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In the production of antibody‐drug conjugates (ADCs), the conjugation reaction is a central step defining the final product composition and, hence, directly affecting product safety and efficacy. To enable real‐time monitoring, spectroscopic sensors in combination with multivariate regression models have gained popularity in recent years. The extended Kalman filter (EKF) can be used as so‐called soft‐sensor to fuse sensor predictions with long‐horizon forecasts by process models. This enables the dynamic update of the current state and provides increased robustness against experimental noise or model errors. Due to the uncertainty associated with sensor and process models in biopharmaceutical applications, the deployment of such soft‐sensors is challenging. In this study, we demonstrate the combination of an uncertainty‐aware sensor model with a kinetic reaction model using an EKF to monitor a site‐directed ADC conjugation reaction. As the sensor model, a Gaussian process regression model is presented to realize a time‐variant determination of the sensor uncertainty. The EKF fuses the time‐discrete predictions of the amount of conjugated drug from the sensor model with the time‐continuous predictions from the kinetic model. While the ADC species are not distinguishable by on‐line recorded UV/Vis spectra, the developed soft‐sensor is able to dynamically update all relevant reaction species. It could be shown that the use of time‐variant process and sensor noise computation approaches improved the performance of the EKF and achieved a reduction of the prediction error of up to 23% compared with the kinetic model. The developed framework proved to enhance robustness against noisy sensor measurements or wrong model initialization and was successfully transferred from batch to fed‐batch mode. In future, this framework could be implemented for model‐based process control and be adopted for other ADC conjugation reaction types. [ABSTRACT FROM AUTHOR]

The development of biopharmaceutical downstream processes relies on exhaustive experimental studies. The root cause is the poorly understood relationship between the protein structure of monoclonal antibodies (mAbs) and their macroscopic process behavior. Especially the development of preparative chromatography processes is challenged by the increasing structural complexity of novel antibody formats and accelerated development timelines. This study introduces a multiscale in silico model consisting of homology modeling, quantitative structure–property relationships (QSPR), and mechanistic chromatography modeling leading from the amino acid sequence of a mAb to the digital representation of its cation exchange chromatography (CEX) process. The model leverages the mAbs' structural characteristics and experimental data of a diverse set of 21 therapeutic antibodies to predict elution profiles of two mAbs that were removed from the training data set. QSPR modeling identified mAb‐specific protein descriptors relevant for the prediction of the thermodynamic equilibrium and the stoichiometric coefficient of the adsorption reaction. The consideration of two discrete conformational states of IgG4 mAbs enabled prediction of split‐peak elution profiles. Starting from the sequence, the presented multiscale model allows in silico development of chromatography processes before protein material is available for experimental studies. [ABSTRACT FROM AUTHOR]

High‐throughput screening (HTS) approaches are commonly used to accelerate downstream process development. Although most HTS approaches use batch isothermal data (KP screen) or bind and elute mode as screening procedure, different or new process designs are rarely investigated. In this paper, a mechanistic model case study for the separation of two different two‐component solutions was conducted and confirmed prior evidence. With these outcomes, a novel HTS screening procedure was developed including the determination of competitive adsorption‐based displacement effects and key parameter identification. The screening procedure employing an overload bind and elute (OBE) mode is presented in a case study dealing with IgG aggregate removal in a typical monoclonal antibody purification step, applying a Sartobind® S membrane adsorber (MA). Based on a MA scale down device, the OBE mode allows the determination of classical process parameters and dynamic effects, such as displacement effects. Competitive adsorption‐based displacement effects are visualized by introducing a displacement identifier leading to a displacement process map. Based on this map, the approach is transferred to and confirmed by the OBE recycle experiments with 4.6 and 8.2 ml benchtop scsale devices resulting in 45% reduced IgG monomer and 88% increased higher molecular weight species binding capacities. [ABSTRACT FROM AUTHOR]

Virus‐like particles (VLPs) are an emerging biopharmaceutical modality with great potential as a platform technology. VLPs can be applied as gene therapy vectors and prophylactic or therapeutic vaccines. For non‐enveloped VLPs, recombinant production of the protein subunits leads to intracellular self‐assembly. The subsequent purification process includes VLP dis‐ and reassembly which aim at removing encapsulated impurities and improving particle properties. Filtration‐based separation and processing has proven successful for VLPs but requires large product quantities and laborious experiments in early development stages. Both challenges can be tackled by implementation of process analytical technology (PAT) to efficiently obtain extensive process information. In this study, an existing PAT setup was extended to comprehensively monitor the diafiltration‐based disassembly of hepatitis B core antigen (HBcAg) VLPs. Process‐related signals were monitored in‐line, while product‐related signals, such as ultraviolet light (UV) spectra as well as static and dynamic light scattering (SLS and DLS), were monitored on‐line. The applicability of the sensors for disassembly monitoring was evaluated under varying processing conditions. HBcAg VLP subunit concentrations were accurately predicted based on UV data using ordinary and partial least squares regression models (Q2 from 0.909 to 0.976). DLS data were used for aggregation monitoring while the SLS intensity qualitatively reflected the disassembly progress. [ABSTRACT FROM AUTHOR]

