Proteomics-based method to comprehensively model the removal of host cell protein impurities.

Mechanistic models mostly focus on the target protein and some selected process- or product-related impurities. For a better process understanding, however, it is advantageous to describe also reoccurring host cell protein impurities. Within the purification of biopharmaceuticals, the binding of host cell proteins to a chromatographic resin is far from being described comprehensively. For a broader coverage of the binding characteristics, large-scale proteomic data and systems level knowledge on protein interactions are key. However, a method for determining binding parameters of the entire host cell proteome to selected chromatography resins is still lacking. In this work, we have developed a method to determine binding parameters of all detected individual host cell proteins in an Escherichia coli harvest sample from large-scale proteomics experiments. The developed method was demonstrated to model abundant and problematic proteins, which are crucial impurities to be removed. For these 15 proteins covering varying concentration ranges, the model predicts the independently measured retention time during the validation gradient well. Finally, we optimized the anion exchange chromatography capture step in silico using the determined isotherm parameters of the persistent host cell protein contaminants. From these results, strategies can be developed to separate abundant and problematic impurities from the target antigen.

Predicting protein retention in ion-exchange chromatography using an open source QSPR workflow.

Protein-based biopharmaceuticals require high purity before final formulation to ensure product safety, making process development time consuming. Implementation of computational approaches at the initial stages of process development offers a significant reduction in development efforts. By preselecting process conditions, experimental screening can be limited to only a subset. One such computational selection approach is the application of Quantitative Structure Property Relationship (QSPR) models that describe the properties exploited during purification. This work presents a novel open-source Python tool capable of extracting a range of features from protein 3D models on a local computer allowing total transparency of the calculations. As open-source tool, it also impacts initial investments in constructing a QSPR workflow for protein property prediction for third parties, making it widely applicable within the field of bioprocess development. The focus of current calculated molecular features is projection onto the protein surface by constructing surface grid representations. Linear regression models were trained with the calculated features to predict chromatographic retention times/volumes. Model validation shows a high accuracy for anion and cation exchange chromatography data (cross-validated R2 of 0.87 and 0.95). Hence, these models demonstrate the potential of the use of QSPR to accelerate process design.

Digital twin in high throughput chromatographic process development for monoclonal antibodies.

The monoclonal antibody (mAb) industry is becoming increasingly digitalized. Digital twins are becoming increasingly important to test or validate processes before manufacturing. High-Throughput Process Development (HTPD) has been progressively used as a tool for process development and innovation. The combination of High-Throughput Screening with fast computational methods allows to study processes in-silico in a fast and efficient manner. This paper presents a hybrid approach for HTPD where equal importance is given to experimental, computational and decision-making stages. Equilibrium adsorption isotherms of 13 protein A and 16 Cation-Exchange resins were determined with pure mAb. The influence of other components in the clarified cell culture supernatant (harvest) has been under-investigated. This work contributes with a methodology for the study of equilibrium adsorption of mAb in harvest to different protein A resins and compares the adsorption behavior with the pure sample experiments. Column chromatography was modelled using a Lumped Kinetic Model, with an overall mass transfer coefficient parameter (kov). The screening results showed that the harvest solution had virtually no influence on the adsorption behavior of mAb to the different protein A resins tested. kov was found to have a linear correlation with the sample feed concentration, which is in line with mass transfer theory. The hybrid approach for HTPD presented highlights the roles of the computational, experimental, and decision-making stages in process development, and how it can be implemented to develop a chromatographic process. The proposed white-box digital twin helps to accelerate chromatographic process development.

Real-time detection of mAb aggregates in an integrated downstream process.

The implementation of continuous processing in the biopharmaceutical industry is hindered by the scarcity of process analytical technologies (PAT). To monitor and control a continuous process, PAT tools will be crucial to measure real-time product quality attributes such as protein aggregation. Miniaturizing these analytical techniques can increase measurement speed and enable faster decision-making. A fluorescent dye (FD)-based miniaturized sensor has previously been developed: a zigzag microchannel which mixes two streams under 30 s. Bis-ANS and CCVJ, two established FDs, were employed in this micromixer to detect aggregation of the biopharmaceutical monoclonal antibody (mAb). Both FDs were able to robustly detect aggregation levels starting at 2.5%. However, the real-time measurement provided by the microfluidic sensor still needs to be implemented and assessed in an integrated continuous downstream process. In this work, the micromixer is implemented in a lab-scale integrated system for the purification of mAbs, established in an ÄKTA™ unit. A viral inactivation and two polishing steps were reproduced, sending a sample of the product pool after each phase directly to the microfluidic sensor for aggregate detection. An additional UV sensor was connected after the micromixer and an increase in its signal would indicate that aggregates were present in the sample. The at-line miniaturized PAT tool provides a fast aggregation measurement, under 10 min, enabling better process understanding and control.

