Current state of implementation of in silico tools in the biopharmaceutical industry-Proceedings of the 5th modeling workshop.

The fifth modeling workshop (5MW) was held in June 2023 at Favrholm, Denmark and sponsored by Recovery of Biological Products Conference Series. The goal of the workshop was to assemble modeling practitioners to review and discuss the current state, progress since the last fourth mini modeling workshop (4MMW), gaps and opportunities for development, deployment and maintenance of models in bioprocess applications. Areas of focus were four categories: biophysics and molecular modeling, mechanistic modeling, computational fluid dynamics (CFD) and plant modeling. Highlights of the workshop included significant advancements in biophysical/molecular modeling to novel protein constructs, mechanistic models for filtration and initial forays into modeling of multiphase systems using CFD for a bioreactor and mapped strategically to cell line selection/facility fit. A significant impediment to more fully quantitative and calibrated models for biophysics is the lack of large, anonymized datasets. A potential solution would be the use of specific descriptors in a database that would allow for detailed analyzes without sharing proprietary information. Another gap identified was the lack of a consistent framework for use of models that are included or support a regulatory filing beyond the high-level guidance in ICH Q8-Q11. One perspective is that modeling can be viewed as a component or precursor of machine learning (ML) and artificial intelligence (AI). Another outcome was alignment on a key definition for "mechanistic modeling." Feedback from participants was that there was progression in all of the fields of modeling within scope of the conference. Some areas (e.g., biophysics and molecular modeling) have opportunities for significant research investment to realize full impact. However, the need for ongoing research and development for all model types does not preclude the application to support process development, manufacturing and use in regulatory filings. Analogous to ML and AI, given the current state of the four modeling types, a prospective investment in educating inter-disciplinary subject matter experts (e.g., data science, chromatography) is essential to advancing the modeling community.

Factors affecting product association as a mechanism of host-cell protein persistence in bioprocessing.

Product association of host-cell proteins (HCPs) to monoclonal antibodies (mAbs) is widely regarded as a mechanism that can enable HCP persistence through multiple purification steps and even into the final drug substance. Discussion of this mechanism often implies that the existence or extent of persistence is directly related to the strength of binding but actual measurements of the binding affinity of such interactions remain sparse. Two separate avenues of investigation of HCP-mAb binding are reported here. One is the measurement of the affinity of binding of individual, commonly persistent Chinese hamster ovary (CHO) HCPs to each of a set of mAbs, and the other uses quantitative proteomic measurements to assess binding of HCPs in a null CHO harvested cell culture fluid (HCCF) to mAbs produced in the same cell line. The individual HCP measurements show that the binding affinities of individual HCPs to different mAbs can vary appreciably but are rarely very high, with only weak pH dependence. The measurements on the null HCCF allow estimation of individual HCP-mAb affinities; these are typically weaker than those seen in affinity measurements on isolated HCPs. Instead, the extent of binding appears correlated with the initial abundance of individual HCPs in the HCCF and the forms of the HCPs in the solution, i.e., whether HCPs are present as free molecules or as parts of large aggregates. Separate protein A chromatography experiments performed by feeding different fractions of a mAb-containing HCCF obtained by size-exclusion chromatography (SEC) showed clear differences in the number and identity of HCPs found in the protein A eluate. These results indicate a significant role for HCP-mAb association in determining HCP persistence through protein A chromatography, presumably through binding of HCP-mAb complexes to the resin. Overall, the results illustrate the importance of considering more fully the biophysical context of HCP-product association in assessing the factors that may affect the phenomenon and determine its implications. Knowledge of the abundances and the forms of individual or aggregated HCPs in HCCF are particularly significant, emphasizing the integration of upstream and downstream bioprocessing and the importance of understanding the collective properties of HCPs in addition to just the biophysical properties of individual HCPs.

Identification and characterization of CHO host-cell proteins in monoclonal antibody bioprocessing.

