Identification and classification of host cell proteins during biopharmaceutical process development

Applying UHPLC-HRAM MS/MS Method to Assess Host Cell Protein Clearance during the Purification Process Development of Therapeutic mAbs

Host cell proteins (HCPs) are one of the process-related impurities that need to be well characterized and controlled throughout biomanufacturing processes to assure the quality, safety, and efficacy of monoclonal antibodies (mAbs) and other protein-based biopharmaceuticals. Although ELISA remains the gold standard method for quantification of total HCPs, it lacks the specificity and coverage to identify and quantify individual HCPs. As a complementary method to ELISA, the LC-MS/MS method has emerged as a powerful tool to identify and profile individual HCPs during the downstream purification process. In this study, we developed a sensitive, robust, and reproducible analytical flow ultra-high-pressure LC (UHPLC)-high-resolution accurate mass (HRAM) data-dependent MS/MS method for HCP identification and monitoring using an Orbitrap Ascend BioPharma Tribrid mass spectrometer. As a case study, the developed method was applied to an in-house trastuzumab product to assess HCP clearance efficiency of the newly introduced POROS™ Caprylate Mixed-Mode Cation Exchange Chromatography resin (POROS Caprylate mixed-mode resin) by monitoring individual HCP changes between the trastuzumab sample collected from the Protein A pool (purified by Protein A chromatography) and polish pool (purified by Protein A first and then further purified by POROS Caprylate mixed-mode resin). The new method successfully identified the total number of individual HCPs in both samples and quantified the abundance changes in the remaining HCPs in the polish purification sample.

Proteomic analysis of host cell protein fouling during bioreactor harvesting

Chinese hamster ovary (CHO) cells are among the most common cell lines used for therapeutic protein production. Membrane fouling during bioreactor harvesting is a major limitation for the downstream purification of therapeutic proteins. Host cell proteins (HCP) are the most challenging impurities during downstream purification processes. The present work focuses on identification of HCP foulants during CHO bioreactor harvesting using reverse asymmetrical commercial membrane BioOptimal™ MF-SL. In order to investigate foulants and fouling behavior during cell clarification, for the first time a novel backwash process was developed to effectively elute almost all the HCP and DNA from the fouled membrane filter. The isoelectric points (pIs) and molecular weights (MWs) of major HCP in the bioreactor harvest and fouled on the membrane were successfully characterized using two-dimensional gel electrophoresis (2D SDS-PAGE). In addition, a total of 8 HCP were identified using matrix-assisted laser desorption/ionization-mass spectroscopy (MALDI-MS). The majority of these HCP are enzymes or associated with exosomes, both of which can form submicron-sized particles which could lead to the plugging of the filters.

Adaptive modeling optimized by the data fusion strategy: Real-time dying cell percentage prediction using capacitance spectroscopy

The previous research showcased a partial least squares (PLS) regression model accurately predicting cell death percentages using in-line capacitance spectra. The current study advances the model accuracy through adaptive modeling employing a data fusion approach. This strategy enhances prediction performance by incorporating variables from the Cole-Cole model, conductivity and its derivatives over time, and Mahalanobis distance into the predictor matrix (X-matrix). Firstly, the Cole-Cole model, a mechanistic model with parameters linked to early cell death onset, was integrated to enhance prediction performance. Secondly, the inclusion of conductivity and its derivatives over time in the X-matrix mitigated prediction fluctuations resulting from abrupt conductivity changes during process operations. Thirdly, Mahalanobis distance, depicting spectral changes relative to a reference spectrum from a previous time point, improved model adaptability to independent test sets, thereby enhancing performance. The final data fusion model substantially decreased root-mean squared error of prediction (RMSEP) by around 50%, which is a significant boost in prediction accuracy compared to the prior PLS model. Robustness against reference spectrum selection was confirmed by consistent performance across various time points. In conclusion, this study illustrates that the data fusion strategy substantially enhances the model accuracy compared to the previous model relying solely on capacitance spectra.

Effect of Host Cell Protein on Chinese Hamster Ovary Recombinant Protein Production and its Removal Strategies: A Mini Review

Chinese hamster ovary cells are the main expression system for recombinant therapeutic proteins. During the production of these proteins, certain host cell proteins are secreted, broken down, and released by host cells in the culture along with the proteins of interest. These host cell proteins are often difficult to remove during the downstream purification process, and thus affect the quality, safety, and effectiveness of recombinant protein biopharmaceutical products and increase the production cost of recombinant therapeutic proteins. Therefore, host cell protein production must be reduced as much as possible during the production process and eliminated during purification. This article reviews the harm caused by host cell proteins in the production of recombinant protein drugs using Chinese hamster ovary cell, factors affecting host cell proteins, the monitoring and identification of these proteins, and methods to reduce their type and quantity in the final product.

Application of Formulation Principles to Stability Issues Encountered During Processing, Manufacturing, and Storage of Drug Substance and Drug Product Protein Therapeutics

The field of formulation and stabilization of protein therapeutics has become rather extensive. However, most of the focus has been on stabilization of the final drug product. Yet, proteins experience stress and degradation through the manufacturing process, starting with fermentaition. This review describes how formulation principles can be applied to stabilize biopharmaceutical proteins during bioprocessing and manufacturing, considering each unit operation involved in prepration of the drug substance. In addition, the impact of the container on stabilty is discussed as well.