Residence time distribution in continuous virus filtration.

Regulatory authorities recommend using residence time distribution (RTD) to address material traceability in continuous manufacturing. Continuous virus filtration is an essential but poorly understood step in biologics manufacturing in respect to fluid dynamics and scale-up. Here we describe a model that considers nonideal mixing and film resistance for RTD prediction in continuous virus filtration, and its experimental validation using the inert tracer NaNO3. The model was successfully calibrated through pulse injection experiments, yielding good agreement between model prediction and experiment ( R 2 > ${R}^{2}\gt $ 0.90). The model enabled the prediction of RTD with variations-for example, in injection volumes, flow rates, tracer concentrations, and filter surface areas-and was validated using stepwise experiments and combined stepwise and pulse injection experiments. All validation experiments achieved R 2 > ${R}^{2}\gt $ 0.97. Notably, if the process includes a porous material-such as a porous chromatography material, ultrafilter, or virus filter-it must be considered whether the molecule size affects the RTD, as tracers with different sizes may penetrate the pore space differently. Calibration of the model with NaNO3 enabled extrapolation to RTD of recombinant antibodies, which will promote significant savings in antibody consumption. This RTD model is ready for further application in end-to-end integrated continuous downstream processes, such as addressing material traceability during continuous virus filtration processes.

Realization of digital twin for dynamic control toward sample variation of ion exchange chromatography in antibody separation.

Digital twin (DT) is a virtual and digital representation of physical objects or processes. In this paper, this concept is applied to dynamic control of the collection window in the ion exchange chromatography (IEC) toward sample variations. A possible structure of a feedforward model-based control DT system was proposed. Initially, a precise IEC mechanistic model was established through experiments, model fitting, and validation. The average root mean square error (RMSE) of fitting and validation was 8.1% and 7.4%, respectively. Then a model-based gradient optimization was performed, resulting in a 70.0% yield with a remarkable 11.2% increase. Subsequently, the DT was established by systematically integrating the model, chromatography system, online high-performance liquid chromatography, and a server computer. The DT was validated under varying load conditions. The results demonstrated that the DT could offer an accurate control with acidic variants proportion and yield difference of less than 2% compared to the offline analysis. The embedding mechanistic model also showed a positive predictive performance with an average RMSE of 11.7% during the DT test under >10% sample variation. Practical scenario tests indicated that tightening the control target could further enhance the DT robustness, achieving over 98% success rate with an average yield of 72.7%. The results demonstrated that the constructed DT could accurately mimic real-world situations and perform an automated and flexible pooling in IEC. Additionally, a detailed methodology for applying DT was summarized.

Downstream processing of virus-like particles with aqueous two-phase systems: Applications and challenges.

The advancement of recombinant virus-like particle-based vaccines has attracted global attention owing to substantially safety and high efficacy in provoking a protective immunity against various chronic and infectious diseases in humans and animals. A robust, low-cost, and scalability separation and purification technology is of utmost importance in the downstream processing of recombinant virus-like particles to produce affordable and safe vaccines. Being a relatively simple, environmentally friendly, and efficient biomolecules recovery approach, aqueous two-phase systems have received great attention from researchers worldwide. This review aims to highlight the challenges and outlook in addition to the current applications of aqueous two-phase systems in downstream processing of virus-like particles. The efforts will confidently reinforce scholars' knowledge and fill in the valuable research gap in the aspect of concerning recombinant virus-like particle-based vaccines development, particularly related to the virus-like particles downstream production processes.

Analysis and optimal design of batch and two-column continuous chromatographic frontal processes for monoclonal antibody purification.

