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A fundamental understanding of the protein retention mechanism in preparative ion exchange (IEX) chromatography columns is essential for a model-based process development approach. For the past three decades, the mechanistic description of protein retention has been based predominantly on the steric mass action (SMA) model. In recent years, however, retention profiles of proteins have been reported more frequently for preparative processes that are not consistent with the mechanistic understanding relying on the SMA model. In this work, complex elution behavior of proteins in preparative IEX processes is analyzed using a colloidal particle adsorption (CPA) model. The CPA model is found to be capable of reproducing elution profiles that cannot be described by the traditional SMA model. According to the CPA model, the reported complex behavior can be ascribed to a strong compression and concentration of the elution front in the lower unsaturated part of the chromatography column. As the unsaturated part of the column decreases with increasing protein load density, exceeding a critical load density can lead to the formation of a shoulder in the peak front. The general applicability of the model in describing preparative IEX processes is demonstrated using several industrial case studies including multiple monoclonal antibodies on different IEX adsorber systems. In this context, the work covers both salt controlled and pH-controlled protein elution., Competing Interests: Declaration of Competing Interest The authors affiliated to GoSilico declare that the software ChromX used in this study is a commercial product of GoSilico. The presented research does not depend on the usage of ChromX, the model can be implemented in any kind of modeling software., (Copyright © 2021. Published by Elsevier B.V.)

For mechanistic modeling of ion exchange (IEX) processes, a profound understanding of the adsorption mechanism is important. While the description of protein adsorption in IEX processes has been dominated by stoichiometric models like the steric mass action (SMA) model, discrepancies between experimental data and model results suggest that the conceptually simple stoichiometric description of protein adsorption provides not always an accurate representation of nonlinear adsorption behavior. In this work an alternative colloidal particle adsorption (CPA) model is introduced. Based on the colloidal nature of proteins, the CPA model provides a non-stoichiometric description of electrostatic interactions within IEX columns. Steric hindrance at the adsorber surface is considered by hard-body interactions between proteins using the scaled-particle theory. The model's capability of describing nonlinear protein adsorption is demonstrated by simulating adsorption isotherms of a monoclonal antibody (mAb) over a wide range of ionic strength and pH. A comparison of the CPA model with the SMA model shows comparable model results in the linear adsorption range, but significant differences in the nonlinear adsorption range due to the different mechanistic interpretation of steric hindrance in both models. The results suggest that nonlinear adsorption effects can be overestimated by the stoichiometric formalism of the SMA model and are generally better reproduced by the CPA model., Competing Interests: Declaration of Competing Interest The authors affiliated to GoSilico declare that the software ChromX used in this study is a commercial product of GoSilico. The presented research does not depend on the usage of ChromX, the model can be implemented in any kind of modeling software., (Copyright © 2021. Published by Elsevier B.V.)

Imaging is increasingly more utilized as analytical technology in biopharmaceutical formulation research, with applications ranging from subvisible particle characterization to thermal stability screening and residual moisture analysis. This review offers a comprehensive overview of analytical imaging for scientists active in biopharmaceutical formulation research and development, where it presents the unique information provided by the ultraviolet (UV), visible (Vis), and infrared (IR) sections in the electromagnetic spectrum. The main body of this review consists of an outline of UV, Vis, and IR imaging techniques for several (bio)physical properties that are commonly determined during protein-based biopharmaceutical formulation characterization and development studies. The review concludes with a future perspective of applied imaging within the field of biopharmaceutical formulation research., (Copyright © 2021 The Authors. Published by Elsevier B.V. All rights reserved.)

Formulation conditions have a significant influence on the degree of freeze/thaw (FT) stress-induced protein instabilities. Adding cryoprotectants might stabilize the induced FT stress instabilities. However, a simple preservation of protein stability might be insufficient and further methods are necessary. This study aims to evaluate the addition of a heat cycle following FT application as a function of different cryoprotectants with lysozyme as exemplary protein. Sucrose and glycerol were shown to be the most effective cryoprotectants when compared to PEG200 and Tween20. In terms of heat-induced reversibility of aggregates, glycerol showed the best performance followed by sucrose, NaCl and Tween20 systems. The analysis was performed using a novel approach to visualize complex interplays by a clustering and data reduction scheme. In addition, solubility and structural integrity were measured and confirmed the obtained results.

Ultrafiltration/diafiltration (UF/DF) plays an important role in the manufacturing of biopharmaceuticals. Monitoring critical process parameters and quality attributes by process analytical technology (PAT) during those steps can facilitate process development and assure consistent quality in production processes. In this study, a lab-scale cross-flow filtration (CFF) device was equipped with a variable pathlength (VP) ultraviolet and visible (UV/Vis) spectrometer, a light scattering photometer, and a liquid density sensor (microLDS). Based on the measured signals, the protein concentration, buffer exchange, apparent molecular weight, and hydrodynamic radius were monitored. The setup was tested in three case studies. First, lysozyme was used in an UF/DF run to show the comparability of on-line and off-line measurements. The corresponding correlation coefficients exceeded 0.97. Next, urea-induced changes in protein size of glucose oxidase (GOx) were monitored during two DF steps. Here, correlation coefficients were ≥ 0.92 for static light scattering (SLS) and dynamic light scattering (DLS). The correlation coefficient for the protein concentration was 0.82, possibly due to time-dependent protein precipitation. Finally, a case study was conducted with a monoclonal antibody (mAb) to show the full potential of this setup. Again, off-line and on-line measurements were in good agreement with all correlation coefficients exceeding 0.92. The protein concentration could be monitored in-line in a large range from 3 to 120 g L - 1 . A buffer-dependent increase in apparent molecular weight of the mAb was observed during DF, providing interesting supplemental information for process development and stability assessment. In summary, the developed setup provides a powerful testing system for evaluating different UF/DF processes and may be a good starting point to develop process control strategies. Graphical Abstract Piping and instrumentation diagram of the experimental setup and data generated by the different sensors. A VP UV/Vis spectrometer (FlowVPE, yellow) measures the protein concentration. From the data of the light scattering photometer (Zetasizer, green) in the on-line measurement loop, the apparant molecular weight and z-average are calculated. The density sensor (microLDS) measures density and viscosity of the fluid in the on-line loop.

The influence of process parameters during freeze/thaw (FT) operations is essential for the preservation of the protein stability/activity during production and storage processes in the biopharmaceutical industry. Process parameters, such as FT ramps, the final storage time and temperature, affect the occurring FT stress onto the target protein in different ways. FT stress includes cold denaturation, freeze concentration, and ice crystal formation which can result in protein aggregation. To visualize the impact of variations in FT ramps, descriptors such as solubility, phase behavior and crystal morphology were evaluated. The phase diagram-based toolbox in combination with an HTS-compatible cryo-device allowed the identification of suitable ramping schemes during FT operations. It could be clearly shown that rapid operations are needed above the glass transition temperature of the target protein to circumvent precipitation during FT cycles. Finally, a stability index is introduced which allows ranking of the systems investigated.

