Next generation multimodal chromatography resins via an iterative mapping approach: Chemical diversity, high-throughput screening, and chromatographic modelling

Multimodal chromatography resins are becoming a key tool in the purification of biomolecules. The main objective of this research was the establishment of an iterative framework for the rapid development of new multimodal resins to provide novel selectivity for the future purification challenges. A large chemically diverse virtual library of 100 multimodal Capto™ MMC ligand analogues was created, and a broad array of chemical descriptors were calculated for each ligand in silico. Principal component analysis (PCA) was used to map the chemical diversity and guide selection of ligands for synthesis and coupling to the Capto ImpRes agarose base matrix. Twelve new ligands were prepared in two groups: ‘group one’ consist of L00-L07 and ‘group two’ consist of L08-L12. These ligands are diverse in the influence of varied secondary interactions such as hydrophobic interactions, H-bonding, etc. Additional resin prototypes were also prepared to look at the chromatographic impact of ligand density variation. High-throughput plate-based studies were performed for parallel resin screening for batch-binding of six model proteins at different chromatographic binding pH and sodium chloride concentration conditions. Principal component analysis of the binding data provided a chromatographic diversity map leading to the identification of ligands with improved binding. Further, the new ligands have improved separation resolution between a monoclonal antibody (mAb1) and product related impurities, a Fab fragment and high molecular weight (HMW) aggregates, using linear salt gradient elutions. To quantify the importance of secondary interactions, analysis of the retention factor of mAb1 on the ligands at various isocratic conditions lead to estimations of (a) the total number of water molecules and counter salt ions released during adsorption, and (b) hydrophobic contact area (HCA). The iterative mapping approach of chemical and chromatography diversity maps described in the paper proves to be a promising method for identifying new chromatography ligands for biopharmaceutical purification challenges.