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Improve Bioreactor Performance via Soft-Sensors with CHO Predictive Models
This Webinar is over| Date | Jul 29, 2020 |
| Time | 10:00 AM EDT |
| Cost | Free |
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Online
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Webinar Description:
Fed-batch mammalian cell culture in stirred-tank bioreactors for cell and biologic production is a standard bioprocess application. Probes and control systems are frequently used for monitoring and automating adjustments of parameters such as pH, gases and temperature. Although effective at stabilizing a healthy physical growth environment, sampling and off-line assays are still often required to monitor growth phase and media depletion effects for supplementation with vital nutrients.
By use of optical (spectroscopy) probes, media concentrations of key components (i.e. glucose and lactate) can be monitored in real-time. This data, when coupled with automated delivery, can drive the controlled supply of key nutrients throughout the cell culture timeline. Furthermore, impedance spectroscopy (based on electrical capacitance) can also be employed to detect cellular biomass accumulation. However, a critical and challenging issue with both of these soft-sensor technologies is the development of dynamic cell models (computer algorithms) to properly interpret the information in real-time for a specific bioproduction system. Furthermore, integration of all the essential probes, instruments, software and delivery systems can be a daunting task.
We have created a default control algorithm and next generation integrated system for CHO cell expression of biologics that can be customized in as little as three optimization runs. The protocol and tools lead to an optimized algorithm that precisely aligns the real-time sensor data with off-line biochemical assays uniquely matched to your CHO cell medium and expression system from early-stage to late-stage culture. This eliminates the need for repeated sample testing and provides the means for real-time data to drive precision process control. By employing a proprietary self-learning predictive-control algorithm, continuous glucose adjustments are made, resulting in high cell counts, better viability, and improved biologic yield.
Yokogawa’s expertise in automation, sensors, control systems and engineering in various commercial applications are now being re-purposed and employed to bring better performance to biopharmaceutical production. Designated the BR1000 Advanced Control Bioreactor System, the instrument can speed process development and open new possibilities for control of biopharmaceutical production.
Learning Objectives:
-Critical considerations in soft-sensor use that impede more widespread adoption of spectroscopic technologies for real-time process control, and how we have overcome these challenges
-Data demonstrating how calibration with off-line assays has been simplified using software tools to produce accurate cells models with minimal effort
-How dynamic predictive control for glucose feeding can affect bioreactor performance and biopharmaceutical integrity
Fed-batch mammalian cell culture in stirred-tank bioreactors for cell and biologic production is a standard bioprocess application. Probes and control systems are frequently used for monitoring and automating adjustments of parameters such as pH, gases and temperature. Although effective at stabilizing a healthy physical growth environment, sampling and off-line assays are still often required to monitor growth phase and media depletion effects for supplementation with vital nutrients.
By use of optical (spectroscopy) probes, media concentrations of key components (i.e. glucose and lactate) can be monitored in real-time. This data, when coupled with automated delivery, can drive the controlled supply of key nutrients throughout the cell culture timeline. Furthermore, impedance spectroscopy (based on electrical capacitance) can also be employed to detect cellular biomass accumulation. However, a critical and challenging issue with both of these soft-sensor technologies is the development of dynamic cell models (computer algorithms) to properly interpret the information in real-time for a specific bioproduction system. Furthermore, integration of all the essential probes, instruments, software and delivery systems can be a daunting task.
We have created a default control algorithm and next generation integrated system for CHO cell expression of biologics that can be customized in as little as three optimization runs. The protocol and tools lead to an optimized algorithm that precisely aligns the real-time sensor data with off-line biochemical assays uniquely matched to your CHO cell medium and expression system from early-stage to late-stage culture. This eliminates the need for repeated sample testing and provides the means for real-time data to drive precision process control. By employing a proprietary self-learning predictive-control algorithm, continuous glucose adjustments are made, resulting in high cell counts, better viability, and improved biologic yield.
Yokogawa’s expertise in automation, sensors, control systems and engineering in various commercial applications are now being re-purposed and employed to bring better performance to biopharmaceutical production. Designated the BR1000 Advanced Control Bioreactor System, the instrument can speed process development and open new possibilities for control of biopharmaceutical production.
Learning Objectives:
-Critical considerations in soft-sensor use that impede more widespread adoption of spectroscopic technologies for real-time process control, and how we have overcome these challenges
-Data demonstrating how calibration with off-line assays has been simplified using software tools to produce accurate cells models with minimal effort
-How dynamic predictive control for glucose feeding can affect bioreactor performance and biopharmaceutical integrity
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