Physicochemical factors in polypeptide and protein purification and analysis by high-performance liquid chromatographic techniques: current status and challenges for the future

Mechanistic modeling based process analytical technology implementation for pooling in hydrophobic interaction chromatography

A major challenge in chromatography purification of therapeutic proteins is batch-to-batch variability with respect to impurity levels and product concentration in the feed. Mechanistic model can enable process analytical technology (PAT) implementation by predicting impact of such variations and thereby improving the robustness of the resulting process and controls. This article presents one such application of mechanistic model of hydrophobic interaction chromatography (HIC) as a PAT tool for making robust pooling decisions to enable clearance of aggregates for a monoclonal antibody (mAb) therapeutic. Model predictions were performed before the actual chromatography experiments to facilitate feedforward control. The approach has been successfully demonstrated for four different feeds with varying aggregate levels (3.84%-5.54%) and feed concentration (0.6 mg/mL-1 mg/mL). The resulting pool consistently yielded a product with 1.32 ± 0.03% aggregate vs. a target of 1.5%. A comparison of the traditional approach involving column fractionation with the proposed approach indicates that the proposed approach results in achievement of satisfactory product purity (98.68 ± 0.03% for mechanistic model based PAT controlled pooling vs. 98.64 ± 0.16% for offline column fractionation based pooling). © 2018 American Institute of Chemical Engineers Biotechnol. Prog., 35: e2758, 2019.

Design of experiments applications in bioprocessing: Chromatography process development using split design of experiments

Development of a chromatographic step in a time and resource efficient manner remains a serious bottleneck in protein purification. Chromatographic performance typically depends on raw material attributes, feed material attributes, process factors, and their interactions. Design of experiments (DOE) based process development is often chosen for this purpose. A challenge is, however, in performing a DOE with such a large number of process factors. A split DOE approach based on process knowledge in order to reduce the number of experiments is proposed. The first DOE targets optimizing factors that are likely to significantly impact the process and their effect on process performance is unknown. The second DOE aims to fine-tune another set of interacting process factors, impact of whom on process performance is known from process understanding. Furthermore, modeling of a large set of output response variables has been achieved by fitting the output responses to an empirical equation and then using the parametric constants of the equation as output response variables for regression modeling. Two case studies involving hydrophobic interaction chromatography for removal of aggregates and cation exchange chromatography for separation of charge variants and aggregates have been utilized to illustrate the proposed approach. Proposed methodology reduced total number of experiments by 25% and 72% compared to a single DOE based on central composite design and full factorial design, respectively. The proposed approach is likely to result in a significant reduction in resources required as well as time taken during process development. © 2018 American Institute of Chemical Engineers Biotechnol. Prog., 35: e2730, 2019.

Peptide mapping by reversed-phase high-performance liquid chromatography employing silica rod monoliths

In this paper, a general procedure is described for the generation of peptide maps of proteins with monolithic silica-based columns. The peptide fragments were obtained by tryptic digestion of various cytochrome c species with purification of the tryptic fragments achieved by reversed-phase high-performance liquid chromatographic methods. Peak assignment of the various peptides was based on evaluation of the biophysical properties of the individual peptides and via mass spectrometric identification. The performance of several different monolithic sorbents prepared as columns of identical cross-sectional dimensions were investigated as part of these peptide mapping studies and the data evaluated by applying solvent strength theory. These studies revealed curvilinear dependencies in the corresponding relative resolution maps. These findings directly impact on the selection of specific sorbent types or column configurations for peptide separations with silica rod monoliths. Moreover, the influence of variations in the amino acid sequence of the cytochrome cs were evaluated with respect to their effect on intrinsic hydrophobicity, the number of experimental observed tryptic cleavage sites, detection limits of the derived fragments in relation to their molecular size, and the chromatographic selectivity and resolution of the various peptides obtained following enzymatic fragmentation of the parent protein. Finally, the scope of these approaches in method development was examined in terms of robustness and efficiency.

HPLC of peptides and proteins: preparation and system set-up

The eight basic modes of HPLC currently in use for peptide and protein analysis and purification are presented in this overview. They include: size-exclusion chromatography (HP-SEC), ion-exchange chromatography (HP-IEX), normal phase chromatography (HP-NPC), hydrophobic interaction chromatography (HP-HIC), reversed-phase chromatography (RP-HPLC), hydrophilic interaction chromatography (HP-HILIC), immobilized metal ion affinity chromatography (HP-IMAC), and biospecific/biomimetic affinity chromatography (HP-BAC). In addition, some subsets of these chromatographic modes, e.g., mixed mode chromatography (HP-MMC), charge transfer chromatography (HP-CTC), or ligand-exchange chromatography (HP-LEC) are described. The unit includes overviews of the system requirements and planning strategies for set-up of the systems.