Host-cell proteins (HCPs) are the foremost class of process-related impurities to be controlled and removed in downstream processing steps in monoclonal antibody (mAb) manufacturing. However, some HCPs may evade clearance in multiple purification steps and reach the final drug product, potentially threatening drug stability and patient safety. This study extends prior work on HCP characterization and persistence in mAb process streams by using mass spectrometry (MS)-based methods to track HCPs through downstream processing steps for seven mAbs that were generated by five different cell lines. The results show considerable variability in HCP identities in the processing steps but extensive commonality in the identities and quantities of the most abundant HCPs in the harvests for different processes. Analysis of HCP abundance in the harvests shows a likely relationship between abundance and the reproducibility of quantification measurements and suggests that some groups of HCPs may hinder the characterization. Quantitative monitoring of HCPs persisting through purification steps coupled with the findings from the harvest analysis suggest that multiple factors, including HCP abundance and mAb-HCP interactions, can contribute to the persistence of individual HCPs and the identification of groups of common, persistent HCPs in mAb manufacturing.

Insulin purification-Innovation continuum via synthesis of fundamentals, technology, and modeling.

Advancement in all disciplines (art, science, education, and engineering) requires a careful balance of disruption and advancement of classical techniques. Often technologies are created with a limited understanding of fundamental principles and are prematurely abandoned. Over time, knowledge improves, new opportunities are identified, and technology is reassessed in a different light leading to a renaissance. Recovery of biological products is currently experiencing such a renaissance. Crystallization is one example of an elegant and ancient technology that has been applied in many fields and was employed to purify insulins from naturally occurring sources. Crystallization can also be utilized to determine protein structures. However, a multitude of parameters can impact protein crystallization and the "hit rate" for identifying protein crystals is relatively low, so much so that the development of a crystallization process is often viewed as a combination of art and science even today. Supplying the worldwide requirement for insulin (and associated variants) requires significant advances in process intensification to support scale of production and to minimize the overall cost to enable broader access. Expanding beyond insulin, the increasing complexity and diversity of biologics agents challenge the current purification methodologies. To harness the full potential of biologics, there is a need to fully explore a broader range of purification technologies, including nonchromatographic approaches. This impetus requires one to challenge and revisit the classical techniques including crystallization, chromatography, and filtration from a different vantage point and with a new set of tools, including molecular modeling. Fortunately, computational biophysics tools now exist to provide insights into mechanisms of protein/ligand interactions and molecular assembly processes (including crystallization) that can be used to support de novo process development. For example, specific regions or motifs of insulins and ligands can be identified and used as targets to support crystallization or purification development. Although the modeling tools have been developed and validated for insulin systems, the same tools can be applied to more complex modalities and to other areas including formulation, where the issue of aggregation and concentration-dependent oligomerization could be mechanistically modeled. This paper will illustrate a case study juxtaposing historical approaches to insulin downstream processes to a recent production process highlighting the application and evolution of technologies. Insulin production from Escherichia coli via inclusion bodies is an elegant example since it incorporates virtually all the unit operations associated with protein production-recovery of cells, lysis, solubilization, refolding, purification, and crystallization. The case study will include an example of an innovative application of existing membrane technology to combine three-unit operations into one, significantly reducing solids handling and buffer consumption. Ironically, a new separations technology was developed over the course of the case study that could further simplify and intensify the downstream process, emphasizing and highlighting the ever-accelerating pace of innovation in downstream processing. Molecular biophysics modeling was also employed to enhance the mechanistic understanding of the crystallization and purification processes.

Characterization and implications of host-cell protein aggregates in biopharmaceutical processing.

In the production of biopharmaceuticals such as monoclonal antibodies (mAbs) and vaccines, the residual amounts of host-cell proteins (HCPs) are among the critical quality attributes. In addition to overall HCP levels, individual HCPs may elude purification, potentially causing issues in product stability or patient safety. Such HCP persistence has been attributed mainly to biophysical interactions between individual HCPs and the product, resin media, or residual chromatin particles. Based on measurements on process streams from seven mAb processes, we have found that HCPs in aggregates, not necessarily chromatin-derived, may play a significant role in the persistence of many HCPs. Such aggregates may also hinder accurate detection of HCPs using existing proteomics methods. The findings also highlight that certain HCPs may be difficult to remove because of their functional complementarity to the product; specifically, chaperones and other proteins involved in the unfolded protein response (UPR) are disproportionately present in the aggregates. The methods and findings described here expand our understanding of the origins and potential behavior of HCPs in cell-based biopharmaceutical processes and may be instrumental in improving existing techniques for HCP detection and clearance.

Scale-up issues for commercial depth filters in bioprocessing.