In biopharmaceutical process development time, cost and reliability are the relevant keywords. During the development of chromatographic processes these targets are challenged by many possible scaffolds, ligands and process parameters. The common response to this diversity is the establishment of platform processes in the development of chromatographic unit operations. However, while developing a platform library to simplify and accelerate chromatographic processes, the potential combination of scaffold, ligands and process parameters need to be characterized. This challenge is addressed in a case study on novel mixed mode (MM) adsorber for the removal of monoclonal antibody (mAb) aggregates. We propose a rigorous strategy to reduce the various experimental design space resulting from possible combinations in scaffolds, backbones and ligands. This strategy is based on theoretical considerations, identification of adsorber selectivity and capacity for the identification of a suitable membrane system. For this system, each potential MM membrane adsorber candidate is investigated in its high molecular weight species reduction potential for a given mAb feed stream and referenced to the performance of Capto™ Adhere. The introduced strategy can reduce the developmental effort in an early stage from three to two possible stationary phases. Thereafter, initial examinations at different ionic capacities enlighten one favorable stationary phase. Finalizing the development strategy procedure by studying five different MM ligands by HTS and confirming the study with a 2–3 MV higher dynamic breakthrough capacity in benchtop experiments and provides an insight in the benefits of a living process platform library. [ABSTRACT FROM AUTHOR]

Freezing processes are a well‐established unit operation in the biopharmaceutical industry to increase the shelf‐life of protein‐based drugs. While freezing reduces degradation reaction rates, it may also exert stresses such as freeze concentration. Macroscopic freeze concentration in large‐scale freezing processes has been described thoroughly by examination of frozen bulk material, but the transient process leading to such freeze concentration profiles has not been monitored yet for biopharmaceutical solutions. In this study, Raman spectroscopy as a process analytical technology is demonstrated for model formulations containing monoclonal antibodies (mAbs) or bovine serum albumin (BSA) in varying concentrations of sucrose and buffer salts. Therefore, a Raman probe was immersed into a bulk volume at different heights, monitoring the freeze concentration in the liquid phase during the freezing processes. Partial least square regression models were used to quantitatively discriminate between the protein and excipients simultaneously. The freeze concentration profiles were dependend on freezing temperature and formulation with freeze concentrations up to 2.4‐fold. Convection currents at the bottom of the freezing container were observed with a maximum height of 1 mm. Furthermore, freeze concentration was correlated with the sucrose concentration in a formulation. Analysis of the freeze concentration slope indicated diffusion from the bottom to the top of the container. In summary, Raman spectroscopy is a valuable tool for process validation of freeze concentration simulations and to overcome scale‐dependent challenges. [ABSTRACT FROM AUTHOR]

A promising application of Process Analytical Technology to the downstream process of monoclonal antibodies (mAbs) is the monitoring of the Protein A load phase as its control promises economic benefits. Different spectroscopic techniques have been evaluated in literature with regard to the ability to quantify the mAb concentration in the column effluent. Raman and Ultraviolet (UV) spectroscopy are among the most promising techniques. In this study, both were investigated in an in‐line setup and directly compared. The data of each sensor were analyzed independently with Partial‐Least‐Squares (PLS) models and Convolutional Neural Networks (CNNs) for regression. Furthermore, data fusion strategies were investigated by combining both sensors in hierarchical PLS models or in CNNs. Among the tested options, UV spectroscopy alone allowed for the most precise and accurate prediction of the mAb concentration. A Root Mean Square Error of Prediction (RMSEP) of 0.013 g L−1 was reached with the UV‐based PLS model. The Raman‐based PLS model reached an RMSEP of 0.232 g L−1. The different data fusion techniques did not improve the prediction accuracy above the prediction accuracy of the UV‐based PLS model. Data fusion by PLS models seems meritless when combining a very accurate sensor with a less accurate signal. Furthermore, the application of CNNs for UV and Raman spectra did not yield significant improvements in the prediction quality. For the presented application, linear regression techniques seem to be better suited compared with advanced nonlinear regression techniques, like, CNNs. In summary, the results support the application of UV spectroscopy and PLS modeling for future research and development activities aiming to implement spectroscopic real‐time monitoring of the Protein A load phase. [ABSTRACT FROM AUTHOR]