The increasing demand for efficient and robust processes in the purification of monoclonal antibodies (mAbs) has recently brought frontal chromatography to the forefront. Applied during the polishing step, it enables the removal of high molecular weight aggregates from the target product, achieving high purities. Typically, this process is operated in batch using a single column, which makes it intrinsically subjected to a purity-yield tradeoff. This means that high purities can only be achieved at the cost of lowering the product yield and vice versa. Recently, a two-column continuous implementation of frontal chromatography, referred to as Flow2, was developed. Despite being able of alleviating the purity-yield tradeoff typical of batch operations, the increase in the number of process parameters complicates its optimal design, with the risk of not exploiting its full potential. In this study, we developed an ad hoc design procedure (DP) suitable for the optimization of both batch frontal chromatography and Flow2 in terms of purity, yield, and productivity. This procedure provided similar results as a multiobjective optimization based on genetic algorithm but with lower computational effort. Then, batch and Flow2 operated at their optimal conditions were compared. Besides showing a more favorable Pareto front of yield and productivity at a specified purity, the Flow2 process demonstrated improved robustness compared to the batch process with respect to modifications in the loading linear velocity, washing buffer ionic strength and loading time, thus providing an appealing operation for integrated processes.

Process development and optimization of continuous capture with three-column periodic counter-current chromatography.

Continuous capture with affinity chromatography is one of the most important units for continuous manufacturing of monoclonal antibody (mAb). Due to the complexity of three-column periodic counter-current chromatography (3C-PCC), three approaches (experimental, model-based, and simplified approaches) were studied for process development and optimization. The effects of residence time for interconnected load (RT C ), breakthrough percentage of the first column for interconnected load (s) and feed protein concentration (c 0 ) on productivity and capacity utilization were focused. The model-based approach was found superior to the experimental approach in process optimization and evaluation. Two phases of productivity were observed and the optimal RT C for the maximum productivity was located at the boundary of the two phases. The comprehensive effects of the operating parameters (RT C , s, and c 0 ) were evaluated by the model-based approach, and the operation space was predicted. The best performance of 34.5 g/L/h productivity and 97.6% capacity utilization were attained for MabSelect SuRe LX resin under 5 g/L concentration at RT C = 2.8 min and s = 87.5%. Moreover, a simplified approach was suggested to obtain the optimal RT C for the maximum productivity. The results demonstrated that model-assisted tools are useful to determine the optimum conditions for 3C-PCC continuous capture with high productivity and capacity utilization.

A novel dextran-grafted tetrapeptide resin for antibody purification.

Short peptide biomimetic affinity chromatography as a novel antibody separation chromatography is a potential alternative to protein A chromatography. However, if directly attaching ligand to matrix, the adsorption capacity and mass transfer rate would be affected by pore blockage and steric effect. Grafting resin is an effective method to solve this problem by using polymer as a bridge between matrix and ligand. In this work, a novel resin was prepared by grafting a tetrapeptide to the dextran-grafted matrix. Then, the adsorption properties for human immunoglobin G and BSA were determined. The results showed the saturation adsorption capacity could reach to 133 mg/g resin at pH 8.9 with a significantly low dissociation constant (0.03 mg/mL). The influence of flow rates to dynamic binding capacity of this resin was less than that of the non-grafted resin. The separation performance of the resin showed monoclonal antibody could be well isolated from the Chinese hamster ovary culture supernatant at pH 9.0 with the purity of 93.0% and yield of 84.7% by one step. Overall, this resin could achieve higher binding capacity by the possible of gaining higher ligand density, indicating its potential significance for separation in larger scale systems.

Rational design of specific ligands for human serum albumin separation and applications.

Human serum albumin is widely used in clinical practice, and the development of new ligands with high affinity is beneficial to improve its separation efficiency. The Site II of human serum albumin is an active binding site of various molecules such as l-tryptophan, which was studied with molecular simulation to obtain insights for the design of new ligands. The results showed that the carboxyl and indolyl groups of l-tryptophan were critical for the binding on Site II. Seven ligands containing carboxyl groups and indolyl groups were designed, and molecular simulation showed that indole-3-pentanoic acid was the best ligand. A new ligand combined indole-3-acetic acid and cysteine was designed for easier resin preparation, and molecular simulation also indicated that the new ligand bound strongly to Site II. Resins with the new ligand designed was prepared and static adsorption experiments indicated that the new resin had high adsorption capacity of human serum albumin and strong salt tolerance. Finally, recombinant human serum albumin was separated from yeast broth with high purity of 90.4% and recovery of 94.2%, which indicated that the new resin had good adsorption selectivity and strong potential for applications.