Significant increases in cell density and product titer have led to renewed interest in the application of depth filtration for initial clarification of cell culture fluid in antibody production. The performance of these depth filters will depend on the local pressure and velocity distribution within the filter capsule, but these are very difficult to probe experimentally, leading to challenges in both process design and scale-up. We have used a combination of carefully designed experimental studies and computational fluid dynamics (CFD) to examine these issues in both lab-scale (SupracapTM 50) and pilot-scale (StaxTM ) depth filter modules, both employing dual-layer lenticular PDH4 media containing diatomaceous earth. The SupracapTM 50 showed a more rapid increase in transmembrane pressure and a more rapid DNA breakthrough during filtration of a Chinese Hamster Ovary cell culture fluid. These results were explained using CFD calculations which showed very different flow distributions within the modules. CFD predictions were further validated using measurements of the residence time distribution and dye binding in both the lab-scale and pilot-plant modules. These results provide important insights into the factors controlling the performance and scale-up of these commercially important depth filters as well as a framework that can be broadly applied to develop more effective depth filters and depth filtration processes.

Towards continuous mAb purification: Clearance of host cell proteins from CHO cell culture harvests via "flow-through affinity chromatography" using peptide-based adsorbents.

The growth of advanced analytics in manufacturing monoclonal antibodies (mAbs) has highlighted the challenges associated with the clearance of host cell proteins (HCPs). Of special concern is the removal of "persistent" HCPs, including immunogenic and mAb-degrading proteins, that co-elute from the Protein A resin and can escape the polishing steps. Responding to this challenge, we introduced an ensemble of peptide ligands that target the HCPs in Chinese hamster ovary (CHO) cell culture fluids and enable mAb purification via flow-through affinity chromatography. This study describes their integration into LigaGuard™, an affinity adsorbent featuring an equilibrium binding capacity of ~30 mg of HCPs per mL of resin as well as dynamic capacities up to 16 and 22 mg/ml at 1- and 2-min residence times, respectively. When evaluated against cell culture harvests with different mAb and HCP titers and properties, LigaGuard™ afforded high HCP clearance, with logarithmic removal values (LRVs) up to 1.5, and mAb yield above 90%. Proteomic analysis of the effluents confirmed the removal of high-risk HCPs, including cathepsins, histones, glutathione-S transferase, and lipoprotein lipases. Finally, combining LigaGuard™ for HCP removal with affinity adsorbents for product capture afforded a global mAb yield of 85%, and HCP and DNA LRVs > 4.

Identification of preferred multimodal ligand-binding regions on IgG1 FC using nuclear magnetic resonance and molecular dynamics simulations.

In this study, the binding of multimodal chromatographic ligands to the IgG1 FC domain were studied using nuclear magnetic resonance and molecular dynamics simulations. Nuclear magnetic resonance experiments carried out with chromatographic ligands and a perdeuterated 15 N-labeled FC domain indicated that while single-mode ion exchange ligands interacted very weakly throughout the FC surface, multimodal ligands containing negatively charged and aromatic moieties interacted with specific clusters of residues with relatively high affinity, forming distinct binding regions on the FC . The multimodal ligand-binding sites on the FC were concentrated in the hinge region and near the interface of the CH 2 and CH 3 domains. Furthermore, the multimodal binding sites were primarily composed of positively charged, polar, and aliphatic residues in these regions, with histidine residues exhibiting some of the strongest binding affinities with the multimodal ligand. Interestingly, comparison of protein surface property data with ligand interaction sites indicated that the patch analysis on FC corroborated molecular-level binding information obtained from the nuclear magnetic resonance experiments. Finally, molecular dynamics simulation results were shown to be qualitatively consistent with the nuclear magnetic resonance results and to provide further insights into the binding mechanisms. An important contribution to multimodal ligand-FC binding in these preferred regions was shown to be electrostatic interactions and π-π stacking of surface-exposed histidines with the ligands. This combined biophysical and simulation approach has provided a deeper molecular-level understanding of multimodal ligand-FC interactions and sets the stage for future analyses of even more complex biotherapeutics.

Probing IgG1 FC-Multimodal Nanoparticle Interactions: A Combined Nuclear Magnetic Resonance and Molecular Dynamics Simulations Approach.

