Proteomics-based method to comprehensively model the removal of host cell protein impurities

Journal Article (2024)
Author(s)

R.C. Disela (TU Delft - BT/Bioprocess Engineering)

Daphne Keulen (TU Delft - BT/Bioprocess Engineering)

Eleni Fotou (Student TU Delft)

T. Neijenhuis (TU Delft - BT/Bioprocess Engineering)

Olivier Le Bussy (GlaxoSmithKline)

Geoffroy Geldhof (GlaxoSmithKline)

Martin Pabst (TU Delft - BT/Environmental Biotechnology)

M Ottens (TU Delft - BT/Design and Engineering Education)

Research Group
BT/Bioprocess Engineering
DOI related publication
https://doi.org/10.1002/btpr.3494
More Info
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Publication Year
2024
Language
English
Research Group
BT/Bioprocess Engineering
Issue number
6
Volume number
40
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Abstract

Mechanistic models mostly focus on the target protein and some selected process- or product-related impurities. For a better process understanding, however, it is advantageous to describe also reoccurring host cell protein impurities. Within the purification of biopharmaceuticals, the binding of host cell proteins to a chromatographic resin is far from being described comprehensively. For a broader coverage of the binding characteristics, large-scale proteomic data and systems level knowledge on protein interactions are key. However, a method for determining binding parameters of the entire host cell proteome to selected chromatography resins is still lacking. In this work, we have developed a method to determine binding parameters of all detected individual host cell proteins in an Escherichia coli harvest sample from large-scale proteomics experiments. The developed method was demonstrated to model abundant and problematic proteins, which are crucial impurities to be removed. For these 15 proteins covering varying concentration ranges, the model predicts the independently measured retention time during the validation gradient well. Finally, we optimized the anion exchange chromatography capture step in silico using the determined isotherm parameters of the persistent host cell protein contaminants. From these results, strategies can be developed to separate abundant and problematic impurities from the target antigen.