With the quality by design (QbD) initiative, regulatory authorities demand a consistent drug quality originating from a well‐understood manufacturing process. This study demonstrates the application of a previously published mechanistic chromatography model to the in silico process characterization (PCS) of a monoclonal antibody polishing step. The proposed modeling workflow covered the main tasks of traditional PCS studies following the QbD principles, including criticality assessment of 11 process parameters and establishment of their proven acceptable ranges of operation. Analyzing effects of multi‐variate sampling of process parameters on the purification outcome allowed identification of the edge‐of‐failure. Experimental validation of in silico results demanded approximately 75% less experiments compared to a purely wet‐lab based PCS study. Stochastic simulation, considering the measured variances of process parameters and loading material composition, was used to estimate the capability of the process to meet the acceptance criteria for critical quality attributes and key performance indicators. The proposed workflow enables the implementation of digital process twins as QbD tool for improved development of biopharmaceutical manufacturing processes. [ABSTRACT FROM AUTHOR]

Virus‐like particles (VLPs) are particulate structures, which are applied as vaccines or delivery vehicles. VLPs assemble from subunits, named capsomeres, composed of recombinantly expressed viral structural proteins. During downstream processing, in vivo‐assembled VLPs are typically dis‐ and reassembled to remove encapsulated impurities and to improve particle morphology. Disassembly is achieved in a high‐pH solution and by the addition of a denaturant or reducing agent. The optimal disassembly conditions depend on the VLP amino acid sequence and structure, thus requiring material‐consuming disassembly experiments. To this end, we developed a low‐volume and high‐resolution disassembly screening that provides time‐resolved insight into the VLP disassembly progress. In this study, two variants of C‐terminally truncated hepatitis B core antigen were investigated showing different disassembly behaviors. For both VLPs, the best capsomere yield was achieved at moderately high urea concentration and pH. Nonetheless, their disassembly behaviors differed particularly with respect to disassembly rate and aggregation. Based on the high‐throughput screening results, a diafiltration‐based disassembly process step was developed. Compared with mixing‐based disassembly, it resulted in higher yields of up to 0.84 and allowed for integrated purification. This process step was embedded in a filtration‐based process sequence of disassembly, capsomere separation, and reassembly, considerably reducing high‐molecular‐weight species. [ABSTRACT FROM AUTHOR]

Freezing of cell culture supernatant (CCS) is a standard procedure in process development of monoclonal antibody (mAb) platform processes as up‐ and downstream development are usually separated. In the manufacturing process of mAb, however, freezing is avoided, which poses the question of comparability and transferability from process development to manufacturing. In this case study, mAb CCS from Chinese hamster ovary (CHO) cells is frozen and thawed in a novel active freezing device and subsequently captured by protein A chromatography. Critical quality attributes such as host cell protein (HCP) concentration and soluble mAb dimer shares have been monitored throughout the case study. Furthermore, cryo‐concentration of individual proteins was investigated. The main factors that drive cryo‐concentration are diffusion and natural convection. Natural convection in freezing processes was found to increase at warmer freezing temperatures and thus slower freezing, leading to higher concentration gradients from top to bottom of a freezing chamber. The freeze concentration was dependent on protein size and correlated to diffusivity, where smaller proteins are exposed to higher cryo‐concentration. Our results suggest that as a result of freezing processes, large particles based on mAb and specific host cell proteins (HCPs) expressing a certain affinity to mAbs are formed that have to be removed before purification. This leads to a significant improvement in HCP reduction by the protein A step, when compared with reference samples, where twice as much HCP remained in the eluate. Furthermore, HCP and mAb dimer concentrations in protein A eluate were dependent on the freezing temperature. As a conclusion, CCS should be frozen as rapidly as possible during process development to minimize issues of transferability from process development to manufacturing. [ABSTRACT FROM AUTHOR]

A vital part of biopharmaceutical research is decision making around which lead candidate should be progressed in early‐phase development. When multiple antibody candidates show similar biological activity, developability aspects are taken into account to ease the challenges of manufacturing the potential drug candidate. While current strategies for developability assessment mainly focus on drug product stability, only limited information is available on how antibody candidates with minimal differences in their primary structure behave during downstream processing. With increasing time‐to‐market pressure and an abundance of monoclonal antibodies (mAbs) in development pipelines, developability assessments should also consider the ability of mAbs to integrate into the downstream platform. This study investigates the influence of amino acid substitutions in the complementarity‐determining region (CDR) of a full‐length IgG1 mAb on the elution behavior in preparative cation exchange chromatography. Single amino acid substitutions within the investigated mAb resulted in an additional positive charge in the light chain (L) and heavy chain (H) CDR, respectively. The mAb variants showed an increased retention volume in linear gradient elution compared with the wild‐type antibody. Furthermore, the substitution of tryptophan with lysine in the H‐CDR3 increased charge heterogeneity of the product. A multiscale in silico analysis, consisting of homology modeling, protein surface analysis, and mechanistic chromatography modeling increased understanding of the adsorption mechanism. The results reveal the potential effects of lead optimization during antibody drug discovery on downstream processing. [ABSTRACT FROM AUTHOR]

