High throughput process development workflow with advanced decision-support for antibody purification.

Chromatography remains the workhorse in antibody purification; however process development and characterisation still require significant resources. The high number of operating parameters involved requires extensive experimentation, traditionally performed at small- and pilot-scale, leading to demands in terms of materials and time that can be a challenge. The main objective of this research was the establishment of a novel High Throughput Process Development (HTPD) workflow combining scale-down chromatography experimentation with advanced decision-support techniques in order to minimise the consumption of resources and accelerate the development timeframe. Additionally, the HTPD workflow provides a framework to rapidly manipulate large datasets in an automated fashion. The central component of the HTPD workflow is the systematic integration of a microscale chromatography experimentation strategy with an advanced chromatogram evaluation method, design of experiments (DoE) and multivariate data analysis. The outputs of this are leveraged into the screening and optimisation components of the workflow. For the screening component, a decision-support tool was developed combining different multi-criteria decision-making techniques to enable a fair comparison of a number of CEX resin candidates and determine those that demonstrate superior purification performance. This provided a rational methodology for screening chromatography resins and process parameters. For the optimisation component, the workflow leverages insights provided through screening experimentation to guide subsequent DoE experiments so as to tune significant process parameters for the selected resin. The resulting empirical correlations are linked to a stochastic modelling technique so as to predict the optimal and most robust chromatographic process parameters to achieve the desired performance criteria.

Data-driven multi-objective optimization via grid compatible simplex technique and desirability approach for challenging high throughput chromatography applications.

Recently, a grid compatible Simplex variant has been demonstrated to identify optima consistently and rapidly in challenging high throughput (HT) applications in early bioprocess development. Here, this method is extended by deploying it to multi-objective optimization problems. Three HT chromatography case studies are presented, each posing challenging early development situations and including three responses which were amalgamated by the adoption of the desirability approach. The suitability of a design of experiments (DoE) methodology per case study, using regression analysis in addition to the desirability approach, was evaluated for a large number of weights and in the presence of stringent and lenient performance requirements. Despite the adoption of high-order models, this approach had low success in identification of the optimal conditions. For the deployment of the Simplex approach, the deterministic specification of the weights of the merged responses was avoided by including them as inputs in the formulated multi-objective optimization problem, facilitating this way the decision making process. This, and the ability of the Simplex method to locate optima, rendered the presented approach highly successful in delivering rapidly operating conditions, which belonged to the Pareto set and offered a superior and balanced performance across all outputs compared to alternatives. Moreover, its performance was relatively independent of the starting conditions and required sub-minute computations despite its higher order mathematical functionality compared to DoE techniques. These evidences support the suitability of the grid compatible Simplex method for early bioprocess development studies involving complex data trends over multiple responses. © 2018 The Authors Biotechnology Progress published by Wiley Periodicals, Inc. on behalf of American Institute of Chemical Engineers Biotechnol. Prog., 34:1393-1406, 2018.

Economic evaluation of the primary recovery of tetracycline with traditional and novel aqueous two-phase systems.

Antibiotics are a key pharmaceutical to inhibit growth or kill microorganisms. They represent a profitable market and, in particular, tetracycline has been listed as an essential medicine by the WHO. Therefore it is important to improve their production processes. Recently novel and traditional aqueous two-phase systems for the extraction have been developed with positive results. The present work performs an economic analysis of the production and recovery of tetracycline through the use of several ATPS through bioprocess modeling using specialized software (BioSolve, Biopharm Services Ltd, UK) to determine production costs per gram (CoG/g). First, a virtual model was constructed using published data on the recovery of tetracycline and extended to incorporate uncertainties. To determine how the model behaved, a sensitivity analysis and Monte Carlo simulations were performed. Results showed that ATPS formed by cholinium chloride/K3PO4 was the best option to recover tetracycline, as it had the lowest CoG/g (US$ 672.83/g), offered the highest recovery yield (92.42%), second best sample input capacity (45% of the ATPS composition) and one of the lowest materials contribution to cost. The ionic liquid-based method of ATPS is a promising alternative for recovering tetracycline from fermentation broth.

Effects of bed compression on protein separation on gel filtration chromatography at bench and pilot scale.