Mechanistic modeling of protein adsorption has gained increasing importance in the development of ion-exchange (IEX) chromatography processes. The most common adsorption models use a stoichiometric representation of the adsorption process based on the law of mass action. Despite the importance of these models in model-based development, the stoichiometric representation of the adsorption process is not accurate for the description of long-range electrostatic interactions in IEX chromatography, limiting the application and mechanistic extension of these models. In this work an adsorption model is introduced describing the non-stoichiometric electrostatic interaction in IEX chromatography based on the linear Poisson-Boltzmann equation and a simplified colloidal representation of the protein. In contrast to most recent non-stoichiometric models, the introduced model accounts for charge regulation during the adsorption process. Its capability of describing the adsorption equilibrium is demonstrated by simulating partitioning coefficients of multiple proteins on different adsorber systems as a function of ionic strength and pH. Despite model simplifications the physical meaning and predictive value of the model could be preserved. By transferring model parameters of a monoclonal antibody (mAb) from one adsorber system to another, it could be demonstrated that protein parameters are theoretically not only valid on a specific adsorber system but freely transferable to other adsorbers. The predictive value of the mechanistic model on the new adsorber system was highlighted by predicting the elution behavior of charge variants of the mAb., (Copyright © 2019 Elsevier B.V. All rights reserved.)

Identification of long-term stable biopharmaceutical formulations is essential for biopharmaceutical product development. Reduction of the number of long-term storage experiments and a well-defined formulation search space requires knowledge-based formulation screenings and a detailed protein phase behavior understanding. To achieve this, short-term analytical techniques can serve as predictors for long-term protein phase behavior. Protein phase behavior studies that investigate this concept commonly display shortcomings such as limited and small datasets, sample adjustments, or simplistic data analysis. To overcome these shortcomings, 150 unique lysozyme solutions were analyzed using six different short-term analytical techniques. Lysozyme's structural properties, conformational stability, colloidal stability, surface charge, and surface hydrophobicity were obtained directly after formulation preparation. Employing the empirical phase diagram method, this short-term data was correlated to long-term physical stability data obtained during 40 days of storage. Short-term protein properties showed partial correlation to long-term phase behavior. Structural differences, changing surface properties, colloidal stability, and conformation stability as a function of formulation conditions were observed. This study contributes to long-term protein phase behavior research by presenting a systematic, data-dependent, and multidimensional data evaluation workflow to create a comprehensive overview of short-term protein analytics in relation to long-term protein phase behavior., (Copyright © 2019 Elsevier B.V. All rights reserved.)

Solution stability attributes are one of the key parameters within the production and launching phase of new biopharmaceuticals. Instabilities of active biological compounds can reduce the yield of biopharmaceutical productions, and may induce undesired reactions in patients, such as immunogenic rejections. Protein solution stability thus needs to be engineered and monitored throughout production and storage. In contrast to the gold standard of long-term storage experiments applied in industry, novel experimental and in silico molecular dynamics tools for predicting protein solution stability can be applied within several minutes or hours. Here, a rheological approach in combination with molecular dynamics simulations are presented, for determining and predicting long-term phase behavior of highly concentrated protein solutions. A diversity of liquid phase conditions, including salt type, ionic strength, pH and protein concentration are tested in a Glutathione-S-Transferase (GST) case study, in combination with the enzyme with and without solubility-enhancing Cherry-Tag™. The rheological characterization of GST and Cherry-GST solutions enabled a fast and efficient prediction of protein instabilities without the need of long-term protein phase diagrams. Finally, the strong solubility enhancing properties of the Cherry-Tag™ were revealed by investigating protein surface properties in MD simulations. The tag highly altered the overall surface charge and hydrophobicity of GST, making it less accessible to alteration by the chemical surrounding., (Copyright © 2017 Elsevier B.V. All rights reserved.)

In protein chromatography, process variations, such as aging of column or process errors, can result in deviations of the product and impurity levels. Consequently, the process performance described by purity, yield, or production rate may decrease. Based on visual inspection of the UV signal, it is hard to identify the source of the error and almost unfeasible to determine the quantity of deviation. The problem becomes even more pronounced, if multiple root causes of the deviation are interconnected and lead to an observable deviation. In the presented work, a novel method based on the combination of mechanistic chromatography models and the artificial neural networks is suggested to solve this problem. In a case study using a model protein mixture, the determination of deviations in column capacity and elution gradient length was shown. Maximal errors of 1.5% and 4.90% for the prediction of deviation in column capacity and elution gradient length respectively demonstrated the capability of this method for root cause investigation., (Copyright © 2017 The Author(s). Published by Elsevier B.V. All rights reserved.)

The aggregation of proteins became one of the major challenges in the development of biopharmaceu-ticals since the formation of aggregates can affect drug quality and immunogenicity. However, aggregation mechanisms are highly complex and the investigation requires cost, time, and material intensive experi-mental effort. In the present work, the predictive power of protein characteristics for the phase behavior of three different proteins which are very similar in size and structure was studied. In particular, the surface hydrophobicity, zeta potential, and conformational flexibility of human lysozyme, lysozyme from chicken egg white, and α-lactalbumin at pH 3, 5, 7, and 9 were assessed and examined for correlation with experimental stability studies focusing on protein phase behavior induced by sodium chloride and ammonium sulfate. The molecular dynamics (MD) simulation based study of the conformational flexibility without precipitants was able to identify highly flexible protein regions which could be associated to the less regular secondary structure elements and random coiled and terminal regions in particular. Conformational flex-ibility of the entire protein structure and protein surface hydrophobicity could be correlated to differing aggregation propensities among the studied proteins and could be identified to be applicable for predic-tion of protein phase behavior in aqueous solution without precipitants. For prediction of protein phase behavior and aggregation propensity in aqueous solution with precipitants, protein flexibility was further studied in dependency of salt concentration and species by means of human lysozyme. Even though the results of the salt dependent MD simulations could not be shown to be sufficient for prediction of salt depending phase behavior, this study revealed a more pronounced destabilizing effect of ammonium sulfate in comparison to sodium chloride and thus, was found to be in good agreement with theoretical considerations along the Hofmeister series as well as experimentally evaluated phase behavior. Biotechnol. Bioeng. 2017;114: 1170-1183. © 2016 Wiley Periodicals, Inc., (© 2016 Wiley Periodicals, Inc.)

