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Multimodal chromatography has emerged as a promising technique for antibody purification, owing to its capacity to selectively capture and separate target molecules. However, the optimization of chromatography parameters remains a challenge due to the intricate nature of protein-ligand interactions. To tackle this issue, efficient predictive tools are essential for the development and optimization of multimodal chromatography processes. In this study, we introduce a methodology that predicts the elution behavior of antibodies in multimodal chromatography based on their amino acid sequences. We analyzed a total of 64 full-length antibodies, including IgG1, IgG4, and IgG-like multispecific formats, which were eluted using linear pH gradients from pH 9.0 to 4.0 on the anionic mixed-mode resin Capto adhere. Homology models were constructed, and 1312 antibody-specific physicochemical descriptors were calculated for each molecule. Our analysis identified six key structural features of the multimodal antibody interaction, which were correlated with the elution behavior, emphasizing the antibody variable region. The results show that our methodology can predict pH gradient elution for a diverse range of antibodies and antibody formats, with a test set R² of 0.898. The developed model can inform process development by predicting initial conditions for multimodal elution, thereby reducing trial and error during process optimization. Furthermore, the model holds the potential to enable an in silico manufacturability assessment by screening target antibodies that adhere to standardized purification conditions. In conclusion, this study highlights the feasibility of using structure-based prediction to enhance antibody purification in the biopharmaceutical industry. This approach can lead to more efficient and cost-effective process development while increasing process understanding., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Author(s). Published by Elsevier B.V. All rights reserved.)

Multimodal chromatography offers an increased selectivity compared to unimodal chromatographic methods and is often employed for challenging separation tasks in industrial downstream processing (DSP). Unfortunately, the implementation of multimodal polishing into a generic downstream platform can be hampered by non-robust platform conditions leading to a time and cost intensive process development. Mechanistic modeling can assist experimental process development but readily applicable and easy to calibrate multimodal chromatography models are lacking. In this work, we present a mechanistic modeling aided approach that paves the way for an accelerated development of anionic mixed-mode chromatography (MMC) for biopharmaceutical purification. A modified multimodal isotherm model was calibrated using only three chromatographic experiments and was employed in the retention prediction of four antibody formats including a Fab, a bispecific, as well as an IgG1 and IgG4 antibody subtype at pH 5.0 and 6.0. The chromatographic experiments were conducted using the anionic mixed-mode resin Capto adhere at industrial relevant process conditions to enable flow through purification. An existing multimodal isotherm model was reduced to hydrophobic interactions in the linear range of the adsorption isotherm and successfully employed in the simulation of six chromatographic experiments per molecule in concert with the transport dispersive model (TDM). The model reduction to only three parameters did prevent structural parameter non-identifiability and enabled an analytical isotherm parameter determination that was further refined by incorporation of size exclusion effects of the selected multimodal resin. During the model calibration, three linear salt gradient elution experiments were performed for each molecule followed by an isotherm parameter uncertainty assessment. Lastly, each model was validated with a set of step and isocratic elution experiments. This standardized modeling approach facilitates the implementation of multimodal chromatography as a key unit operation for the biopharmaceutical downstream platform, while increasing the mechanistic insight to the multimodal adsorption behavior of complex biologics., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier B.V. All rights reserved.)

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., (© 2022 The Authors. Biotechnology and Bioengineering published by Wiley Periodicals LLC.)

High-throughput screening (HTS) approaches are commonly used to accelerate downstream process development. Although most HTS approaches use batch isothermal data (K P 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., (© 2021 International Union of Biochemistry and Molecular Biology, Inc.)

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., (© 2021 American Institute of Chemical Engineers.)

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., (© 2021 The Authors. Biotechnology and Bioengineering published by Wiley Periodicals LLC.)

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.)