BACKGROUND: Poorly packed chromatography columns are known to reduce drastically the column efficiency and produce broader peaks. Controlled bed compression has been suggested to be a useful approach for solving this problem. Here the relationship between column efficiency and resolution of protein separation are examined when preparative chromatography media were compressed using mechanical and hydrodynamic methods. Sepharose CL-6B, an agarose based size exclusion media was examined at bench and pilot scale. The asymmetry and height equivalent of a theoretical plate (HETP) was determined by using 2% v/v acetone, whereas the void volume and intraparticle porosity (ϵ p) were estimated by using blue dextran. A protein mixture of ovalbumin (chicken), bovine serum albumin (BSA) and γ'- globulin (bovine) with molecular weights of 44, 67 and 158 kDa, respectively, were used as a 'model' separation challenge. RESULTS: Mechanical compression achieved a reduction in plate height for the column with a concomitant improvement in asymmetry. Furthermore, the theoretical plate height decreased significantly with mechanical compression resulting in a 40% improvement in purity compared with uncompressed columns at the most extreme conditions of compression used. CONCLUSION: The results suggest that the mechanical bed compression of Sepharose CL-6B can be used to improve the resolution of protein separation. © 2017 The Authors. Journal of Chemical Technology & Biotechnology published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Optimization-based framework for resin selection strategies in biopharmaceutical purification process development.

This work addresses rapid resin selection for integrated chromatographic separations when conducted as part of a high-throughput screening exercise during the early stages of purification process development. An optimization-based decision support framework is proposed to process the data generated from microscale experiments to identify the best resins to maximize key performance metrics for a biopharmaceutical manufacturing process, such as yield and purity. A multiobjective mixed integer nonlinear programming model is developed and solved using the ε-constraint method. Dinkelbach's algorithm is used to solve the resulting mixed integer linear fractional programming model. The proposed framework is successfully applied to an industrial case study of a process to purify recombinant Fc Fusion protein from low molecular weight and high molecular weight product related impurities, involving two chromatographic steps with eight and three candidate resins for each step, respectively. The computational results show the advantage of the proposed framework in terms of computational efficiency and flexibility. © 2017 The Authors Biotechnology Progress published by Wiley Periodicals, Inc. on behalf of American Institute of Chemical Engineers Biotechnol. Prog., 33:1116-1126, 2017.

Life-cycle and cost of goods assessment of fed-batch and perfusion-based manufacturing processes for mAbs.

Life-cycle assessment (LCA) is an environmental assessment tool that quantifies the environmental impact associated with a product or a process (e.g., water consumption, energy requirements, and solid waste generation). While LCA is a standard approach in many commercial industries, its application has not been exploited widely in the bioprocessing sector. To contribute toward the design of more cost-efficient, robust and environmentally-friendly manufacturing process for monoclonal antibodies (mAbs), a framework consisting of an LCA and economic analysis combined with a sensitivity analysis of manufacturing process parameters and a production scale-up study is presented. The efficiency of the framework is demonstrated using a comparative study of the two most commonly used upstream configurations for mAb manufacture, namely fed-batch (FB) and perfusion-based processes. Results obtained by the framework are presented using a range of visualization tools, and indicate that a standard perfusion process (with a pooling duration of 4 days) has similar cost of goods than a FB process but a larger environmental footprint because it consumed 35% more water, demanded 17% more energy, and emitted 17% more CO2 than the FB process. Water consumption was the most important impact category, especially when scaling-up the processes, as energy was required to produce process water and water-for-injection, while CO2 was emitted from energy generation. The sensitivity analysis revealed that the perfusion process can be made more environmentally-friendly than the FB process if the pooling duration is extended to 8 days. © 2016 American Institute of Chemical Engineers Biotechnol. Prog., 32:1324-1335, 2016.

Integrated economic and experimental framework for screening of primary recovery technologies for high cell density CHO cultures.

Increases in mammalian cell culture titres and densities have placed significant demands on primary recovery operation performance. This article presents a methodology which aims to screen rapidly and evaluate primary recovery technologies for their scope for technically feasible and cost-effective operation in the context of high cell density mammalian cell cultures. It was applied to assess the performance of current (centrifugation and depth filtration options) and alternative (tangential flow filtration (TFF)) primary recovery strategies. Cell culture test materials (CCTM) were generated to simulate the most demanding cell culture conditions selected as a screening challenge for the technologies. The performance of these technology options was assessed using lab scale and ultra scale-down (USD) mimics requiring 25-110mL volumes for centrifugation and depth filtration and TFF screening experiments respectively. A centrifugation and depth filtration combination as well as both of the alternative technologies met the performance selection criteria. A detailed process economics evaluation was carried out at three scales of manufacturing (2,000L, 10,000L, 20,000L), where alternative primary recovery options were shown to potentially provide a more cost-effective primary recovery process in the future. This assessment process and the study results can aid technology selection to identify the most effective option for a specific scenario.

