Efficient optimization of time-varying inputs in a fed-batch cell culture process using design of dynamic experiments

Area of Science:

• Biotechnology
• Chemical Engineering
• Process Development

Background:

• Traditional cell culture process development relies on limited, iterative experiments.
• Design of Experiments (DoE) offers systematic analysis but struggles with time-varying inputs.
• Studying dynamic feeding profiles in bioreactors typically requires excessive resources.

Purpose of the Study:

• To apply Design of Dynamic Experiments (DoDE) for optimizing time-varying feeding profiles in monoclonal antibody production.
• To efficiently incorporate dynamic feeding strategies into late-stage bioprocess development.
• To improve process efficiency and product yield through dynamic optimization.

Main Methods:

• Adoption and application of Design of Dynamic Experiments (DoDE) methodology.
• Incorporation of dynamic feeding profiles into late-stage cell culture process development.
• Statistical modeling to analyze the impact of feed rate slopes and higher-order dynamics.

Main Results:

• Successfully estimated the effect of nutrient feed amount and optimized the slope of time-trended feed rates.
• Demonstrated that higher-order dynamic characteristics of feed rates had no significant impact on measured responses.
• Achieved a 27% increase in titer and >92% viability in a 200-L batch compared to a baseline process.

Conclusions:

• DoDE provides an efficient framework for optimizing dynamic process conditions in biopharmaceutical manufacturing.
• The developed statistical models enable significant improvements in productivity and product quality.
• This methodology serves as a foundation for more efficient bioprocess development workflows.