Population balance modelling captures host cell protein dynamics in CHO cell cultures

Abstract

Monoclonal antibodies (mAbs) have been extensively studied for their wide therapeutic and research applications. Increases in mAb titre has been achieved mainly by cell culture media/feed improvement and cell line engineering to increase cell density and specific mAb productivity. However, this improvement has shifted the bottleneck to downstream purification steps. The higher accumulation of the main cell-derived impurities, host cell proteins (HCPs), in the supernatant can negatively affect product integrity and immunogenicity in addition to increasing the cost of capture and polishing steps. Mathematical modelling of bioprocess dynamics is a valuable tool to improve industrial production at fast rate and low cost. Herein, a single stage volume-based population balance model (PBM) has been built to capture Chinese hamster ovary (CHO) cell behaviour in fed-batch bioreactors. Using cell volume as the internal variable, the model captures the dynamics of mAb and HCP accumulation extracellularly under physiological and mild hypothermic culture conditions. Model-based analysis and orthogonal measurements of lactate dehydrogenase activity and double-stranded DNA concentration in the supernatant show that a significant proportion of HCPs found in the extracellular matrix is secreted by viable cells. The PBM then served as a platform for generating operating strategies that optimise antibody titre and increase cost-efficiency while minimising impurity levels.

Fig 1. Comparison of model simulation results with experimental data.

The red and blue lines represent the model output for the physiological and mild hypothermic bioreactors, respectively. The experimental data are represented in square (physiological temperature) and circular (mild hypothermia) points for (A) viable cell density; (B) dead cell density (C) mAb titre, (D) extracellular HCP concentration, (E) culture osmolality, (F) and (G) normalised cell volume for physiological temperature and mild hypothermic case, respectively. Error bars represent one standard deviation.

Fig 2

Normalised cell distribution for the physiological temperature (A) and mild hypothermic cultures (B). The cell diameters were taken from the NucleoCunter™ and the given distributions are obtained from distribution fitting in MATLAB.

Fig 3

(A) Concentration of cells that have lysed as inferred from the results of the LDH assay; (B) Double stranded DNA concentration in the supernatant.

Fig 4

Results for the six optimisation scenarios shown in Table 1 for: (A) culture viability, (B) bioreactor run duration, (C) mAb concentration at harvest, (D) total feed input, (E) mAb/HCP concentration ratio, (F) HCP concentration at harvest. Cases 1 and 4 are the control experiments (standard cases) at physiological and mild hypothermic conditions, respectively, which were used for parameter estimation. The first three cases are for cultures grown under physiological temperature whereas cases 4–6 are cultures operated with a shift to mild hypothermia. The optimum temperature downshift time is after 140 h and 100 h for cases 5 and 6, respectively.