Equipment characterization to mitigate risks during transfers of cell culture manufacturing processes.

The production of monoclonal antibodies by mammalian cell culture in bioreactors up to 25,000 L is state of the art technology in the biotech industry. During the lifecycle of a product, several scale up activities and technology transfers are typically executed to enable the supply chain strategy of a global pharmaceutical company. Given the sensitivity of mammalian cells to physicochemical culture conditions, process and equipment knowledge are critical to avoid impacts on timelines, product quantity and quality. Especially, the fluid dynamics of large scale bioreactors versus small scale models need to be described, and similarity demonstrated, in light of the Quality by Design approach promoted by the FDA. This approach comprises an associated design space which is established during process characterization and validation in bench scale bioreactors. Therefore the establishment of predictive models and simulation tools for major operating conditions of stirred vessels (mixing, mass transfer, and shear force.), based on fundamental engineering principles, have experienced a renaissance in the recent years. This work illustrates the systematic characterization of a large variety of bioreactor designs deployed in a global manufacturing network ranging from small bench scale equipment to large scale production equipment (25,000 L). Several traditional methods to determine power input, mixing, mass transfer and shear force have been used to create a data base and identify differences for various impeller types and configurations in operating ranges typically applied in cell culture processes at manufacturing scale. In addition, extrapolation of different empirical models, e.g. Cooke et al. (Paper presented at the proceedings of the 2nd international conference of bioreactor fluid dynamics, Cranfield, UK, 1988), have been assessed for their validity in these operational ranges. Results for selected designs are shown and serve as examples of structured characterization to enable fast and agile process transfers, scale up and troubleshooting.

Influence of pluronic F68 on oxygen mass transfer.

Pluronic F68 is one of the most used shear protecting additives in cell culture cultivations. It is well known from literature that such surface-active surfactants lower the surface tension at the gas-liquid interface, which influences the mass transfer. In this study, the effect of Pluronic F68 on oxygen mass transfer in aqueous solutions was examined. Therefore, the gassing in/gassing out method and bubble size measurements were used. At low concentrations of 0.02 g/L, a 50% reduction on mass transfer was observed for all tested spargers and working conditions. An explanation of the observed effects by means of Higbie's penetration or Dankwerts surface renewal theory was applied. It could be demonstrated that the suppressed movement of the bubble surface layer is the main cause for the significant drop down of the kL a-values. For Pluronic F68 concentrations above 0.1 g/L, it was observed that it comes to changes in bubble appearance and bubble size strongly dependent on the sparger type. By using the bubble size measurement data, it could be shown that only small changes in mass transfer coefficient (kL ) take place above the critical micelle concentration. Further changes on overall mass transfer at higher Pluronic F68 concentrations are mainly based on increasing of gas holdup and, more importantly, by increasing of the surface area available for mass transfer.

Insights into large-scale cell-culture reactors: I. Liquid mixing and oxygen supply.

In the pharmaceutical industry, it is state of the art to produce recombinant proteins and antibodies with animal-cell cultures using bioreactors with volumes of up to 20 m(3) . Recent guidelines and position papers for the industry by the US FDA and the European Medicines Agency stress the necessity of mechanistic insights into large-scale bioreactors. A detailed mechanistic view of their practically relevant subsystems is required as well as their mutual interactions, i.e., mixing or homogenization of the culture broth and sufficient mass and heat transfer. In large-scale bioreactors for animal-cell cultures, different agitation systems are employed. Here, we discuss details of the flows induced in stirred tank reactors relevant for animal-cell cultures. In addition, solutions of the governing fluid dynamic equations obtained with the so-called computational fluid dynamics are presented. Experimental data obtained with improved measurement techniques are shown. The results are compared to previous studies and it is found that they support current hypotheses or models. Progress in improving insights requires continuous interactions between more accurate measurements and physical models. The paper aims at promoting the basic mechanistic understanding of transport phenomena that are crucial for large-scale animal-cell culture reactors.

Insights into large-scale cell-culture reactors: II. Gas-phase mixing and CO2 stripping.

Most discussions about stirred tank bioreactors for cell cultures focus on liquid-phase motions and neglect the importance of the gas phase for mixing, power input and especially CO(2) stripping. Particularly in large production reactors, CO(2) removal from the culture is known to be a major problem. Here, we show that stripping is mainly affected by the change of the gas composition during the movement of the gas phase through the bioreactor from the sparger system towards the headspace. A mathematical model for CO(2)-stripping and O(2)-mass transfer is presented taking gas-residence times into account. The gas phase is not moving through the reactor in form of a plug flow as often assumed. The model is validated by measurement data. Further measurement results are presented that show how the gas is partly recirculated by the impellers, thus increasing the gas-residence time. The gas-residence times can be measured easily with stimulus-response techniques. The results offer further insights on the gas-residence time distributions in stirred tank reactors.