Cross‐scale quality assessment of a mechanistic cation exchange chromatography model. (25th September 2020)

• Record Type: Journal Article
• Authors: Saleh, David; Wang, Gang; Mueller, Benedict; Rischawy, Federico; Kluters, Simon; Studts, Joey; Hubbuch, Jürgen
• Is Part Of: Biotechnology progress. Volume 37:Number 1(2021)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2020-09-25
• Subjects: antibody purification -- cation exchange chromatography -- mechanistic model qualification -- scale down model -- scale‐up; Biotechnology -- Periodicals; Food industry and trade -- Periodicals; Bioengineering -- Periodicals; 660.6
• DOI: 10.1002/btpr.3081
• Languages: English
• ISSNs: 8756-7938

Abstract

Abstract: Cation exchange chromatography (CEX) is an essential part of most monoclonal antibody (mAb) purification platforms. Process characterization and root cause investigation of chromatographic unit operations are performed using scale down models (SDM). SDM chromatography columns typically have the identical bed height as the respective manufacturing‐scale, but a significantly reduced inner diameter. While SDMs enable process development demanding less material and time, their comparability to manufacturing‐scale can be affected by variability in feed composition, mobile phase and resin properties, or dispersion effects depending on the chromatography system at hand. Mechanistic models can help to close gaps between scales and reduce experimental efforts compared to experimental SDM applications. In this study, a multicomponent steric mass‐action (SMA) adsorption model was applied to the scale‐up of a CEX polishing step. Based on chromatograms and elution pool data ranging from laboratory‐ to manufacturing‐scale, the proposed modeling workflow enabled early identification of differences between scales, for example, system dispersion effects or ionic capacity variability. A multistage model qualification approach was introduced to measure the model quality and to understand the model's limitations across scales. The experimental SDM and the in silico model were qualified against large‐scale data using the identical state of the art equivalence testing procedure. The mechanistic chromatography model avoided limitations of the SDM by capturing effects of bed height, loading density, feed composition, and mobile phase properties. The results demonstrate the applicability of mechanistic chromatography models as a possible alternative to conventional SDM approaches.