Real‐time monitoring and control of protein A capture steps by process analytical technologies (PATs) promises significant economic benefits due to the improved usage of the column's binding capacity, by eliminating time‐consuming off‐line analytics and costly resin lifetime studies, and enabling continuous production. The PAT method proposed in this study relies on ultraviolet (UV) spectroscopy with a dynamic background subtraction based on the leveling out of the conductivity signal. This point in time can be used to collect a reference spectrum for removing the majority of spectral contributions by process‐related contaminants. The removal of the background spectrum facilitates chemometric model building and model accuracy. To demonstrate the benefits of this method, five different feedstocks from our industry partner were used to mix the load material for a case study. To our knowledge, such a large design space, which covers possible variations in upstream condition besides the product concentration, has not been disclosed yet. By applying the conductivity‐based background subtraction, the root mean square error of prediction (RMSEP) of the partial least squares (PLS) model improved from 0.2080 to 0.0131 g L−1. Finally, the potential of the background subtraction method was further evaluated for single wavelength‐based predictions to facilitate implementation in production processes. An RMSEP of 0.0890 g L−1 with univariate linear regression was achieved, showing that by subtraction of the background better prediction accuracy is achieved then without subtraction and a PLS model. In summary, the developed background subtraction method is versatile, enables accurate prediction results, and is easily implemented into existing chromatography setups with typically already integrated sensors. [ABSTRACT FROM AUTHOR]

Cation exchange chromatography (CEX) is an essential part of most monoclonal antibody (mAb) purification platforms. Process characterization and root cause investigation of chromatographic unit operations are performed using scale down models (SDM). SDM chromatography columns typically have the identical bed height as the respective manufacturing‐scale, but a significantly reduced inner diameter. While SDMs enable process development demanding less material and time, their comparability to manufacturing‐scale can be affected by variability in feed composition, mobile phase and resin properties, or dispersion effects depending on the chromatography system at hand. Mechanistic models can help to close gaps between scales and reduce experimental efforts compared to experimental SDM applications. In this study, a multicomponent steric mass‐action (SMA) adsorption model was applied to the scale‐up of a CEX polishing step. Based on chromatograms and elution pool data ranging from laboratory‐ to manufacturing‐scale, the proposed modeling workflow enabled early identification of differences between scales, for example, system dispersion effects or ionic capacity variability. A multistage model qualification approach was introduced to measure the model quality and to understand the model's limitations across scales. The experimental SDM and the in silico model were qualified against large‐scale data using the identical state of the art equivalence testing procedure. The mechanistic chromatography model avoided limitations of the SDM by capturing effects of bed height, loading density, feed composition, and mobile phase properties. The results demonstrate the applicability of mechanistic chromatography models as a possible alternative to conventional SDM approaches. [ABSTRACT FROM AUTHOR]

In biopharmaceutical process development, resin‐based high throughput screening (HTS) is well known for overcoming experimental limitations by permitting automated parallel processing at miniaturized scale, which results in fast data generation and reduced feed consumption. For membrane adsorber (MA), HTS solutions have so far only been available to a partial extent. Three case studies were performed with the aim of aligning HTS applications for MAs with those established for column chromatography: Process parameter range determination, mechanistic modeling (MM), and scalability. In order to exploit the MA typically features, such as high mass transfer and easy scalability, for scalable high throughput process development, a scale‐down device (SDD) for MA was developed. Its applicability is confirmed for a monoclonal antibody aggregate removal step. The first case study explores the experimental application of the SDD developed. It uses bind and elute mode and variations of pH and salt concentration to obtain process operation windows for ion‐exchange MAs Sartobind® S and Q. In the second case study, we successfully developed a mechanistic model based on parameters obtained from the SDD–HTS setup. The results proved to validate the use of the SDD developed for parameter estimation and thus model‐based process development. The third case study shows the transferability and scalability of data from the SDD–HTS setup using both a direct scale factor and MM. Both approaches show good applicability with a deviation below 20% in the prediction of 10% dynamic breakthrough capacity and reliable scale‐up from 0.42 to 800 ml. [ABSTRACT FROM AUTHOR]

Mechanistic modeling of chromatography processes is one of the most promising techniques for the digitalization of biopharmaceutical process development. Possible applications of chromatography models range from in silico process optimization in early phase development to in silico root cause investigation during manufacturing. Nonetheless, the cumbersome and complex model calibration still decelerates the implementation of mechanistic modeling in industry. Therefore, the industry demands model calibration strategies that ensure adequate model certainty in a limited amount of time. This study introduces a directed and straightforward approach for the calibration of pH‐dependent, multicomponent steric mass action (SMA) isotherm models for industrial applications. In the case investigated, the method was applied to a monoclonal antibody (mAb) polishing step including four protein species. The developed strategy combined well‐established theories of preparative chromatography (e.g. Yamamoto method) and allowed a systematic reduction of unknown model parameters to 7 from initially 32. Model uncertainty was reduced by designing two representative calibration experiments for the inverse estimation of remaining model parameters. Dedicated experiments with aggregate‐enriched load material led to a significant reduction of model uncertainty for the estimates of this low‐concentrated product‐related impurity. The model was validated beyond the operating ranges of the final unit operation, enabling its application to late‐stage downstream process development. With the proposed model calibration strategy, a systematic experimental design is provided, calibration effort is strongly reduced, and local minima are avoided. [ABSTRACT FROM AUTHOR]

