Rapid peptide mapping of monoclonal antibodies with direct infusion mass spectrometry

Peptide mapping is a critical tool for characterizing biotherapeutic proteins and is essential for the development of monoclonal antibody drugs. Here we describe a new direct infusion technology that streamlines peptide mapping data collection and analysis, accelerating the method by up to 100-fold. This method, which we term RaPiD-mAb-MS, combines high-throughput plate-based sample preparation with direct infusion mass spectrometry analysis. RaPiD-mAb-MS allows analysis of 96 samples within ∼ 1.5 to 2 hours, routinely achieves >95% sequence coverage, and has been successfully applied to 28 unique antibodies and over 2,000 samples. Here we demonstrate that RaPiD-mAb-MS detects and quantifies oxidation, deamidation, isomerization, glycosylation, and sequence variants with results comparable to conventional LC-MS based methods in a fraction of the time. Further, by eliminating chromatography, data analysis is greatly streamlined and simplified. By allowing for the collection of ∼ 1,000 peptide maps per day, RaPiD-mAb-MS is positioned to accelerate all phases of antibody-based drug discovery & development and sets the stage for collection of massive datasets that would allow artificial intelligent prediction of optimal antibody variants and formulations.

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Publication Details

Journal
Communications Chemistry
Published
2026-11-06
DOI
https://doi.org/10.1038/s42004-026-02260-8
Citations
1
Primary Topic
Mass Spectrometry Techniques and Applications
Type
article
Field-Weighted Citation Impact
1.36

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article

Rapid peptide mapping of monoclonal antibodies with direct infusion mass spectrometry

John S. Chlystek, Gihoon Lee, Benton J. Anderson, Joomi Ahn et al.
1 citations
Communications Chemistry
Mass Spectrometry Techniques and Applications
1.36
article

Rapid peptide mapping of monoclonal antibodies with direct infusion mass spectrometry

John S. Chlystek, Gihoon Lee, Benton J. Anderson, Joomi Ahn, Pavel G. Sinitcyn, Alayna M. George Thompson, Harsha P. Gunawardena, Lloyd M. Smith, Marcel Morgenstern, Lia R. Serrano, Alexander S. Hebert, Bhavin R. Patel, Scott T. Quarmby, Austin Z. Salome, Keaton L. Mertz, Ian J. Miller, Malika P. Godamudunage, Craig D. Wenger, Joshua J. Coon, Erik Miller-Galow, Michael Batt
article en
1 citations

Abstract

Peptide mapping is a critical tool for characterizing biotherapeutic proteins and is essential for the development of monoclonal antibody drugs. Here we describe a new direct infusion technology that streamlines peptide mapping data collection and analysis, accelerating the method by up to 100-fold. This method, which we term RaPiD-mAb-MS, combines high-throughput plate-based sample preparation with direct infusion mass spectrometry analysis. RaPiD-mAb-MS allows analysis of 96 samples within ∼ 1.5 to 2 hours, routinely achieves >95% sequence coverage, and has been successfully applied to 28 unique antibodies and over 2,000 samples. Here we demonstrate that RaPiD-mAb-MS detects and quantifies oxidation, deamidation, isomerization, glycosylation, and sequence variants with results comparable to conventional LC-MS based methods in a fraction of the time. Further, by eliminating chromatography, data analysis is greatly streamlined and simplified. By allowing for the collection of ∼ 1,000 peptide maps per day, RaPiD-mAb-MS is positioned to accelerate all phases of antibody-based drug discovery & development and sets the stage for collection of massive datasets that would allow artificial intelligent prediction of optimal antibody variants and formulations.

Communications Chemistry
Johnson & Johnson (United States) (US), University of Wisconsin–Madison (US), Eli Lilly (United States) (US), AbbVie (United States) (US), Morgridge Institute for Research (US)
University of Wisconsin-Madison, National Institutes of Health, National Institute of Standards and Technology, Genentech, National Institute of General Medical Sciences
Good health and well-being
Openalex Percentile: Top 19%
Mass Spectrometry Techniques and Applications
1.36
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