Mathematical modelling of expanded bed adsorption - a perspective on in silico process design.

Expanded bed adsorption (EBA) emerged in the early 1990s in an attempt to integrate the clarification, capture and initial product concentration/purification process. Several mathematical models have been put forward to describe its operation. However, none of the models developed specifically for EBA allows simultaneous prediction of bed hydrodynamics, mass transfer/adsorption and (unwanted) interactions and fouling. This currently limits the development and early optimization of EBA-based separation processes. In multiphase reactor engineering, the use of multiphase computational fluid dynamics has been shown to improve fundamental understanding of fluidized beds. To advance EBA technology, a combination of particle, equipment and process scale models should be used. By employing a cascade of multiscale simulations, the various challenges EBA currently faces can be addressed. This allows for optimal design and selection of equipment, materials and process conditions, and reduces risks and development times of downstream processes involving EBA. © 2018 The Authors. Journal of Chemical Technology & Biotechnology published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Poly(glycidyl methacrylate)-grafted hydrophobic charge-induction agarose resins with 5-aminobenzimidazole as a functional ligand.

Hydrophobic charge-induction chromatography is a new technology for antibody purification. To improve antibody adsorption capacity of hydrophobic charge-induction resins, new poly(glycidyl methacrylate)-grafted hydrophobic charge-induction resins with 5-aminobenzimidazole as a functional ligand were prepared. Adsorption isotherms, kinetics, and dynamic binding behaviors of the poly(glycidyl methacrylate)-grafted resins prepared were investigated using human immunoglobulin G as a model protein, and the effects of ligand density were discussed. At the moderate ligand density of 330 µmol/g, the saturated adsorption capacity and equilibrium constant reached the maximum of 140 mg/g and 25 mL/mg, respectively, which were both much higher than that of non-grafted resin with same ligand. In addition, effective pore diffusivity and dynamic binding capacity of human immunoglobulin G onto the poly(glycidyl methacrylate)-grafted resins also reached the maximum at the moderate ligand density of 330 µmol/g. Dynamic binding capacity at 10% breakthrough was as high as 76.3 mg/g when the linear velocity was 300 cm/h. The results indicated that the suitable polymer grafting combined with the control of ligand density would be a powerful tool to improve protein adsorption of resins, and new poly(glycidyl methacrylate)-grafted hydrophobic charge-induction resins have a promising potential for antibody purification applications.

Antibody-ligand interactions for hydrophobic charge-induction chromatography: a surface plasmon resonance study.

This article describes the use of surface plasmon resonance (SPR) spectroscopy to study antibody-ligand interactions for hydrophobic charge-induction chromatography (HCIC) and its versatility in investigating the surface and solution factors affecting the interactions. Two density model surfaces presenting the HCIC ligand (mercapto-ethyl-pyridine, MEP) were prepared on Au using a self-assembly technique. The surface chemistry and structure, ionization, and protein binding of such model surfaces were characterized by X-ray photoelectron spectroscopy (XPS), near-edge X-ray absorption fine structure (NEXAFS), contact-angle titration, and SPR, respectively. The influences of the surface and solution factors, e.g., ligand density, salt concentration, and solution pH, on protein adsorption were determined by SPR. Our results showed that ligand density affects both equilibrium and dynamic aspects of the interactions. Specifically, a dense ligand leads to an increase in binding strength, rapid adsorption, slow desorption, and low specificity. In addition, both hydrophobic interactions and hydrogen bonding contribute significantly to the protein adsorption at neutral pH, while the electrostatic repulsion is overwhelmed under acidic conditions. The hydrophobic interaction at a high concentration of lyotropic salt would cause drastic conformational changes in the adsorbed protein. Combined with the self-assembly technique, SPR proves to be a powerful tool for studying the interactions between an antibody and a chromatographic ligand.

Hydrophobic charge-induction resin with 5-aminobenzimidazol as the functional ligand: preparation, protein adsorption and immunoglobulin G purification.