Continuous flow systems for chemical synthesis are becoming a major focus in organic chemistry and there is a growing interest in the integration of biocatalysts due to their high regio‐ and stereoselectivity. Methods established for 3D bioprinting enable the fast and simple production of agarose‐based modules for biocatalytic reactors if thermally stable enzymes are available. We report here on the characterization of four different cofactor‐free phenacrylate decarboxylase enzymes suitable for the production of 4‐vinylphenol and test their applicability for the encapsulation and direct 3D printing of disk‐shaped agarose‐based modules that can be used for compartmentalized flow microreactors. Using the most active and stable phenacrylate decarboxylase from Enterobacter spec. in a setup with four parallel reactors and a subsequent palladium(II) acetate‐catalysed Heck reaction, 4‐hydroxystilbene was synthesized from p‐coumaric acid with a total yield of 14.7 % on a milligram scale. We believe that, due to the convenient direct immobilization of any thermostable enzyme and straightforward tuning of the reaction sequence by stacking of modules with different catalytic activities, this simple process will facilitate the establishment and use of cascade reactions and will therefore be of great advantage for many research approaches. [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]

Virus‐like particles (VLPs) have shown great potential as biopharmaceuticals in the market and in clinics. Nonenveloped, in vivo assembled VLPs are typically disassembled and reassembled in vitro to improve particle stability, homogeneity, and immunogenicity. At the industrial scale, cross‐flow filtration (CFF) is the method of choice for performing reassembly by diafiltration. Here, we developed an experimental CFF setup with an on‐line measurement loop for the implementation of process analytical technology (PAT). The measurement loop included an ultraviolet and visible (UV/Vis) spectrometer as well as a light scattering photometer. These sensors allowed for monitoring protein concentration, protein tertiary structure, and protein quaternary structure. The experimental setup was tested with three Hepatitis B core Antigen (HBcAg) variants. With each variant, three reassembly processes were performed at different transmembrane pressures (TMPs). While light scattering provided information on the assembly progress, UV/Vis allowed for monitoring the protein concentration and the rate of VLP assembly based on the microenvironment of Tyrosine‐132. VLP formation was verified by off‐line dynamic light scattering (DLS) and transmission electron microscopy (TEM). Furthermore, the experimental results provided evidence of aggregate‐related assembly inhibition and showed that off‐line size‐exclusion chromatography does not provide a complete picture of the particle content. Finally, a Partial‐Least Squares (PLS) model was calibrated to predict VLP concentrations in the process solution. Q2 values of 0.947–0.984 were reached for the three HBcAg variants. In summary, the proposed experimental setup provides a powerful platform for developing and monitoring VLP reassembly steps by CFF. [ABSTRACT FROM AUTHOR]

Abstract: The compartmentalization of chemical reactions is an essential principle of life that provides a major source of innovation for the development of novel approaches in biocatalysis. To implement spatially controlled biotransformations, rapid manufacturing methods are needed for the production of biocatalysts that can be applied in flow systems. Whereas three‐dimensional (3D) printing techniques offer high‐throughput manufacturing capability, they are usually not compatible with the delicate nature of enzymes, which call for physiological processing parameters. We herein demonstrate the utility of thermostable enzymes in the generation of biocatalytic agarose‐based inks for a simple temperature‐controlled 3D printing process. As examples we utilized an esterase and an alcohol dehydrogenase from thermophilic organisms as well as a decarboxylase that was thermostabilized by directed protein evolution. We used the resulting 3D‐printed parts for a continuous, two‐step sequential biotransformation in a fluidic setup. [ABSTRACT FROM AUTHOR]

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Abstract: BACKGROUND: 3D printing and bioprinting in particular are emerging technologies in the field of biotechnology. The developments of bioprinters and applications lie mostly in the highly observed working fields of tissue engineering and regenerative medicine. Until now only little attention has been paid to the application of 3D bioprinting for the investigation of hydrogel–liquid phase interactions in biotechnological applications. This can mostly be attributed to the need for complex and expensive equipment. RESULTS: In this work, an entry‐level bioprinter on the base of a commercially available Fused‐Filament‐Fabrication 3D printer and an easy to handle user interface was designed. This newly developed bioprinter allowed the structuring of bioinks and hydrogels in microwell plates and even complex models were printed. The applicability of the presented printer setup in the field of biotechnology was shown by the encapsulation of β‐galactosidase (EC 3.2.1.23) in poly(ethylene glycol) diacrylate based hydrogels. Subsequently, an automated screening of the biocatalytic conversion of the substrate ONPG by the encapsulated enzyme was executed on a liquid handling station. Under varied pH conditions in the surrounding liquid phase highest substrate turnover rates were detected at pH 3 and pH 5 which is in good accordance with previously reported pH optima of β‐galactosidase. CONCLUSION: This approach shows an easy access to 3D bioprinting in the field of biotechnology and the implementation of 3D printed hydrogels in high‐throughput experimentation. © 2017 Society of Chemical Industry [ABSTRACT FROM AUTHOR]

