Downstream process development strategies for effective bioprocesses: Trends, progress, and combinatorial approaches

Precision engineering of antibodies: A review of modification and design in the Fab region

The binding of functional groups to antibodies is crucial for disease treatment, diagnosis, and basic scientific research. Traditionally, antibody modifications have focused on the Fc region to maintain antigen-antibody binding activity. However, such modifications may impact critical antibody functions, including immune cell surface receptor activation, cytokine release, and other immune responses. In recent years, modifications targeting the antigen-binding fragment (Fab) region have garnered increasing attention. Precise modifications of the Fab region not only maximize the retention of antigen-antibody binding capacity but also enhance numerous physicochemical properties of antibodies. This paper reviews the chemical, biological, biochemical, and computer-assisted methods for modifying the Fab region of antibodies, discussing their advantages, limitations, recent advances, and future trends.

A modular and multi-functional purification strategy that enables a common framework for manufacturing scale integrated and continuous biomanufacturing

Biopharmaceutical manufacture is transitioning from batch to integrated and continuous biomanufacturing (ICB). The common framework for most ICB, potentially enables a global biomanufacturing ecosystem utilizing modular and multi-function manufacturing equipment. Integrating unit operation hardware and software from multiple suppliers, complex supply chains enabled by multiple customized single-use flow paths, and large volume buffer production/storage make this ICB vision difficult to achieve with commercially available manufacturing equipment. Thus, we developed SymphonX™, a downstream processing skid with advanced buffer management capabilities, a single disposable generic flow path design that provides plug-and-play flexibility across all downstream unit operations and a single interface to reduce operational risk. Designed for multi-product and multi-process cGMP facilities, SymphonX™ can perform stand-alone batch processing or ICB. This study utilized an Apollo™ X CHO-DG44 mAb-expressing cell line in a steady-state perfusion bioreactor, harvesting product continuously with a cell retention device and connected SymphonX™ purification skids. The downstream process used the same chemistry (resins, buffer composition, membrane composition) as our historical batch processing platform, with SymphonX™ in-line conditioning and buffer concentrates. We used surge vessels between unit operations, single-column chromatography (protein A, cation and anion exchange) and two-tank batch virus inactivation. After the first polishing step (cation exchange), we continuously pooled product for 6 days. These 6 day pools were processed in batch-mode from anion exchange to bulk drug substance. This manufacturing scale proof-of-concept ICB produced 0.54 kg/day of drug substance with consistent product quality attributes and demonstrated successful bioburden control for unit-operations undergoing continuous operation.

Challenges and Opportunities in the Process Development of Chimeric Vaccines

Vaccines are integral to human life to protect them from life-threatening diseases. However, conventional vaccines often suffer limitations like inefficiency, safety concerns, unavailability for non-culturable microbes, and genetic variability among pathogens. Chimeric vaccines combine multiple antigen-encoding genes of similar or different microbial strains to protect against hyper-evolving drug-resistant pathogens. The outbreaks of dreadful diseases have led researchers to develop economical chimeric vaccines that can cater to a large population in a shorter time. The process development begins with computationally aided omics-based approaches to design chimeric vaccines. Furthermore, developing these vaccines requires optimizing upstream and downstream processes for mass production at an industrial scale. Owing to the complex structures and complicated bioprocessing of evolving pathogens, various high-throughput process technologies have come up with added advantages. Recent advancements in high-throughput tools, process analytical technology (PAT), quality-by-design (QbD), design of experiments (DoE), modeling and simulations, single-use technology, and integrated continuous bioprocessing have made scalable production more convenient and economical. The paradigm shift to innovative strategies requires significant attention to deal with major health threats at the global scale. This review outlines the challenges and emerging avenues in the bioprocess development of chimeric vaccines.