In this study, NMR and molecular dynamics simulations were employed to study IgG1 FC binding to multimodal surfaces. Gold nanoparticles functionalized with two multimodal cation-exchange ligands (Capto and Nuvia) were synthesized and employed to carry out solution-phase NMR experiments with the FC. Experiments with perdeuterated 15N-labeled FC and the multimodal surfaces revealed micromolar residue-level binding affinities as compared to millimolar binding affinities with these ligands in free solution, likely due to cooperativity and avidity effects. The binding of FC with the Capto ligand nanoparticles was concentrated near an aliphatic cluster in the CH2/CH3 interface, which corresponded to a focused hydrophobic region. In contrast, binding with the Nuvia ligand nanoparticles was more diffuse and corresponded to a large contiguous positive electrostatic potential region on the side face of the FC. Results with lower-ligand-density nanoparticles indicated a decrease in binding affinity for both systems. For the Capto ligand system, several aliphatic residues on the FC that were important for binding to the higher-density surface did not interact with the lower-density nanoparticles. In contrast, no significant difference was observed in the interacting residues on the FC to the high- and low-ligand density Nuvia surfaces. The binding affinities of FC to both multimodal-functionalized nanoparticles decreased in the presence of salt due to the screening of multiple weak interactions of polar and positively charged residues. For the Capto ligand nanoparticle system, this resulted in an even more focused hydrophobic binding region in the interface of the CH2 and CH3 domains. Interestingly, for the Nuvia ligand nanoparticles, the presence of salt resulted in a large transition from a diffuse binding region to the same focused binding region determined for Capto nanoparticles at 150 mM salt. Molecular dynamics simulations corroborated the NMR results and provided important insights into the molecular basis of FC binding to these different multimodal systems containing clustered (observed at high-ligand densities) and nonclustered ligand surfaces. This combined biophysical and simulation approach provided significant insights into the interactions of FC with multimodal surfaces and sets the stage for future analyses with even more complex biotherapeutics.

Toward in silico CMC: An industrial collaborative approach to model-based process development.

The Third Modeling Workshop focusing on bioprocess modeling was held in Kenilworth, NJ in May 2019. A summary of these Workshop proceedings is captured in this manuscript. Modeling is an active area of research within the biotechnology community, and there is a critical need to assess the current state and opportunities for continued investment to realize the full potential of models, including resource and time savings. Beyond individual presentations and topics of novel interest, a substantial portion of the Workshop was devoted toward group discussions of current states and future directions in modeling fields. All scales of modeling, from biophysical models at the molecular level and up through large scale facility and plant modeling, were considered in these discussions and are summarized in the manuscript. Model life cycle management from model development to implementation and sustainment are also considered for different stages of clinical development and commercial production. The manuscript provides a comprehensive overview of bioprocess modeling while suggesting an ideal future state with standardized approaches aligned across the industry.

Highland games: A benchmarking exercise in predicting biophysical and drug properties of monoclonal antibodies from amino acid sequences.

Biopharmaceutical product and process development do not yet take advantage of predictive computational modeling to nearly the degree seen in industries based on smaller molecules. To assess and advance progress in this area, spirited coopetition (mutually beneficial collaboration between competitors) was successfully used to motivate industrial scientists to develop, share, and compare data and methods which would normally have remained confidential. The first "Highland Games" competition was held in conjunction with the October 2018 Recovery of Biological Products Conference in Ashville, NC, with the goal of benchmarking and assessment of the ability to predict development-related properties of six antibodies from their amino acid sequences alone. Predictions included purification-influencing properties such as isoelectric point and protein A elution pH, and biophysical properties such as stability and viscosity at very high concentrations. Essential contributions were made by a large variety of individuals, including companies which consented to provide antibody amino acid sequences and test materials, volunteers who undertook the preparation and experimental characterization of these materials, and prediction teams who attempted to predict antibody properties from sequence alone. Best practices were identified and shared, and areas in which the community excels at making predictions were identified, as well as areas presenting opportunities for considerable improvement. Predictions of isoelectric point and protein A elution pH were especially good with all-prediction average errors of 0.2 and 1.6 pH unit, respectively, while predictions of some other properties were notably less good. This manuscript presents the events, methods, and results of the competition, and can serve as a tutorial and as a reference for in-house benchmarking by others. Organizations vary in their policies concerning disclosure of methods, but most managements were very cooperative with the Highland Games exercise, and considerable insight into common and best practices is available from the contributed methods. The accumulated data set will serve as a benchmarking tool for further development of in silico prediction tools.

