Monitoring and Control of High-Density Cell Culture Systems

Motivation

An obvious approach to optimize yields in vaccine manufacturing is the increase in cell concentration before infecting the cultures [1]. However, due to media limitations, accumulation of inhibitors and mass transfer limits cell specific virus productivity is often reduced in high-density cell cultures, the so-called 'cell density effect'.

Aims of the project

Design and optimization of high-density cell culture systems for influenza virus production. Monitoring of critical state and process variables to characterize cell growth and virus replication dynamics. Establishment of mathematical models for control of cultivation conditions to increase process productivity.

High-density cell culture
Medium exchange via perfusion or repeated fed-batch

*Figure 1.1: High-density cultures of MDCK cells using repeated fed-batch mode: (o) number of cells on microcarriers (MC), (◘) HA virus titre; vertical line at 96 h: ▬ infection*

© MPI Magdeburg (BPE)

*Figure 1.1: High-density cultures of MDCK cells using repeated fed-batch mode: (o) number of cells on microcarriers (MC), (◘) HA virus titre; vertical line at 96 h: ▬ infection*

© MPI Magdeburg (BPE)

*Figure 1.2: Experimental set-up*

© MPI Magdeburg (BPE)

*Figure 1.2: Experimental set-up*

© MPI Magdeburg (BPE)

Process monitoring and simulation
Estimation of viable cell number using oxygen uptake rates [2]

Figure 2: Growth of MDCK cells in serum containing medium (GMEM, 5 L wv, 2 g/L MC). Viable cell numbers for cultivation and infection: (□) experimental cell number (trypan blue dye); (●) estimated viable cell number using online data of oxygen uptake rate; vertical line at 116 h ▬ infection

© MPI Magdeburg (BPE)

Figure 2: Growth of MDCK cells in serum containing medium (GMEM, 5 L wv, 2 g/L MC). Viable cell numbers for cultivation and infection: (□) experimental cell number (trypan blue dye); (●) estimated viable cell number using online data of oxygen uptake rate; vertical line at 116 h ▬ infection

© MPI Magdeburg (BPE)

Simulation of viable cell number and virus titres using unstructured,
segregated mathematical models [3], [4]

Figure 3: Growth of MDCK cells in serum containing medium (GMEM, 5 L wv, 2 g/L MC). Viable cell numbers (o) data, (─) simulation; HA virus titre (◘) data, (─) simulation; vertical line at 96 h: ▬ infection

© MPI Magdeburg (BPE)

Figure 3: Growth of MDCK cells in serum containing medium (GMEM, 5 L wv, 2 g/L MC). Viable cell numbers (o) data, (─) simulation; HA virus titre (◘) data, (─) simulation; vertical line at 96 h: ▬ infection

© MPI Magdeburg (BPE)

Outlook

Results of model simulations and experimental data clearly suggest that cultivations with cell numbers of about 20 x 10⁶ (1/mL) and more are feasible. To overcome limitations during cell growth and virus replication concepts for control of medium exchange should be applied [5]. Online estimation of cell numbers using oxygen transfer rates should allow determination of optimal time point of infection.

References

[1] Möhler L, Flockerzi D, Sann H and Reichl U. 2005. A Mathematical Model of Influenza A Virus Production in Large-Scale Microcarrier Culture. Biotechnology and Bioengineering (90)1:46-58
[2] Bock A, Reichl U. Monitoring of cell activity: online oxygen uptake rates in pulsed aerated cell culture. In: Noll T, editor. 20th meeting of ESACT; 2007; Dresden, Germany: Springer; 2007.
[3] Möhler L, Bock A, Reichl U. Segregated mathematical model for growth of anchorage-dependent MDCK cells in microcarrier culture. Biotechnology Progress 2008 ;24(1):110-9.
[4] Bock A, Möhler L, Sann H, Schulze-Horsel J, Genzel Y, Reichl U. Growth behaviour of number distributed adherent MDCK cells for optimization in large scale microcarrier cultures. Biotechnology Progress 2009, 25(6): 1717-1731
[5] Bock A, Schulze-Horsel J, Schwarzer J, Rapp E, Genzel Y, Reichl U.High-Density Microcarrier Cell Cultures for Inﬂuenza Virus Production. Biotechnology Progress 2011, 27(1): 241-250

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