Model based process optimization of an industrial chromatographic process for separation of lactoferrin from bovine milk

Model based process development using predictive mechanistic models is a powerful tool for in-silico downstream process development. It allows to obtain a thorough understanding of the process reducing experimental effort. While in pharma industry, mechanistic modeling becomes more common in the last years, it is rarely applied in food industry. This case study investigates risk ranking and possible optimization of the industrial process of purifying lactoferrin from bovine milk using SP Sepharose Big Beads with a resin particle diameter of 200 µm, based on a minimal number of lab-scale experiments combining traditional scale-down experiments with mechanistic modeling. Depending on the location and season, process water pH and the composition of raw milk can vary, posing a challenge for highly efficient process development. A predictive model based on the general rate model with steric mass action binding, extended for pH dependence, was calibrated to describe the elution behavior of lactoferrin and main impurities. The gained model was evaluated against changes in flow rate, step elution conditions, and higher loading and showed excellent agreement with the observed experimental data. The model was then used to investigate the critical process parameters, such as water pH, conductivity of elution steps, and flow rate, on process performance and purity. It was found that the elution behavior of lactoferrin is relatively consistent over the pH range of 5.5 to 7.6, while the elution behavior of the main impurities varies greatly with elution pH. As a result, a significant loss in lactoferrin is unavoidable to achieve desired purities at pH levels below pH 6.0. Optimal process parameters were identified to reduce water and salt consumption and increase purity, depending on water pH and raw milk composition. The optimal conductivity for impurity removal in a low conductivity elution step was found to be 43 mS/cm, while a conductivity of 95 mS/cm leads to the lowest overall salt usage during lactoferrin elution. Further increasing the conductivity during lactoferrin elution can only slightly lower the elution volume thus can also lead to higher total salt usage. Low flow rates during elution of 0.2 column volume per minute are beneficial compared to higher flow rates of 1 column volume per minute. The, on lab-scale, calibrated model allows predicting elution volume and impurity removal for large-scale experiments in a commercial plant processing over 106 liters of milk per day. The successful model extrapolation was possible without recalibration or detailed knowledge of the manufacturing plant. This study therefore provides a possible pathway for rapid process development of chromatographic purification in the food industries combining traditional scale-down experiments with mechanistic modeling.

Yields and product comparison between Escherichia coli BL21 and W3110 in industrially relevant conditions: anti-c-Met scFv as a case study

INTRODUCTION

In the biopharmaceutical industry, Escherichia coli is one of the preferred expression hosts for large-scale production of therapeutic proteins. Although increasing the product yield is important, product quality is a major factor in this industry because greatest productivity does not always correspond with the highest quality of the produced protein. While some post-translational modifications, such as disulphide bonds, are required to achieve the biologically active conformation, others may have a negative impact on the product's activity, effectiveness, and/or safety. Therefore, they are classified as product associated impurities, and they represent a crucial quality parameter for regulatory authorities.

RESULTS

In this study, fermentation conditions of two widely employed industrial E. coli strains, BL21 and W3110 are compared for recombinant protein production of a single-chain variable fragment (scFv) in an industrial setting. We found that the BL21 strain produces more soluble scFv than the W3110 strain, even though W3110 produces more recombinant protein in total. A quality assessment on the scFv recovered from the supernatant was then performed. Unexpectedly, even when our scFv is correctly disulphide bonded and cleaved from its signal peptide in both strains, the protein shows charge heterogeneity with up to seven distinguishable variants on cation exchange chromatography. Biophysical characterization confirmed the presence of altered conformations of the two main charged variants.

CONCLUSIONS

The findings indicated that BL21 is more productive for this specific scFv than W3110. When assessing product quality, a distinctive profile of the protein was found which was independent of the E. coli strain. This suggests that alterations are present in the recovered product although the exact nature of them could not be determined. This similarity between the two strains' generated products also serves as a sign of their interchangeability. This study encourages the development of innovative, fast, and inexpensive techniques for the detection of heterogeneity while also provoking a debate about whether intact mass spectrometry-based analysis of the protein of interest is sufficient to detect heterogeneity in a product.

