The current state-of-the-art in control of cultivation processes for recombinant protein production is examined including the quantitative knowledge that can be activated for this purpose and the measurement techniques that can be employed for control at industrial manufacturing sites.

Increasing capacity utilization and lowering manufacturing costs are critical for pharmaceutical companies to improve their competitiveness in a challenging environment. Development of next generation cell lines, improved media formulations, application of mature technologies and innovative operational strategies have been deployed to improve yields and capacity utilization. This article describes a large-scale perfusion strategy for the N-1 seed train bioreactor that was successfully applied to achieve higher inoculation cell densities in the production culture. The N-1 perfusion at 3,000-L scale, utilizing a inclined settler, achieved cell densities of up to 158 × 10(5) cell mL(-1) at perfusion rates of 2950 L day(-1) and a retention efficiency of >85%. This approach increased inoculation cell densities and decreased cultivation times by ~20% in a CHO-based, fed-batch antibody manufacturing process while providing comparable culture performance, productivity, and product quality. The strategy therefore yielded significant increase in capacity utilization and concomitant cost improvement in a large scale cGMP facility. Details of the strategy, the cell retention device, and the cell culture performance are described in this article.

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.

Online biomass estimation for bioprocess supervision and control purposes is addressed. As the biomass concentration cannot be measured online during the production to sufficient accuracy, indirect measurement techniques are required. Here we compare several possibilities for the concrete case of recombinant protein production with genetically modified Escherichia coli bacteria and perform a ranking. At normal process operation, the best estimates can be obtained with artificial neural networks (ANNs). When they cannot be employed, statistical correlation techniques can be used such as multivariate regression techniques. Simple model-based techniques, e.g., those based on the Luedeking/Piret-type are not as accurate as the ANN approach; however, they are very robust. Techniques based on principal component analysis can be used to recognize abnormal cultivation behavior. For the cases investigated, a complete ranking list of the methods is given in terms of the root-mean-square error of the estimates. All techniques examined are in line with the recommendations expressed in the process analytical technology (PAT)-initiative of the FDA.

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