The biopharmaceutical industry is at a turning point moving toward a more customized and patient-oriented medicine (precision medicine). Straightforward routines such as the antibody platform process are extended to production processes for a new portfolio of molecules. As a consequence, individual and tailored productions require generic approaches for a fast and dedicated purification process development. In this article, different effective strategies in biopharmaceutical purification process development are reviewed that can analogously be used for the new generation of antibodies. Conventional approaches based on heuristics and high-throughput process development are discussed and compared to modern technologies such as multivariate calibration and mechanistic modeling tools. Such approaches constitute a good foundation for fast and effective process development for new products and processes, but their full potential becomes obvious in a correlated combination. Thus, different combinatorial approaches are presented, which might become future directions in the biopharmaceutical industry. [ABSTRACT FROM AUTHOR]

Lyme disease is the most common tick-borne infectious disease in Europe and North America. Previous studies discovered the immunogenic role of a surface-exposed lipoprotein (VlsE) of Borreliella burgdorferi. We employed high density peptide arrays to investigate the antibody response to the VlsE protein in VlsE-positive patients by mapping the protein as overlapping peptides and subsequent in-depth epitope substitution analyses. These investigations led to the identification of antibody fingerprints represented by a number of key residues that are indispensable for the binding of the respective antibody. This approach allows us to compare the antibody specificities of different patients to the resolution of single amino acids. Our study revealed that the sera of VlsE-positive patients recognize different epitopes on the protein. Remarkably, in those cases where the same epitope is targeted, the antibody fingerprint is almost identical. Furthermore, we could correlate two fingerprints with human autoantigens and an Epstein-Barr virus epitope; yet, the link to autoimmune disorders seems unlikely and must be investigated in further studies. The other three fingerprints are much more specific for B. burgdorferi. Since antibody fingerprints of longer sequences have proven to be highly disease specific, our findings suggest that the fingerprints could function as diagnostic markers that can reduce false positive test results. [ABSTRACT FROM AUTHOR]

In this study, influenza A/Puerto Rico/8/34 H1N1 virus particles (VP) produced in adherent and suspension Madin Darby canine kidney cells were investigated with a broad analytical toolbox to obtain more information on the VP's surface properties potentially affecting their aggregation behavior. First, differences in aggregation behavior were revealed by VP size distributions obtained via differential centrifugal sedimentation and confirmed by dynamic light scattering. The VP produced in adherent cells showed increased levels of aggregation in a 20 mM NaCl 10 mM Tris-HCl pH 7.4 low-salt buffer. This included the formation of multimers (dimers up to pentamers), whereas VP produced in suspension cells displayed no tendency toward aggregate formation. To investigate the cause of these differences in aggregation behavior, the VP samples were compared based on their zeta potential, their surface hydrophobicity, their lipid composition, and the N-glycosylation of their major VP surface protein hemagglutinin. The zeta potential and the hydrophobicity of the VP produced in the adherent cells was significantly decreased compared to the VP produced in the suspension cells. The lipid composition of both VP systems was approximately identical. The hemagglutinin of the VP produced in adherent cells included more of the larger N-glycans, whereas the VP produced in suspension cells included more of the smaller N-glycans. These results indicate that differences in the glycosylation of viral surface proteins should be monitored to characterize VP hydrophobicity and aggregation behavior, and to avoid aggregate formation and product losses in virus purification processes for vaccines and gene therapy. [ABSTRACT FROM AUTHOR]

ABSTRACT The aggregation of proteins became one of the major challenges in the development of biopharmaceu­ticals 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 experi­mental 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 flex­ibility 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 predic­tion 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. [ABSTRACT FROM AUTHOR]

ABSTRACT 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 [ABSTRACT FROM AUTHOR]

ABSTRACT The load phase in preparative Protein A capture steps is commonly not controlled in real-time. The load volume is generally based on an offline quantification of the monoclonal antibody (mAb) prior to loading and on a conservative column capacity determined by resin-life time studies. While this results in a reduced productivity in batch mode, the bottleneck of suitable real-time analytics has to be overcome in order to enable continuous mAb purification. In this study, Partial Least Squares Regression (PLS) modeling on UV/Vis absorption spectra was applied to quantify mAb in the effluent of a Protein A capture step during the load phase. A PLS model based on several breakthrough curves with variable mAb titers in the HCCF was successfully calibrated. The PLS model predicted the mAb concentrations in the effluent of a validation experiment with a root mean square error (RMSE) of 0.06 mg/mL. The information was applied to automatically terminate the load phase, when a product breakthrough of 1.5 mg/mL was reached. In a second part of the study, the sensitivity of the method was further increased by only considering small mAb concentrations in the calibration and by subtracting an impurity background signal. The resulting PLS model exhibited a RMSE of prediction of 0.01 mg/mL and was successfully applied to terminate the load phase, when a product breakthrough of 0.15 mg/mL was achieved. The proposed method has hence potential for the real-time monitoring and control of capture steps at large scale production. This might enhance the resin capacity utilization, eliminate time-consuming offline analytics, and contribute to the realization of continuous processing. Biotechnol. Bioeng. 2017;114: 368-373. © 2016 The Authors. Biotechnology and Bioengineering published by Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

