Host cell proteins (HCPs) are residual impurities generated by the expression cell line during the production of biopharmaceuticals. Although the majority of these contaminants are removed during purification, HCPs can represent a considerable risk to the efficacy and safety of a therapeutic protein if not actively monitored. The enzyme-linked immunosorbent assay (ELISA) is commonly used throughout production to monitor HCP levels but has limited ability to identify novel HCPs or provide detailed quantification. Liquid chromatography tandem mass spectrometry (LC-MS2) methods are increasingly being used in conjunction with established ELISA techniques to provide rapid adaptability to increasingly complex samples as well as highly quantitative and informative results. However, MS-based methods are still hindered by the large dynamic range between high abundance biopharmaceutical proteins and low abundance HCPs. Here, we propose a multifactorial approach designed to optimize HCP detection in purified monoclonal antibody samples with LC-MS2. By first depleting the sample of antibody on a protein A column, then specifically digesting HCPs while precipitating remaining antibody, and finally reducing spectral complexity through compensation voltage (CV) switching using high-field asymmetric waveform ion mobility spectrometry (FAIMS), we identified multiple-fold more HCPs in the NIST monoclonal antibody standard than any single established mass spectrometry technique reported in the literature. Our analyses consistently identified over 600 high confidence mouse HCPs, a multifold increase over established methods, while maintaining high reproducibility.

Middle-down analysis of monoclonal antibodies (mAbs) by tandem mass spectrometry (MS2) can provide detailed insight into their primary structure with minimal sample preparation. The middle-down approach uses an enzyme to cleave mAbs into Fc/2, LC, and Fd subunits that are then analyzed by reversed phase liquid chromatography tandem mass spectrometry (RPLC–MS2). As maximum sequence coverage is desired to obtain meaningful structural information at the subunit level, a host of dissociation methods have been developed, and sometimes combined, to bolster fragmentation and increase the number of identified fragments. Here, we present a design of experiments (DOE) approach to optimize MS2 parameters, in particular those that may influence electron transfer dissociation (ETD) efficiency to increase the sequence coverage of antibody subunits. Applying this approach to the NIST monoclonal antibody standard (NISTmAb) using three RPLC–MS2 runs resulted in high sequence coverages of 67%, 67%, and 52% for Fc/2, LC, and Fd subunits, respectively. In addition, we apply this DOE strategy to model the parameters required to maximize the number of fragments produced in “low”, “medium”, and “high” mass ranges, which ultimately resulted in even higher sequence coverages of NISTmAb subunits (75%, 78%, and 64% for Fc/2, LC, and Fd subunits, respectively). The DOE approach provides high sequence coverage percentages utilizing only one fragmentation method, ETD, and could be extended to other state-of-the-art techniques that combine multiple fragmentation mechanisms to increase coverage.

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