A scale-down mini-bioreactor for the acceleration of data-driven bioprocess optimisation in cell therapy

Area of Science:

• Biotechnology
• Cell Therapy
• Bioprocess Engineering

Background:

• Cell therapies show promise but face challenges in clinical translation due to lengthy development and suboptimal processing.
• Optimizing bioprocesses requires extensive, costly, and resource-intensive experimentation.

Purpose of the Study:

• To develop a modular, 3D-printed mini-bioreactor for parallelized stirred cell cultures.
• To enable AI-driven bioprocess development through real-time monitoring and data generation.
• To efficiently screen and optimize bioprocess parameters for cell therapy development.

Main Methods:

• A modular, 3D-printed scaled-down bioreactor system for parallel stirred cell cultures.
• Integration of real-time monitoring of critical culture parameters.
• Application of a sequential screening design to evaluate bioprocess parameters (e.g., inoculum, surface area ratio, rotation speed).
• Implementation of a soft-sensing framework using metabolic indicators to estimate cell number.

Main Results:

• The mini-bioreactor facilitated rapid, cost-effective, and efficient optimization of bioprocess conditions.
• The integrated sensor system enabled non-invasive estimation of cell number and culture dynamics.
• Cells expanded in the mini-bioreactor maintained stemness and multipotency, confirmed by successful differentiation into osteogenic, chondrogenic, and adipogenic lineages.

Conclusions:

• The developed mini-bioreactor system accelerates cell therapy bioprocess development and optimization.
• Real-time monitoring and soft-sensing provide valuable insights for efficient process control.
• The system supports the generation of high-quality cells for therapeutic applications.