Using artificial neural networks to accelerate flowsheet optimization for downstream process development.

An optimal purification process for biopharmaceutical products is important to meet strict safety regulations, and for economic benefits. To find the global optimum, it is desirable to screen the overall design space. Advanced model-based approaches enable to screen a broad range of the design-space, in contrast to traditional statistical or heuristic-based approaches. Though, chromatographic mechanistic modeling (MM), one of the advanced model-based approaches, can be speed-limiting for flowsheet optimization, which evaluates every purification possibility (e.g., type and order of purification techniques, and their operating conditions). Therefore, we propose to use artificial neural networks (ANNs) during global optimization to select the most optimal flowsheets. So, the number of flowsheets for final local optimization is reduced and consequently the overall optimization time. Employing ANNs during global optimization proved to reduce the number of flowsheets from 15 to only 3. From these three, one flowsheet was optimized locally and similar final results were found when using the global outcome of either the ANN or MM as starting condition. Moreover, the overall flowsheet optimization time was reduced by 50% when using ANNs during global optimization. This approach accelerates the early purification process design; moreover, it is generic, flexible, and regardless of sample material's type.

Application of a fluorescent dye-based microfluidic sensor for real-time detection of mAb aggregates.

The lack of process analytical technologies able to provide real-time information and process control over a biopharmaceutical process has long impaired the transition to continuous biomanufacturing. For the monoclonal antibody (mAb) production, aggregate formation is a major critical quality attribute (CQA) with several known process parameters (i.e., protein concentration and agitation) influencing this phenomenon. The development of a real-time tool to monitor aggregate formation is then crucial to gain control and achieve a continuous processing. Due to an inherent short operation time, miniaturized biosensors placed after each step can be a powerful solution. In this work, the development of a fluorescent dye-based microfluidic sensor for fast at-line PAT is described, using fluorescent dyes to examine possible mAb size differences. A zigzag microchannel, which provides 90% of mixing efficiency under 30 s, coupled to an UV-Vis detector, and using four FDs, was studied and validated. With different generated mAb aggregation samples, the FDs Bis-ANS and CCVJ were able to robustly detect from, at least, 2.5% to 10% of aggregation. The proposed FD-based micromixer is then ultimately implemented and validated in a lab-scale purification system, demonstrating the potential of a miniaturized biosensor to speed up CQAs measurement in a continuous process.

Characterisation of the E. coli HMS174 and BLR host cell proteome to guide purification process development.

Mass-spectrometry-based proteomics is increasingly employed to monitor purification processes or to detect critical host cell proteins in the final drug substance. This approach is inherently unbiased and can be used to identify individual host cell proteins without prior knowledge. In process development for the purification of new biopharmaceuticals, such as protein subunit vaccines, a broader knowledge of the host cell proteome could promote a more rational process design. Proteomics can establish qualitative and quantitative information on the complete host cell proteome before purification (i.e., protein abundances and physicochemical properties). Such information allows for a more rational design of the purification strategy and accelerates purification process development. In this study, we present an extensive proteomic characterisation of two E. coli host cell strains widely employed in academia and industry to produce therapeutic proteins, BLR and HMS174. The established database contains the observed abundance of each identified protein, information relating to their hydrophobicity, the isoelectric point, molecular weight, and toxicity. These physicochemical properties were plotted on proteome property maps to showcase the selection of suitable purification strategies. Furthermore, sequence alignment allowed integration of subunit information and occurrences of post-translational modifications from the well-studied E. coli K12 strain.

Genipin prevents alpha-synuclein aggregation and toxicity by affecting endocytosis, metabolism and lipid storage.