Information about protein-protein interactions provides valuable knowledge about the phase behavior of protein solutions during the biopharmaceutical production process. Up to date it is possible to capture their overall impact by an experimentally determined potential of mean force. For the description of this potential, the second virial coefficient B22, the diffusion interaction parameter kD, the storage modulus G', or the diffusion coefficient D is applied. In silico methods do not only have the potential to predict these parameters, but also to provide deeper understanding of the molecular origin of the protein-protein interactions by correlating the data to the protein's three-dimensional structure. This methodology furthermore allows a lower sample consumption and less experimental effort. Of all in silico methods, QSAR modeling, which correlates the properties of the molecule's structure with the experimental behavior, seems to be particularly suitable for this purpose. To verify this, the study reported here dealt with the determination of a QSAR model for the diffusion coefficient of proteins. This model consisted of diffusion coefficients for six different model proteins at various pH values and NaCl concentrations. The generated QSAR model showed a good correlation between experimental and predicted data with a coefficient of determination R2 = 0.9 and a good predictability for an external test set with R2 = 0.91. The information about the properties affecting protein-protein interactions present in solution was in agreement with experiment and theory. Furthermore, the model was able to give a more detailed picture of the protein properties influencing the diffusion coefficient and the acting protein-protein interactions. Biotechnol. Bioeng. 2017;114: 821-831. © 2016 Wiley Periodicals, Inc., (© 2016 Wiley Periodicals, Inc.)

Mechanistic modeling has been repeatedly successfully applied in process development and control of protein chromatography. For each combination of adsorbate and adsorbent, the mechanistic models have to be calibrated. Some of the model parameters, such as system characteristics, can be determined reliably by applying well-established experimental methods, whereas others cannot be measured directly. In common practice of protein chromatography modeling, these parameters are identified by applying time-consuming methods such as frontal analysis combined with gradient experiments, curve-fitting, or combined Yamamoto approach. For new components in the chromatographic system, these traditional calibration approaches require to be conducted repeatedly. In the presented work, a novel method for the calibration of mechanistic models based on artificial neural network (ANN) modeling was applied. An in silico screening of possible model parameter combinations was performed to generate learning material for the ANN model. Once the ANN model was trained to recognize chromatograms and to respond with the corresponding model parameter set, it was used to calibrate the mechanistic model from measured chromatograms. The ANN model's capability of parameter estimation was tested by predicting gradient elution chromatograms. The time-consuming model parameter estimation process itself could be reduced down to milliseconds. The functionality of the method was successfully demonstrated in a study with the calibration of the transport-dispersive model (TDM) and the stoichiometric displacement model (SDM) for a protein mixture., (Copyright © 2017 The Author(s). Published by Elsevier B.V. All rights reserved.)

A main requirement for the implementation of model-based process development in industry is the capability of the model to predict high protein load densities. The frequently used steric mass action isotherm assumes a thermodynamically ideal system and, hence constant activity coefficients. In this manuscript, an industrial antibody purification problem under high load conditions is considered where this assumption does not hold. The high protein load densities, as commonly applied in industrial downstream processing, may lead to complex elution peak shapes. Using Mollerup's generalized ion-exchange isotherm (GIEX), the observed elution peak shapes could be modeled. To this end, the GIEX isotherm introduced two additional parameters to approximate the asymmetric activity coefficient. The effects of these two parameters on the curvature of the adsorption isotherm and the resulting chromatogram are investigated. It could be shown that they can be determined by inverse peak fitting and conform with the mechanistic demands of model-based process development., (Copyright © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.)

Precipitation of proteins is considered to be an effective purification method for proteins and has proven its potential to replace costly chromatography processes. Besides salts and polyelectrolytes, polymers, such as polyethylene glycol (PEG), are commonly used for precipitation applications under mild conditions. Process development, however, for protein precipitation steps still is based mainly on heuristic approaches and high-throughput experimentation due to a lack of understanding of the underlying mechanisms. In this work we apply quantitative structure-activity relationships (QSARs) to model two parameters, the discontinuity point m* and the β-value, that describe the complete precipitation curve of a protein under defined conditions. The generated QSAR models are sensitive to the protein type, pH, and ionic strength. It was found that the discontinuity point m* is mainly dependent on protein molecular structure properties and electrostatic surface properties, whereas the β-value is influenced by the variance in electrostatics and hydrophobicity on the protein surface. The models for m* and the β-value exhibit a good correlation between observed and predicted data with a coefficient of determination of R 2 ≥0.90 and, hence, are able to accurately predict precipitation curves for proteins. The predictive capabilities were demonstrated for a set of combinations of protein type, pH, and ionic strength not included in the generation of the models and good agreement between predicted and experimental data was achieved., (Copyright © 2016 Elsevier B.V. All rights reserved.)

Mechanistic models are successfully used for protein purification process development as shown for ion-exchange column chromatography (IEX). Modeling and simulation of hydrophobic interaction chromatography (HIC) in the column mode has been seldom reported. As a combination of these two techniques is often encountered in biopharmaceutical purification steps, accurate modeling of protein adsorption in HIC is a core issue for applying holistic model-based process development, especially in the light of the Quality by Design (QbD) approach. In this work, a new mechanistic isotherm model for HIC is derived by consideration of an equilibrium between well-ordered water molecules and bulk-like ordered water molecules on the hydrophobic surfaces of protein and ligand. The model's capability of describing column chromatography experiments is demonstrated with glucose oxidase, bovine serum albumin (BSA), and lysozyme on Capto™ Phenyl (high sub) as model system. After model calibration from chromatograms of bind-and-elute experiments, results were validated with batch isotherms and prediction of further gradient elution chromatograms., (Copyright © 2016 Elsevier B.V. All rights reserved.)

In the biopharmaceutical industry it is mandatory to know and ensure the correct protein phase state as a critical quality attribute in every process step. Unwanted protein precipitation or crystallization can lead to column, pipe or filter blocking. In formulation, the formation of aggregates can even be lethal when injected into the patient. The typical methodology to illustrate protein phase states is the generation of protein phase diagrams. Commonly, protein phase behavior is shown in dependence of protein and precipitant concentration. Despite using high-throughput methods for the generation of phase diagrams, the time necessary to reach equilibrium is the bottleneck. Faster methods to predict protein phase behavior are desirable. In this study, hydrophobic interaction chromatography retention times were correlated to crystal size and form. High-throughput thermal stability measurements (melting and aggregation temperatures), using an Optim(®)2 system, were successfully correlated to glucose isomerase stability. By using hydrophobic interaction chromatography and thermal stability determinations, glucose isomerase conformational and colloidal stability were successfully predicted for different salts in a specific pH range., (Copyright © 2016 Elsevier B.V. All rights reserved.)

