Automatic generation of a digital twin for continuous antibody capture
- 1Division of Chemical Engineering, Department of Process and Life Science Engineering, Lund University, Lund, Sweden.
- 0Division of Chemical Engineering, Department of Process and Life Science Engineering, Lund University, Lund, Sweden.
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View abstract on PubMed
Summary
This summary is machine-generated.We developed an automated procedure to create and calibrate digital twins for monoclonal antibody purification. This digitalization enhances process efficiency and sustainability, reducing costs and accelerating drug discovery.
Area Of Science
- Biotechnology
- Chemical Engineering
- Process Automation
Background
- Digitalization offers enhanced efficiency and sustainability in monoclonal antibody downstream processing.
- Digital twins provide process insights and optimization but are challenging to create.
- Automated generation and calibration of digital twins are needed for wider adoption.
Purpose Of The Study
- To develop an automated procedure for generating and calibrating digital twins for chromatography.
- To demonstrate the utility of digital twins for process optimization in monoclonal antibody purification.
- To reduce the time and effort required for digital twin acquisition.
Main Methods
- Automatic generation of a digital twin based on chromatography setup configuration.
- Automated execution of a calibration procedure involving experiments and simulations.
- Application of the digital twin for optimizing yield, resin utilization, and column capacity variations.
Main Results
- Experimental validation showed a 0.6% difference in yield and resin utilization compared to simulation.
- Optimization for reduced column capacity increased resin utilization by 1.2% with 99.8% yield.
- The automated procedure efficiently generated and calibrated a functional digital twin.
Conclusions
- The developed procedure enables efficient digital twin generation and calibration for monoclonal antibody downstream processing.
- Integrating digitalization through digital twins can lower production costs and improve sustainability.
- This work represents a significant step towards automated and optimized biopharmaceutical manufacturing.
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