Intact multi-attribute method (iMAM): a flexible tool for the analysis of monoclonal antibodies.
Eur J Pharm Biopharm 2022;
177:241-248. [PMID:
35840072 DOI:
10.1016/j.ejpb.2022.07.005]
[Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2022] [Revised: 07/08/2022] [Accepted: 07/09/2022] [Indexed: 11/22/2022]
Abstract
The availability of rapid methods that can accurately define and quantify biopharmaceutical critical quality attributes has been the driving force for the implementation of mass spectrometry techniques throughout the development and production pipeline. While the multi-attribute method (MAM) has become widely adopted and developed, some critical information cannot be monitored through this workflow, such as correct chain assembly or the presence of fragments or aggregates. In this study, we combine intact mass spectrometry and the multi-attribute method to create an intact multi-attribute method - or iMAM. Using a CFR Part 11 compliant data system, we evaluated the proposed workflow using several intact analysis approaches under both denaturing and native conditions. As for the standard MAM approach, iMAM involves the creation of an intact protein target workbook which is created from a reference sample, with ID confirmation obtained from deconvolution results and chromatographic retention times while quantitation is obtained from the intensities of the m/z of most abundant charge states. The created processing method is then applied to any other sample. New peak detection can also be performed, monitoring the number of components revealed after each analysis. The entire data process can be automated to generate a report within the chromatography data system software. Three case studies presented herein show the potential of iMAM for implementation at different stages of the production pipeline, from product development to stability testing and batch release.
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