PEGylation, i.e. the covalent attachment of chemically activated polyethylene glycol (PEG) to proteins, is a technique commonly used in biopharmaceutical industry to improve protein stability, pharmacokinetics and resistance to proteolytic degradation. Therefore, PEGylation represents a valuable strategy to reduce autocatalysis of biopharmaceutical relevant proteases during production, purification and storage. In case of non-specific random conjugation the existence of more than one accessible binding site results in conjugates which vary in position and number of attached PEG molecules. These conjugates may differ considerably in their physicochemical properties. Optimizing the reaction conditions with respect to the degree of PEGylation (number of linked PEG molecules) using high-throughput screening (HTS) technologies requires a fast and reliable analytical method which allows stopping the reaction at defined times. In this study an analytical protocol for PEGylated proteases is proposed combining preservation of sample composition by trichloroacetic acid (TCA) precipitation with high-throughput capillary gel electrophoresis (HT-CGE). The well-studied protein hen egg-white lysozyme served as a model system for validating the newly developed analytical protocol for 10kDa mPEG-aldehyde conjugates. PEGamer species were purified by chromatographic separation for calibrating the HT-CGE system. In a case study, the serine protease Savinase(®) which is highly sensitive to autocatalysis was randomly modified with 5kDa and 10kDa mPEG-aldehyde and analyzed. Using the presented TCA protocol baseline separation between PEGamer species was achieved allowing for the analysis of heterogeneous PEGamer mixtures while preventing protease autocatalysis., (Copyright © 2016 Elsevier B.V. All rights reserved.)

Microrheological measurements prove to be suitable to identify rheological parameters of biopharmaceutical solutions. These give information about the flow characteristics but also about the interactions and network structures in protein solutions. For the microrheological measurement tracer particles are required. Due to their specific surface characteristic not all are suitable for reliable measurement results in biopharmaceutical systems. In the present work a screening of melamine, PMMA, polystyrene and surface modified polystyrene as tracer particles were investigated at various protein solution conditions. The surface characteristics of the screened tracer particles were evaluated by zeta potential measurements. Furthermore each tracer particle was used to determine the dynamic viscosity of lysozyme solutions by microrheology and compared to a standard. The results indicate that the selection of the tracer particle had a strong impact on the quality of the microrheological measurement dependent on pH and additive type. Surface modified polystyrene was the only tracer particle that yielded good microrheological results for all tested conditions. The study indicated that the electrostatic surface charge of the tracer particle had a minor impact than its hydrophobicity. This characteristic was the crucial surface property that needs to be considered for the selection of a suitable tracer particle to achieve high measurement accuracy., (Copyright © 2016 Elsevier B.V. All rights reserved.)

In chromatographic protein purification, process variations, aging of columns, or processing errors can lead to deviations of the expected elution behavior of product and contaminants and can result in a decreased pool purity or yield. A different elution behavior of all or several involved species leads to a deviating chromatogram. The causes for deviations are however hard to identify by visual inspection and complicate the correction of a problem in the next cycle or batch. To overcome this issue, a tool for root cause investigation in protein chromatography was developed. The tool combines a spectral deconvolution with inverse mechanistic modelling. Mid-UV spectral data and Partial Least Squares Regression were first applied to deconvolute peaks to obtain the individual elution profiles of co-eluting proteins. The individual elution profiles were subsequently used to identify errors in process parameters by curve fitting to a mechanistic chromatography model. The functionality of the tool for root cause investigation was successfully demonstrated in a model protein study with lysozyme, cytochrome c, and ribonuclease A. Deviating chromatograms were generated by deliberately caused errors in the process parameters flow rate and sodium-ion concentration in loading and elution buffer according to a design of experiments. The actual values of the three process parameters and, thus, the causes of the deviations were estimated with errors of less than 4.4%. Consequently, the established tool for root cause investigation is a valuable approach to rapidly identify process variations, aging of columns, or processing errors. This might help to minimize batch rejections or contribute to an increased productivity., (Copyright © 2016 Elsevier B.V. All rights reserved.)

The surface hydrophobicity of a protein is an important factor for its interactions in solution and thus the outcome of its production process. Yet most of the methods are not able to evaluate the influence of these hydrophobic interactions under natural conditions. In the present work we have established a high resolution stalagmometric method for surface tension determination on a liquid handling station, which can cope with accuracy as well as high throughput requirements. Surface tensions could be derived with a low sample consumption (800 μL) and a high reproducibility (<0.1‰ for water) within a reasonable time (3.5 min per sample). This method was used as a non-invasive HTP compatible approach to determine surface tensions of protein solutions dependent on protein content. The protein influence on the solutions' surface tension was correlated to the hydrophobicity of lysozyme, human lysozyme, BSA, and α-lactalbumin. Differences in proteins' hydrophobic character depending on pH and species could be resolved. Within this work we have developed a pH dependent hydrophobicity ranking, which was found to be in good agreement with literature. For the studied pH range of 3-9 lysozyme from chicken egg white was identified to be the most hydrophilic. α-lactalbumin at pH 3 exhibited the most pronounced hydrophobic character. The stalagmometric method occurred to outclass the widely used spectrophotometric method with bromophenol blue sodium salt as it gave reasonable results without restrictions on pH and protein species., (© 2015 Wiley Periodicals, Inc.)

With an increased number of applications in the field of the avidin-biotin technology, the resulting demand for highly-purified protein avidin has drawn our attention to the purification process of avidin that naturally occurs in chicken egg white. The high-throughput process development (HTPD) methodology was exploited, in order to evaluate purification process alternatives to commonly used ion-exchange chromatography. In a high-throughput format, process parameters for aqueous two-phase extraction, selective precipitation with salts and polyethylene glycol, and hydrophobic interaction and mixed-mode column chromatography experiments were performed. The HTPD strategy was complemented by a high-throughput tandem high-performance liquid chromatography assay for protein quantification. Suitable conditions for the separation of avidin from the major impurities ovalbumin, ovomucoid, ovotransferrin, and lysozyme were identified in the screening experiments. By combination of polyethylene glycol precipitation with subsequent resolubilization and separation in a polyethylene glycol/sulfate/sodium chloride two-phase system an avidin purity of 77% was obtained with a yield >90% while at the same time achieving a significant reduction of the process volume. The two-phase extraction and precipitation results were largely confirmed in larger scale with scale-up factors of 230 and 133, respectively. Seamless processing of the avidin enriched bottom phase was found feasible by using mixed-mode chromatography. By gradient elution a final avidin purity of at least 97% and yield >90% was obtained in the elution pool. The presented identification of a new and beneficial alternative for the purification of the high value protein thus represents a successful implementation of HTPD for an industrially relevant purification task., (© 2015 American Institute of Chemical Engineers.)

