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Continuous processing is the future production method for monoclonal antibodies (mAbs). A fully continuous, fully automated downstream process based on disposable equipment was developed and implemented inside the MoBiDiK pilot plant. However, a study evaluating the comparability between batch and continuous processing based on product quality attributes was not conducted before. The work presented fills this gap comparing both process modes experimentally by purifying the same harvest material (side‐by‐side comparability). Samples were drawn at different time points and positions in the process for batch and continuous mode. Product quality attributes, product‐related impurities, as well as process‐related impurities were determined. The resulting polished material was processed to drug substance and further evaluated regarding storage stability and degradation behavior. The in‐process control data from the continuous process showed the high degree of accuracy in providing relevant process parameters such as pH, conductivity, and protein concentration during the entire process duration. Minor differences between batch and continuous samples are expected as different processing conditions are unavoidable due to the different nature of batch and continuous processing. All tests revealed no significant differences in the intermediates and comparability in the drug substance between the samples of both process modes. The stability study of the final product also showed no differences in the stability profile during storage and forced degradation. Finally, online data analysis is presented as a powerful tool for online‐monitoring of chromatography columns during continuous processing.

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The performance of most bioprocesses can be improved significantly by the application of model-based methods from advanced process control (APC). However, due to the complexity of the processes and the limited knowledge of them, plant–model mismatch is unavoidable. A variety of different modeling strategies (each with individual advantages and deficiencies) can be applied, but still, the confidence in a single process model is often low; therefore, the application of classical APC is difficult. In order to operate under possible plant–model mismatch, a robust closed-loop optimizing control strategy was developed in which the mismatch is counteracted by an adaptive model correction and the parallel usage and evaluation of structurally different models. Robust multistage nonlinear model predictive control is used for the online optimization of the process trajectories in order to maximize the performance. The adapted, structurally different models are used herein as weighted scenarios for the prediction of the process, which account for structural uncertainties. It is shown in simulation studies of a CHO cultivation process that the usage of multiple, adapted models as scenarios improves (1) the accuracy of the state estimation and (2) the overall process performance.

Die bekannten Testgemische n‐Heptan/Methylcyclohexan und n‐Decan/trans‐Decalin werden auf ihr ideales Verhalten hin untersucht. Beide Systeme verhalten sich in dem untersuchten Temperaturbereich pseudoideal gemäß der Auffassung von L. Sieg. – Zum Test von Kolonnen mit mehr als 100 theoretischen Böden wird das System m‐Xylol/p‐Xylol vorgeschlagen, dessen Dampfdrucke gemessen wurden. Ein Diagramm zur Bestimmung der theoretischen Bodenzahl mit m‐Xylol/p‐Xylol als Testgemisch bei 760 Torr wird angegeben.

Es werden einfache Anordnungen beschrieben, die die Automatisierung von Destillationskolonnen im Laboratorium ermöglichen.