Bioprocess automation and bioprocess design

An integrated continuous downstream process with real-time control: A case study with periodic countercurrent chromatography and continuous virus inactivation

Integrated continuous downstream processes with process analytical technology offer a promising opportunity to reduce production costs and increase process flexibility and adaptability. In this case study, an integrated continuous process was used to purify a recombinant protein on laboratory scale in a two-system setup that can be used as a general downstream setup offering multiproduct and multipurpose manufacturing capabilities. The process consisted of continuous solvent/detergent virus inactivation followed by periodic countercurrent chromatography in the capture step, and a final chromatographic polishing step. A real-time controller was implemented to ensure stable operation by adapting the downstream process to external changes. A concentration disturbance was introduced to test the controller. After the disturbance was applied, the product output recovered within 6 h, showing the effectiveness of the controller. In a comparison of the process with and without the controller, the product output per cycle increased by 27%, the resin utilization increased from 71.4% to 87.9%, and the specific buffer consumption was decreased by 21% with the controller, while maintaining a similar yield and purity as in the process without the disturbance. In addition, the integrated continuous process outperformed the batch process, increasing the productivity by 95% and the yield by 28%.

Monitoring Parallel Robotic Cultivations with Online Multivariate Analysis

In conditional microbial screening, a limited number of candidate strains are tested at different conditions searching for the optimal operation strategy in production (e.g., temperature and pH shifts, media composition as well as feeding and induction strategies). To achieve this, cultivation volumes of >10 mL and advanced control schemes are required to allow appropriate sampling and analyses. Operations become even more complex when the analytical methods are integrated into the robot facility. Among other multivariate data analysis methods, principal component analysis (PCA) techniques have especially gained popularity in high throughput screening. However, an important issue specific to high throughput bioprocess development is the lack of so-called golden batches that could be used as a basis for multivariate analysis. In this study, we establish and present a program to monitor dynamic parallel cultivations in a high throughput facility. PCA was used for process monitoring and automated fault detection of 24 parallel running experiments using recombinant E. coli cells expressing three different fluorescence proteins as the model organism. This approach allowed for capturing events like stirrer failures and blockage of the aeration system and provided a good signal to noise ratio. The developed application can be easily integrated in existing data- and device-infrastructures, allowing automated and remote monitoring of parallel bioreactor systems.

An advanced monitoring platform for rational design of recombinant processes

Bioprocess engineering is an application-oriented science in an interdisciplinary environment, and a meaningful combination of different scientific disciplines is the only way to meet the challenges of bioprocess complexity. Setting up a reasoned process monitoring platform is the first step in an iterative procedure aiming at process and systems understanding, being the key to rational and innovative bioprocess design. This chapter describes a comprehensive process monitoring platform and how the resulting knowledge is translated into new strategies in process and/or host cell design.

Fermentation reactor coupled with capillary electrophoresis for on-line bioprocess monitoring

In this paper, a filter probe integrated into a computerized pneumatic sampler for capillary electroseparations was developed for an on-line monitoring of bioprocesses. The optimization of the performance of the coupled system was done by using a response surface modeling and three-level two-factor design. The resolution was found to be the most important parameter influencing the performance of an on-line analysis of the microbial metabolism. For the on-line analysis the migration time and detection limit were also found to be important parameters. Different parameters were combined by using an overall desirability function to find optimum conditions for all parameters. The equipment with an optimized separation protocol was used to monitor the bioaccumulation of Cu, Zn, Co and Cd (with detection limits 0.46, 0.37, 1.2, 0.84 mM correspondingly) by the Rhodococcus sp. bacteria isolated from the highly polluted technogenic soil of northeastern Estonia during a 2-week experiment.

Microbial biomass estimation

The development of a fully automated on-line monitoring and control system is very important in bioprocesses. One of the most important parameters in these processes is biomass. This review discusses different methods for biomass quantification. A general definition of biomass and biovolume are presented. Interesting concepts about active but not culturable cells considerations are included as well as concepts that must be taken into account when selecting biomass quantification technology. Chemical methods have had few applications in biomass measurement to date; however, bioluminescence can selectively enumerate viable cells. Photometric methods including fluorescence and scattered light measurements are presented. Reference methods including dry and wet weight, viable counts and direct counts are discussed, as well as the physical methods of flow cytometry, impedancimetric and dielectric techniques.

Computer applications in bioprocessing

Biotechnologists have stayed at the forefront for practical applications for computing. As hardware and software for computing have evolved, the latest advances have found eager users in the area of bioprocessing. Accomplishments and their significance can be appreciated by tracing the history and the interplay between the computing tools and the problems that have been solved in bioprocessing.