Pooling decisions in preparative liquid chromatography for protein purification are usually based on univariate UV absorption measurements that are not able to differentiate between product and co-eluting contaminants. This can result in inconsistent pool purities or yields, if there is a batch-to-batch variability of the feedstock. To overcome this analytical bottleneck, a tool for selective inline quantification of co-eluting model proteins using mid-UV absorption spectra and Partial Least Squares Regression (PLS) was presented in a previous study and applied for real-time pooling decisions. In this paper, a process-data-based method for the PLS model calibration will be introduced that allows the application of the tool towards chromatography steps of real-life processes. The process-data-based calibration method uses recorded inline mid-UV absorption spectra that are correlated with offline fraction analytics to calibrate PLS models. In order to generate average spectra from the inline data, a Visual Basic for Application macro was successfully developed. The process-data-based model calibration was established using a ternary model protein system. Afterwards, it was successfully demonstrated in two case studies that the calibration method is applicable towards real-life separation issues. The calibrated PLS models allowed a successful quantification of the co-eluting species in a cation-exchange-based aggregate and fraction removal during the purification of monoclonal antibodies and of co-eluting serum proteins in an anion-exchange-based purification of Cohn supernatant I. Consequently, the presented process-data-based PLS model calibration in combination with the tool for selective inline quantification has a great potential for the monitoring of future chromatography steps and may contribute to manage batch-to-batch variability by real-time pooling decisions., (© 2015 Wiley Periodicals, Inc.)

Hydrophobic interaction chromatography (HIC) is one of the most frequently used purification methods in biopharmaceutical industry. A major drawback of HIC, however, is the rather low dynamic binding capacity (DBC) obtained when compared to e.g. ion exchange chromatography (IEX). The typical purification procedure for HIC includes binding at neutral pH, independently of the proteins nature and isoelectric point. Most approaches to process intensification are based on resin and salt screenings. In this paper a combination of protein solubility data and varying binding pH leads to a clear enhancement of dynamic binding capacity. This is shown for three proteins of acidic, neutral, and alkaline isoelectric points. High-throughput solubility screenings as well as miniaturized and parallelized breakthrough curves on Media Scout RoboColumns (Atoll, Germany) were conducted at pH 3-10 on a fully automated robotic workstation. The screening results show a correlation between the DBC and the operational pH, the protein's isoelectric point and the overall solubility. Also, an inverse relationship of DBC in HIC and the binding kinetics was observed. By changing the operational pH, the DBC could be increased up to 30% compared to the standard purification procedure performed at neutral pH. As structural changes of the protein are reported during HIC processes, the applied samples and the elution fractions were proven not to be irreversibly unfolded., (Copyright © 2015 Elsevier B.V. All rights reserved.)

In downstream processing, the underlying adsorption mechanism of biomolecules to adsorbent material are still subject of extensive research. One approach to more mechanistic understanding is simulating this adsorption process and hereby the possibility to identify the parameters with strongest impact. So far this method was applied with all-atom molecular dynamics simulations of two model proteins on one cation exchanger. In this work we developed a molecular dynamics tool to simulate protein-adsorber interaction for various proteins on an anion exchanger and ran gradient elution experiments to relate the simulation results to experimental data. We were able to show that simulation results yield similar results as experimental data regarding retention behavior as well as binding orientation. We could identify arginines in case of cation exchangers and aspartic acids in case of anion exchangers as major contributors to binding., (Copyright © 2015 Elsevier B.V. All rights reserved.)

Selective quantification of co-eluting proteins in chromatography is usually performed by offline analytics. This is time-consuming and can lead to late detection of irregularities in chromatography processes. To overcome this analytical bottleneck, a methodology for selective protein quantification in multicomponent mixtures by means of spectral data and partial least squares regression was presented in two previous studies. In this paper, a powerful integration of software and chromatography hardware will be introduced that enables the applicability of this methodology for a selective inline quantification of co-eluting proteins in chromatography. A specific setup consisting of a conventional liquid chromatography system, a diode array detector, and a software interface to Matlab® was developed. The established tool for selective inline quantification was successfully applied for a peak deconvolution of a co-eluting ternary protein mixture consisting of lysozyme, ribonuclease A, and cytochrome c on SP Sepharose FF. Compared to common offline analytics based on collected fractions, no loss of information regarding the retention volumes and peak flanks was observed. A comparison between the mass balances of both analytical methods showed, that the inline quantification tool can be applied for a rapid determination of pool yields. Finally, the achieved inline peak deconvolution was successfully applied to make product purity-based real-time pooling decisions. This makes the established tool for selective inline quantification a valuable approach for inline monitoring and control of chromatographic purification steps and just in time reaction on process irregularities., (© 2014 Wiley Periodicals, Inc.)

The accelerating growth of the market for proteins and the growing interest in new, more complex molecules are bringing new challenges to the downstream process development of these proteins. This results in a demand for faster, more cost efficient, and highly understood downstream processes. Screening procedures based on high-throughput methods are widely applied nowadays to develop purification processes for proteins. However, screening highly complex biotechnological feedstocks, such as complete cell lysates containing target proteins often expressed with a low titre, is still very challenging. In this work we demonstrate a multidimensional, analytical screening approach based on pH gradient ion exchange chromatography (IEC), gel electrophoresis and protein identification via mass spectrometry to rationally characterize a biotechnological feedstock for the purpose of purification process development. With this very simple characterization strategy a two-step purification based on consecutive IEC operations was rapidly laid out for the purification of a diagnostic protein from a cell lysate reaching a purity of ∼80%. The target protein was recombinantly produced using an insect cell expression system., (Copyright © 2013 Elsevier B.V. All rights reserved.)

Chromatography is the method of choice for the separation of proteins, at both analytical and preparative scale. Orthogonal purification strategies for industrial use can easily be implemented by combining different modes of adsorption. Nevertheless, with flexibility comes the freedom of choice and optimal conditions for consecutive steps need to be identified in a robust and reproducible fashion. One way to address this issue is the use of mathematical models that allow for an in silico process optimization. Although this has been shown to work, model parameter estimation for complex feedstocks becomes the bottleneck in process development. An integral part of parameter assessment is the accurate measurement of retention times in a series of isocratic or gradient elution experiments. As high-resolution analytics that can differentiate between proteins are often not readily available, pure protein is mandatory for parameter determination. In this work, we present an approach that has the potential to solve this problem. Based on the uniqueness of UV absorption spectra of proteins, we were able to accurately measure retention times in systems of up to four co-eluting compounds. The presented approach is calibration-free, meaning that prior knowledge of pure component absorption spectra is not required. Actually, pure protein spectra can be determined from co-eluting proteins as part of the methodology. The approach was tested for size-exclusion chromatograms of 38 mixtures of co-eluting proteins. Retention times were determined with an average error of 0.6 s (1.6% of average peak width), approximated and measured pure component spectra showed an average coefficient of correlation of 0.992., (Copyright © 2012 Wiley Periodicals, Inc.)

