The replacement of manual processes with automation is a trend in the biopharmaceutical industry. For complete automation of fed-batch mammalian cell culture, the control of glucose, a key nutrient source, is critical. Through in-line sensing and model predictive control software, automated feeding and a stable concentration of glucose in bioreactors can be achieved.

High-precision real-time monitoring of cell activity

We have made it possible to measure cell activities in real time using state-of-the-art in-line sensors that detect viable cell densities and concentrations of glucose and lactate with high accuracy.

Automatic cell culture by advanced control

By leveraging in-line sensor data, a model predictive control algorithm designed specifically for mammalian cell culture enables automatic control of glucose concentration with high accuracy. Sampling and off-line analytics are not required.


Technology to measure cell activity

Near-infrared (NIR) spectroscopy is used to measure in real time the concentration of nutrient sources taken in by cells and the concentration of metabolites expelled by cells in the extracellular space. Since nutrient sources and metabolites absorb near-infrared light, changes in concentration are captured by measuring the near-infrared absorption spectra of nutrient sources and metabolites with a measurement probe placed in the culture medium. Cells take up a nutrient source into the cell and metabolize it to produce antibodies, proteins and other drugs. By monitoring the nutrient source (glucose) taken up by cells and the metabolite (lactic acid) expelled from the cell by metabolism, it is possible to measure the activity of cells in culture.

Technology to measure cellular activity

Technology to measure the state of cells

The number of live cells is measured in real time by the electrical impedance measurement method. Live cells in an electric field cause dielectric relaxation, which polarizes the charges inside and outside the cell membrane. Dead cells, on the other hand, do not undergo charge polarization because their membranes are broken. As a result, the capacitance of the culture medium changes in proportion to the number of living cells. Using this characteristic, a measurement probe placed in the culture medium can measure the change in the capacitance of the culture medium to determine the number of living cells.

Technology to measure the number of living cells

Technology to predict and control cellular metabolism

Mathematical modeling of cell movement predicts the metabolic state of cells and controls the cell's appropriate culture environment for the production of drugs. Changes in the metabolic state of cells are expressed in changes in the rate of cell growth and consumption of nutrient sources. Therefore, we build a mathematical model of cell metabolism based on real-time measurements of the number of living cells and the concentration of nutrient sources and metabolites to estimate and predict the growth rate of cells and the rate of consumption of nutrient sources. Based on these predictions, the culture environment can be controlled to maintain optimal cell activity.

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A critical requirement in biopharmaceutical development is the integration and automation of process equipment and analytical instruments used in the laboratory. Bioprocess labs with multiple lab-scale bioreactors often execute cultivation experiments in parallel for research or process development purposes.

As part of a collaboration between Securecell (Zurich, SW) and Yokogawa Life Science (Tokyo, Japan), this application note demonstrates the effective use of the Lucullus® Process Information Management System (Lucullus®) to assist in the control of three Advanced Control Bioreactor Systems (BR1000) to study glucose utilization of CHO cells for optimal monoclonal antibody productivity.


This paper describes how the Yokogawa BR1000 bioreactor can be used to automate through real-time sensing and improve productivity through accurate and efficient glucose control.


Exploring the technologies needed to achieve automatic control of cell culture processes.




Our approach is to leverage state-of-the-art technologies for real-time monitoring and predictive control that allow virtual environments where "digital twin" processes can provide distinct advantages.

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