Parkinson's Disease (PD) is a common neurodegenerative disorder affecting millions of people worldwide for which there are only symptomatic therapies. Small molecules able to target key pathological processes in PD have emerged as interesting options for modifying disease progression. We have previously shown that a (poly)phenol-enriched fraction (PEF) of Corema album L. leaf extract modulates central events in PD pathogenesis, namely α-synuclein (αSyn) toxicity, aggregation and clearance. PEF was now subjected to a bio-guided fractionation with the aim of identifying the critical bioactive compound. We identified genipin, an iridoid, which relieves αSyn toxicity and aggregation. Furthermore, genipin promotes metabolic alterations and modulates lipid storage and endocytosis. Importantly, genipin was able to prevent the motor deficits caused by the overexpression of αSyn in a Drosophila melanogaster model of PD. These findings widens the possibility for the exploitation of genipin for PD therapeutics.

Design of a microfluidic mixer channel: First steps into creating a fluorescent dye-based biosensor for mAb aggregate detection.

A major challenge in the transition to continuous biomanufacturing is the lack of process analytical technology (PAT) tools which are able to collect real-time information on the process and elicit a response to facilitate control. One of the critical quality attributes (CQAs) of interest during monoclonal antibodies production is aggregate formation. The development of a real-time PAT tool to monitor aggregate formation is then crucial to have immediate feedback and process control. Miniaturized sensors placed after each unit operation can be a powerful solution to speed up an analytical measurement due to their characteristic short reaction time. In this work, a micromixer structure capable of mixing two streams is presented, to be employed in the detection of mAb aggregates using fluorescent dyes. Computational fluid dynamics (CFD) simulations were used to compare the mixing performance of a series of the proposed designs. A final design of a zigzag microchannel with 45° angle was reached and this structure was subsequently fabricated and experimentally validated with colour dyes and, later, with a FITC-IgG molecule. The designed zigzag micromixer presents a mixing index of around 90%, obtained in less than 30 seconds. Therefore, a micromixer channel capable of a fast and efficient mixing is hereby demonstrated, to be used as a real-time PAT tool for a fluorescence based detection of protein aggregation.

Small, smaller, smallest: Miniaturization of chromatographic process development.

Biopharmaceuticals are becoming increasingly important in modern healthcare. Monoclonal antibodies (mAb) are one of the most widely used therapeutic proteins and are important for the treatment of cancer and autoimmune diseases, among others. After cell culture there are still large amounts of other impurities (e.g. host cell proteins) in solution. Chromatography is usually the first purification step, allowing to increase purity and reduce volume. This comes associated with high costs and chromatography accounts for a significant portion of total production costs for therapeutic proteins. Chromatographic process development may be time consuming and use large amounts of resins. Therefore, there is increased interest in finding cheaper techniques for chromatographic process development without compromising accuracy. This paper presents a highly sophisticated microfluidic chip approach for efficient adsorption isotherm determinations compared to current chromatographic process development. Implementation of an image analysis software ensures that chromatographic resin volume is accurately determined. The adsorption isotherm performance of microfluidics was compared to the robotic Liquid-handling Station (LHS) and labor intensive Eppendorf tubes. The microfluidic chip allows a 15-fold volume reduction and resin consumptions as low as 100/200 nl (200/100-fold reduction). The microfluidic chip performed comparably to the other miniaturized techniques, using less liquid and resin volume. For process development of expensive products (e.g. monoclonal antibodies), miniaturization (provided by the microfluidic chip) proved to be the most cost effective alternative whereas for less valuable products (e.g. lysozyme) automation (provided by the LHS) was the most cost effective alternative.

Recent advances to accelerate purification process development: A review with a focus on vaccines.

The safety requirements for vaccines are extremely high since they are administered to healthy people. For that reason, vaccine development is time-consuming and very expensive. Reducing time-to-market is key for pharmaceutical companies, saving lives and money. Therefore the need is raised for systematic, general and efficient process development strategies to shorten development times and enhance process understanding. High throughput technologies tremendously increased the volume of process-related data available and, combined with statistical and mechanistic modeling, new high throughput process development (HTPD) approaches evolved. The introduction of model-based HTPD enabled faster and broader screening of conditions, and furthermore increased knowledge. Model-based HTPD has particularly been important for chromatography, which is a crucial separation technique to attain high purities. This review provides an overview of downstream process development strategies and tools used within the (bio)pharmaceutical industry, focusing attention on (protein subunit) vaccine purification processes. Subsequently high throughput process development and other combinatorial approaches are discussed and compared according to their experimental effort and understanding. Within a growing sea of information, novel modeling tools and artificial intelligence (AI) gain importance for finding patterns behind the data and thereby acquiring a deeper process understanding.

