A strategy for clone selection under different production conditions.

Area of Science:

• Biotechnology
• Bioprocess Engineering
• Cell Line Development

Background:

• Traditional clone screening methods often fail to identify top performers for manufacturing scale.
• Robustness and critical process factors are difficult to assess with conventional approaches.

Purpose of the Study:

• To evaluate micro-bioreactor systems as a high-throughput tool for clone screening and process optimization.
• To assess the dynamic ranking strategy for selecting optimal clones and conditions for recombinant monoclonal antibody (mAb) production.

Main Methods:

• Screened eight Chinese Hamster Ovary (CHO) clones producing recombinant mAb using 240 micro-bioreactors across multiple process variations (feeding, temperature, pH).
• Conducted a follow-up study with 180 micro-bioreactors in a full factorial design, comparing 12 clone/process combinations in shake flasks.
• Utilized a fully monitored and controlled small-scale platform for parallel experimentation.

Main Results:

• Successfully identified the best and worst performing clones and processes based on maximum mAb titer.
• Demonstrated good correlation (Pearson correlation value of 0.94) between micro-bioreactor predictions and shake flask results.
• Achieved simultaneous clone screening and process optimization, leading to significant titer improvements.

Conclusions:

• Micro-bioreactor systems are effective high-throughput tools for clone evaluation and process optimization in biopharmaceutical development.
• The dynamic ranking strategy supports informed decisions for selecting production clones, mitigating risks associated with manufacturing scale-up.
• This approach enhances the efficiency and accuracy of identifying high-performing clones and optimizing bioprocesses for increased mAb titers.