Cation exchange chromatography (CEX) is a widely used technique for the removal of monoclonal antibody (mAb) aggregates. At present, resins are mainly used for this purpose, as convective types of adsorbents such as membrane adsorbers (MAs) have often not demonstrated overall comparable performance for this particular application. Fiber-based adsorbents can overcome the current limitations of MAs with respect to permeability, binding capacity, and adsorbent cost, and could therefore be a viable alternative to resins for the removal of mAb aggregates. It has not been evaluated, however, whether and under which conditions the use of such adsorbents is feasible for this purpose. In the present study, the use of fiber-based CEX adsorbents for mAb aggregate removal was examined. Two types of fiber-based adsorbents, an uncontrolled grafted and a controlled grafted fiber-based adsorbent, were evaluated with respect to permeability, dynamic mAb binding capacity (DBC), resolution capabilities, and the performance in bind and elute (B/E) and frontal chromatography mode with respect to typical performance indicators. The permeabilities of the fiber-based adsorbents ranged from 200 to 1700 mD, making it possible to use the fiber-based adsorbents at larger bed heights than membrane adsorbers with fast mobile phase velocities. Antibody DBCs ranged from 20 to 41 g/L at 150 cm/h, and at higher mobile phase velocities exceeded the DBC of an existing resin material, Poros 50 HS, which has frequently been used for aggregate removal. Both fiber types showed good resolution capabilities of monomer and aggregates, and provided better resolution per column length than Poros 50 HS. Typical purity and yield constraints were fulfilled for both fiber types in both B/E and frontal chromatography mode for mobile phase velocities ranging up to 480 cm/h and 1060 cm/h. The overall performance of the controlled grafted fibers was found to be superior to the performance of uncontrolled grafted fiber-based adsorbents due to higher productivity and lower buffer consumption. The overall performance of the fiber-based adsorbents was found to be comparable to the performance of Poros 50 HS at typical operating conditions. The results in this study indicate that the use of fiber-based adsorbents for mAb aggregate removal is feasible with a performance that is comparable to the performance of an existing resin material. Depending on the cost of the adsorbents and the use scenario, the usage of such adsorbents could be beneficial., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 Elsevier B.V. All rights reserved.)

There has been a growing interest in fibers and fiber-based adsorbents as alternative adsorbents for preparative chromatography. While the benefits of fiber-based adsorbents in terms of productivity have been highlighted in several recent studies, microscale tools that enable a fast characterization of these novel adsorbents, and an easy integration into process development workflows, are still lacking. In the present study an automated high-throughput screening (HTS) for fiber-based adsorbents was established on a robotic liquid handling station in 96 well filter plates. Two techniques - punching and weighing - were identified as techniques that enabled accurate and reproducible portioning of short-cut fiber-based adsorbents. The impact of several screening parameters such as phase ratio, shaking frequency, and incubation time were investigated and optimized for different types of fiber-based adsorbents. The data from the developed HTS correlated with data from packed fiber columns, and binding capacities from both scales matched closely. Subsequently, the developed HTS was utilized to optimize the hydrogel architecture of anion exchange (AEX) fiber-based adsorbent prototypes. A novel AEX fiber-based adsorbent was developed that compared favorably with existing resin and membrane adsorbents in terms of productivity and DNA binding capacity. In addition, the developed HTS was also successfully employed in order to identify step elution conditions for the purification of a monoclonal antibody from product- and process-related impurities with a cation exchange (CEX) fiber-based adsorbent. Trends from the HTS were found to be in good agreement with trends from lab scale column runs. The tool developed in this paper will enable a faster and more complete characterization of fiber-based adsorbents, easier tailoring of such adsorbents towards specific process applications, and an easier integration of such materials into processes. In comparison to previous lab scale experiments, material requirements are reduced by a factor of 3-40 and time requirements are reduced by a factor of 2-5., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 Elsevier B.V. All rights reserved.)

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., (© 2021 The Authors. Biotechnology and Bioengineering published by Wiley Periodicals LLC.)

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., (© 2020 The Authors. Biotechnology Progress published by Wiley Periodicals LLC on behalf of American Institute of Chemical Engineers.)

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., (© 2020 American Institute of Chemical Engineers.)

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., (© 2020 American Institute of Chemical Engineers.)