White paper on high-throughput process development for integrated continuous biomanufacturing.

Continuous manufacturing is an indicator of a maturing industry, as can be seen by the example of the petrochemical industry. Patent expiry promotes a price competition between manufacturing companies, and more efficient and cheaper processes are needed to achieve lower production costs. Over the last decade, continuous biomanufacturing has had significant breakthroughs, with regulatory agencies encouraging the industry to implement this processing mode. Process development is resource and time consuming and, although it is increasingly becoming less expensive and faster through high-throughput process development (HTPD) implementation, reliable HTPD technology for integrated and continuous biomanufacturing is still lacking and is considered to be an emerging field. Therefore, this paper aims to illustrate the major gaps in HTPD and to discuss the major needs and possible solutions to achieve an end-to-end Integrated Continuous Biomanufacturing, as discussed in the context of the 2019 Integrated Continuous Biomanufacturing conference. The current HTPD state-of-the-art for several unit operations is discussed, as well as the emerging technologies which will expedite a shift to continuous biomanufacturing.

Enzymatic Hydrolysis of Sugarcane Bagasse in Aqueous Two-Phase Systems (ATPS): Exploration and Conceptual Process Design.

The enzymatic conversion of lignocellulosic material to sugars can provide a carbon source for the production of energy (fuels) and a wide range of renewable products. However, the efficiency of this conversion is impaired due to product (sugar) inhibition. Even though several studies investigate how to overcome this challenge, concepts on the process to conduct the hydrolysis are still scarce in literature. Aqueous two-phase systems (ATPS) can be applied to design an extractive reaction due to their capacity to partition solutes to different phases in such a system. This work presents strategies on how to conduct extractive enzymatic hydrolysis in ATPS and how to explore the experimental results in order to design a feasible process. While only a limited number of ATPS was explored, the methods and strategies described could easily be applied to any further ATPS to be explored. We studied two promising ATPS as a subset of a previously high throughput screened large set of ATPS, providing two configurations of processes having the reaction in either the top phase or in the bottom phase. Enzymatic hydrolysis in these ATPS was performed to evaluate the partitioning of the substrate and the influence of solute partitioning on conversion. Because ATPS are able to partition inhibitors (sugar) between the phases, the conversion rate can be maintained. However, phase forming components should be selected to preserve the enzymatic activity. The experimental results presented here contribute to a feasible ATPS-based conceptual process design for the enzymatic conversion of lignocellulosic material.

Anything but Conventional Chromatography Approaches in Bioseparation.

While packed bed chromatography, known as conventional chromatography, has been serving the biopharmaceutical industry for decades as the bioseparation method of choice, alternative approaches are likely to take an increasing leading role in the next few years. The high number of new biological drugs under development, and the need to make biopharmaceuticals widely accessible, has been driving the academia and industry in the quest of anything but conventional chromatography approaches. In this perspective paper, these alternative approaches are discussed in view of current and future challenges in the downstream processing field.

Systematic Investigation of Insulin Fibrillation on a Chip.

A microfluidic protein aggregation device (microPAD) that allows the user to perform a series of protein incubations with various concentrations of two reagents is demonstrated. The microfluidic device consists of 64 incubation chambers to perform individual incubations of the protein at 64 specific conditions. Parallel processes of metering reagents, stepwise concentration gradient generation, and mixing are achieved simultaneously by pneumatic valves. Fibrillation of bovine insulin was selected to test the device. The effect of insulin and sodium chloride (NaCl) concentration on the formation of fibrillar structures was studied by observing the growth rate of partially folded protein, using the fluorescent marker Thioflavin-T. Moreover, dual gradients of different NaCl and hydrochloric acid (HCl) concentrations were formed, to investigate their interactive roles in the formation of insulin fibrils and spherulites. The chip-system provides a bird's eye view on protein aggregation, including an overview of the factors that affect the process and their interactions. This microfluidic platform is potentially useful for rapid analysis of the fibrillation of proteins associated with many misfolding-based diseases, such as quantitative and qualitative studies on amyloid growth.

A robotic platform to screen aqueous two-phase systems for overcoming inhibition in enzymatic reactions.