A new hydrophobic charge-induction chromatography resin was prepared with 5-aminobenzimidazol as functional ligand and polyacrylic ester beads as matrix. Adsorption isotherms and adsorption in columns were investigated using human immunoglobulin G and bovine serum albumin as model proteins, and the influence of pH and NaCl concentration was discussed. Results showed that the ligand density was 195 µmol/mL gel, and protein selectivity can be improved by controlling pH and salt addition. An optimized purification process (sample loading at pH 8.0 with 0.2 M NaCl and elution at pH 5.0) was performed to purify human immunoglobulin G from bovine serum albumin containing feedstock, which resulted in human immunoglobulin G purity of 99.7% and recovery of 94.6%. A similar process was applied for the purification of monoclonal antibody from cell culture supernatant, which showed antibody purity of 94.9% and recovery of 92.5%. The results indicated that the new resin developed had comparable performance as Protein A chromatography and would be suitable for antibody purification from complex feedstock.

Molecular insights into the binding selectivity of a synthetic ligand DAAG to Fc fragment of IgG.

Affinity chromatography with synthetic ligands has been focused as the potential alternative to protein A-based chromatography for antibody capture because of its comparable selectivity and efficiency. Better understanding on the molecular interactions between synthetic ligand and antibody is crucial for improving and designing novel ligands. In this work, the molecular interaction mechanism between Fc fragment of IgG and a synthetic ligand (DAAG) was studied with molecular docking and dynamics simulation. The docking results on the consensus binding site (CBS) indicated that DAAG could bind to the CBS with the favorable orientation like a tripod for the top-ranked binding complexes. The ligand-Fc fragment complexes were then tested by molecular dynamics simulation at neutral condition (pH 7.0) for 10 ns. The results indicated that the binding of DAAG on the CBS of Fc fragment was achieved by the multimodal interactions, combining the hydrophobic interaction, electrostatic interaction, hydrogen bond, and so on. It was also found that multiple secondary interactions endowed DAAG with an excellent selectivity to Fc fragment. In addition, molecular dynamics simulation conducted at acidic condition (pH 3.0) showed that the departure of DAAG ligand from the surface of Fc fragment was the result of reduced interaction energies. The binding modes between DAAG and CBS not only shed light on the molecular mechanisms of DAAG for antibody purification but also provide useful information for the improvement of ligand design.

Molecular recognition of Fc-specific ligands binding onto the consensus binding site of IgG: insights from molecular simulation.

Immunoglobulin G (IgG) plays an important role in clinical diagnosis and therapeutics. Meanwhile, the consensus binding site (CBS) on the Fc domain of IgG is responsible for ligand recognition, especially for Fc-specific ligands. In this study, molecular simulation methods were used to investigate molecular interactions between the CBS of the Fc domain and seven natural Fc-specific ligands. The analysis on the binding energy of the Fc-ligand complex indicated that hydrophobic interactions provide the main driving force for the Fc-ligand binding processes. The hot spots on the ligands and Fc were identified with the computational alanine scanning approach. It was found that the residues of tryptophan and tyrosine on the ligands have significant contributions for the Fc-ligand binding, while Met252, Ile253, Asn434, His435, and Tyr436 are the key residues of Fc. Moreover, two binding modes based on tryptophan or tyrosine were summarized and constructed according to the pairwise interaction analysis. Guidelines for the rational design of CBS-specific ligands with high affinity and specificity were proposed.

Protein adsorption behavior and immunoglobulin separation with a mixed-mode resin based on p-aminohippuric acid.

p-Aminohippuric acid is a newly developed ligand for mixed-mode chromatography with a commercial resin name of Nuvia cPrime. In this study, bovine immunoglobulin G and bovine serum albumin were used as two model proteins, and the adsorption isotherms with Nuvia cPrime were investigated under different pH and salt concentrations. The results showed that pH had a strong but different influence on the adsorption of these two proteins. The adsorption capacity for bovine immunoglobulin G and BSA was 170.4 and 28.1 mg/g at pH 6.0, respectively. Different salts also showed varying effects on the protein adsorption. Moreover, the adsorption and elution behaviors of the two proteins in a column were determined under varying pH and salt concentrations. An optimized process showed that feedstock loaded under pH 6.0 with 0.8 M (NH4)2SO4 and eluted under pH 8.0 with 1.0 M NaCl could effectively purify bovine immunoglobulin G from feedstock containing BSA. The purity of bovine immunoglobulin G could reach 99.8% and the recovery was 92.7%. The results demonstrated that the control of pH and salt addition during the loading and elution processes were two key factors in improving separation efficiency with Nuvia cPrime resin.

