Maximizing biomass concentration in baker’s yeast process by using a decoupled geometric controller for substrate and dissolved oxygen

Biotech & Bioengineering

Holzberg

et al. 2020

Self Cite

Mass transfer is known to play a critical role in bioprocess performance and henceforth monitoring dissolved O2 (DO) and dissolved CO2 (dCO2) is of paramount importance. At bioreactor level these parameters can be monitored online and can be controlled by sparging air/oxygen or stirrer speed. However, traditional small‐scale systems such as shake flasks lack real time monitoring and also employ only surface aeration with additional diffusion limitations imposed by the culture plug. Here we present implementation of intensifying surface aeration by sparging air in the headspace of the reaction vessel and real‐time monitoring of DO and dCO2 in the bioprocesses to evaluate the impact of intensified surface aeration. We observed that sparging air in the headspace allowed us to keep dCO2 at low level, which significantly improved not only biomass growth but also protein yield. We expect that implementing such controlled smart shake flasks can minimize the process development gap which currently exists in shake flask level and bioreactor level results.

Section: Discussionmentioning

confidence: 99%

Real‐time dissolved carbon dioxide monitoring II: Surface aeration intensification for efficient CO₂ removal in shake flasks and mini‐bioreactors leads to superior growth and recombinant protein yields

Biotech & Bioengineering

Holzberg

et al. 2020

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“…To improve control performance, we introduced nonlinear control (NLC) to regulate the DO concentration precisely near the set points. Detailed information about the controller has been addressed in a previous publication, which was focused on the evaluation of controller performance [33]. As expected, performance of DO control is significantly better using NLC as evident from significantly less oscillations and lower offset values.…”

Section: Implementation Of Non-linear Control (Nlc) Schemementioning

confidence: 73%

Bridging the gap between PAT concepts and implementation: An integrated software platform for fermentation

Gomes

Rathore

2015

Biotechnology Journal

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Bioreactor control significantly impacts both the amount and quality of the product being manufactured. The complexity of the control strategy that is implemented increases with reactor size, which may vary from thousands to tens of thousands of litres in commercial manufacturing. The Process Analytical Technology (PAT) initiative has highlighted the need for having robust monitoring tools and effective control schemes that are capable of taking real time information about the critical quality attributes (CQA) and the critical process parameters (CPP) and executing immediate response as soon as a deviation occurs. However, the limited flexibility that present commercial software packages offer creates a hurdle. Visual programming environments have gradually emerged as potential alternatives to the available text based languages. This paper showcases development of an integrated programme using a visual programming environment for a Sartorius BIOSTAT® B Plus 5L bioreactor through which various peripheral devices are interfaced. The proposed programme facilitates real-time access to data and allows for execution of control actions to follow the desired trajectory. Major benefits of such integrated software system include: (i) improved real time monitoring and control; (ii) reduced variability; (iii) improved performance; (iv) reduced operator-training time; (v) enhanced knowledge management; and (vi) easier PAT implementation.

“…Figure c shows the overlap of the dCO 2 trend for both yeasts where the significant distinction in their metabolic pattern can be seen. The initial sharp rise in dCO 2 concentration (first 7 hr) in the case of baker's yeast was probably due to the Crabtree effect where respire‐fermentative glucose metabolism led to the production of CO 2 and ethanol (Chopda, Rathore, & Gomes, ; Chopda, Rathore, & Gomes, ; Persad, Chopda, Rathore, & Gomes, ). Thereafter, dCO 2 concentration decreased indicating exhaustion of glucose.…”

Section: Resultsmentioning

confidence: 99%

“…However, until now, CO 2 is mostly monitored in the exhaust gas, which itself cannot give real‐time culture broth conditions as the information captured is filtered through the headspace. This means there exists an inherent lag in relaying the dCO 2 concentrations to the gaseous phase CO 2 (Chopda et al, ). Very few sensors are available in the market which can measure dCO 2 concentration, and most will not fit in small‐scale systems such as shake flasks or mini bioreactors.…”

Section: Discussionmentioning

confidence: 99%

Real‐time dissolved carbon dioxide monitoring I: Application of a novel in situ sensor for CO₂ monitoring and control

Biotech & Bioengineering

Holzberg

et al. 2020

Self Cite

Dissolved carbon dioxide (dCO2) is a well‐known critical parameter in bioprocesses due to its significant impact on cell metabolism and on product quality attributes. Processes run at small‐scale faces many challenges due to limited options for modular sensors for online monitoring and control. Traditional sensors are bulky, costly, and invasive in nature and do not fit in small‐scale systems. In this study, we present the implementation of a novel, rate‐based technique for real‐time monitoring of dCO2 in bioprocesses. A silicone sampling probe that allows the diffusion of CO2 through its wall was inserted inside a shake flask/bioreactor and then flushed with air to remove the CO2 that had diffused into the probe from the culture broth (sensor was calibrated using air as zero‐point calibration). The gas inside the probe was then allowed to recirculate through gas‐impermeable tubing to a CO2 monitor. We have shown that by measuring the initial diffusion rate of CO2 into the sampling probe we were able to determine the partial pressure of the dCO2 in the culture. This technique can be readily automated, and measurements can be made in minutes. Demonstration experiments conducted with baker's yeast and Yarrowia lipolytica yeast cells in both shake flasks and mini bioreactors showed that it can monitor dCO2 in real‐time. Using the proposed sensor, we successfully implemented a dCO2‐based control scheme, which resulted in significant improvement in process performance.