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Accelerated development of new therapeutics in an increasingly competitive landscape requires the use of high throughput analytical platforms. In addition, the complexity of novel biotherapeutic formats (e.g. fusion proteins, protein-polymer conjugates, co-formulations, etc.) reinforces the need to improve the selectivity and resolution of conventional one-dimensional (1D) liquid chromatography (LC). Liquid chromatography-mass spectrometry (LC-MS)-based technologies such as native LC-MS for intact mass analysis or peptide mapping (also called bottom-up approach)-based multi-attribute methods (MAM) have already demonstrated their potential to complement the conventional analytical toolbox for monoclonal antibody (mAb) characterization. Two-dimensional liquid-chromatography (2D-LC-MS) methods have emerged in the last ten years as promising approaches to address the increasing analytical challenges faced with novel antibody formats. However, off-line sample preparation procedures are still required for conventional 1D and 2D-LC-MS methods for the in-depth variant characterization at the peptide level. Multi-dimensional LC-MS (mD-LC-MS) combine sample preparation and multi-level (i.e. intact, reduced, middle-up and peptide) analysis within the same chromatographic set-up. This review presents an overview of the benefits and limitations of mD-LC-MS approaches in comparison to conventional chromatographic methods (i.e. 1D-LC-UV methods at intact protein level and 1D-LC-MS methods at peptide level). The current analytical trends in antibody characterization by mD-LC-MS approaches, beyond the 2D-LC-MS workhorse, are also reviewed, and our vision on a more integrated multi-level mD-LC-MS characterization platform is shared.

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Multi-dimensional LC-MS: the next generation characterization of antibody-based therapeutics by unified online bottom-up, middle-up and intact approaches