A novel approach for perfusion process design based on a "Grey-Box" kinetic model

Area of Science:

• Biotechnology and Bioprocessing
• Cell Culture Engineering
• Biomanufacturing Optimization

Background:

• Perfusion cell culture offers advantages like higher cell densities and productivities in biomanufacturing.
• However, operational complexity and high costs hinder perfusion process development.
• Chinese Hamster Ovary (CHO) cell culture optimization remains a key challenge.

Purpose of the Study:

• To develop a model-based approach for designing optimized perfusion cultures of CHO cells.
• To identify optimal operational parameters (perfusion rate, feed medium proportion) for target steady-state viable cell density (VCD).
• To minimize medium cost and perfusion rate while addressing cell-growth inhibition and nutrient depletion.

Main Methods:

• Model parameter fitting using bench-top reactor continuous-perfusion-culture data.
• Model-based design to find optimal steady-state operational parameters.
• Model-based dynamic adjustment strategy for osmolality-induced growth inhibition.
• Dynamic feedback control to prevent nutrient depletion.

Main Results:

• Successfully identified theoretically optimal operational parameters for perfusion cultures.
• Demonstrated a dynamic adjustment strategy to mitigate osmolality issues.
• Validated the approach in shake flask and bench-top reactor cultures at high cell densities.
• Significantly reduced experimental effort in process design and development.

Conclusions:

• The model-based approach accelerates the design and development of perfusion cell-culture processes.
• This methodology enables efficient optimization for high-density CHO cell cultures.
• It provides a pathway to reduce costs and improve efficiency in biomanufacturing.