Literature DB >> 26053232

Comparison of Traditional 2-AB Fluorescence LC-MS/MS and Automated LC-MS for the Comparative Glycan Analysis of Monoclonal Antibodies.

John E Schiel1, Sarah M Rogstad2, Michael T Boyne2.   

Abstract

Monoclonal antibody therapeutics are a heterogeneous mixture of glycoforms. Multiple methods exist for defining the glycan composition and relative abundance of species present. In the current report, two MS-based methods were compared for their ability to both identify glycans and monitor differences in the glycoprofile. Gross changes in the glycoprofile can be identified either by visual inspection of fluorescence profiles and correlated to glycan identities when coupled with online MS/MS (LC-F-MS/MS) or through extracted ion chromatograms using LC-MS. In the present study, both an LC-F-MS/MS method and an automated LC-MS label free approach were able to identify minor differences in low abundance glycoforms, and data indicate a disparity in glycosylation between the analyzed batches of US and foreign-sourced mAb X. Thus, either method may be useful in characterizing monoclonal antibody therapeutics products and could serve as a potential screening test for understanding process, comparability, similarity, and possibly detecting counterfeit agents. Published 2015. This article is a U.S. Government work and is in the public domain in the USA.

Entities:  

Keywords:  Fluorescence spectroscopy; Glycosylation; LC-MS; Mass spectrometry; Monoclonal antibody

Mesh:

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Year:  2015        PMID: 26053232     DOI: 10.1002/jps.24522

Source DB:  PubMed          Journal:  J Pharm Sci        ISSN: 0022-3549            Impact factor:   3.534


  2 in total

Review 1.  Characterization of Pharmaceutical IgG and Biosimilars Using Miniaturized Platforms and LC-MS/MS.

Authors:  Kerry M Wooding; Wenjing Peng; Yehia Mechref
Journal:  Curr Pharm Biotechnol       Date:  2016       Impact factor: 2.837

2.  Glycan characterization of the NIST RM monoclonal antibody using a total analytical solution: From sample preparation to data analysis.

Authors:  Mark Hilliard; William R Alley; Ciara A McManus; Ying Qing Yu; Sinead Hallinan; John Gebler; Pauline M Rudd
Journal:  MAbs       Date:  2017-09-12       Impact factor: 5.857

  2 in total

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