The application of high throughput experimentation (HTE) in protein purification process development has created an analytical bottleneck. Recently, a new label-free and non-invasive methodology for analyzing multicomponent protein mixtures by means of spectral measurements was presented. Analytics based on the methodology was shown to increase analytical throughput for selective protein quantification significantly, however this was only demonstrated for one particular protein combination. In this work, the possibilities and limitations of the analytical method are investigated further. Principal component analysis (PCA) was performed on a broad range of absorption spectra to investigate their common characteristics and differences. The PCA was used both for cluster analysis and to define a measure for spectral similarity. For binary protein combinations, the calibration precision was shown to decrease exponentially with the defined spectral similarity factor. Knowledge of this correlation can be used to determine a priori whether a calibration will be successful or not. Calibration robustness was investigated by applying the analytics to liquid chromatography performed in HTE mode. Further it was shown, that a spectral difference of 0.6% was sufficient to sucessfully preform a spectral based calibration of two IgG1 monoclonals., (Copyright © 2012 Wiley Periodicals, Inc.)

Size exclusion chromatography (SEC) is often applied for characterization of protein-polyethylene glycol (PEG) conjugates regarding the number of attached PEG chains (PEGamers). SEC analysis is advantageous as it is precise, robust, and straightforward to establish. However, most SEC based assays have a maximal throughput of a few samples per hour. We present a strategy to increase analytical throughput based on combining a short column with a fast flow rate, and finally multivariate calibration in order to compensate for the resolution lost in the trade off for speed. Different multivariate approaches were compared and multilinear regression was shown to result in the most precise calibrations. Further, a dynamic calibration approach was developed in order to account for changes in column performance over time. In this way, it was possible to establish a highly precise assay for protein PEGamer quantification with a throughput of 30 samples per hour., (Copyright © 2012 Elsevier B.V. All rights reserved.)

The application of high throughput experimentation (HTE) in protein purification process development has created an analytical bottleneck. Using a new label-free and non-invasive methodology for analyzing multicomponent protein mixtures by means of spectral measurements, we show that the analytical throughput for selective protein quantification can be increased significantly. An analytical assay based on this new methodology was shown to generate very precise results. Further, the assay was successfully applied as analytics for a resin screening performed in HTE mode. The increase in analytical throughput was obtained without decreasing the level of information when compared to analytical chromatography. This proves its potential as a valuable analytical tool in conjugation with high throughput process development (HTPD). Further, fast selective protein quantification can enhance process control in a commercial production environment and, hence, minimize the need for off-line release analysis., (Copyright © 2011 Wiley Periodicals, Inc.)

Current biopharmaceutical manufacturing strongly relies on using purification platform processes, offering harmonization of practices and speed-to-market. However, the ability of such processes to respond quickly to anticipated higher quality and capacity demands is under question. Here, we describe novel approaches for purification process development that incorporate biothermodynamics, modern high throughput experimentation and simulation tools. Such development leads to production platform-specific databases containing thermodynamic protein descriptors of major host cell proteins over a range of experimental conditions. This will pave the way for in silico purification process development, providing better process understanding and the potential to respond quickly to product quality and market demands. Future efforts will focus on improving this field further and enabling more rationale in process development.

A novel two-zone model (TZM) is presented to describe the rate of solute uptake by the stationary phase of a sorption-type chromatography column. The TZM divides the porous stationary-phase particle into an inner protein-free core and an outer protein-containing zone where intraparticle transport is limited by pore diffusion and binding follows Langmuir theory. The TZM and the classic pore-diffusion model (PDM) of chromatography are applied to the prediction of stationary-phase uptake and elution bands within a cellulose-based affinity chromatography column designed to selectively purify proteins genetically labelled with a CBM9 (family 9 cellulose binding module) affinity tag. Under both linear and nonlinear loading conditions, the TZM closely matches rates of protein uptake within the stationary phase particles as measured by confocal laser scanning microscopy, while the PDM deviates from experiment in the linear-binding region. As a result, the TZM is shown to provide improved predictions of product breakthrough, including elution behavior from a bacterial lysate feed.

Diffusion coefficients of proteins in chromatographic media are important parameters for the rational design of stationary phases and purification schemes. In contrast to free diffusion, intraparticle diffusion is hindered by the porous structure of the media. Direct intraparticle diffusion analysis (IDA) is a novel approach for the determination of intraparticle protein diffusion coefficients. IDA is based on the evaluation of spatially and temporally resolved intraparticle concentration profiles. To prevent adsorption and to study diffusion only, the chromatographic media are investigated in underivatized form. With IDA, intraparticle concentration profiles are measured in a microcolumn by confocal laser scanning microscopy (CLSM). From this dynamic data, the diffusion coefficients are determined by parameter estimation, using a spheric diffusion model. The boundary condition is given by the measured protein concentration in the bulk phase. IDA is applied to determine intraparticle diffusion coefficients of seven different proteins in Sepharose 6 FF. The results show excellent congruence of experimental data and simulation results. Moreover, the determined diffusion coefficients lie well within the range of data published in the literature. Given that the material in question allows optical analysis, IDA is a general approach for studying protein diffusion in porous particles and is easily adapted to different proteins, solution conditions and stationary phases.

Confocal laser scanning microscopy (CLSM) is being increasingly used for observing protein uptake in porous chromatography resins. Recent CLSM studies have revealed the possible existence of a nondiffusive protein transport mechanism. Observing protein uptake with CLSM requires labeling the protein with a fluorescent probe. This study examines the effect of the probe identity on the subsequent CLSM adsorption profiles. The adsorption of lysozyme conjugated with different fluorescent probes (Cy5, BODIPY FL, Atto 635, and Atto 520) on SP Sepharose Fast Flow was measured using CLSM and zonal chromatography experiments. Results from zonal chromatography show that the retention time of lysozyme-dye conjugates differ significantly from unlabeled lysozyme. The change in retention of lysozyme upon conjugation with a fluorescent probe is consistent with the difference in net charge between the lysozyme-dye conjugate and unlabeled lysozyme. The adsorption profiles measured by CLSM show significantly different behavior depending upon whether the lysozyme-dye conjugate is retained longer or shorter than the unlabeled lysozyme. These results strongly suggest that the lysozyme concentration overshoot observed in previous CLSM experiments is the result of displacement of weaker binding labeled lysozyme by stronger binding unlabeled lysozyme.

A new experimental set-up for on-line visualization of the intra-particle uptake kinetics during packed bed chromatography has been designed and tested. Confocal laser scanning microscopy was used to analyze the dynamics of protein adsorption to porous stationary phases. In combination with this, a flow cell was developed that could be packed with chromatography media and operated as a fully functional mini-scale chromatography column. Adsorption profiles of single- and two-component mixtures containing BSA and IgG 2a during packed bed cation-exchange chromatography were investigated. The two proteins appear to exhibit different transport characteristics. For BSA a classical "shrinking core" behavior could be detected. The profiles obtained during IgG 2a adsorption point toward a different transport mode, which deviates from the classical pore-diffusion picture. For the two-component system, a superposition of the single-component profiles combined with a classical displacement of the weaker bound protein species was found. The results indicate that depending on the adsorbed protein the uptake can vary tremendously, even for adsorption to the same chromatographic support. It is clearly shown that the new microcolumn allows in situ quantitative investigations of protein adsorption dynamics within a single particle, which adds a new tool to the available methods for characterizing and optimizing protein adsorption chromatography., (Copyright 2002 Wiley Periodicals, Inc.)

