Inter-laboratory study to evaluate the performance of automated online characterization of antibody charge variants by multi-dimensional LC-MS/MS.

Automation Charge variants Multi-dimensional liquid chromatography Multi-site evaluation PTMs

Journal

Talanta
ISSN: 1873-3573
Titre abrégé: Talanta
Pays: Netherlands
ID NLM: 2984816R

Informations de publication

Date de publication:
01 Nov 2021
Historique:
received: 03 05 2021
revised: 11 06 2021
accepted: 15 06 2021
entrez: 8 8 2021
pubmed: 9 8 2021
medline: 11 8 2021
Statut: ppublish

Résumé

An international study was conducted to evaluate the performance and reliability of an online multi-dimensional (mD)-LC-MS/MS approach for the characterization of antibody charge variants. The characterization of antibody charge variants is traditionally performed by time-consuming, offline isolation of charge variant fractions by ion exchange chromatography (IEC) that are subsequently subjected individually to LC-MS/MS peptide mapping. This newly developed mD-LC-MS/MS approach enables automated and rapid characterization of charge variants using much lower sample requirements. This online workflow includes sample reduction, digestion, peptide mapping, and subsequent mass spectrometric analysis within a single, fully-automated procedure. The benefits of using online mD-LC-MS/MS for variant characterization include fewer handling steps, a more than 10-fold reduction in required sample amount, reduced sample hold time as well as a shortening of the overall turnaround time from weeks to few days compared to standard offline procedures. In this site-to-site comparison study, we evaluated the online peptide mapping data collected from charge variants of trastuzumab (Herceptin®) across three international laboratories. The purpose of this study was to compare the overall performance of the online mD-LC-MS/MS approach for antibody charge variant characterization, with all participating sites employing different mD-LC-MS/MS setups (e.g., instrument vendors, modules, columns, CDS software). The high sequence coverage (95%-97%) obtained in each laboratory, enabled a reproducible generation of tryptic peptides and the comparison of values of the charge variants. Results obtained at all three participating sites were in good agreement, highlighting the reliability and performance of this approach, and correspond with data gained by the standard offline procedure. Overall, our results underscore of the benefit mD-LC-MS/MS technology for therapeutic antibody characterization, confirming its potential to become an important tool in the toolbox of protein characterization scientists.

Identifiants

pubmed: 34364437
pii: S0039-9140(21)00549-X
doi: 10.1016/j.talanta.2021.122628
pii:
doi:

Substances chimiques

Antibodies, Monoclonal 0

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

122628

Informations de copyright

Copyright © 2021. Published by Elsevier B.V.

Auteurs

Julien Camperi (J)

Protein Analytical Chemistry, Genentech, 1 DNA Way, South San Francisco, CA, 94080, USA.

Ingrid Grunert (I)

Pharma Technical Development, Roche, Nonnenwald 2, 82377, Penzberg, Germany.

Katrin Heinrich (K)

Pharma Technical Development, Roche, Nonnenwald 2, 82377, Penzberg, Germany.

Martin Winter (M)

Pharma Technical Development, Roche, Nonnenwald 2, 82377, Penzberg, Germany.

Saban Özipek (S)

Pharma Technical Development, F. Hoffmann-La Roche, Grenzacherstrasse 124, 4070, Basel, Switzerland.

Sina Hoelterhoff (S)

Pharma Technical Development, F. Hoffmann-La Roche, Grenzacherstrasse 124, 4070, Basel, Switzerland.

Thomas Weindl (T)

Pharma Research and Early Development, Roche, Nonnenwald 2, 82377, Penzberg, Germany.

Kilian Mayr (K)

Pharma Research and Early Development, Roche, Nonnenwald 2, 82377, Penzberg, Germany.

Patrick Bulau (P)

Pharma Technical Development, Roche, Nonnenwald 2, 82377, Penzberg, Germany.

Monika Meier (M)

Pharma Technical Development, Roche, Nonnenwald 2, 82377, Penzberg, Germany.

Michael Mølhøj (M)

Pharma Research and Early Development, Roche, Nonnenwald 2, 82377, Penzberg, Germany.

Michael Leiss (M)

Pharma Technical Development, Roche, Nonnenwald 2, 82377, Penzberg, Germany.

Davy Guillarme (D)

School of Pharmaceutical Sciences, University of Geneva, CMU - Rue Michel-Servet, 1, 1206, Geneva, Switzerland; Institute of Pharmaceutical Sciences of Western Switzerland (ISPSO), University of Geneva, CMU-Rue Michel Servet 1, 1211, Geneva 4, Switzerland.

Anja Bathke (A)

Pharma Technical Development, F. Hoffmann-La Roche, Grenzacherstrasse 124, 4070, Basel, Switzerland.

Cinzia Stella (C)

Protein Analytical Chemistry, Genentech, 1 DNA Way, South San Francisco, CA, 94080, USA. Electronic address: stella.cinzia@gene.com.

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Classifications MeSH