Adeno-Associated virus 8 delivers an immunomodulatory peptide to mouse liver more efficiently than to rat liver

Targeting the Kv1.3 potassium channel has proven effective in reducing obesity and the severity of animal models of autoimmune disease. Stichodactyla toxin (ShK), isolated from the sea anemone Stichodactyla helianthus, is a potent blocker of Kv1.3. Several of its analogs are some of the most potent and selective blockers of this channel. However, like most biologics, ShK and its analogs require injections for their delivery, and repeated injections reduce patient compliance during the treatment of chronic diseases. We hypothesized that inducing the expression of an ShK analog by hepatocytes would remove the requirement for frequent injections and lead to a sustained level of Kv1.3 blocker in the circulation. To this goal, we tested the ability of Adeno-Associated Virus (AAV)8 vectors to target hepatocytes for expressing the ShK analog, ShK-235 (AAV-ShK-235) in rodents. We designed AAV8 vectors expressing the target transgene, ShK-235, or Enhanced Green fluorescent protein (EGFP). Transduction of mouse livers led to the production of sufficient levels of functional ShK-235 in the serum from AAV-ShK-235 single-injected mice to block Kv1.3 channels. However, AAV-ShK-235 therapy was not effective in reducing high-fat diet-induced obesity in mice. In addition, injection of even high doses of AAV8-ShK-235 to rats resulted in a very low liver transduction efficiency and failed to reduce inflammation in a well-established rat model of delayed-type hypersensitivity. In conclusion, the AAV8-based delivery of ShK-235 was highly effective in inducing the secretion of functional Kv1.3-blocking peptide in mouse, but not rat, hepatocytes yet did not reduce obesity in mice fed a high-fat diet.

Bioprocessing of recombinant proteins from Escherichia coli inclusion bodies: insights from structure-function relationship for novel applications

The formation of inclusion bodies (IBs) during expression of recombinant therapeutic proteins using E. coli is a significant hurdle in producing high-quality, safe, and efficacious medicines. The improved understanding of the structure-function relationship of the IBs has resulted in the development of novel biotechnologies that have streamlined the isolation, solubilization, refolding, and purification of the active functional proteins from the bacterial IBs. Together, this overall effort promises to radically improve the scope of experimental biology of therapeutic protein production and expand new prospects in IBs usage. Notably, the IBs are increasingly used for applications in more pristine areas such as drug delivery and material sciences. In this review, we intend to provide a comprehensive picture of the bio-processing of bacterial IBs, including assessing critical gaps that still need to be addressed and potential solutions to overcome them. We expect this review to be a useful resource for those working in the area of protein refolding and therapeutic protein production.

Deep learning in drug discovery: an integrative review and future challenges

Recently, using artificial intelligence (AI) in drug discovery has received much attention since it significantly shortens the time and cost of developing new drugs. Deep learning (DL)-based approaches are increasingly being used in all stages of drug development as DL technology advances, and drug-related data grows. Therefore, this paper presents a systematic Literature review (SLR) that integrates the recent DL technologies and applications in drug discovery Including, drug-target interactions (DTIs), drug-drug similarity interactions (DDIs), drug sensitivity and responsiveness, and drug-side effect predictions. We present a review of more than 300 articles between 2000 and 2022. The benchmark data sets, the databases, and the evaluation measures are also presented. In addition, this paper provides an overview of how explainable AI (XAI) supports drug discovery problems. The drug dosing optimization and success stories are discussed as well. Finally, digital twining (DT) and open issues are suggested as future research challenges for drug discovery problems. Challenges to be addressed, future research directions are identified, and an extensive bibliography is also included.

An Experimental and Modeling Combined Approach in Preparative Hydrophobic Interaction Chromatography

Chromatography is a technique widely used in the purification of biopharmaceuticals, and generally consists of several chromatographic steps. In this work, Hydrophobic Interaction Chromatography (HIC) is investigated as a polishing step for the purification of therapeutic proteins. Adsorption mechanisms in hydrophobic interaction chromatography are still not completely clear and a limited amount of published data is available. In addition to new data on adsorption isotherms for some proteins (obtained both by high-throughput and frontal analysis method), and a comparison of different models proposed in the literature, two different approaches are compared in this work to investigate HIC. The predictive approach exploits an in-house code that simulates the behavior of the component in the column using the model parameters found from the fitting of experimental data. The estimation approach, on the other hand, exploits commercial software in which the model parameters are found by the fitting of a few experimental chromatograms. The two approaches are validated on some bind-elute runs: the predictive approach is very informative, but the experimental effort needed is high; the estimation approach is more effective, but the knowledge gained is lower. The second approach is also applied to an in-development industrial purification process and successfully resulted in predicting the behavior of the system, allowing for optimization with a reduction in the time and amount of sample needed.