Image-based protein phase diagram analysis is key for understanding and exploiting protein phase behavior in the biopharmaceutical field. However, required data analysis has become a notorious time-consuming task since high-throughput screening approaches were implemented. A variety of computational tools have been developed to support analysis, but these tools primarily use end point visible light images. This study investigates the combined effect of end point and time-dependent image features obtained from cross-polarized and ultraviolet light features, supplementary to visible light, on protein phase diagram image classification. In addition, external validation was performed to evaluate the classification algorithm's applicability to support protein phase diagram scoring. The predicted protein phase behavior classes were subsequently used to automatically construct multidimensional protein phase diagrams to prevent image information loss without complicating the used image classification algorithm. Combining end point and time-dependent features from 3 light sources resulted in a balanced accuracy of 86.4 ± 4.3%, which is comparable to or better than more complex classifiers reported in literature. External validation resulted in a correct formulation classification rate of 91.7%. Subsequent automated construction of the multidimensional protein phase diagrams, using predicted classes, allowed visualization of details such as crystallization rate and protein phase behavior type coexistence. [ABSTRACT FROM AUTHOR]

Preparative protein crystallization can possibly replace one or more chromatographic steps in downstream processing. The development of such crystallization processes is demanding: first, promising principal crystallization conditions must be identified; second, details about the process must be defined; and third, the crystals have to be separated from the mother liquor without putting harm of their crystalline integrity. State‐of‐the‐art about these three steps is developing fast by (i) employing new screening methods which are based on fundamental understanding of the interaction of the protein molecules, (ii) application of existing concepts of technical bulk crystallization of small molecules to preparative protein crystallization, and (iii) making available specific gentle separation machinery. [ABSTRACT FROM AUTHOR]

Protein phase diagrams are a tool to investigate the cause and consequence of solution conditions on protein phase behavior. The effects are scored according to aggregation morphologies such as crystals or amorphous precipitates. Solution conditions affect morphologic features, such as crystal size, as well as kinetic features, such as crystal growth time. Commonly used data visualization techniques include individual line graphs or phase diagrams based on symbols. These techniques have limitations in terms of handling large data sets, comprehensiveness or completeness. To eliminate these limitations, morphologic and kinetic features obtained from crystallization images generated with high throughput microbatch experiments have been visualized with radar charts in combination with the empirical phase diagram method. Morphologic features (crystal size, shape, and number, as well as precipitate size) and kinetic features (crystal and precipitate onset and growth time) are extracted for 768 solutions with varying chicken egg white lysozyme concentration, salt type, ionic strength, and pH. Image-based aggregation morphology and kinetic features were compiled into a single and easily interpretable figure, thereby showing that the empirical phase diagram method can support high-throughput crystallization experiments in its data amount as well as its data complexity. [ABSTRACT FROM AUTHOR]

Hydrophobic interaction chromatography (HIC) is one of the most frequently used purification methods in downstream processing of biopharmaceuticals. During HIC, salts are the governing additives contributing to binding strength, binding capacity, and protein solubility in the liquid phase. A relatively recent approach to increase the dynamic binding capacity (DBC) of HIC adsorbers is the use of salt mixtures. By mixing chaotropic with kosmotropic salts, the DBC can strongly be influenced. For salt mixtures with a higher proportion of chaotropic than kosmotropic salt, higher DBCs were achieved compared with single salt approaches. By measuring the surface tensions of the protein salt solutions, the cavity theory-proposed by Melander and Horváth-that higher surface tensions lead to higher DBCs, was found to be invalid for salt mixtures. Aggregation temperatures of lysozyme in the salt mixtures, as a degree of hydrophobic forces, were correlated to the DBCs. Measuring the aggregation temperatures has proven to be a fast analytical methodology to estimate the hydrophobic interactions and thus can be used as a measure for an increase or decrease in the DBCs. © 2016 American Institute of Chemical Engineers Biotechnol. Prog., 32:346-354, 2016 [ABSTRACT FROM AUTHOR]

Abstract: pH gradient protein separations are widely used techniques in the field of protein analytics, of which isoelectric focusing is the most well known application. The chromatographic variant, based on the formation of pH gradients in ion exchange columns is only rarely applied due to the difficulties to form controllable, linear pH gradients over a broad pH range. This work describes a method for the systematic generation of buffer compositions with linear titration curves, resulting in well controllable pH gradients. To generate buffer compositions with linear titration curves an in silico method was successfully developed. With this tool, buffer compositions for pH gradient ion exchange chromatography with pH ranges spanning up to 7.5 pH units were established and successfully validated. Subsequently, the buffer systems were used to characterize the elution behavior of 22 different model proteins in cation and anion exchange pH gradient chromatography. The results of both chromatographic modes as well as isoelectric focusing were compared to describe differences in between the methods. [Copyright &y& Elsevier]

Abstract: Much work has been done to qualify and quantify chromatographic adsorption and transportation mechanisms in different adsorber materials. An important aspect in all studies is the understanding of the binding mechanism between protein and resin on a molecular level in order to optimize processes on the level of adsorber design. We established a method to determine the binding orientation of lysozyme for different materials under various experimental conditions enabling us to observe changes in the mode of adsorption. We varied the protein load of two different adsorber types, Source 15S, a conventional cation exchange resin and EMD Fractogel SO3, a tentacle-type cation exchanger. We found similar preferential binding sites for the interaction between lysozyme and the surface of these adsorbers at low surface coverage, however, the tentacle adsorber exhibited multi-point binding whereas the binding on Source was limited to one binding site only. With increasing protein density on the surface, lysozyme rotates from a space-consuming side-on to a space-saving end-on orientation on Fractogel, explaining a higher maximum binding capacity for Fractogel. This re-orientation could not be observed for Source. [Copyright &y& Elsevier]

The production of modern pharma proteins is one of the most rapid growing fields in biotechnology. The overall development and production is a complex task ranging from strain development and cultivation to the purification and formulation of the drug. Downstream processing, however, still accounts for the major part of production costs. This is mainly due to the high demands on purity and thus safety of the final product and results in processes with a sequence of typically more than 10 unit operations. Consequently, even if each process step would operate at near optimal yield, a very significant amount of product would be lost. The majority of unit operations applied in downstream processing have a long history in the field of chemical and process engineering; nevertheless, mathematical descriptions of the respective processes and the economical large-scale production of modern pharmaceutical products are hampered by the complexity of the biological feedstock, especially the high molecular weight and limited stability of proteins. In order to develop new operational steps as well as a successful overall process, it is thus a necessary prerequisite to develop a deeper understanding of the thermodynamics and physics behind the applied processes as well as the implications for the product. [ABSTRACT FROM AUTHOR]

