Development of orthogonal NISTmAb size heterogeneity control methods.

The NISTmAb is a monoclonal antibody Reference Material from the National Institute of Standards and Technology; it is a class-representative IgG1κ intended to serve as a pre-competitive platform for harmonization and technology development in the biopharmaceutical industry. The publication series of which this paper is a part describes NIST's overall control strategy to ensure NISTmAb quality and availability over its lifecycle. In this paper, the development of a control strategy for monitoring NISTmAb size heterogeneity is described. Optimization and qualification of size heterogeneity measurement spanning a broad size range are described, including capillary electrophoresis-sodium dodecyl sulfate (CE-SDS), size exclusion chromatography (SEC), dynamic light scattering (DLS), and flow imaging analysis. This paper is intended to provide relevant details of NIST's size heterogeneity control strategy to facilitate implementation of the NISTmAb as a test molecule in the end user's laboratory. Graphical abstract Representative size exclusion chromatogram of the NIST monoclonal antibody (NISTmAb). The NISTmAb is a publicly available research tool intended to facilitate advancement of biopharmaceutical analytics. HMW = high molecular weight (trimer and dimer), LMW = low molecular weight (2 fragment peaks). Peak labeled buffer is void volume of the column from L-histidine background buffer.

Harmonizing lipidomics: NIST interlaboratory comparison exercise for lipidomics using SRM 1950-Metabolites in Frozen Human Plasma.

As the lipidomics field continues to advance, self-evaluation within the community is critical. Here, we performed an interlaboratory comparison exercise for lipidomics using Standard Reference Material (SRM) 1950-Metabolites in Frozen Human Plasma, a commercially available reference material. The interlaboratory study comprised 31 diverse laboratories, with each laboratory using a different lipidomics workflow. A total of 1,527 unique lipids were measured across all laboratories and consensus location estimates and associated uncertainties were determined for 339 of these lipids measured at the sum composition level by five or more participating laboratories. These evaluated lipids detected in SRM 1950 serve as community-wide benchmarks for intra- and interlaboratory quality control and method validation. These analyses were performed using nonstandardized laboratory-independent workflows. The consensus locations were also compared with a previous examination of SRM 1950 by the LIPID MAPS consortium. While the central theme of the interlaboratory study was to provide values to help harmonize lipids, lipid mediators, and precursor measurements across the community, it was also initiated to stimulate a discussion regarding areas in need of improvement.

LipidQC: Method Validation Tool for Visual Comparison to SRM 1950 Using NIST Interlaboratory Comparison Exercise Lipid Consensus Mean Estimate Values.

As advances in analytical separation techniques, mass spectrometry instrumentation, and data processing platforms continue to spur growth in the lipidomics field, more structurally unique lipid species are detected and annotated. The lipidomics community is in need of benchmark reference values to assess the validity of various lipidomics workflows in providing accurate quantitative measurements across the diverse lipidome. LipidQC addresses the harmonization challenge in lipid quantitation by providing a semiautomated process, independent of analytical platform, for visual comparison of experimental results of National Institute of Standards and Technology Standard Reference Material (SRM) 1950, "Metabolites in Frozen Human Plasma", against benchmark consensus mean concentrations derived from the NIST Lipidomics Interlaboratory Comparison Exercise.

Analysis of deamidation artifacts induced by microwave-assisted tryptic digestion of a monoclonal antibody.

The thorough characterization of biopharmaceuticals is essential for ensuring their quality and safety since many potential variations can cause changes to the properties of a drug that may be detrimental to the patient such as decreased efficacy, shorter half-life or increased immunogenicity. Prior to approval and release, protein-based drugs are subject to a battery of analyses to assess the nature of those parameters that are considered critical quality attributes. In some cases the analytical method used may itself cause modifications that are impossible to distinguish from those induced by the intended test conditions (e.g. storage time/temperature, light exposure) which are used to assess drug stability. It is therefore important to develop and utilize analytical methods which impose as few artifactual modifications as possible. Asparagine deamidation is a common protein modification and it is known to be induced during tryptic digestion. Therefore we examined common tryptic digestion protocols and compared their propensities towards asparagine modification. Since microwave assisted hydrolysis techniques are often used to shorten digestion times and the effect on deamidation is unknown we sought to compare this method against alternate digestion protocols.

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.

New Peak Detection Performance Metrics from the MAM Consortium Interlaboratory Study.

The Multi-Attribute Method (MAM) Consortium was initially formed as a venue to harmonize best practices, share experiences, and generate innovative methodologies to facilitate widespread integration of the MAM platform, which is an emerging ultra-high-performance liquid chromatography-mass spectrometry application. Successful implementation of MAM as a purity-indicating assay requires new peak detection (NPD) of potential process- and/or product-related impurities. The NPD interlaboratory study described herein was carried out by the MAM Consortium to report on the industry-wide performance of NPD using predigested samples of the NISTmAb Reference Material 8671. Results from 28 participating laboratories show that the NPD parameters being utilized across the industry are representative of high-resolution MS performance capabilities. Certain elements of NPD, including common sources of variability in the number of new peaks detected, that are critical to the performance of the purity function of MAM were identified in this study and are reported here as a means to further refine the methodology and accelerate adoption into manufacturer-specific protein therapeutic product life cycles.