Model-based cell number quantification using online single-oxygen sensor data for tissue engineering perfusion...

Area of Science:

• Biotechnology
• Biomedical Engineering
• Cellular Engineering

Background:

• Automated manufacturing of cellular products requires non-invasive monitoring of tissue engineering (TE) constructs within bioreactors.
• Current monitoring techniques are insufficient for real-time quality assessment in TE bioreactors.

Purpose of the Study:

• To develop a generic and robust method for quantifying cell number and metabolic activity in TE constructs.
• To enable online, non-invasive quality attribute monitoring in perfusion bioreactors.

Main Methods:

• Utilized a data-based mechanistic modeling technique correlating oxygen sensor data to cell attributes.
• Applied dynamic perfusion conditions with step changes in perfusion rate.
• Analyzed oxygen response dynamics to infer cell number and metabolic activity.

Main Results:

• Successfully correlated cell number (R(2) = 0.80) and metabolic activity (R(2) = 0.82) to oxygen dynamics.
• Demonstrated effectiveness for cell quantities ranging from 1.0 × 10^5 to millions of cells.
• Validated a non-destructive measurement technique for bioprocess monitoring.

Conclusions:

• The developed method provides a non-invasive, robust approach for monitoring TE constructs in bioreactors.
• This technique supports the cost-effective up-scaling and automation of cellular construct manufacturing.
• Opens new possibilities for effective bioprocess monitoring and quality control.