Abstract

Significant progress in the manufacturing of biopharmaceuticals has been made by increasing the overall titers in the USP (upstream processing) titers without raising the cost of the USP. In addition, the development of platform processes led to a higher process robustness. Despite or even due to those achievements, novel challenges are in sight. The higher upstream titers created more complex impurity profiles, both in mass and composition, demanding higher separation capacities and selectivity in downstream processing (DSP). This creates a major shift of costs from USP to DSP. In order to solve this issue, USP and DSP integration approaches can be developed and used for overall process optimization. This study focuses on the characterization and classification of host cell proteins (HCPs) in each unit operation of the DSP (i.e., aqueous two-phase extraction, integrated countercurrent chromatography). The results create a data-driven feedback to the USP, which will serve for media and process optimizations in order to reduce, or even eliminate nascent critical HCPs. This will improve separation efficiency and may lead to a quantitative process understanding. Different HCP species were classified by stringent criteria with regard to DSP separation parameters into “The Good, the Bad, and the Ugly” in terms of pI and MW using 2D-PAGE analysis depending on their positions on the gels. Those spots were identified using LC-MS/MS analysis. HCPs, which are especially difficult to remove and persistent throughout the DSP (i.e., “Bad” or “Ugly”), have to be evaluated by their ability to be separated. In this approach, HCPs, considered “Ugly,” represent proteins with a MW larger than 15 kDa and a pI between 7.30 and 9.30. “Bad” HCPs can likewise be classified using MW (>15 kDa) and pI (4.75–7.30 and 9.30–10.00). HCPs with a MW smaller than 15 kDa and a pI lower than 4.75 and higher than 10.00 are classified as “Good” since their physicochemical properties differ significantly from the product. In order to evaluate this classification scheme, it is of utmost importance to use orthogonal analytical methods such as IEX, HIC, and SEC. View Full-Text