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Multiple reaction monitoring (MRM) is a liquid chromatography−mass spectrometry (LC−MS) based quantification platform with high sensitivity, specificity, and throughput. It is extensively used across the pharmaceutical industry for the quantitative analysis of therapeutic molecules. The potential of MRM analysis for the quantification of specific host cell proteins (HCPs) in bioprocess, however, has yet to be well established. In this work, we introduce a multiplex LC−MRM assay that simultaneously monitors two high risk lipases known to impact biologics product quality, Phospholipase B-like 2 protein (PLBL2) and Group XV lysosomal phospholipase A2 (LPLA2). Quantitative data generated from the LC−MRM assay were used to monitor the clearance of these lipases during biologics process development. The method is linear over a dynamic range of 1 to 500 ng/ mg. To demonstrate the fitness for use and robustness of this assay, we evaluate a comprehensive method qualification package that includes intra-and inter-run precision and accuracy across all evaluated concentrations, selectivity, recovery and matrix effect, dilution linearity, and carryover. Additionally, we illustrate that this assay provides a rapid and accurate means of monitoring high risk HCP clearance for in-process support and can actively guide process improvement and optimization. Lastly, we compare direct digestion platforms and affinity depletion platforms to demonstrate the impact of HCP−mAb interaction on lipase quantification.

The mass spectrometry based multi-attribute method (MAM) has gained popularity in the field of biopharmaceutical analysis as it promises a single method for comprehensive monitoring of multiple product quality attributes (PQAs) and product purity. Sample preparation for protein digestion and peptide separation are critical considerations for a reduced peptide mapping-based MAM. To avoid desalting steps required in tryptic protein digestion and in order to improve peptide separation for hydrophilic peptides, we developed an improved robust sample preparation using Lys-C protease for high-throughput MAM testing. Additionally, this method optimizes the peptide retention and separation of a stability-indicating VSNK peptide using a HSS T3 column for comprehensive PQA monitoring. A fully automated sample preparation had similar assay variations for PQAs monitoring compared to manual sample preparation. To the best of our knowledge, this is the first report of a high-resolution MS-based MAM using Lys-C digestion with enhanced PQA monitoring for hydrophilic peptides. The improved, robust MAM workflow for protein digestion and peptide separation will pave the way for broader MAM qualification and its applications for the characterization and quality control of therapeutic monoclonal antibodies.

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