High-throughput microscale chromatography for process characterization and control strategy development in biologics...

Area of Science:

• Biopharmaceutical Manufacturing
• Process Development
• Chromatography

Background:

• Microscale models accelerate bioprocess development for modalities like monoclonal antibodies.
• Hurdles remain for microscale model adoption in late-stage validation due to perceived risks.
• Growing literature supports the widespread adoption of microscale models, including Robocolumns.

Purpose of the Study:

• To provide a case study on the practical application of Robocolumn scale-down models for process characterization and validation.
• To increase confidence in developing robust process control strategies using Robocolumn data.
• To rigorously compare the predictive capability of microscale models against traditional methods for manufacturing scale performance.

Main Methods:

• Process characterization of a bispecific antibody using replicate Robocolumn and traditional bench-scale chromatography models.
• Evaluation of three chromatography steps impacting seven process performance and product quality attributes.
• Statistical comparison of predictive capabilities for manufacturing scale performance.

Main Results:

• Robocolumn scale-down models demonstrated excellent agreement with manufacturing scale performance at target conditions.
• Outcomes from Robocolumn models aligned with bench-scale results from multivariate studies.
• Consistent process parameter classifications were derived from both microscale and traditional scale-down models.

Conclusions:

• Microscale Robocolumn models are validated for process characterization and validation in biopharmaceutical manufacturing.
• These models provide reliable data for developing robust process control strategies.
• Robocolumns offer a viable alternative to traditional scale-down models, supporting wider adoption.