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.

Rapid identification of an antibody DNA construct rearrangement sequence variant by mass spectrometry.

During cell line development for an IgG1 antibody candidate (mAb1), a C-terminal extension was identified in 2 product candidate clones expressed in CHO-K1 cell line. The extension was initially observed as the presence of anomalous new peaks in these clones after analysis by cation exchange chromatography (CEX-HPLC) and reduced capillary electrophoresis (rCE-SDS). Reduced mass analysis of these CHO-K1 clones revealed that a larger than expected mass was present on a sub-population of the heavy chain species, which could not be explained by any known chemical or post-translational modifications. It was suspected that this additional mass on the heavy chain was due to the presence of an additional amino acid sequence. To identify the suspected additional sequence, de novo sequencing in combination with proteomic searching was performed against translated DNA vectors for the heavy chain and light chain. Peptides unique to the clones containing the extension were identified matching short sequences (corresponding to 9 and 35 amino acids, respectively) from 2 non-coding sections of the light chain vector construct. After investigation, this extension was observed to be due to the re-arrangement of the DNA construct, with the addition of amino acids derived from the light chain vector non-translated sequence to the C-terminus of the heavy chain. This observation showed the power of proteomic mass spectrometric techniques to identify an unexpected antibody sequence variant using de novo sequencing combined with database searching, and allowed for rapid identification of the root cause for new peaks in the cation exchange and rCE-SDS assays.