Björn Frahm

Determination of dissolved CO2 concentration and CO2 production rate of mammalian cell suspension culture based on off-gas measurement

The determination of dissolved CO(2) and HCO(3)(-) concentrations as well as the carbon dioxide production rate in mammalian cell suspension culture is attracting more and more attention since the effects on major cell properties, such as cell growth rate, product quality/production rate, intracellular pH and apoptosis, have been revealed. But the determination of these parameters by gas analysis is complicated by the solution/dissolution of carbon dioxide in the culture medium. This means that the carbon dioxide transfer rate (CTR; which can easily be calculated from off-gas measurement) is not necessarily equal to carbon dioxide production rate (CPR). In this paper, a mathematical method to utilize off-gas measurement and culture pH for cell suspension culture is presented. The method takes pH changes, buffer and medium characteristics that effect CO(2) mass transfer into account. These calculations, based on a profound set of equations, allow the determination of the respiratory activity of the cells, as well as the determination of dissolved CO(2), HCO(3)(-) and total dissolved carbonate. The method is illustrated by application to experimental data. The calculated dissolved CO(2) concentrations are compared with measurements from an electrochemical CO(2) probe.

Adaptive, Model-Based Control by the Open-Loop-Feedback-Optimal (OLFO) Controller for the Effective Fed-Batch Cultivation of Hybridoma Cells

Although fed‐batch suspension culture of animal cells continues to be of industrial importance for the large scale production of pharmaceutical products, existing control concepts are still insufficient. Changes in cell metabolism during cultivation and between similar cultivations, the complexity of the cell metabolism, and the lack of on‐line state variables restrict the transfer of available control strategies established in bioprocess engineering. A process control strategy designed to achieve optimized process control must account for all these difficulties and fit sophisticated requirements toward adaptability and flexibility. The combination of a fed‐batch process and an Open‐Loop‐Feedback‐Optimal (OLFO) control provides a new approach for cell culture process control that couples an efficient cultivation concept to a capable process control strategy. The application of an adaptive, model‐based OLFO controller to a hybridoma cultivation and experimental results are presented.

Evaluation of selected control strategies for fed‐batch cultures of a hybridoma cell line

While fed‐batch suspension culture of animal cells continues to be of industrial importance for the large‐scale production of pharmaceutical products, existing control concepts are still insufficient. The present paper illustrates the advantages and disadvantages of different fed‐batch strategies, including fixed‐feed trajectories, control via OUR (oxygen uptake rate) (stoichiometric feeding), a priori determination of feed trajectories based on a kinetic model and the model‐based adaptive OLFO (open‐loop‐feedback‐optimal) control strategy. A recommendation as to which control strategy should be used for a specific process has to consider the respective process. For an established process with a well characterized and stable production cell line, probably the application of a fixed feed trajectory should be recommended. An adaptive, model‐based control strategy could be the method of choice during cell‐line development or for rapid production of small amounts of product for clinical trials, owing to its universal character and because it does not require intensive process development.

Seed Train Optimization for Cell Culture

For the production of biopharmaceuticals a seed train is required to generate an adequate number of cells for inoculation of the production bioreactor. This seed train is time- and cost-intensive but offers potential for optimization. A method and a protocol are described for the seed train mapping, directed modeling without major effort, and its optimization regarding selected optimization criteria such as optimal points in time for cell passaging. Furthermore, the method can also be applied for the set-up of a new seed train, for example for a new cell line. Although the chapter is directed towards suspension cell lines, the method is also generally applicable, e.g. for adherent cell lines.

Model-based design of the first steps of a seed train for cell culture processes

Concept Production of biopharmaceuticals for diagnostic and therapeutic applications with suspension cells in bioreactors requires a seed train up to production scale [1]. For the final process steps in pilot and production scale the scale-up steps are usually defined (e.g. a factor of 5 10). More difficult in this respect are the first steps, the transitions between T-flasks, spinner tubes, roller bottles, shake flasks, stirred bioreactors or single-use reactors, because here often scale-up steps are different. The experimental effort to lay these steps out is correspondingly high. At the same time it is known that the first cultivation steps have a significant impact on the success or failure on production scale. The concept for a model based design of the seed train consists of the following steps:

Advanced Process and Control Strategies for Bioreactors

Bioreactor processes have to provide an almost optimal environment to microorganisms or cells to promote growth and product formation. The design and operation of a bioreactor as the main element of fermentation is a complex task, not only with respect to a reactors configuration and size but to the control and mode of operation. In this chapter, some fundamentals are discussed, including process and control strategies and concepts for process development. Next, examples for the use of model-based concepts for the design of experiments, feeding strategies, seed train layout, and control strategies, including simulation tools supporting biotechnological training and education, are shown.

Seed train optimization for suspension cell culture

The purpose of a seed train is the generation of an adequate number of cells for the inoculation of a production bioreactor. This is time- and cost-intensive: From volumes used for cell thawing or cell line maintenance the cell number has to be increased. The cells are usually run through many cultivation systems which become larger with each passage (e.g. T-flasks, roller bottles or shake flasks, small scale bioreactor systems and subsequently larger bioreactors. Single-use systems may be applied and systems which are inoculated at a partly filled state and culture volume is increased afterwards by medium addition). The production bioreactor is inoculated out of the largest seed train scale.

Model-Based Control of Hybridoma Cell Cultures

Abstract The optimal control of hybridoma cell cultivations requires adaptive model based control strategies like the Open-Loop-Feedback-Optirnal-(OLFO) controller In this controller, the applied models must be able to predict the states of a cultivation reasonably well. Theoretical investigations show how the online-prediction performance of a model may be evaluated. Experimental results obtained by the application of a simple unstructured process model in a simplified OLFO-strategy illustrates the potential of this controlleL Experiments have been carried out, that show the value of oxygen-uptake-rate measurements for controlling the process under glutamine limiting conditions.

Model-based strategy for cell culture seed train layout verified at lab scale

Cell culture seed trains—the generation of a sufficient viable cell number for the inoculation of the production scale bioreactor, starting from incubator scale—are time- and cost-intensive. Accordingly, a seed train offers potential for optimization regarding its layout and the corresponding proceedings. A tool has been developed to determine the optimal points in time for cell passaging from one scale into the next and it has been applied to two different cell lines at lab scale, AGE1.HNAAT and CHO-K1. For evaluation, experimental seed train realization has been evaluated in comparison to its layout. In case of the AGE1.HNAAT cell line, the results have also been compared to the formerly manually designed seed train. The tool provides the same seed train layout based on the data of only two batches.

Considerations for cell passaging in cell culture seed trains

Background The purpose of a seed train is the generation of an adequate number of cells for the inoculation of a production bioreactor. This is timeand cost-intensive. From volumes used for cell thawing or cell line maintenance the cell number has to be increased. The cells are usually run through many cultivation systems which become larger with each passage. The seed train steps have a significant impact on the product titer and cell growth in production scale, as well as the success and the reproducibility of the seed train itself. Furthermore, cell line changes in the existing facility require adaptions of the seed train protocol. The design of a new facility involves the choice of the optimal seed train scales in order to meet the future requirements of the cultivated cell lines.