Objective: The purpose of the study was to use DoE and first principles based modeling to evaluate criticality of process parameters and explain observed performance differences of a HIC step for an ADC upon scale-up. Methods: A Plackett-Burman DoE was conducted to screen the significance of 11 process parameters. Two parameters identified as significant, along with three additional parameters known to be critical based on prior process knowledge, were included in a definitive screening DoE. To evaluate the effect of resin ligand density, nominal process was performed on three columns with different ligand densities. A fraction of the experimental data was fitted into a first principles based model accounting for effects of loading, pH, salt concentration, temperature, and ligand density. Learnings from both experiments and modeling were used to understand the offset of an impurity rejection between lab scale and manufacturing scale. Results: Four process parameters, load amount, pH, salt concentration, and temperature, were identified as critical process parameters. Resin ligand density and total porosity also impacted HIC performance. The HIC model predictions were consistent with DoE outcomes. The model further identified resin ligand density and total porosity as contributing factors to the offset of impurity rejection between the lab and manufacturing scales. Conclusions: Both DoE and first principles based modeling provided valuable insights into the HIC step. DoE identified critical process parameters. First principles based modeling incorporated both chromatography process parameters as well as parameters representing resin properties and column packing. It helped explain the difference across scales by incorporating effects of ligand density and total porosity. All authors are employees of AbbVie and may own AbbVie stock. AbbVie sponsored and funded the study; contributed to the design; participated in the collection, analysis, and interpretation of data, and in writing, reviewing, and approval of the final publication.

Understanding hydrophobic interaction chromatography (HIC) purification of an antibody drug conjugate (ADC) using design of experiments (DoE) and first principles based modeling

ACS Spring 2022

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