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.

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Monoclonal antibodies (mAbs) and related products undergo a wide range of modifications, many of which can often be directly associated to culture conditions during upstream processing. Ideally, such conditions should be monitored and fine-tuned based on real-time or close to real-time information obtained by the assessment of the product quality attribute (PQA) profile of the biopharmaceutical produced, which is the fundamental idea of process analytical technology. Therefore, methods that are simple, quick and robust, but sufficiently powerful, to allow for the generation of a comprehensive picture of the PQA profile of the protein of interest are required. A major obstacle for the analysis of proteins directly from cultures is the presence of impurities such as cell debris, host cell DNA, proteins and small-molecule compounds, which usually requires a series of capture and polishing steps using affinity and ion-exchange chromatography before characterization can be attempted. In the current study, we demonstrate direct coupling of protein A affinity chromatography with native mass spectrometry (ProA-MS) for development of a robust method that can be used to generate information on the PQA profile of mAbs and related products in as little as 5 min. The developed method was applied to several samples ranging in complexity and stability, such as simple and more complex monoclonal antibodies, as well as cysteine-conjugated antibody–drug conjugate mimics. Moreover, the method demonstrated suitability for the analysis of protein amounts of <1 μg, which suggests applicability during early-stage development activities.

Ensuring the removal of host cell proteins (HCPs) during downstream processing of recombinant proteins such as monoclonal antibodies (mAbs) remains a challenge. Since residual HCPs might affect product stability or safety, constant monitoring is required to demonstrate their removal to be below the regulatory accepted level of 100 ng/mg. The current standard analytical approach for this procedure is based on ELISA; however, this approach only measures the overall HCP content. Therefore, the use of orthogonal methods, such as liquid chromatography-mass spectrometry (LC-MS), has been established, as it facilitates the quantitation of total HCPs as well as the identification and quantitation of the individual HCPs present. In the present study, a workflow for HCP detection and quantitation using an automated magnetic bead-based sample preparation, in combination with a data-independent acquisition (DIA) LC-MS analysis, was established. Employing the same instrumental setup commonly used for peptide mapping analysis of mAbs allows for its quick and easy implementation into pre-existing workflows, avoiding the need for dedicated instrumentation or personnel. Thereby, quantitation of HCPs over a broad dynamic range was enabled to allow monitoring of problematic HCPs or to track changes upon altered bioprocessing conditions.

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