Industrial ion-exchange chromatography development using discontinuous Galerkin methods coupled with forward...

Area of Science:

• Biochemical Engineering
• Computational Chemistry
• Chromatography

Background:

• Model-based development of ion-exchange chromatography is computationally intensive.
• Optimizing chromatography processes, like Protein G purification, requires efficient methods.
• Industrial load samples present challenges for traditional chromatography modeling.

Purpose of the Study:

• To present a discontinuous Galerkin method coupled with forward sensitivity analysis (DG-FSA) for reduced computational cost.
• To demonstrate the application of DG-FSA in designing an anion-exchange chromatography step for peptide purification.
• To enable advanced analysis of process uncertainties and probability distributions.

Main Methods:

• Implementation of a discontinuous Galerkin method (DG) combined with forward sensitivity analysis (FSA).
• Development and application of a fourth-order DG-FSA for inverse problems in chromatography.
• Utilizing industrial load samples for process design and validation.

Main Results:

• The fourth-order DG-FSA reduced computational cost by a factor of 16 compared to the second-order method.
• Enabled computation of probability distributions for optimized processing conditions under parameter uncertainty.
• Experimental validation showed a 70% increase in productivity with a 4% yield sacrifice for Protein G purification.

Conclusions:

• The fourth-order DG-FSA offers a significant computational advantage for chromatography development.
• This method facilitates robust process optimization by accounting for parameter uncertainty.
• The approach successfully optimized a peptide purification step, enhancing productivity.