Air sparging for prevention of antibody disulfide bond reduction in harvested CHO cell culture fluid.

During the scale-up of several Chinese Hamster Ovary (CHO) cell monoclonal antibody production processes, significant reduction of the antibody interchain disulfide bonds was observed. The reduction was correlated with excessive mechanical cell shear during the harvest operations. These antibody reduction events resulted in failed product specifications and the subsequent loss of the drug substance batches. Several methods were recently developed to prevent antibody reduction, including modifying the cell culture media, using pre- and post-harvest chemical additions to the cell culture fluid (CCF), lowering the pH, and air sparging of the harvested CCF (HCCF). The work described in this paper further explores the option of HCCF air sparging for preventing antibody reduction. Here, a small-scale model was developed using a 3-L bioreactor to mimic the conditions of a manufacturing-scale harvest vessel and was subsequently employed to evaluate several air sparging strategies. In addition, these studies enabled further understanding of the relationships between cell lysis levels, oxygen consumption, and antibody reduction. Finally, the effectiveness of air sparging for several CHO cell lines and the potential impact on product quality were assessed to demonstrate that air sparging is an effective method in preventing antibody reduction.

Predicting Formulation Conditions During Ultrafiltration and Dilution to Drug Substance Using a Donnan Model with Homology-Model Based Protein Charge.

In the manufacturing of therapeutic monoclonal antibodies (mAbs), the final steps of the purification process are typically ultrafiltration/diafiltration (UF/DF), dilution, and conditioning. These steps are developed such that the final drug substance (DS) is formulated to the desired mAb, buffer, and excipient concentrations. To develop these processes, process and formulation development scientists often perform experiments to account for the Gibbs-Donnan and volume-exclusion effects during UF/DF, which affect the output pH and buffer concentration of the UF/DF process. This work describes the development of an in silico model for predicting the DS pH and buffer concentration after accounting for the Gibbs-Donnan and volume-exclusion effects during the UF/DF operation and the subsequent dilution and conditioning steps. The model was validated using statistical analysis to compare model predictions against experimental results for nine molecules of varying protein concentrations and formulations. In addition, our results showed that the structure-based in silico approach used to calculate the protein charge was more accurate than a sequence-based approach. Finally, we used the model to gain fundamental insights about the Gibbs-Donnan effect by highlighting the role of the protein charge concentration (the protein concentration multiplied with protein charge at the formulation pH) on the Gibbs-Donnan effect. Overall, this work demonstrates that the Gibbs-Donnan and volume-exclusions effects can be predicted using an in silico model, potentially alleviating the need for experiments.