Antibody-drug conjugates (ADCs) are hybrid molecules based on monoclonal antibodies (mAbs) with covalently attached cytotoxic small-molecule drugs. Due to their potential for targeted cancer therapy, they form part of the diversifying pipeline of various biopharmaceutical companies, in addition to currently seven commercial ADCs. With other new modalities, ADCs contribute to the increasing complexity of biopharmaceutical development in times of growing costs and competition. Another challenge is the implementation of quality by design (QbD), which receives a lot of attention. In order to answer these challenges, mechanistic models are gaining interest as tools for enhanced process understanding and efficient process development. The drug-to-antibody ratio (DAR) is a critical quality attribute (CQA) of ADCs. After the conjugation reaction, the DAR can still be adjusted by including a hydrophobic interaction chromatography (HIC) step. In this work, we developed a mechanistic model for the preparative separation of cysteine-engineered mAbs with different degrees of conjugation with a non-toxic surrogate drug. The model was successfully validated for varying load compositions with linear and optimized step gradient runs, applying conditions differing from the calibration runs. In two in silico studies, we then present scenarios for how the model can be applied profitably to ensure a more robust achievement of the target DAR and for the efficient characterization of the design space. For this, we also used the model in a linkage study with a kinetic reaction model developed by us previously. The combination of the two models effectively widens system boundaries over two adjacent process steps. We believe this work has great potential to help advance the incorporation of digital tools based on mechanistic models in ADC process development by illustrating their capabilities for efficient process development and increased robustness. Mechanistic models can support the implementation of QbD and eventually might be the basis for digital process twins able to represent multiple unit operations., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Preparative protein precipitation is known as a cost-efficient and easy-to-use alternative to chromatographic purification steps. This said, at the moment, there is no process for monoclonal antibodies (mAb) on the market, although especially polyethylene glycol-induced precipitation has shown great potential. One reason might be the highly complex behavior of each component of a crude feedstock during the precipitation process. For different investigated mAbs, significant variations in the host cell protein (HCP) reduction are observed. In contrast to the precipitation behavior of single components, the interactions and interplay in a complex feedstock are not fully understood yet. This work discusses the influence of contaminants on the precipitation behavior of two different mAbs, an IgG1, and an IgG2. By spiking the mAbs with mock solution, a complex feedstock could successfully be mimicked. Spiking contaminants influenced the yield and purity of the mAbs after the precipitation step, compared to the precipitation behavior of the single components. The mixture showed a decrease in the contaminant and mAb solubility. By re-buffering the mock solution prior to spiking, special salts, small molecules like amino acids, vitamins, or sugars could be depleted while larger ones like HCP or DNA were still present. Therefore, it was possible to distinguish the influence of small molecules and larger ones. Hence, mAb-macromolecular interaction could be identified as a possible reason for the observed higher precipitation propensity, while small molecules of the cell culture medium were identified as solubilisation factors during the precipitation process.

For the purification of biopharmaceutical proteins, liquid chromatography is still the gold standard. Especially with increasing product titers, drawbacks like slow volumetric throughput and high resin costs lead to an intensifying need for alternative technologies. Selective preparative protein precipitation is one promising alternative technique. Although the capability has been proven, there has been no precipitation process realized for large-scale monoclonal antibody (mAb) production yet. One reason might be that the mechanism behind protein phase behavior is not completely understood and the precipitation process development is still empirical. Mechanistic modeling can be a means for faster, material-saving process development and a better process understanding at the same time. In preparative chromatography, mechanistic modeling was successfully shown for a variety of applications. Lately, a new isotherm for hydrophobic interaction chromatography (HIC) under consideration of water molecules as participants was proposed, enabling an accurate description of HIC. In this work, based on similarities between protein precipitation and HIC, a new precipitation model was derived. In the proposed model, the formation of protein-protein interfaces is thought to be driven by hydrophobic effects, involving a reorganization of the well-ordered water structure on the hydrophobic surfaces of the protein-protein complex. To demonstrate model capability, high-throughput precipitation experiments with pure or prior to the experiments purified proteins lysozyme, myoglobin, bovine serum albumin, and one mAb were conducted at various pH values. Polyethylene glycol (PEG) 6000 was used as precipitant. The precipitant concentration as well as the initial protein concentration was varied systematically. For all investigated proteins, the initial protein concentrations were varied between 1.5 mg/mL and 12 mg/mL. The calibrated models were successfully validated with experimental data. This mechanistic description of protein precipitation process offers mathematical explanation of the precipitation behavior of proteins at PEG concentration, protein concentration, protein size, and pH.