Aqueous two-phase systems (ATPS) can be applied to enzymatic reactions that are affected by product inhibition. In the biorefinery context, sugars inhibit the cellulolytic enzymes in charge of converting the biomass. Here, we present a strategy to select an ATPS (formed by polymer and salt) that can separate sugar and enzymes. This automated and miniaturized method is able to determine phase diagrams and partition coefficients of solutes in these. Tailored approaches to quantify the solutes are presented, taking into account the limitations of techniques that can be applied with ATPS due to the interference of phase forming components with the analytics. The developed high-throughput (HT) platform identifies suitable phase forming components and the tie line of operation. This fast methodology proposes to screen up to six different polymer-salt systems in eight days and supplies the results to understand the influence of sugar and protein concentrations on their partition coefficients.

The Investigation of Protein Diffusion via H-Cell Microfluidics.

In this study, we developed a microfluidics method, using a so-called H-cell microfluidics device, for the determination of protein diffusion coefficients at different concentrations, pHs, ionic strengths, and solvent viscosities. Protein transfer takes place in the H-cell channels between two laminarly flowing streams with each containing a different initial protein concentration. The protein diffusion coefficients are calculated based on the measured protein mass transfer, the channel dimensions, and the contact time between the two streams. The diffusion rates of lysozyme, cytochrome c, myoglobin, ovalbumin, bovine serum albumin, and etanercept were investigated. The accuracy of the presented methodology was demonstrated by comparing the measured diffusion coefficients with literature values measured under similar solvent conditions using other techniques. At low pH and ionic strength, the measured lysozyme diffusion coefficient increased with the protein concentration gradient, suggesting stronger and more frequent intermolecular interactions. At comparable concentration gradients, the measured lysozyme diffusion coefficient decreased drastically as a function of increasing ionic strength (from zero onwards) and increasing medium viscosity. Additionally, a particle tracing numerical simulation was performed to achieve a better understanding of the macromolecular displacement in the H-cell microchannels. It was found that particle transfer between the two channels tends to speed up at low ionic strength and high concentration gradient. This confirms the corresponding experimental observation of protein diffusion measured via the H-cell microfluidics.

Identification and Microbial Production of the Raspberry Phenol Salidroside that Is Active against Huntington's Disease.

Edible berries are considered to be among nature's treasure chests as they contain a large number of (poly)phenols with potentially health-promoting properties. However, as berries contain complex (poly)phenol mixtures, it is challenging to associate any interesting pharmacological activity with a single compound. Thus, identification of pharmacologically interesting phenols requires systematic analyses of berry extracts. Here, raspberry (Rubus idaeus, var Prestige) extracts were systematically analyzed to identify bioactive compounds against pathological processes of neurodegenerative diseases. Berry extracts were tested on different Saccharomyces cerevisiae strains expressing disease proteins associated with Alzheimer's, Parkinson's, or Huntington's disease, or amyotrophic lateral sclerosis. After identifying bioactivity against Huntington's disease, the extract was fractionated and the obtained fractions were tested in the yeast model, which revealed that salidroside, a glycosylated phenol, displayed significant bioactivity. Subsequently, a metabolic route to salidroside was reconstructed in S cerevisiae and Corynebacterium glutamicum The best-performing S cerevisiae strain was capable of producing 2.1 mm (640 mg L-1) salidroside from Glc in shake flasks, whereas an engineered C glutamicum strain could efficiently convert the precursor tyrosol to salidroside, accumulating up to 32 mm (9,700 mg L-1) salidroside in bioreactor cultivations (yield: 0.81 mol mol-1). Targeted yeast assays verified that salidroside produced by both organisms has the same positive effects as salidroside of natural origin.

Polyphenol Liquid-Liquid Extraction Process Development Using NRTL-SAC.

Liquid-liquid extraction (LLE) can be an effective strategy for the purification of polyphenols from a fermentation broth. However, solvents need to be chosen to ensure high extraction capacity and selectivity. For that purpose, a systematic study is here presented, where the partition of different polyphenols-naringin, naringenin, p-coumaric acid, and trans-resveratrol-was measured in different solvents and solvent mixtures and described using the semipredictive NRTL-SAC model. The minimum average absolute deviation obtained, based on predicted activity coefficients, was of 40%. With the exception of naringin, the NRTL-SAC molecular descriptors were estimated using solubility data already available in the literature. The obtained results made it possible to propose suitable LLE-based downstream process schemes for two possible purification scenarios: the recovery of trans-resveratrol and the purification of both naringenin and trans-resveratrol, two similar hydrophobic polyphenols, both from a fermentation broth containing hydrophilic impurities (e.g., sugars, proteins).

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

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