Formation of Ligand Clusters on Multimodal Chromatographic Surfaces.

Multimodal chromatography is a powerful tool which uses multiple modes of interaction, such as charge and hydrophobicity, to purify protein-based therapeutics. In this work, we performed molecular dynamics simulations of a series of multimodal cation-exchange ligands immobilized on a hydrophilic self-assembled monolayer surface at the commercially relevant surface density (1 ligand/nm2). We found that ligands that were flexible and terminated in a hydrophobic group had a propensity to aggregate on the surface, while less flexible ligands containing a hydrophobic group closer to the surface did not aggregate. For aggregating ligands, this resulted in the formation of a surface pattern that contained relatively large patches of hydrophobicity and charge whose sizes exceeded the length scale of the individual ligands. On the other hand, lowering the surface density to 1 ligand/3 nm2 reduced or eliminated this aggregation behavior. In addition, the introduction of a flexible linker (corresponding to the commercially available ligand) enhanced cluster formation and allowed aggregation to occur at lower surface densities. Further, the use of flexible linkers enabled hydrophobic groups to collapse to the surface, reducing their accessibility. Finally, we developed an approach for quantifying differences in the observed surface patterns by calculating distributions of the patch size and patch length. This clustering phenomenon is likely to play a key role in governing protein-surface interactions in multimodal chromatography. This new understanding of multimodal surfaces has important implications for developing improved predictive models and designing new classes of multimodal separation materials.

13C metabolic flux analysis identifies limitations to increasing specific productivity in fed-batch and perfusion.

Industrial cell culture requires substantial energy to generate protein. The protein generated is not only the product of interest (IgG in this case), but also the protein associated with biomass. Here, 13C-Metabolic Flux Analysis (13C-MFA) was utilized to compare the stationary phase of a fed-batch process to a perfusion process producing the same product by the same clone. The fed-batch process achieved significantly higher specific productivity, approximately 60% greater than the perfusion process. In spite of this, a general lack of difference was observed when globally comparing glycolysis, pentose phosphate pathway, and TCA cycle fluxes. In contrast, gross growth rate was significantly different, approximately 80% greater in the perfusion process. This difference was concealed by a significantly greater death rate in the perfusion process, such that net growth rates were both similar and near-zero. When considering gross growth rate and IgG specific productivity, total protein specific productivity (Biomass+ IgG) differed little, offering rationale for the observed central carbon pathway similarities. Significant differences were identified in anaplerotic branched-chain amino acid (BCAA) contributions by 13C-MFA. The perfusion process exhibited markedly higher (up to three times) BCAA catabolism, an observation often associated with increased death.

A step-wise approach to define binding mechanisms of surrogate viral particles to multi-modal anion exchange resin in a single solute system.

Multi-modal anion exchange resins combine properties of both anion exchange and hydrophobic interaction chromatography for commercial protein polishing and may provide some viral clearance as well. From a regulatory viral clearance claim standpoint, it is unclear if multi-modal resins are truly orthogonal to either single-mode anion exchange or hydrophobic interaction columns. To answer this, a strategy of solute surface assays and High Throughput Screening of resin in concert with a scale-down model of large scale chromatography purification was employed to determine the predominant binding mechanisms of a panel of bacteriophage (i.e., PR772, PP7, and ϕX174) to multi-modal and single mode resins under various buffer conditions. The buffer conditions were restricted to buffer environments suggested by the manufacturer for the multi-modal resin. Each phage was examined for estimated net charge expression and relative hydrophobicity using chromatographic based methods. Overall, PP7 and PR772 bound to the multimodal resin via both anionic and hydrophobic moieties, while ϕX174 bound predominantly by the anionic moiety. Biotechnol. Bioeng. 2017;114: 1487-1494. © 2017 Wiley Periodicals, Inc.

High throughput chromatography strategies for potential use in the formal process characterization of a monoclonal antibody.