Mechanistic modeling and simulation of a complex low and high loading elution behavior of a polypeptide in cation exchange chromatography

The mechanistic modeling of preparative liquid chromatography is still a challenging task. Non-ideal thermodynamic conditions may require activity coefficients for the mechanistic description of preparative chromatography. In this work, a chromatographic cation exchange step with a polypeptide having a complex elution behavior in low and high loading situations is modeled. Model calibration in the linear range of the isotherm is done by applying counterion-induced linear gradient elution experiments between pH 3.3 and pH 4.3. Inverse fitting with column loads up to 25 mg/mL_CV is performed for parameter estimation in the non-linear range. The polypeptide elution peak shows an anti-Langmuirian behavior with fronting under low loading conditions and a switch to a Langmuirian behavior with increasing load. This unusual elution behavior could be described with an extended version of the sigmoidal Self-Association isotherm, including two activity coefficients for the polypeptide and counterion in solution. The activity coefficient of the solute polypeptide shows a strong influence on the model parameters and is crucial in the linear and non-linear range of the isotherm. The modeling procedure results in a unique and robust model parameter set that is sufficient to describe the complex elution behavior and allows modeling over the full isotherm range. This article is protected by copyright. All rights reserved.

Pichia pastoris (Komagataella phaffii) as a Cost-Effective Tool for Vaccine Production for Low- and Middle-Income Countries (LMICs)

Vaccination is of paramount importance to global health. With the advent of the more recent pandemics, the urgency to expand the range has become even more evident. However, the potential limited availability and affordability of vaccines to resource low- and middle-income countries has created a need for solutions that will ensure cost-effective vaccine production methods for these countries. Pichia pastoris (P. pastoris) (also known as Komagataella phaffii) is one of the most promising candidates for expression of heterologous proteins in vaccines development. It combines the speed and ease of highly efficient prokaryotic platforms with some key capabilities of mammalian systems, potentially reducing manufacturing costs. This review will examine the latest developments in P. pastoris from cell engineering and design to industrial production systems with focus on vaccine development and with reference to specific key case studies.

Purification of Modified Therapeutic Proteins Available on the Market: An Analysis of Chromatography-Based Strategies

Proteins, which have inherent biorecognition properties, have long been used as therapeutic agents for the treatment of a wide variety of clinical indications. Protein modification through covalent attachment to different moieties improves the therapeutic's pharmacokinetic properties, affinity, stability, confers protection against proteolytic degradation, and increases circulation half-life. Nowadays, several modified therapeutic proteins, including PEGylated, Fc-fused, lipidated, albumin-fused, and glycosylated proteins have obtained regulatory approval for commercialization. During its manufacturing, the purification steps of the therapeutic agent are decisive to ensure the quality, effectiveness, potency, and safety of the final product. Due to the robustness, selectivity, and high resolution of chromatographic methods, these are recognized as the gold standard in the downstream processing of therapeutic proteins. Moreover, depending on the modification strategy, the protein will suffer different physicochemical changes, which must be considered to define a purification approach. This review aims to deeply analyze the purification methods employed for modified therapeutic proteins that are currently available on the market, to understand why the selected strategies were successful. Emphasis is placed on chromatographic methods since they govern the purification processes within the pharmaceutical industry. Furthermore, to discuss how the modification type strongly influences the purification strategy, the purification processes of three different modified versions of coagulation factor IX are contrasted.

Optimization and kinetic modeling of interchain disulfide bond reoxidation of monoclonal antibodies in bioprocesses

