Modelling and optimization of a recombinant BHK-21 cultivation process using hybrid grey-box systems

Area of Science:

• Biotechnology
• Bioprocess Engineering
• Mammalian Cell Culture

Background:

• BHK-21 cell metabolism presents unique complexities compared to other mammalian cell lines.
• Accurate kinetic modeling for optimization is challenging due to intricate metabolic pathways and numerous parameters.
• Traditional model-based optimization faces difficulties with BHK-21 cell complexity.

Purpose of the Study:

• To develop a cost-effective methodology for optimizing fed-batch cultures of BHK-21 cells.
• To investigate hybrid grey-box models for capturing specific BHK-21 metabolic characteristics.
• To enhance the production of human fusion glycoprotein IgG1-IL2.

Main Methods:

• Utilized hybrid grey-box models combining first principles and black-box approaches.
• Analyzed data from both batch and fed-batch experimental cultures.
• Developed a risk monitoring method for hybrid model reliability during optimization.

Main Results:

• Hybrid models effectively captured the particularities of BHK-21 cell metabolism.
• The proposed risk monitoring method constrained optimization to acceptable levels.
• Identified optimal feeding strategies for increased process productivity.

Conclusions:

• Hybrid grey-box models offer a viable and cost-effective alternative to complex kinetic models for BHK-21 cultures.
• Controlling glucose and glutamine concentrations is critical for optimizing glycoprotein production.
• Strategic adjustments in glutamine feeding can significantly boost process productivity.