Multi attribute method implementation using a High Resolution Mass Spectrometry platform: From sample preparation to batch analysis

PLoS One. 2022 Jan 27;17(1):e0262711. doi: 10.1371/journal.pone.0262711. eCollection 2022.

Abstract

Quality control of biopharmaceuticals such as monoclonal antibodies (mAbs) has been evolving and becoming more challenging as the requirements of the regulatory agencies increase due to the demanding complexity of products under evaluation. Mass Spectrometry (MS)-based methods such as the multi-attribute method (MAM) are being explored to achieve a deeper understanding of the attributes critical for the safety, efficacy, and quality of these products. MAM uses high mass accuracy/high-resolution MS data that enables the direct and simultaneous monitoring of relevant product quality attributes (PQAs, in particular, chemical modifications) in a single workflow, replacing several orthogonal methods, reducing time and costs associated with these assays. Here we describe a MAM implementation process using a QTOF high resolution platform. Method implementation was accomplished using NIST (National Institute for Standards and Technology) mAb reference material and an in-process mAb sample. PQAs as glycosylation profiles, methionine oxidation, tryptophan dioxidation, asparagine deamidation, pyro-Glu at N-terminal and glycation were monitored. Focusing on applications that require batch analysis and high-throughput, sample preparation and LC-MS parameters troubleshooting are discussed. This MAM workflow was successfully explored as reference analytical tool for comprehensive characterization of a downstream processing (DSP) polishing platform and for a comparability study following technology transfer between different laboratories.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Antibodies, Monoclonal / chemistry
  • Biological Products / chemistry*
  • Chromatography, Liquid / methods
  • Mass Spectrometry / methods*
  • Quality Control
  • Research Design
  • Trypsin / chemistry
  • Workflow

Substances

  • Antibodies, Monoclonal
  • Biological Products
  • Trypsin

Grants and funding

This work was funded by iNOVA4Health – UIDB/04462/2020 and UIDP/04462/2020, a program financially supported by Fundação para a Ciência e Tecnologia / Ministério da Ciência, Tecnologia e Ensino Superior, through national funds is acknowledged. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.