Disulfide bonds play a crucial role in folding and structural stabilization of monoclonal antibodies (mAbs). Disulfide bond reduction may happen during the mAb manufacturing process, resulting in low molecular weight species and possible failure to meet product specifications. Although many mitigation strategies have been developed to prevent disulfide reduction, to the best of our knowledge, reforming disulfide bonds from the reduced antibody in manufacturing has not previously been reported. Here, we explored a novel rescue strategy in the downstream process to repair the broken disulfide bonds via in-vitro redox reactions on Protein A resin. Redox conditions including redox pair (cysteine/cystine ratio), pH, temperature, and reaction time were examined to achieve high antibody purity and a high reaction rate. Under the optimal redox condition, >90% reduced antibody could be reoxidized to form an intact antibody on Protein A resin in an hour. In addition, this study showed high flexibility on the range of the intact mAb fraction in the initial reduced mAb sample (the lower limit of intact mAb faction could be 14% based on the data reported in this study). Furthermore, a kinetic model based on elementary oxidative reactions was constructed to help optimize the reoxidation conditions and to predict product purity. Together, the deep understanding of interchain disulfide bond reoxidation, combined with the predictive kinetic model, provided a good foundation to implement a rescue strategy to generate high-purity antibodies with substantial cost savings in manufacturing processes.

Bioproduced Proteins On Demand (Bio-POD) in hydrogels using Pichia pastoris

Traditional production of industrial and therapeutic proteins by eukaryotic cells typically requires large-scale fermentation capacity. As a result, these systems are not easily portable or reusable for on-demand protein production applications. In this study, we employ Bioproduced Proteins On Demand (Bio-POD), a F127-bisurethane methacrylate hydrogel-based technique that immobilizes engineered Pichia pastoris for preservable, on-demand production and secretion of medium- and high-molecular weight proteins (in this case, SEAP, α-amylase, and anti-HER2). The gel samples containing encapsulated-yeast demonstrated sustained protein production and exhibited productivity immediately after lyophilization and rehydration. The hydrogel platform described here is the first hydrogel immobilization using a P. pastoris system to produce recombinant proteins of this breadth. These results highlight the potential of this formulation to establish a cost-effective bioprocessing strategy for on-demand protein production.

In silico process characterization for biopharmaceutical development following the quality by design concept

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.

Impact of freeze-thaw processes on monoclonal antibody platform process development

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.

Hybrid Models for the simulation and prediction of chromatographic processes for protein capture

The biopharmaceutical industries are continuously faced with the pressure to reduce the development costs and accelerate development time scales. The traditional approach of heuristic-based or platform process-based optimization is soon getting obsolete, and more generalized tools for process development and optimization are required to keep pace with the emerging trends. Thus, advanced model-based methods that can reduce the can ensure accelerated development of robust processes with minimal experiments are necessary. Though mechanistic models for chromatography are quite popular, their success is limited by the need to have accurate knowledge of adsorption isotherms and mass transfer kinetics. As an alternative, in this work, a hybrid modeling approach is proposed. Thereby, the chromatographic unit behavior is learned by a combination of neural network and mechanistic model while fitting suitable experimental breakthrough curves. Since this approach does not require identifying suitable mechanistic assumptions for all the phenomena, it can be developed with lower effort. Thus, allowing the scientists to concentrate their focus on process development. The performance of the hybrid model is compared with the mechanistic Lumped kinetic Model for in-silico data and experiments conducted on a system of industrial relevance. The flexibility of the hybrid modeling approach results in about three times higher accuracies compared to Lumped Kinetic Model. This is validated for five different isotherm models used to simulate data, with the hybrid model showing about two to three times lower prediction errors in all the cases. Not only in prediction, but we could also show that the hybrid model is more robust in extrapolating across process conditions with about three times lower error than the LKM. Additionally, it could be demonstrated that an appropriately tailored formulation of the hybrid model can be used to generate representations for the underlying principles such as adsorption equilibria and mass transfer kinetics.

Marine Actinobacteria Bioflocculant: A Storehouse of Unique Biotechnological Resources for Wastewater Treatment and Other Applications

The bioactive compounds produced by actinobacteria have played a major role in antimicrobials, bioremediation, biofuels, enzymes, and anti-cancer activities. Biodegradable microbial flocculants have been produced by bacteria, algae, and fungi. Microbial bioflocculants have also attracted biotechnology importance over chemical flocculants as a result of degradability and environmentally friendly attributes they possess. Though, freshwater actinobacteria flocculants have been explored in bioflocculation. Yet, there is a paucity of information on the application of actinobacteria flocculants isolated from the marine environment. Similarly, marine habitats that supported the biodiversity of actinobacteria strains in the field of biotechnology have been underexplored in bioflocculation. Hence, this review reiterates the need to optimize culture conditions and other parameters that affect bioflocculant production by using a response surface model or artificial neural network.

