4.5 Article

Automated mass spectrometry multi-attribute method analyses for process development and characterization of mAbs

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ELSEVIER
DOI: 10.1016/j.jchromb.2021.122540

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Multi-attribute method; LC-MS; MAM; Automation; Process development; Critical quality attributes

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The biologics industry is expanding with over 370 products approved by regulatory agencies in the US and EU markets. However, improvements in analytical techniques, such as the multi-attribute method (MAM) using LC-MS, are necessary for better product characterization.
More than 370 biotherapeutics drug products have been approved by regulator y agencies on the US and EU markets and this industry continues to expand. Process change and optimization is necessar y to develop new effective biologics in a cost effective and productive way. Consequently, improvement of analytical techniques is required for better product characterization according to Quality by Design (QbD) approach recommended by regulatory agencies. Recently, multi-attribute method (MAM) has emerged to meet such demands using mass spectrometry coupled to liquid chromatography (LC-MS). However, traditional sample preparation or data processing would not be suitable to guide process development, because one of the common challenges during development of analytical platforms is instrument or method variability which can cause deviation in results. Here, we show a new automated analytical platform for MAM implemented on 3 different sites: the components of MAM platform include automated sample preparation, LC-MS based MAM, and data treatment automation. To our knowledge, this is the first study to show global harmonization on automated MAM platforms and the intersites comparability including the automated sample preparation and LC-MS instrument. Also, we demonstrate the applicability of MAM to support ce l l line development, cel l culture process development and downstream process development. We expect that this MAM platform w i l l effectively guide process development across multiple projects.

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