Within the Quality by Design (QbD) framework proposed by the International Conference on Harmonisation (ICH), high-throughput process development (HTPD) and mechanistic modeling are of outstanding importance for future biopharmaceutical chromatography process development. In order to compare the data derived from different column scales or batch chromatographies, the amount of adsorber has to be quantified with the same noninvasive method. Similarly, an important requirement for the implementation of mechanistic modeling is the reliable determination of column characteristics such as the ionic capacity Λ for ion-exchange chromatography with the same method at all scales and formats. We developed a method to determine the ionic capacity in column and batch chromatography, based on the adsorption/desorption of the natural, uv-detectable amino acid histidine. In column chromatography, this method produces results comparable to those of classical acid−base titration. In contrast to acid−base titration, this method can be adapted to robotic batch chromatographic experiments. We are able to convert the adsorber volumes in batch chromatography to the equivalent volume of a compressed column. In a case study, we demonstrate that this method increases the quality of SMA parameters fitted to batch adsorption isotherms, and the capability to predict column breakthrough experiments. © 2016 American Institute of Chemical Engineers Biotechnol. Prog., 32:666-677, 2016 [ABSTRACT FROM AUTHOR]

ABSTRACT This study aims at defining rheological parameters for the characterization of highly concentrated protein solutions. As a basis for comparing rheological behavior with protein solution characteristics the protein phase behavior of Lysozyme from chicken egg white with concentrations up to 225 mg/mL, changing pH values and additive concentrations was studied in a microbatch scale format. The prepared phase diagrams, scored after 40 days ( [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]

The identification of optimal process parameters for the isolation of a target component from multicomponent mixtures is especially challenging in industrial applications. With constantly increasing time-to-market pressure, screening a large parameter space is not feasible and design-of-experiment approaches with few experiments might fail due to dynamic and nonlinear reactions to small parameter changes. Model-based optimization can determine optimal operating conditions, once the model has been calibrated to the specific process step. In this work, parameters for the steric mass action model were estimated for the target protein and three impurities of an industrial antibody cation-exchange purification step using only chromatograms at different wavelengths and additional fraction analyses with size exclusion chromatography. Information on the molar or mass concentrations in the feed are not available. The model-based optimization results coincide with conventional chromatogram-based optimization. [ABSTRACT FROM AUTHOR]

UV absorbance measurements play an important role in bioprocess development. Yield and purity are often evaluated in terms of peak percentages in analytical SEC or ion-exchange chromatography. Also, industrial chromatography steps are usually controlled based on UV data with pooling decisions according to absorbance thresholds. Model-based process development would make elaborate screening experiments redundant, once the model has been calibrated to the specific process step. So far, absorbance measurements could not be used directly for modeling chromatography steps as the commonly applied models rely on mass or molar concentration. This study presents mechanistic modeling of an industrially relevant chromatography setting without any knowledge of the feed composition. The model equations were rewritten to employ boundary conditions in UV absorbance units, the absorption coefficients were shifted into the isotherm, and standard parameter estimation procedures could be applied. An anion-exchange chromatography case study of a target protein expressed in Escherichia coli and 11 lumped impurity peaks demonstrated practical applicability. The target protein concentration in the feed material was estimated from chromatograms. Using this method, initially unknown feed concentrations can be determined a posteriori for ion-exchange and multimodal chromatography from single-component absorbance curves. [ABSTRACT FROM AUTHOR]

ABSTRACT 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. Biotechnol. Bioeng. 2015;112: 2485-2494. © 2015 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

ABSTRACT Upstream processes are rather complex to design and the productivity of cells under suitable cultivation conditions is hard to predict. The method of choice for examining the design space is to execute high-throughput cultivation screenings in micro-scale format. Various predictive in silico models have been developed for many downstream processes, leading to a reduction of time and material costs. This paper presents a combined optimization approach based on high-throughput micro-scale cultivation experiments and chromatography modeling. The overall optimized system must not necessarily be the one with highest product titers, but the one resulting in an overall superior process performance in up- and downstream. The methodology is presented in a case study for the Cherry-tagged enzyme Glutathione-S-Transferase from Escherichia coli SE1. The Cherry-Tag™ (Delphi Genetics, Belgium) which can be fused to any target protein allows for direct product analytics by simple VIS absorption measurements. High-throughput cultivations were carried out in a 48-well format in a BioLector micro-scale cultivation system (m2p-Labs, Germany). The downstream process optimization for a set of randomly picked upstream conditions producing high yields was performed in silico using a chromatography modeling software developed in-house (ChromX). The suggested in silico-optimized operational modes for product capturing were validated subsequently. The overall best system was chosen based on a combination of excellent up- and downstream performance. Biotechnol. Bioeng. 2015;112: 2123-2133. © 2015 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

