4.6 Article

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

期刊

PLOS ONE
卷 17, 期 1, 页码 -

出版社

PUBLIC LIBRARY SCIENCE
DOI: 10.1371/journal.pone.0262711

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资金

  1. iNOVA4Health [UIDB/04462/2020, UIDP/04462/2020]
  2. Fundacao para a Ciencia e Tecnologia/Ministerio da Ciencia, Tecnologia e Ensino Superior

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As the requirements of regulatory agencies for the quality of biopharmaceuticals increase, the use of mass spectrometry-based methods such as the multi-attribute method (MAM) has become a valuable tool for quality control. MAM allows for the direct and simultaneous monitoring of critical product quality attributes using high-quality mass spectrometry data, replacing traditional orthogonal methods and reducing time and costs. This article describes the implementation of MAM using a QTOF high-resolution platform and discusses sample preparation and LC-MS parameters troubleshooting for batch analysis and high-throughput applications.
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.

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