Cross-scale quality assessment of a mechanistic cation exchange chromatography model

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.

Optimized polymer-based glucose release in microtiter plates for small-scale E. coli fed-batch cultivations

Background

Small-scale cultivation vessels, which allow fed-batch operation mode, become more and more important for fast and reliable early process development. Recently, the polymer-based feeding system was introduced to allow fed-batch conditions in microtiter plates. Maximum glucose release rates of 0.35 mg/h per well (48-well-plate) at 37 °C can be achieved with these plates, depending on the media properties. The fed-batch cultivation of fluorescent protein-expressing E. coli at oxygen transfer rate levels of 5 mmol/L/h proved to be superior compared to simple batch cultivations. However, literature suggests that higher glucose release rates than achieved with the currently available fed-batch microtiter plate are beneficial, especially for fast-growing microorganisms. During the fed-batch phase of the cultivation, a resulting oxygen transfer rate level of 28 mmol/L/h should be achieved.

Results

Customization of the polymer matrix enabled a considerable increase in the glucose release rate of more than 250% to up to 0.90 mg/h per well. Therefore, the molecular weight of the prepolymer and the addition of a hydrophilic PDMS-PEG copolymer allowed for the individual adjustment of a targeted glucose release rate. The newly developed polymer matrix was additionally invariant to medium properties like the osmotic concentration or the pH-value. The glucose release rate of the optimized matrix was constant in various synthetic and complex media. Fed-batch cultivations of E. coli in microtiter plates with the optimized matrix revealed elevated oxygen transfer rates during the fed-batch phase of approximately 28 mmol/L/h. However, these increased glucose release rates resulted in a prolonged initial batch phase and oxygen limitations. The newly developed polymer-based feeding system provides options to manufacture individual feed rates in a range from 0.24–0.90 mg/h per well.

Conclusions

The optimized polymer-based fed-batch microtiter plate allows higher reproducibility of fed-batch experiments since cultivation media properties have almost no influence on the release rate. The adjustment of individual feeding rates in a wide range supports the early process development for slow, average and fast-growing microorganisms in microtiter plates. The study underlines the importance of a detailed understanding of the metabolic behavior (through online monitoring techniques) to identify optimal feed rates.

Digital Twins in Pharmaceutical and Biopharmaceutical Manufacturing: A Literature Review

The development and application of emerging technologies of Industry 4.0 enable the realization of digital twins (DT), which facilitates the transformation of the manufacturing sector to a more agile and intelligent one. DTs are virtual constructs of physical systems that mirror the behavior and dynamics of such physical systems. A fully developed DT consists of physical components, virtual components, and information communications between the two. Integrated DTs are being applied in various processes and product industries. Although the pharmaceutical industry has evolved recently to adopt Quality-by-Design (QbD) initiatives and is undergoing a paradigm shift of digitalization to embrace Industry 4.0, there has not been a full DT application in pharmaceutical manufacturing. Therefore, there is a critical need to examine the progress of the pharmaceutical industry towards implementing DT solutions. The aim of this narrative literature review is to give an overview of the current status of DT development and its application in pharmaceutical and biopharmaceutical manufacturing. State-of-the-art Process Analytical Technology (PAT) developments, process modeling approaches, and data integration studies are reviewed. Challenges and opportunities for future research in this field are also discussed.

Fractal dimension of antibody-PEG precipitate: Light microscopy for the reconstruction of 3D precipitate structures

Protein and in particular antibody precipitation by PEG is a cost-effective alternative for the first capture step. The 3D structure of precipitates has a large impact on the process parameters for the recovery and dissolution, but current technologies for determination of precipitate structures are either very time consuming (cryo-TEM) or only generate an average fractal dimension (light scattering). We developed a light microscopy based reconstruction of 3D structures of individual particles with a resolution of 0.1-0.2 µm and used this method to characterize particle populations generated by batch as well as continuous precipitation in different shear stress environments. The resulting precipitate structures show a broad distribution in terms of fractal dimension. While the average fractal dimension is significantly different for batch and continuous precipitation, the distribution is broad and samples overlap significantly. The precipitate flocs were monofractal from micro- to nanoscale showing a random but consistent nature of precipitate formation. We showed that the fractal dimension and 3D reconstruction is a valuable tool for characterization of protein precipitate processes. The current switch from batch to continuous manufacturing has to take the 3D structure and population of different protein precipitates into account in their design, engineering, and scale up.