ABSTRACT 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. Biotechnol. Bioeng. 2015;112: 1406-1416. © 2015 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

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 Biotechnol. Prog., 31:957-973, 2015 [ABSTRACT FROM AUTHOR]

Chromatography is an essential tool for purifying biopharmaceutical products. Many processes are still developed based on traditional routines and empirical procedures. Product losses are mostly due to insufficient optimization of purification setups and product sensitivity to process conditions. In order to eliminate these shortcomings, a systematic strategy for the setup of ion-exchange chromatography is presented, which considers both product stability as well as operational conditions. The stages-a hybrid approach combining high-throughput screening and analytical small-scale chromatography-are as follows: (1) pH stability (short-term); (2) pH stability (long-term), followed by a screening of additives to enhance protein stability, if required; (3) analytical pH gradient chromatography for evaluation of the operational pH window; and (4) salt stability (long-term) in the operational pH window determined. The efficiency and straightforwardness of the strategy were shown in a case study on capturing the human α-galactosidase A enzyme. Following the above procedure, the enzyme was found to be salt-unstable; a purification factor of 13.2, a concentration factor of 4, and an overall yield of 84.3% were achieved. The applied strategy allowed for a quick establishment of a dedicated capture step at low salt concentrations under stable conditions by well-chosen prior screening experiments. [ABSTRACT FROM AUTHOR]

Photoinitiated polymerization in aerosols is employed for the preparation of spherical polymer particles via cationic polymerization. The UV irradiation of aerosol monomer droplets starts the cationic curing process without the employment of any solvent or additives such as stabilizers, resulting in highly pure polymers. Crosslinked polymer spheres with a high gel content are obtained by processing vinyl ether and epoxy monomers via this aerosol-photopolymerization technique, which exhibits great potential for the development of multifunctional materials. [ABSTRACT FROM AUTHOR]

Nanostructured non-spherical (named nanocaps) and spherical porous particles (named mosaic nanoparticles) are generated by aerosol-photopolymerization. Nanocaps exhibit well-defined shapes independent of their diameter and are formed by employing a softening agent and a volatile non-solvent in the formulation, combining non-solvent evaporation and retarded gelation. Mosaic nanoparticles are produced by the addition of a non-volatile non-solvent into the monomer formulation, provoking phase separation. Both particle structures are generated in situ in the presence of zinc oxide nanoparticles. Similarly, they are loaded with caffeine for release experiments and feature potential for applications in emerging technologies such as optics, functionalized coatings and nanomedicine. [ABSTRACT FROM AUTHOR]

Protein phase behavior characterization is a multivariate problem due to the high amount of influencing parameters and the diversity of the proteins. Single influences on the protein are not understood and fundamental knowledge remains to be obtained. For this purpose, a systematic screening method was developed to characterize the influence of fluid phase conditions on the phase behavior of proteins in three-dimensional phase diagrams. This approach was applied to three monoclonal antibodies to investigate influences of pH, protein and salt concentrations, with five different salts being tested. Although differences exist between the antibodies, this extensive study confirmed the general applicability of the Hofmeister series over the broad parameter range analyzed. The influence of the different salts on the aggregation (crystallization and precipitation) probability was described qualitatively using this Hofmeister series, with a differentiation between crystallization and precipitation being impossible, however. © 2014 American Institute of Chemical Engineers Biotechnol. Prog., 30:1103-1113, 2014 [ABSTRACT FROM AUTHOR]

ABSTRACT 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. Biotechnol. Bioeng. 2014;111: 1365-1373. © 2014 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

Lyme borreliosis is the most common tick-borne disease in North America and Europe. A two-test approach (an ELISA followed by immunoblots) for testing current and past infection has been adopted in most countries. However, the heterogeneity of Borrelia antigens (ags) and the semiquantitative character of the immunoblot remain a limitation. By combining a microarray system with cell-free expression, we established a procedure for the expression and subsequent printing of different Borrelia ags onto several multiwell microarray plate surfaces. We successfully expressed and partially purified 11 immunodominant ags of Lyme borreliosis from different Borrelia species in a self-generated Escherichia coli cell-free system. Using sera from patients suffering from Lyme disease and different specific mAbs, proteins could be reproducibly detected on the microarray plates. To confirm the diagnostic outcome of the new assay, a comparison to the same cell-based expressed, purified, and printed Borrelia ags was performed. In summary, this approach serves as a proof of principle for the identification of potential biomarkers and offers the possibility of multiplex protein detection for specific diseases. [ABSTRACT FROM AUTHOR]