The conjugation reaction of monoclonal antibodies (mAbs) with small-molecule drugs is a central step during production of antibody-drug conjugates (ADCs). The ability to monitor this step in real time can be advantageous for process understanding and control. Here, we propose a method based on UV/Vis spectroscopy in conjunction with partial least squares (PLS) regression for non-invasive monitoring of conjugation reactions. In experiments, the method was applied to conjugation reactions with two surrogate drugs in microplate format as well as at 20 ml scale. All calibrated PLS models performed well in cross-validation (Q 2 >0.975 for all models). In microplate format, the PLS models were furthermore successfully validated with an independent prediction set (R pred 2 =0.9770 resp. 0.8940). In summary, the proposed method provides a quick and easily implementable tool for reaction monitoring of ADC conjugation reactions and may in the future support the implementation of Process Analytical Technologies (PAT)., (Copyright © 2018 Elsevier B.V. All rights reserved.)

Antibody-drug conjugates (ADCs) form a rapidly growing class of biopharmaceuticals which attracts a lot of attention throughout the industry due to its high potential for cancer therapy. They combine the specificity of a monoclonal antibody (mAb) and the cell-killing capacity of highly cytotoxic small molecule drugs. Site-specific conjugation approaches involve a multi-step process for covalent linkage of antibody and drug via a linker. Despite the range of parameters that have to be investigated, high-throughput methods are scarcely used so far in ADC development. In this work an automated high-throughput platform for a site-specific multi-step conjugation process on a liquid-handling station is presented by use of a model conjugation system. A high-throughput solid-phase buffer exchange was successfully incorporated for reagent removal by utilization of a batch cation exchange step. To ensure accurate screening of conjugation parameters, an intermediate UV/Vis-based concentration determination was established including feedback to the process. For conjugate characterization, a high-throughput compatible reversed-phase chromatography method with a runtime of 7 min and no sample preparation was developed. Two case studies illustrate the efficient use for mapping the operating space of a conjugation process. Due to the degree of automation and parallelization, the platform is capable of significantly reducing process development efforts and material demands and shorten development timelines for antibody-drug conjugates., (Copyright © 2018 Elsevier B.V. All rights reserved.)

In the past decades, research was carried out to find cost-efficient alternatives to Protein A chromatography as a capture step in monoclonal antibody (mAb) purification processes. In this work, polyethylene glycol (PEG) precipitation has shown promising results in the case of mAb yield and purity. Especially with respect to continuous processing, PEG precipitation has many advantages, like low cost of goods, simple setup, easy scalability, and the option to handle perfusion reactors. Nevertheless, replacing Protein A has the disadvantage of renouncing a platform unit operation as well. Furthermore, PEG precipitation is not capable of reducing high molecular weight impurities (HMW) like aggregates or DNA. To overcome these challenges, an integrated process strategy combining PEG precipitation with cation-exchange chromatography (CEX) for purification of a mAb is presented. This work discusses the process strategy as well as the associated fast, easy, and material-saving process development platform. These were implemented through the combination of high-throughput methods with empirical and mechanistic modeling. The strategy allows the development of a common batch process. Additionally, it is feasible to develop a continuous process. In the presented case study, a mAb provided from cell culture fluid (HCCF) was purified. The precipitation and resolubilization conditions as well as the chromatography method were optimized, and the mutual influence of all steps was investigated. A mAb yield of over 95.0% and a host cell protein (HCP) reduction of over 99.0% could be shown. At the same time, the aggregate level was reduced from 3.12% to 1.20% and the DNA level was reduced by five orders of magnitude. Furthermore, the mAb was concentrated three times to a final concentration of 11.9mg/mL., (Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.)

