This paper describes the surface modification of macroporous membranes using ATRP (atom transfer radical polymerization) to create cation-exchange adsorbers with high protein binding capacity at high product throughput. The work is motivated by the need for a more economical and rapid capture step in downstream processing of protein therapeutics. Membranes with three reported nominal pore sizes (0.2, 0.45, 1.0 μm) were modified with poly(3-sulfopropyl methacrylate, potassium salt) tentacles, to create a high density of protein binding sites. A special formulation was used in which the monomer was protected by a crown ether to enable surface-initiated ATRP of this cationic polyelectrolyte. Success with modification was supported by chemical analysis using Fourier-transform infrared spectroscopy and indirectly by measurement of pure water flux as a function of polymerization time. Uniformity of modification within the membranes was visualized with confocal laser scanning microscopy. Static and dynamic binding capacities were measured using lysozyme protein to allow comparisons with reported performance data for commercial cation-exchange materials. Dynamic binding capacities were measured for flow rates ranging from 13 to 109 column volumes (CV)/min. Results show that this unique ATRP formulation can be used to fabricate cation-exchange membrane adsorbers with dynamic binding capacities as high as 70 mg/mL at a throughput of 100 CV/min and unprecedented productivity of 300 mg/mL/min.

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This contribution describes research on the use of a newly developed multimodal membrane (MMM) adsorber that can be used as a chromatographic stationary phase in bioseparation processes. Compared with commercial cationic multimodal adsorbers, this MMM has superior static binding capacity (SBC = 180 mg IgG/ml), dynamic binding capacity (DBC 10% = 60 mg IgG/ml), and load productivity (>10 mg/ml/min). Furthermore, the incorporation of functional groups that provide orthogonal modes of interactions increases the range of ionic strength for operation of the MMM relative to conventional ion-exchange and hydrophobic interaction chromatography media. The effects of different salt types (kosmotropic, neutral, chaotropic salts) and ionic strength on IgG binding were investigated. To further understand the protein adsorption on the MMM, a thermodynamic model was employed to describe IgG adsorption isotherms on the MMM by providing a unique set of physically meaningful parameters for each salt type. The model was also a precise predictor of the adsorption isotherms under non-test conditions. A breakthrough analysis was used to determine dynamic binding capacities. The MMM maintained 70% DBC as ionic strength increased from 0 to 300 mM

While quantitative structure activity relationship (QSAR) models have been employed successfully for the prediction of small model protein chromatographic behavior, there have been few reports to date on the use of this methodology for larger, more complex proteins. Recently our group generated focused libraries of antibody Fab fragment variants with different combinations of surface hydrophobicities and electrostatic potentials, and demonstrated that the unique selectivities of multimodal resins can be exploited to separate these Fab variants. In this work, results from linear salt gradient experiments with these Fabs were employed to develop QSAR models for six chromatographic systems, including multimodal (Capto MMC, Nuvia cPrime, and two novel ligand prototypes), hydrophobic interaction chromatography (HIC; Capto Phenyl), and cation exchange (CEX; CM Sepharose FF) resins. The models utilized newly developed "local descriptors" to quantify changes around point mutations in the Fab libraries as well as novel cluster descriptors recently introduced by our group. Subsequent rounds of feature selection and linearized machine learning algorithms were used to generate robust, well-validated models with high training set correlations (R > 0.70) that were well suited for predicting elution salt concentrations in the various systems. The developed models then were used to predict the retention of a deamidated Fab and isotype variants, with varying success. The results represent the first successful utilization of QSAR for the prediction of chromatographic behavior of complex proteins such as Fab fragments in multimodal chromatographic systems. The framework presented here can be employed to facilitate process development for the purification of biological products from product-related impurities by in silico screening of resin alternatives. Biotechnol. Bioeng. 2017;114: 1231-1240. © 2016 Wiley Periodicals, Inc.

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