High throughput experimental strategies are central to the rapid optimization of biologics purification processes. In this work, we extend common high throughput technologies towards the characterization of a multi-column chromatography process for a monoclonal antibody (mAb). Scale-down strategies were first evaluated by comparing breakthrough, retention, and performance (yields and clearance of aggregates and host cell protein) across miniature and lab scale columns. The process operating space was then evaluated using several integrated formats, with batch experimentation to define process testing ranges, miniature columns to evaluate the operating space, and comparison to traditional scale columns to establish scale-up correlations and verify the determined operating space. When compared to an independent characterization study at traditional lab column scale, the high throughput approach identified the same control parameters and similar process sensitivity. Importantly, the high throughput approach significantly decreased time and material needs while improving prediction robustness. Miniature columns and manufacturing scale centerpoint data comparisons support the validity of this approach, making the high throughput strategy an attractive and appropriate scale-down tool for the formal characterization of biotherapeutic processes in the future if regulatory acceptance of the miniature column data can be achieved. Biotechnol. Bioeng. 2016;113: 1273-1283. © 2015 Wiley Periodicals, Inc.

Exploring preferred binding domains of IgG1 mAbs to multimodal adsorbents using a combined biophysics and simulation approach.

In this work, we employ a recently developed biophysical technique that uses diethylpyrocarbonate (DEPC) covalent labeling and mass spectrometry for the identification of mAb binding patches to two multimodal cation exchange resins at different pH. This approach compares the labeling results obtained in the bound and unbound states to identify residues that are sterically shielded and thus located in the mAb binding domains. The results at pH 6 for one mAb (mAb B) indicated that while the complementarity determining region (CDR) had minimal interactions with both resins, the FC domain was actively involved in binding. In contrast, DEPC/MS data with another mAb (mAb C) indicated that both the CDR and FC domains were actively involved in binding. These results corroborated chromatographic retention data with these two mAbs and their fragments and helped to explain the significantly stronger retention of both the intact mAb C and its Fab fragment. In contrast, labeling results with mAb C at pH 7, indicated that only the CDR played a significant role in resin binding, again corroborating chromatographic data. The binding domains identified from the DEPC/MS experiments were also examined using protein surface hydrophobicity maps obtained using a recently developed sparse sampling molecular dynamics (MD) approach in concert with electrostatic potential maps. These results demonstrate that the DEPC covalent labeling/mass spectrometry technique can provide important information about the domain contributions of multidomain proteins such as monoclonal antibodies when interacting with multimodal resins over a range of pH conditions.

Mechanistic model-based characterization of size-exclusion-mixed-mode resins for removal of monoclonal antibody fragments.

Although antibody fragments are a critical impurity to remove from process streams, few platformable purification techniques have been developed to this end. In this work, a novel size-exclusion-mixed-mode (SEMM) resin was characterized with respect to its efficacy in mAb fragment removal. Inverse size-exclusion chromatography showed that the silica-based resin had a narrow pore size distribution and a median pore radius of roughly 6.2 nm. Model-based characterization was carried out with Chromatography Analysis and Design Toolkit (CADET), using the general rate model and the multicomponent Langmuir isotherm. Model parameters were obtained from fitting breakthrough curves, performed at multiple residence times, for a mixture of mAb, aggregates, and an array of fragments (varying in size). Accurate fits were obtained to the frontal chromatographic data across a range of residence times. Model validation was then performed with a scaled-up column, altering residence time and feed composition from the calibration run. Accurate predictions were obtained, thereby illustrating the model's interpolative and extrapolative capabilities. Additionally, the SEMM resin achieved 90% mAb yield, 37% aggregate removal, 29% [Formula: see text] removal, 54% Fab/Fc removal, 100% Fc fragments removal, and a productivity of 72.3 g mAbL×h. Model predictions for these statistics were all within 5%. Simulated batch uptake experiments showed that resin penetration depth was directly related to protein size, with the exception of the aggregate species, and that separation was governed by differential pore diffusion rates. Additional simulations were performed to characterize the dependence of fragment removal on column dimension, load density, and feed composition. Fragment removal was found to be highly dependent on column load density, where optimal purification was achieved below 100 mg protein/mL column. Furthermore, fragment removal was dependent on column volume (constant load mass), but agnostic to whether column length or diameter was changed. Lastly, the dependence on feed composition was shown to be complex. While fragment removal was inversely related to fragment mass fraction in the feed, the extent depended on fragment size. Overall, the results from this study illustrated the efficacy of the SEMM resin in fragment and aggregate removal and elucidated relationships with key operational parameters through model-based characterization.