Evaluation of a PEG/hydroxypropyl starch aqueous two-phase system for the separation of monoclonal antibodies from cell culture supernatant.

In this study, an aqueous two-phase system (ATPS) with PEG and hydroxypropyl starch (HPS) was used to separate monoclonal antibody (mAb) from Chinese hamster ovary cell culture supernatant. The phase diagram of the PEG/HPS ATPS was determined, and the effects of NaCl addition were investigated. The results showed that NaCl addition could lead to a shift of the binodal curve and that phase separation would occur at higher PEG and HPS concentrations. The effects of NaCl addition, pH, and the load of cell supernatant on the partitioning of mAb in a PEG/HPS ATPS were investigated. It was found that with 6% cell supernatant and 15% NaCl addition at pH 6.0, the yield of mAb in the upper phase was 96.7% with a purity of 96.0%. The back-extraction of mAb with a PEG/phosphate ATPS were also studied, and the results showed that after the two-step extraction with ATPSs the purity of mAb could reach 97.6 ± 0.5% with a yield of 86.8 ± 1.0%, which was comparable to the purification with Protein A chromatography. These results indicate that the two-step extraction with PEG/HPS and PEG/phosphate ATPSs might be a promising alternative for the separation of mAb from cell culture supernatant.

Design of chitosan and its water soluble derivatives-based drug carriers with polyelectrolyte complexes.

Chitosan, the cationic polysaccharide derived from the natural polysaccharide chitin, has been studied as a biomaterial for more than two decades. As a polycationic polymer with favorable properties, it has been widely used to form polyelectrolyte complexes with polyanions for various applications in drug delivery fields. In recent years, a growing number of studies have been focused on the preparation of polyelectrolyte complexes based on chitosan and its water soluble derivatives. They have been considered well-suited as biomaterials for a number of vital drug carriers with targeted/controlled release profiles, e.g., films, capsules, microcapsules. In this work, an overview highlights not only the favorable properties of chitosan and its water soluble derivatives but also the good performance of the polyelectrolyte complexes produced based on chitosan. Their various types of applications as drug carriers are reviewed in detail.

Enhancing thermodynamic consistency: Clarification on the application of asymmetric activity model in multi-component chromatographic separation.

The single-component Mollerup model, with over 40 direct applications and 442 citations, is the most widely used activity model for chromatographic mechanistic modeling. Many researchers have extended this formula to multi-component systems by directly adding subscripts, a modification deemed thermodynamically inconsistent (referred to as the reference model). In this work, we rederived the asymmetric activity model for multi-component systems, using the van der Waals equation of state, and termed it the multi-component Mollerup model. In contrast to the reference model, our proposed model accounts for the contributions of all components to the activity. Three numerical experiments were performed to investigate the impact of the three different activity models on the chromatographic modeling. The results indicate that our proposed model represents a thermodynamically consistent generalization of the single-component Mollerup model to multi-component systems. This communication advocates adopting of the multi-component Mollerup model for activity modeling in multi-component chromatographic separation to enhance thermodynamic consistency.

Parameter-by-parameter estimation method for adsorption isotherm in hydrophobic interaction chromatography.

