Chromatographic host cell protein removal in biopharmaceutical purification

Abstract

The COVID-19 pandemic stressed the need for accelerating the development of novel vaccines. Over the past decades, the bottleneck in the biopharmaceutical process development shifted from optimizing fermentation processes to developing suitable purification strategies. Thereby, improving process understanding can significantly accelerate the development of purification processes. Unlike other biopharmaceutical products, vaccines are often more complex products containing molecules from different origins. The manufacturing process is therefore also more demanding. Consequently, no platform process is available for protein subunit vaccine purification. In the case of expressing a novel antigen in a host cell system, knowledge of the possible impurities – in this case host cell proteins (HCPs) – allows for rational and systematic process development. Therefore, this thesis focuses on developing characterization strategies of recurrent HCP impurities (from E. coli host cells) and on the integration of this information into modeling tools that advance removal strategies of these proteins, with a focus on protein-based antigen vaccines.

Firstly, the complete host cell proteome from antigen expressing E. coli host cells (BLR(DE3) and HMS174(DE3)) were characterized in chapter 2. Around 2000 HCPs were identified from the E. coli harvest sample using mass spectrometry based proteomics. Furthermore, an extensive HCP database including their expression levels, and physicochemical properties was constructed. Additionally, the profiles of an antigen expressing and null plasmid strain were compared. From a downstream processing perspective, the differences may be minor and the findings from the BLR(DE3) null strain can be applied to determine a purification strategy for the BLR(DE3) antigen-producing strain and HMS174(DE3) strain. The dataset of identified proteins was connected to databases describing the physicochemical properties of HCPs. Finally, protein property maps that help to identify a suitable downstream processing (DSP) strategy in comparison with the physicochemical properties of the target antigen, were generated.

Preparative chromatography based on differences in physicochemical properties is one of the main techniques for purification of vaccines. As follow-up to chapter 2, an experimental retention map of the host cell proteome during a salt gradient on hydrophobic interaction chromatography (HIC) and ion exchange chromatography (IEX) was constructed and reported and described in chapter 3. Furthermore, this study identified patterns in the retention behavior of HCPs based on their protein-protein interactions, molecular function, and cell location. To be able to predict the retention behavior of yet uncharacterized proteins, a quantitative structure-property relationship (QSPR) model was constructed using IEX retention data. Subsets of proteins, identified according to retention patterns, were used to build additional QSPR models, with monomer subsets yielding the most accurate predictions.

To achieve a higher level of process understanding, mechanistic models (MM) of chromatography columns are used in process development. These models primarily describe behavior of the target protein and selected process- or product-related impurities. However, it is beneficial to also include recurring HCP impurities in MMs. Hereby, critical HCPs causing issues when remaining in the product, are not necessarily abundant in the cell lysate and are often not individually described. A method for determining binding parameters of the entire host cell proteome including low abundant proteins to selected chromatography resins is still lacking.

Chapter 4 introduces a method to determine the above mentioned isotherm parameters of individual HCPs in a comprehensive manner. Fractions obtained from linear gradient elution experiments with different gradient lengths are analyzed by shotgun proteomics in order to extract the retention times of the individual HCPs. From the extracted retention volumes per gradient, isotherm parameters for all individual HCPs detected in the harvest were regressed. This method was exemplified using the BLR E. coli harvest, validated, and subsequently employed to optimize a capture step in silico.

Finally, chapter 5 gives an overview of the additionally investigated high-throughput sample preparation and analysis methods. This involved packing filter plates with resin for batch adsorption, which was explored to determine isotherm parameters instead of low gradient elution (LGE) experiments. Additionally, ion exchange high-performance liquid chromatography (IEX-HPLC) was investigated as an analytical technique instead of mass spectrometry (MS).

In summary, this thesis presents a comprehensive, large-scale characterization of HCPs from widely employed E. coli host cell strains for the production of protein vaccines. Moreover, a validated approach to determine isotherm parameters of all detectable HCPs in the harvest sample is presented.