High protein titers are gaining importance in biopharmaceutical industry. A major challenge in the development of highly concentrated mAb solutions is their long-term stability and often incalculable viscosity. The complexity of the molecule itself, as well as the various molecular interactions, make it difficult to describe their solution behavior. To study the formulation stability, long- and short-range interactions and the formation of complex network structures have to be taken into account. For a better understanding of highly concentrated solutions, we combined established and novel analytical tools to characterize the effect of solution properties on the stability of highly concentrated mAb formulations. In this study, monoclonal antibody solutions in a concentration range of 50-200 mg/ml at pH 5-9 with and without glycine, PEG4000, and Na 2 SO 4 were analyzed. To determine the monomer content, analytical size-exclusion chromatography runs were performed. ζ-potential measurements were conducted to analyze the electrophoretic properties in different solutions. The melting and aggregation temperatures were determined with the help of fluorescence and static light scattering measurements. Additionally, rheological measurements were conducted to study the solution viscosity and viscoelastic behavior of the mAb solutions. The so-determined analytical parameters were scored and merged in an analytical toolbox. The resulting scoring was then successfully correlated with long-term storage (40 d of incubation) experiments. Our results indicate that the sensitivity of complex rheological measurements, in combination with the applied techniques, allows reliable statements to be made with respect to the effect of solution properties, such as protein concentration, ionic strength, and pH shift, on the strength of protein-protein interaction and solution colloidal stability.

Chromatographic separation of biopharmaceuticals in general and monoclonal antibodies (mAbs) specifically is the bottleneck in terms of cost and throughput in preparative purification. Still, generalized platform processes are used, neglecting molecule specific characteristics, defining protein-resin interaction terms. Currently used in silico modeling approaches do not consider the orientation of the molecule towards the chromatographic resins as a result of the structural features on an atomic level. This paper describes a quantitative structure-activity relationship (QSAR) approach to model the orientation of mAbs on ion exchange chromatographic matrices as a function of property distribution and mobile phase characteristics. 6 mAbs were used to build a predictive QSAR model and to investigate the preferred binding orientations and resulting surface shielding on resins. Thereby different dominating orientations, caused by composition of F ab fragments of the mAbs, could be identified. The presented methodology is suitable to gain extended insight in molecule orientation on chromatographic resins and to tailor purification strategies based on molecule structure., (Copyright © 2017 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.)

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., (© 2016 The Authors. Biotechnology and Bioengineering published by Wiley Periodicals, Inc.)

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.)

Protein drugs continue to grow both in medicinal importance as in scale of their production. This furthers the interest in separation technologies that have the potential to replace chromatographic steps in a protein purification process. Two such unit operations that are employed in large scale in the chemical industry are extraction and precipitation. Their usefulness for the purification of proteins has been demonstrated, but the integration of such unit operations in a way that generate an output stream of high protein concentration and low process related impurities was missing. In this work, we employ centrifugal partitioning chromatography ('CPC') in combination with precipitation of the protein of interest to purify a cell culture supernatant of a monoclonal antibody producing cell line. Centrifugal partitioning chromatography was used as means of multi-step extraction using aqueous two-phase systems and was able to remove up to 88.2% of host cell protein ('HCP'). The following PEG driven precipitation and resolubilization of the protein of interest was use to condition the CPC output stream to suit subsequent chromatographic steps, to increase mAb concentration, remove the phase forming polymer, further improve HCP clearance, and integrate a low pH hold step for viral clearance. The entire process reduced HCP content by 99.4% while recovering 93% of the protein of interest. High throughput screening techniques were extensively employed during the development of the process., (Copyright © 2013 Elsevier B.V. All rights reserved.)

Aqueous two-phase systems have been demonstrated to be a possible alternative to chromatographic separations during the industrial purification of proteins. While convenient high throughput screening methods were shown to drastically reduce experimental effort for the evaluations of ATPS as a unit operation, the selection of which phases to investigate is currently guided largely by prior knowledge. Correlations between protein descriptors and distribution were found, but the general applicability of such correlations especially under conditions of high protein load, is questionable, as currently no correlations take the saturation of the phases with protein into account. In this manuscript, we demonstrate how precipitation experiments using the phase forming components can guide the selection of both system type and tieline length for the purification of monoclonal antibodies. Phase selection and process development time can thus be significantly reduced, as all the necessary precipitation, binodal, and tieline experiments can be conducted within one day. Good qualitative correlations between precipitation data and both distribution and recovery of the target molecule were found. Most promising systems were selected for upscale to a 500mL CPC. Influence of operation condition on the column and on HCP clearance was investigated. An increase in HCP clearance of more than threefold compared to batch extractions was observed. The importance of load protein concentration underlined the value of using a screening approach that incorporated target protein solubility data., (Copyright © 2012 Elsevier B.V. All rights reserved.)