Hydrophobic interaction chromatography (HIC) is used as a critical polishing step in the downstream processing of biopharmaceuticals. Normally the process development of HIC is a cumbersome and time-consuming task, and the mechanical models can provide a powerful tool to characterize the process, assist process design and accelerate process development. However, the current estimation of model parameters relies on the inverse method, which lacks an efficient and logical parameter estimation strategy. In this study, a parameter-by-parameter (PbP) method based on the theoretical derivation and simplifying assumptions was proposed to estimate the Mollerup isotherm parameters for HIC. The method involves three key steps: (1) linear regression (LR) to estimate the salt-protein interaction parameter and the equilibrium constant; (2) linear approximation (LA) to estimate the stoichiometric parameter and the maximum binding capacity; and (3) inverse method to estimate the protein-protein interaction parameter and the kinetic coefficient. The results indicated that the LR step should be used for dilution condition (loading factor below 5%), while the LA step should be conducted when the isotherm is in the transition or nonlinear regions. Six numerical experiments were conducted to implement the PbP method. The results demonstrated that the PbP method developed allows for the systematic estimation of HIC parameters one-by-one, effectively reducing the number of parameters required for inverse method estimation from six to two. This helps prevent non-identifiability of structural parameters. The feasibility of the PbP-HIC method was further validated by real-world experiments. Moreover, the PbP method enhances the mechanistic understanding of adsorption behavior of HIC and shows a promising application to other stoichiometric displacement model-derived isotherms.

Modeling multi-component separation in hydrophobic interaction chromatography with improved parameter-by-parameter estimation method.

Mechanistic models are powerful tools for chromatographic process development and optimization. However, hydrophobic interaction chromatography (HIC) mechanistic models lack an effective and logical parameter estimation method, especially for multi-component system. In this study, a parameter-by-parameter method for multi-component system (called as mPbP-HIC) was derived based on the retention mechanism to estimate the six parameters of the Mollerup isotherm for HIC. The linear parameters (ks,i and keq,i) and nonlinear parameters (ni and qmax,i) of the isotherm can be estimated by the linear regression (LR) and the linear approximation (LA) steps, respectively. The remaining two parameters (kp,i and kkin,i) are obtained by the inverse method (IM). The proposed method was verified with a two-component model system. The results showed that the model could accurately predict the protein elution at a loading of 10 g/L. However, the elution curve fitting was unsatisfactory for high loadings (12 g/L and 14 g/L), which is mainly attributed to the demanding experimental conditions of the LA step and the potential large estimation error of the parameter qmax. Therefore, the inverse method was introduced to further calibrate the parameter qmax, thereby reducing the estimation error and improving the curve fitting. Moreover, the simplified linear approximation (SLA) was proposed by reasonable assumption, which provides the initial guess of qmax without solving any complex matrix and avoids the problem of matrix unsolvable. In the improved mPbP-HIC method, qmax would be initialized by the SLA and finally determined by the inverse method, and this strategy was named as SLA+IM. The experimental validation showed that the improved mPbP-HIC method has a better curve fitting, and the use of SLA+IM reduces the error accumulation effect. In process optimization, the parameters estimated by the improved mPbP-HIC method provided the model with excellent predictive ability and reasonable extrapolation. In conclusion, the SLA+IM strategy makes the improved mPbP-HIC method more rational and can be easily applied to the practical separation of protein mixture, which would accelerate the process development for HIC in downstream of biopharmaceuticals.

Evaluation of dynamic control of continuous capture with periodic counter-current chromatography under feedstock variations.

Multi-column periodic counter-current chromatography is a promising technology for continuous antibody capture. However, dynamic changes due to disturbances and drifts pose some potential risks for continuous processes during long-term operation. In this study, a model-based approach was used to describe the changes in breakthrough curves with feedstock variations in target proteins and impurities. The performances of continuous capture of three-column periodic counter-current chromatography under ΔUV dynamic control were systematically evaluated with modeling to assess the risks under different feedstock variations. As the concentration of target protein decreased rapidly, the protein might not breakthrough from the first column, resulting in the failure of ΔUV control. Small reductions in the concentrations of target proteins or impurities would cause protein losses, which could be predicted by the modeling. The combination of target protein and impurity variations showed complicated effects on the process performance of continuous capture. A contour map was proposed to describe the comprehensive impacts under different situations, and nonoperation areas could be identified due to control failure or protein loss. With the model-based approach, after the model parameters are estimated from the breakthrough curves, it can rapidly predict the process stability under dynamic control and assess the risks under feedstock variations or UV signal drifts. In conclusion, the model-based approach is a powerful tool for continuous process evaluation under dynamic changes and would be useful for establishing a new real-time dynamic control strategy.