Economic analysis of uricase production under uncertainty: Contrast of chromatographic purification and aqueous two-phase extraction (with and without PEG recycle).

Uricase is the enzyme responsible for the breakdown of uric acid, the key molecule leading to gout in humans, into allantoin, but it is absent in humans. It has been produced as a PEGylated pharmaceutical where the purification is performed through three sequential chromatographic columns. More recently an aqueous two-phase system (ATPS) was reported that could recover Uricase with high yield and purity. Although the use of ATPS can decrease cost and time, it also generates a large amount of waste. The ability, therefore, to recycle key components of ATPS is of interest. Economic modelling is a powerful tool that allows the bioprocess engineer to compare possible outcomes and find areas where further research or optimization might be required without recourse to extensive experiments and time. This research provides an economic analysis using the commercial software BioSolve of the strategies for Uricase production: chromatographic and ATPS, and includes a third bioprocess that uses material recycling. The key parameters that affect the process the most were located via a sensitivity analysis and evaluated with a Monte Carlo analysis. Results show that ATPS is far less expensive than chromatography, but that there is an area where the cost of production of both bioprocesses overlap. Furthermore, recycling does not impact the cost of production. This study serves to provide a framework for the economic analysis of Uricase production using alternative techniques.

Economic analysis of Royalactin production under uncertainty: Evaluating the effect of parameter optimization.

Royalactin is a protein with several different potential uses in humans. Research, in insects and in mammalian cells, has shown that it can accelerate cell division and prevent apoptosis. The method of action is through the use of the epidermal growth factor receptor, which is present in humans. Potential use in humans could be to lower cholesterolemic levels in blood, and to elicit similar effects to those seen in bees, e.g., increased lifespan. Mass production of Royalactin has not been accomplished, though a recent article presented a Pichia pastoris fermentation and recovery by aqueous two-phase systems at laboratory scale as a possible basis for production. Economic modelling is a useful tool with which compare possible outcomes for the production of such a molecule and in particular, to locate areas where additional research is needed and optimization may be required. This study uses the BioSolve software to perform an economic analysis on the scale-up of the putative process for Royalactin. The key parameters affecting the cost of production were located via a sensitivity analysis and then evaluated by Monte Carlo analysis. Results show that if titer is not optimized the strategy to maintain a low cost of goods is process oriented. After optimization of this parameter the strategy changes to a product-oriented and the target output becomes the critical parameter determining the cost of goods. This study serves to provide a framework for the evaluation of strategies for future production of Royalactin, by analyzing the factors that influence its cost of manufacture.

Representative mammalian cell culture test materials for assessment of primary recovery technologies: a rapid method with industrial applicability.

Mammalian cell culture material is often difficult to produce accurately and reproducibly for downstream studies. This article presents a methodology for the creation of a set of cell culture test materials where key variables including cell density, cell viability, product, and the host cell protein (HCP) load can be manipulated individually. The methodology was developed using a glutamine synthetase Chinese hamster ovary cell line cultured at 5-L and 70-L scales. Cell concentration post-cell growth was manipulated using tangential flow filtration to generate a range of target cell densities of up to 100 × 10(6) cells/mL. A method to prepare an apoptotic cell stock to achieve target viabilities of 40-90% is also described. In addition, a range of IgG1 and HCP concentrations was achieved. The results illustrate that the proposed methodology is able to mimic different cell culture profiles by decoupling the control of the key variables. The cell culture test materials were shown to be representative of typical cell culture feed material in terms of particle size distribution and HCP population. This provides a rapid method to create the required feeds for assessing the feasibility of primary recovery technologies designed to cope with higher cell density cultures.

Integration of host strain bioengineering and bioprocess development using ultra-scale down studies to select the optimum combination: an antibody fragment primary recovery case study.