Accelerating Biologics Manufacturing by Modeling: Process Integration of Precipitation in mAb Downstream Processing

The demand on biologics has been constantly rising over the past decades and has become crucial in modern medicine. Promising approaches to cope with widespread diseases like cancer and diabetes are gene therapy, plasmid DNA, virus-like particles, and exosomes. Due to progress that has been made in upstream processing (USP), difficulties arise in downstream processing and demand for innovative solutions. This work focuses on the integration of precipitation using a quality by design (QbD) approach for process development. Selective precipitation is achieved with PEG 4000 resulting in an HCP depletion of ≥80% respectively to IgG. Dissolution was executed with a sodium phosphate buffer (pH = 5/50 mM) reaching an IgG recovery of ≥95%. However, the central challenge in process development is still an optimal process design, which is transferable for a broad molecular variety of new products. This is where rigorous modeling becomes vital in order to generate digital twins to support early-stage process development and reduce the experimental overhead. Therefore, a model development and validation concept for construction of a process model for precipitation is also presented.

On-column disulfide bond formation of monoclonal antibodies during Protein A chromatography eliminates low molecular weight species and rescues reduced antibodies

Disulfide bond reduction, which commonly occurs during monoclonal antibody (mAb) manufacturing processes, can result in a drug substance with high levels of low molecular weight (LMW) species that may fail release specifications because the drug's safety and the efficiency may be affected by the presence of this material. We previously studied disulfide reoxidation of mAbs and demonstrated that disulfide bonds could be reformed from the reduced antibody via redox reactions under an optimal redox condition on Protein A resin. The study here implements a redox system in a manufacturing setting to rescue the reduced mAb product and to further eliminate LMW issues in downstream processing. As such, we incorporate the optimized redox system as one of the wash buffers in Protein A chromatography to enable an on-column disulfide reoxidation to form intact antibody in vitro. Studies at laboratory scale (1 cm (ID) x 20 cm (Height), MabSelect SuRe LX) and pilot scale (30 cm (ID) x 20 cm (Height), MabSelect SuRe LX) were performed to demonstrate the effectiveness and robustness of disulfide formation with multiple mAbs using redox wash on Protein A columns. By applying this rescue strategy using ≤50 g/L-resin loading, the intact mAb purity was improved from <5% in the Protein A column load to >90% in the Protein A column elution with a product yield of >90%. Studies were also done to confirm that adding the redox wash has no negative impact on process yield or impurity removal or product quality. The rescued mAbs were confirmed to form complete interchain disulfide bonds, exhibiting comparable biophysical properties to the reference material. Furthermore, since the redox wash is followed by a bridging buffer wash before the final elution, no additional burden is involved in removing the redox components during the downstream steps. Due to its ease of implementation, significant product purity improvement, and minimal impact on other product quality attributes, we demonstrate that the on-column reoxidation using a redox system is a powerful, simple, and safe tool to recover reduced mAb during manufacturing. Moreover, the apparent benefits of using a high-pH redox wash may further drive the evolution of Protein A platform processes.

Recent Developments in Bioprocessing of Recombinant Proteins: Expression Hosts and Process Development

Infectious diseases, along with cancers, are among the main causes of death among humans worldwide. The production of therapeutic proteins for treating diseases at large scale for millions of individuals is one of the essential needs of mankind. Recent progress in the area of recombinant DNA technologies has paved the way to producing recombinant proteins that can be used as therapeutics, vaccines, and diagnostic reagents. Recombinant proteins for these applications are mainly produced using prokaryotic and eukaryotic expression host systems such as mammalian cells, bacteria, yeast, insect cells, and transgenic plants at laboratory scale as well as in large-scale settings. The development of efficient bioprocessing strategies is crucial for industrial production of recombinant proteins of therapeutic and prophylactic importance. Recently, advances have been made in the various areas of bioprocessing and are being utilized to develop effective processes for producing recombinant proteins. These include the use of high-throughput devices for effective bioprocess optimization and of disposable systems, continuous upstream processing, continuous chromatography, integrated continuous bioprocessing, Quality by Design, and process analytical technologies to achieve quality product with higher yield. This review summarizes recent developments in the bioprocessing of recombinant proteins, including in various expression systems, bioprocess development, and the upstream and downstream processing of recombinant proteins.

