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Multi-Attribute Monitoring Method for Process Development of Engineered Antibody for Site-Specific Conjugation

Journal of the American Society for Mass Spectrometry(2023)

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Abstract
Antibodydrug conjugates, a class of biotherapeutic proteins,havebeen extensively developed in recent years, resulting in new approvalsand improved standard of care for cancer patients. Among the numerousstrategies of conjugating cytotoxic payloads to monoclonal antibodies,insertion of a cysteine residue achieves a tightly controlled, site-specificdrug to antibody ratio. Tailored analytical tools are required todirect the development of processes capable of manufacturing novelantibody scaffolds with the desired product quality. Here, we describethe development of a 12 min, mass-spectrometry-based method capableof monitoring four distinct quality attributes simultaneously: variationsin the thiol state of the inserted cysteines, N-linked glycosylation,reduction of interchain disulfide bonds, and polypeptide fragmentation.This method provides new insight into the properties of the antibodyintermediate and associated manufacturing processes. Oxidized thiolstates are formed within the bioreactor, of which a variant containingan additional disulfide bond was produced and remained relativelyconstant throughout the fed-batch process; reduced thiol variantswere introduced upon harvest. Nearly 20 percent of N-linked glycanscontained sialic acid, substantially higher than anticipated for wildtypeIgG1. Lastly, previously unreported polypeptide fragmentation siteswere identified in the C239i constant domain, and the relationshipbetween fragmentation and glycoform were explored. This work illustratesthe utility of applying a high-throughput liquid chromatography-massspectrometry multi-attribute monitoring method to support the developmentof engineered antibody scaffolds.
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Key words
multi-attributemonitoring (MAM),antibody intermediate,antibody-drugconjugate (ADC),site-specific conjugation,biologicmanufacturing processes,glycosylation,mass spectrometry(MS)
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