An experimental study on the interplay of sorbent structure and fluid phase conditions (pH) has been carried out examining adsorption and transport of bovine serum albumin (BSA) and a monoclonal antibody (IgG 2a) on SP Sepharose™ Fast Flow and SP Sepharose™ XL. SP Sepharose™ Fast Flow is characterised by a relatively open pore network, while SP Sepharose™ XL is a composite structure with ligand-carrying dextran chains filling the pore space. Both adsorbents have similar ionic capacity. Protein transport and adsorption profiles were evaluated using confocal laser scanning microscopy. Under all investigated conditions, BSA uptake could be adequately explained by a pore diffusion mechanism. The adsorption profiles obtained for IgG 2a, however, indicated that changes in fluid phase conditions as well as a change in the solid phase structure could result in a more complex uptake mechanism as compared to pore diffusion alone. This mechanism results in a fast transport of proteins into the adsorbent, followed by an overshoot of protein in the center of the sorbent and a setback towards a homogeneous adsorption profile. [Copyright &y& Elsevier]

The impact of different transport mechanism on chromatographic performance was studied by confocal laser scanning microscopy (CLSM) for solutions containing bovine serum albumin (BSA) and monoclonal IgG 2a under different solid- and fluid-phase conditions. During this investigation, a clear influence of the uptake mechanism on the affinity of the respective proteins for the different adsorbents and thus separation performance of the chromatographic process could be observed. For the system SP Sepharose™ Fast Flow at pH 4.5 pore diffusion could be ascribed to be the dominant transport mechanism for both proteins and the adsorption profiles resembled a pattern similar to that described by the ‘shrinking core’ model. Under these conditions a significantly higher affinity towards the adsorbent was found for BSA when compared to IgG 2a. With changing fluid- and solid-phase conditions, however, a change of the transport mode for IgG 2a could be detected. While the exact mechanism is still unresolved it could be concluded that both occurrence and magnitude of the now governing transport mechanism depended on protein properties and interaction with the adsorbent surface. For the system SP Sepharose™ XL at pH 5.0 both parameters leading to the change in IgG 2a uptake were combined resulting in a clear change of the system affinity towards the IgG 2a molecule, while BSA adsorption was restricted to the most outer shell of the sorbent. [Copyright &y& Elsevier]

Redesigning existing food protein formulations is necessary in situations where food authorities propose dose adjustments or removal of currently employed additives. Redesigning formulations involves evaluating substitute additives to obtain similar long-term physical stability as the original formulation. Such formulation screening experiments benefit from comprehensive data visualization, understanding the effects of substitute additives on long-term physical stability, and identification of short-term optimization targets. This work employs empirical phase diagrams to reach these benefits by combining multidimensional long-term protein physical stability data with short-term empirical protein properties. A case study was performed where multidimensional protein phase diagrams (1152 formulations) allowed for identification of stabilizing effects as a result of pH, methionine, sugars, salt, and minimized glycerol content. Corresponding empirical protein property diagrams (144 formulations) resulted in the identification of normalized surface tension as a short-term empirical protein property to reach long-term physical stability presumably similar to the original product, namely via preferential hydration. Additionally, changes in pH and salt were identified as environmental optimization targets to reach stability via repulsive electrostatic forces. This case study shows the applicability of the empirical phase diagram method to rationally perform formulation redesign screenings, while simultaneously expanding knowledge on protein long-term physical stability. Unlabelled Image • Rational high-throughput formulation screening of redesigned food protein formulations • Long-term physical stability data was combined with short-term empirical data. • Stable glycerol-poor and glycerol-free formulations were identified. • Two short-term protein property profiles result in long-term stability. [ABSTRACT FROM AUTHOR]

Fibers are prominent among novel stationary phase supports for preparative chromatography. Several recent studies have highlighted the potential of fiber-based adsorbents for high productivity downstream processing in both batch and continuous mode, but so far the development of these materials and of processes employing these materials has solely been based on experimental data. In this study we assessed whether mechanistic modeling can be performed on fiber-based adsorbents. With a column randomly filled with short cut hydrogel grafted anion exchange fibers, we tested whether tracer, linear gradient elution, and breakthrough data could be reproduced by mechanistic models. Successful modeling was achieved for all of the considered experiments, for both non-retained and retained molecules. For the fibers used in this study the best results were obtained with a transport-dispersive model in combination with a steric mass action isotherm. This approach accurately accounted for the convection and dispersion of non-retained tracers, and the breakthrough and elution behaviors of three different proteins with sizes ranging from 6 to 160 kDa were accurately modeled, with simulation results closely resembling the experimental data. The estimated model parameters were plausible both from their physical meaning, and from an analysis of the underlying model assumptions. Parameters were determined within good confidence levels; the average confidence estimate was below 7% for confidence levels of 95%. This shows that fiber-based adsorbents can be modeled mechanistically, which will be valuable for the future design and evaluation of these novel materials and for the development of processes employing such materials. [ABSTRACT FROM AUTHOR]

Highlights: [•] Using high throughput screening to develop a centrifugal partitioning chromatography process step. [•] Using high throughput screening to develop a precipitation and resolubilization step. [•] Combining aqueous two-phase extraction and precipitation to purify a monoclonal antibody. [•] Using centrifugal partitioning chromatography with citrate-PEG ATPS. [•] Integration into a traditional protein purification process. [Copyright &y& Elsevier]

Highlights: [•] Characterization of complex protein mixtures. [•] Multidimensional analysis applying high-throughput techniques. [•] Estimation of single protein chromatograms from multidimensional analysis. [•] Determination of linear steric-mass action parameters for the single proteins. [•] Retention volume prediction and chromatogram simulation using obtained parameters. [Copyright &y& Elsevier]

Graphical abstract Abstract Knowledge of protein behavior/stability during freeze/thaw (FT) operations is essential for storage and production processes in the biopharmaceutical industry. FT stress involves freeze concentration, cold denaturation, and ice crystals formation which can result in protein aggregation. Therefore, it is important to understand the ongoing FT processes, and the influence of different solution parameters. In order to evaluate the ongoing processes during FT (up to −80°C), phase diagrams with lysozyme from chicken egg white and sodium chloride were generated. Thereby, three different buffer systems with varying buffer substances and ionic strengths at pH 3 and pH 5 were investigated. As indicators for the ongoing FT processes, the phase behavior, crystal morphology and solubility were used. An increased number of cycles led, for example, to the formation of micro crystals, sea urchin crystals – indicating LLPS and/or high supersaturation – and precipitate. Furthermore, the buffer substances had a more distinct influence on the phase behavior and morphology compared to the ionic strength differences. The solubility line itself was only shifted when distinct changes in the phase behavior could be observed. In summary, a tool was developed for using the phase behavior and especially the crystal morphology as indicator for underlying processes during FT operations. [ABSTRACT FROM AUTHOR]