An ultra scale-down primary recovery sequence was established for a platform E. coli Fab production process. It was used to evaluate the process robustness of various bioengineered strains. Centrifugal discharge in the initial dewatering stage was determined to be the major cause of cell breakage. The ability of cells to resist breakage was dependant on a combination of factors including host strain, vector, and fermentation strategy. Periplasmic extraction studies were conducted in shake flasks and it was demonstrated that key performance parameters such as Fab titre and nucleic acid concentrations were mimicked. The shake flask system also captured particle aggregation effects seen in a large scale stirred vessel, reproducing the fine particle size distribution that impacts the final centrifugal clarification stage. The use of scale-down primary recovery process sequences can be used to screen a larger number of engineered strains. This can lead to closer integration with and better feedback between strain development, fermentation development, and primary recovery studies.

Investigating the use of column inserts to achieve better chromatographic bed support.

Chromatography plays an important role in the downstream processing of proteins. Over the past years, there has been a steady move toward the adoption of more rigid, porous particles to combine ease of manufacture with increased levels of productivity. The latter is still constrained by the onset of compression where the level of wall support becomes incapable of withstanding flow-induced particle drag. In this study, we investigate how, by the installation of cylindrical column inserts, it is possible to enhance the level of wall support. Experiments were conducted to examine the effect of the position of the insert in the column, and also of the insert dimensions on the critical velocity at which the onset of compression occurs. It was found that when installed at the bottom of the column, inserts can provide up to a 20% increase in critical velocity without significantly affecting column hydrodynamics, as measured by the level of axial dispersion.

Automated methods for accurate determination of the critical velocity of packed bed chromatography.

Knowing the critical velocity (ucrit) of a chromatography column is an important part of process development as it allows the optimization of chromatographic flow conditions. The conventional flow step method for determining ucrit is prone to error as it depends heavily on human judgment. In this study, two automated methods for determining ucrit have been developed: the automatic flow step (AFS) method and the automatic pressure step (APS) method. In the AFS method, the column pressure drop is monitored upon application of automated incremental increases in flow velocity, whereas in the APS method the flow velocity is monitored upon application of automated incremental increases in pressure drop. The APS method emerged as the one with the higher levels of accuracy, efficiency and ease of application having the greater potential to assist defining the best operational parameters of a chromatography column.

Demonstration of the use of windows of operation to visualize the effects of fouling on the performance of a chromatographic step.

The high resolution afforded by packed bed chromatography makes it an indispensable operation in the downstream processing of therapeutic molecules. Packed bed performance is however inherently susceptible to changes in feed stream characteristics and fouling processes. The impact of fouling is seldom considered during the early stages of bioprocess development which is concerned with the selection of purification conditions. Instead these are performed with rigorously clarified feeds. Under such conditions, chromatography is effectively treated as an isolated step, independent from its preceding unit operations. In this study, we demonstrate how windows of operation could be used to visualize the impact of changes in the preceding clarification step on the fouling response of a subsequent cation exchange capture step. Laboratory columns (2,5 and 12 cm height) were subjected to varying fouling challenges of Escherichia coli lysate containing different amounts of solids carried over from the previous step. Changes in trans-column pressure drop and breakthrough of the target protein (Fab') were monitored. The limits of operability of the resin were determined with respect to the process material's properties. This information was used to extract the parameters for the adsorption kinetics used in the general rate (GR) model to create windows of operation for manufacturing scale operation.

Integrated use of ultra scale-down and financial modeling to identify optimal conditions for the precipitation and centrifugal recovery of milk proteins.

This article investigates the integrated application of ultra scale-down (USD) techniques and economic modeling as a means for identifying optimal bioprocess operating conditions. The benefits of the approach are illustrated for the recovery of lactoperoxidase (LPO) from bovine milk. In the process, milk is skimmed to deplete its lipid content, before being subjected to low pH incubation with acetic acid in order to precipitate the primary impurity (casein). Following removal of the solids by disk stack centrifugation, pH adjustment and filtration, cation exchange chromatography is used as a positive mode column step to bind the LPO before it is polished and freeze dried. An economic model of this process was used to identify where greatest product loss occurs and hence where the largest opportunity cost was being incurred. Scale-down analysis was used to characterize the influence of the critical steps, identified as precipitation and centrifugation, upon LPO recovery. A mathematical model was used to relate the centrifuge feed flowrate and discharge interval to the supernatant yield, and it was shown that increasing the centrifugal solids residence time achieved superior solids de-watering and so higher product yield, although this also increased the overall processing time. To resolve this conflict, scale-down data were used again in conjunction with an economic model to determine the most suitable conditions that maximized annual profit and minimized operating costs. The results demonstrate the power of combining USD data with models of economic and process performance in order to establish the best overall operating strategies for biopharmaceutical manufacture.

