reduced capillary electrophoresis-sodium dodecyl sulfate (rCE-SDS), and 1,2-diamino-4,5-methylenedioxybenzene (DMB) labelling method. The conventional methods often generate individual peaks that contain multiple components, which may obscure the detection and the quantification of individual critical quality attributes (CQAs). Alternatively, Multi-Attribute Method (MAM) enables detection and quantification of specific CQAs. A high resolution MAM has been developed and qualified to replace several conventional methods in monitoring product quality attributes, such as oxidation, deamidation, clipping, and glycosylation. The qualified MAM was implemented in process characterization, as well as release and stability assays in quality control (QC). In combination with a design-of-experiments (DoE), the MAM method identified multivariate process parameter ranges that yield acceptable CQA level, which provides operational flexibility for manufacturing.

Multi-attribute method performance profile for quality control of monoclonal antibody therapeutics.

Multi-attribute method (MAM) using peptide map analysis with high resolution mass spectrometry is increasingly common in product characterization and the identification of critical quality attributes (CQAs) of biotherapeutic proteins. Capable of providing structural information specific to amino acid residues, quantifying relative abundance of product variants or degradants, and detecting profile changes between product lots, a robust MAM can replace multiple traditional methods that generate profile-based information for product release and stability testing. In an effort to provide informative and efficient analytical monitoring for monoclonal antibody (mAb) products, from early development to manufacturing quality control, we describe the desired MAM performance profile and address the major scientific challenges in MAM method validation. Furthermore, to support fast speed investigational product development, we describe a platform method validation strategy and results of an optimized MAM workflow. This strategy is applied to support the use of MAM for multiple mAb products with similar structures and physicochemical properties, requiring minimal product-specific method validation activities. Three mAb products were used to demonstrate MAM performance for common and representative product quality attributes. Method validation design and acceptance criteria were guided by the Analytical Target Profile concept, as well as relevant regulatory guidelines to ensure the method is fit-for-purpose. A comprehensive system suitability control strategy was developed, and reported here, to ensure adequate performance of the method including sample preparation, instrument operation, and data analysis. Our results demonstrated sufficient method performance for the characteristics required for quantitative measurement of product variants and degradants.

Enhancing the multi-attribute method through an automated and high-throughput sample preparation.

The multi-attribute method (MAM), a recent advance in the application of liquid chromatography-mass spectrometry within the pharmaceutical industry, enables the simultaneous monitoring of multiple product quality attributes in a single analytical method. While MAM is coupled with automated data processing and reporting, the sample preparation, based on proteolytic peptide mapping, remains cumbersome and low throughput. The standard sample preparation for MAM relies on protein denaturation, reduction, and alkylation prior to proteolytic digestion, but often a desalting step is required to maintain enzymatic activity. While most of the sample preparation can be automated on a standard robotic liquid handling system, a streamlined approach for protein desalting and temperature modulation is required for a viable, fully automated digestion. In this work, for the first time, a complete tip-based MAM sample preparation is automated on a single robotic liquid handling system, leveraging a deck layout that integrates both heating and cooling functionalities. The fully automated method documented herein achieves a high-throughput sample preparation for MAM, while maintaining superior method performance.Abbreviations: MAM: multi-attribute method; PQAs: product quality attributes; CE: capillary electrophoresis; IEX: ion-exchange chromatography; HILIC-FLR: hydrophilic interaction liquid chromatography coupled to a fluorescence detector; RP-LC/UV: reversed-phase liquid chromatography coupled to a UV detector; MS: mass spectrometry; NPD: new peak detection; GdnHCl: guanidine hydrochloride; TIC: total ion current; pAb: polyclonal antibody; IgG: immunoglobulin G; DTT: dithiothreitol; IAA: iodoacetic acid; TFA: trifluoroacetic acid; A280: absorbance at 280 nm wavelength; 96MPH: 96-channel multi-probe head; CPAC: Cold Plate Air Cooled; HHS: Hamilton Heater Shaker; DWP: Deep-Well Plate; PCR: Polymerase Chain Reaction; NTR: Nested Tip Rack; Met: methionine; Trp: tryptophan; N-term pQ: N-terminal glutamine cyclization; Lys: lysine; PAM: peptidylglycine α-amidating monooxygenase; G0F: asialo-, agalacto-, bi-antennary, core substituted with fucose; G1F: asialo-, mono-galactosylated bi-antennary, core substituted with fucose; G2F: asialo-, bi-galactosylated bi-antennary, core substituted with fucose; G0: asialo-, agalacto-, bi-antennary; Man5: oligomannose 5; Man8: oligomannose 8; TriF: asialo-, tri-galactosylated tri-antennary, core substituted with fucose.

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.

Advancing Mass Spectrometry Technology in cGMP Environments.

Mass spectrometry is a powerful analytical tool that has been widely used in the biotech industry. Recent trends of implementing a liquid chromatography-mass spectrometry (LC-MS) based multi-attribute method (MAM) in cGMP environments enables end-to-end monitoring and control of critical quality attributes (CQAs) of therapeutic proteins to ensure drug product quality.

Rapid Intact mass based multi-attribute method in support of mAb upstream process development.

N-linked glycosylation is a critical quality attribute for monoclonal antibodies (mAbs) as it affects product stability, immunogenicity, receptor binding and antibody effector function, clearance and half-life. It has been widely accepted that the glycosylation process is greatly impacted by several factors during bioreactor operations. Therefore, the timely acquisition of N-linked glycosylation information during cell culture process development is critical for the success of the endeavor. In this paper we describe a simple, rapid, and robust Multi-Attribute Method (MAM) based on intact mass analysis. This method, developed for an open access instrument, has been optimized for the analysis of light and heavy chains generated from dithiothreitol (DTT) reduction of intact mAbs sampled directly out of bioreactors. The N-linked glycosylation profile, identity confirmation of light chain and heavy chain, light chain glycation and non-glycosylated heavy chain (NGHC) can all be monitored by this method. Our results confirm that the N-linked glycosylation profile determined using Intact mass based MAM is comparable with a release glycan assay and LC-MS/MS peptide based MAM assay for the most abundant glycoforms. Furthermore, the results for the NGHC attribute determined with our method are comparable to results from capillary gel electrophoresis (CGE) and LC-MS/MS peptide based MAM.

Development of a quantitative mass spectrometry multi-attribute method for characterization, quality control testing and disposition of biologics.

Regulatory agencies have recently recommended a Quality by Design (QbD) approach for the manufacturing of therapeutic molecules. A QbD strategy requires deep understanding at the molecular level of the attributes that are crucial for safety and efficacy and for insuring that the desired quality of the purified protein drug product is met at the end of the manufacturing process. A mass spectrometry (MS)-based approach to simultaneously monitor the extensive array of product quality attributes (PQAs) present on therapeutic molecules has been developed. This multi-attribute method (MAM) uses a combination of high mass accuracy / high resolution MS data generated by Orbitrap technology and automated identification and relative quantification of PQAs with dedicated software (Pinpoint). The MAM has the potential to replace several conventional electrophoretic and chromatographic methods currently used in Quality Control to release therapeutic molecules. The MAM represents an optimized analytical solution to focus on the attributes of the therapeutic molecule essential for function and implement QbD principles across process development, manufacturing and drug disposition.