Current challenges in biotherapeutic particles manufacturing

Introduction: The development of novel complex biotherapeutics led to new challenges in biopharmaceutical industry. The potential of these particles has been demonstrated by the approval of several products, in the different fields of gene therapy, oncolytic therapy, and tumor vaccines. However, their manufacturing still presents challenges related to the high dosages and purity required.Areas covered: The main challenges that biopharmaceutical industry faces today and the most recent developments in the manufacturing of different biotherapeutic particles are reported here. Several unit operations and downstream trains to purify virus, virus-like particles and extracellular vesicles are described. Innovations on the different purification steps are also highlighted with an eye on the implementation of continuous and integrated processes.Expert opinion: Manufacturing platforms that consist of a low number of unit operations, with higher-yielding processes and reduced costs will be highly appreciated by the industry. The pipeline of complex therapeutic particles is expanding and there is a clear need for advanced tools and manufacturing capacity. The use of single-use technologies, as well as continuous integrated operations, are gaining ground in the biopharmaceutical industry and should be supported by more accurate and faster analytical methods.

Optimization of integrated chromatography sequences for purification of biopharmaceuticals

With continued development of integrated and continuous downstream purification processes, tuning and optimization become increasingly complicated with additional parameters and codependent variables over the sequence. This article offers a novel perspective of nonlinear optimization of integrated sequences with regard to individual column sizes, flow rates, and scheduling. The problem setup itself is a versatile tool to be used in downstream design which is demonstrated in two case studies: a four‐column integrated sequence and a continuously loaded twin‐capture setup with five columns.

Model-based monitoring of industrial reversed phase chromatography to predict insulin variants

Downstream processing in the manufacturing biopharmaceutical industry is a multistep process separating the desired product from process- and product-related impurities. However, removing product-related impurities, such as product variants, without compromising the product yield or prolonging the process time due to extensive quality control analytics, remains a major challenge. Here, we show how mechanistic model-based monitoring, based on analytical quality control data, can predict product variants by modeling their chromatographic separation during product polishing with reversed phase chromatography. The system was described by a kinetic dispersive model with a modified Langmuir isotherm. Solely quality control analytical data on product and product variant concentrations were used to calibrate the model. This model-based monitoring approach was developed for an insulin purification process. Industrial materials were used in the separation of insulin and two insulin variants, one eluting at the product peak front and one eluting at the product peak tail. The model, fitted to analytical data, used one component to simulate each protein, or two components when a peak displayed a shoulder. This monitoring approach allowed the prediction of the elution patterns of insulin and both insulin variants. The results indicate the potential of using model-based monitoring in downstream polishing at industrial scale to take pooling decisions.

Water on hydrophobic surfaces: mechanistic modeling of polyethylene glycol-induced protein precipitation

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.

Microbioreactor Systems for Accelerated Bioprocess Development

In recent years, microbioreactor (MBR) systems have evolved towards versatile bioprocess engineering tools. They provide a unique solution to combine higher experimental throughput with extensive bioprocess monitoring and control, which is indispensable to develop economically and ecologically competitive bioproduction processes. MBR systems are based either on down-scaled stirred tank reactors or on advanced shaken microtiter plate cultivation devices. Importantly, MBR systems make use of optical measurements for non-invasive, online monitoring of important process variables like biomass concentration, dissolved oxygen, pH, and fluorescence. The application range of MBR systems can be further increased by integration into liquid handling robots, enabling automatization and, thus standardization, of various handling and operation procedures. Finally, the tight integration of quantitative strain phenotyping with bioprocess development under industrially relevant conditions greatly increases the probability of finding the right combination of producer strain and bioprocess control strategy. This review will discuss the current state of the art in the field of MBR systems and we can readily conclude that their importance for industrial biotechnology will further increase in the near future.