ArticleJournal of the American Society for Mass Spectrometry2022
Comprehensive Multidimensional Liquid Chromatography-Mass Spectrometry for the Characterization of Charge Variants of a Bispecific Antibody.
Article in Journal of the American Society for Mass Spectrometry, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
1 citing paper in PubMed.
- Establishing Multi-Dimensional LC-MS Systems for Versatile Workflows to Analyze Therapeutic Antibodies at Different Molecular Levels in Routine Operations.Pharmaceuticals (Basel, Switzerland) · 2025Article
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Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Identification and further characterization of antibody charge variants is a crucial step during biopharmaceutical drug development, particularly with regard to the increasing complexity of novel antibody formats. As a standard analytical approach, manual offline fractionation of charge variants by cation-exchange chromatography followed by comprehensive analytical testing is applied. These conventional workflows are time-consuming and labor-intensive and overall reach their limits in terms of chromatographic separation of enhanced structural heterogeneities raised from new antibody formats. For these reasons, we aimed to develop an alternative online characterization strategy for charge variant characterization of a therapeutic bispecific antibody by online mD-LC-MS at middle-up (2D-LC-MS) and bottom-up (4D-LC-MS) level. Using the implemented online mD-LC-MS approach, all medium- and even low-abundant product variants previously identified by offline fraction experiments and liquid chromatography mass spectrometry could be monitored. The herein reported automated online mD-LC-MS methodology therefore represents a complementary and in part alternative approach for analytical method validation including multiattribute monitoring (MAM) strategies by mass spectrometry, offering various benefits including increased throughput and reduced sample handling and combined protein information at intact protein and peptide level.
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