In the last decade, high-throughput downstream process development techniques have entered the biopharmaceutical industry. As chromatography is the standard downstream purification method, several high-throughput chromatographic methods have been developed and applied including miniaturized chromatographic columns for utilization on liquid handling stations. These columns were used to setup a complete downstream process on a liquid handling station for the first time. In this article, a monoclonal antibody process was established in lab-scale and miniaturized afterwards. The scale-down methodology is presented and discussed. Liquid handling in miniaturized single and multicolumn processes was improved and applicability was demonstrated by volume balances. The challenges of absorption measurement are discussed and strategies were shown to improve volume balances and mass balances in 96-well microtiter plates. The feasibility of miniaturizing a complete downstream process was shown. In the future, analytical bottlenecks should be addressed to gain the full benefit from miniaturized complete process development., (Copyright © 2012 American Institute of Chemical Engineers (AIChE).)

In process development and during commercial production of monoclonal antibodies (mAb) the monitoring of aggregate levels is obligatory. The standard assay for mAb aggregate quantification is based on size exclusion chromatography (SEC) performed on a HPLC system. Advantages hereof are high precision and simplicity, however, standard SEC methodology is very time consuming. With an average throughput of usually two samples per hour, it neither fits to high throughput process development (HTPD), nor is it applicable for purification process monitoring. We present a comparison of three different SEC columns for mAb-aggregate quantification addressing throughput, resolution, and reproducibility. A short column (150 mm) with sub-two micron particles was shown to generate high resolution (~1.5) and precision (coefficient of variation (cv)<1) with an assay time below 6 min. This column type was then used to combine interlaced sample injections with parallelization of two columns aiming for an absolute minimal assay time. By doing so, both lag times before and after the peaks of interest were successfully eliminated resulting in an assay time below 2 min. It was demonstrated that determined aggregate levels and precision of the throughput optimized SEC assay were equal to those of a single injection based assay. Hence, the presented methodology of parallel interlaced SEC (PI-SEC) represents a valuable tool addressing HTPD and process monitoring., (Copyright © 2011 Elsevier B.V. All rights reserved.)

Aqueous two-phase systems (ATPSs) as separation technique have regained substantial interest from the biotech industry. Biopharmaceutical companies faced with increasing product titers and stiffening economic competition reconsider ATPS as an alternative to chromatography. As the implementation of an ATPS is material, time, and labor intensive, a miniaturized and automated screening process would be beneficial. In this article such a method, its statistical evaluation, and its application to a biopharmaceutical separation task are shown. To speed up early stage ATPS profiling an automated application of the cloud-point method for binodal determination was developed. PEG4000-PO(4) binodals were measured automatically and manually and were found to be identical within the experimental error. The ATPS screening procedure was applied to a model system and an industrial separation task. PEG4000-PO(4) systems at a protein concentration of 0.75 mg/mL were used. The influence of pH, NaCl addition, and tie line length was investigated. Lysozyme as model protein, two monoclonal antibodies, and a host cell protein pool were used. The method was found to yield partition coefficients identical to manually determined values for lysozyme. The monoclonal antibodies were shifted from the bottom into the upper phase by addition of NaCl. This shift occurred at lower NaCl concentration when the pH of the system was closer to the pI of the distributed protein. Addition of NaCl, increase in PEG4000 concentration and pH led to significant loss of the mAb due to precipitation. Capacity limitations of these systems were thus demonstrated. The chosen model systems allowed a reduction of up to 50% HCP with a recovery of greater than 95% of the target proteins. As these values might not be industrially relevant when compared to current chromatographic procedures, the developed screening procedure allows a fast evaluation of more suitable and optimized ATPS system for a given task., (© 2010 Wiley Periodicals, Inc.)