Abstract

Charge variant characterization of biologics is critical to ensure that product meets the required quality and regulatory requirements to ensure safety and efficacy of the biotherapeutic. Charge variants arise from post-translation modifications (PTMs) during upstream processing and due to enzymatic and non-enzymatic chemical reactions that occur during downstream processing and storage. Some of these modifications may impact therapeutic potency, efficacy, or immunogenicity of a biotherapeutic. The traditional workflow for characterizing charge variants that involves fraction enrichment is time-consuming and labor-intensive. This approach can be especially challenging if the product is manufactured at low concentrations (e.g., ≤2 mg/mL). Recent advances in pH-based elution for ion-exchange chromatography utilizing volatile buffers have enabled rapid native mass-spectrometry-based identification of PTMs and proteoforms associated with protein therapeutics. In this study, we develop a novel workflow to rapidly and unambiguously characterize modifications associated with a new class of biotherapeutics known as bispecific antigen-binding protein (BsABP), including low-level modifications. A cation-exchange separation was optimized using volatile buffers to provide online hyphenation for native mass spectrometry to profile modifications and proteoforms present at the native level of a biotherapeutic, such as deamidation, O-glycosylation, amino acid substitution, N-linked glycosylation and oxidation. Furthermore, a limited proteolysis method was developed to specifically inform about modifications in the different domains of the bispecific antibody. Using this approach, we could efficiently identify PTMs in unstressed, thermally and photo-stressed samples, and provide information about the impact of downstream purification in clearing out modified BsABP species. Furthermore, peptide mapping was performed to identify and confirm modifications at the amino acid residue level. The developed workflow is less time-consumable and reduces sample processing- and analysis-related artifacts compared to traditional approaches.

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