Mixed-mode size-exclusion silica resin for polishing human antibodies in flow-through mode.

The polishing step in the downstream processing of therapeutic antibodies removes residual impurities from Protein A eluates. Among the various classes of impurities, antibody fragments are especially challenging to remove due to the broad biomolecular diversity generated by a multitude of fragmentation patterns. The current approach to fragment removal relies on ion exchange or mixed-mode adsorbents operated in bind-and-gradient-elution mode. However, fragments that bear strong similarity to the intact product or whose biophysical features deviate from the ensemble average can elude these adsorbents, and the lack of a chromatographic technology enabling robust antibody polishing is recognized as a major gap in downstream bioprocessing. Responding to this challenge, this study introduces size-exclusion mixed-mode (SEMM) silica resins as a novel chromatographic adsorbent for the capture of antibody fragments irrespective of their biomolecular features. The pore diameter of the silica beads features a narrow distribution and is selected to exclude monomeric antibodies, while allowing their fragments to access the pores where they are captured by the mixed-mode ligands. The static and dynamic binding capacity of the adsorbent ranged respectively between 30-45 and 25-33 gs of antibody fragments per liter of resin. Selected SEMM-silica resins also demonstrated the ability to capture antibody aggregates, which adsorb on the outer layer of the beads. Optimization of the SEMM-silica design and operation conditions - namely, pore size (10 nm) and ligand composition (quaternary amine and alkyl chain) as well as the linear velocity (100 cm/h), ionic strength (5.7 mS/cm), and pH (7) of the mobile phase - afforded a significant reduction of both fragments and aggregates, resulting into a final antibody yield up to 80% and monomeric purity above 97%.

Proceedings of the 2019 Viral Clearance Symposium, Session 4: Viral Clearance Strategy and Process Understanding.

This article describes a summary of discussions and outcomes from the 2019 Viral Clearance Symposium Session 4 on the utilization of knowledge, both from within and external to a given organization (e.g., across the interdisciplinary space), that supports viral clearance strategy and process understanding, including engagement with Health Authorities in the development and implementation. Several significant areas were identified for prioritization in an ICHQ5A update including application of next-generation sequencing (NGS) and replacement of in vivo tests, resin reuse, and use of a parvovirus as a single model virus for virus filtration. Specific opportunities were identified based on case studies for application of prior knowledge to support risk assessments, to guide viral clearance study designs, and to support viral clearance claims based on a limited number of confirmatory runs. One discussion focused specifically on how to apply best practices and prior knowledge to an assessment of the potential impact of resin reuse on viral clearance. Prior experience showed a trend toward larger log reduction values (LRVs) with reused protein A resin. For other resins, differences in LRV (>1.0) between new and reused resins were mainly found when validation was performed in independent studies, not side by side. Another example of applying prior knowledge was an assessment of potential variability and worst-case retrovirus-like particle (RVLP) levels in unprocessed bulk presented by Paul-Ehrlich-Institut. The opportunity to utilize noninfectious surrogates for viruses (such as RVLPs or parvovirus-like particles) in screening experiments to determine the impact of process parameters on viral clearance, and the associated current limitations owing to analytics, was also reviewed.

The measurement and control of high-risk host cell proteins for polysorbate degradation in biologics formulation.

Nonionic surfactant polysorbates, including PS-80 and PS-20, are commonly used in the formulation of biotherapeutic products for both preventing surface adsorption and acting as stabilizer against protein aggregation. Trace levels of residual host cell proteins (HCPs) with lipase or esterase enzymatic activity have been shown to degrade polysorbates in biologics formulation. The measurement and control of these low abundance, high-risk HCPs for polysorbate degradation are an industry-wide challenge to achieve desired shelf life of biopharmaceuticals in liquid formulation, especially for high-concentration formulation product development. Here, we reviewed the challenges, recent advances, and future opportunities of analytical method development, risk assessment, and control strategies for polysorbate degradation during formulation development with a focus on enzymatic degradation. Continued efforts to advance our understanding of polysorbate degradation in biologics formulation will help develop high-quality medicines for patients.