The simplex algorithm for the rapid identification of operating conditions during early bioprocess development: case studies in FAb' precipitation and multimodal chromatography.

This study describes a data-driven algorithm as a rapid alternative to conventional Design of Experiments (DoE) approaches for identifying feasible operating conditions during early bioprocess development. In general, DoE methods involve fitting regression models to experimental data, but if model fitness is inadequate then further experimentation is required to gain more confidence in the location of an optimum. This can be undesirable during very early process development when feedstock is in limited supply and especially if a significant percentage of the tested conditions are ultimately found to be sub-optimal. An alternative approach involves focusing solely upon the feasible regions by using the knowledge gained from each condition to direct the choice of subsequent test locations that lead towards an optimum. To illustrate the principle, this study describes the application of the Simplex algorithm which uses accumulated knowledge from previous test points to direct the choice of successive conditions towards better regions. The method is illustrated by two case studies; a two variable precipitation example investigating how salt concentration and pH affect FAb' recovery from E. coli homogenate and a three-variable chromatography example identifying the optimal pH and concentrations of two salts in an elution buffer used to recover ovine antibody bound to a multimodal cation exchange matrix. Two-level and face-centered central composite regression models were constructed for each study and statistical analysis showed that they provided a poor fit to the data, necessitating additional experimentation to confirm the robust regions of the search space. By comparison, the Simplex algorithm identified a good operating point using 50% and 70% fewer conditions for the precipitation and chromatography studies, respectively. Hence, data-driven approaches have significant potential for early process development when material supply is at a premium.

An automated packed protein G micro-pipette tip assay for rapid quantification of polyclonal antibodies in ovine serum.

The demands on the biopharmaceutical sector to expedite process development have instigated the deployment of micro-biochemical engineering techniques to acquire manufacturing insight with extremely small sample volumes. In conjunction with automated liquid handlers, this permits the simultaneous evaluation of multiple operating conditions and reduces manual intervention. For these benefits to be sustained, novel ways are now required to accelerate analysis and so prevent this becoming a throughput bottleneck. For example, although Protein G HPLC is used to quantify antibody titres in bioprocess feedstocks, it can be time-consuming owing to the serial nature of its application. Although commercial options are available that can process many samples simultaneously, these require separate, potentially expensive instruments. A more integrated approach is desirable wherein the assay is implemented directly on a robot. This article describes a high-throughput alternative to antibody HPLC analysis which uses an eight-channel liquid handler to control pipette tips packed with 40 µL of Protein G affinity matrix. The linearity, range, limit of detection, specificity and precision of the method were established, with results showing that antibody was detected reliably and specifically between 0.10 and 1.00 mg/mL. Subsequently, the technique was used to quantify the antibody titre in ovine serum, which is used as feed material by BTG PLC for manufacturing FDA-approved polyclonal bio-therapeutics. The mean concentration determined by the tips was comparable to that found by HPLC, but the tip method delivered its results in less than 40% of the time and with the potential for further, substantial time-savings possible by using higher capacity robots.

Exploiting the intracellular compartmentalization characteristics of the S. cerevisiae host cell for enhancing primary purification of lipid-envelope virus-like particles.

This article demonstrates how the intracellular compartmentalization of the S. cerevisiae host cell can be exploited to impart selectivity during the primary purification of lipid-envelope virus-like particles (VLPs). The hepatitis B surface antigen (HBsAg) was used as the VLP model in this study. Expressed HBsAg remain localized on the endoplasmic reticulum and the recovery process involves treating cell homogenate with a detergent for HBsAg liberation. In our proposed strategy, a centrifugation step is introduced immediately following cell disruption but prior to the addition of detergent to allow the elimination of bulk cytosolic contaminants in the supernatant, achieving approximately 70% reduction of contaminating yeast proteins, lipids, and nucleic acids. Recovery and subsequent treatment of the solids fraction with detergent then releases the HBsAg into a significantly enriched product stream with a yield of approximately 80%. The selectivity of this approach is further enhanced by operating under moderate homogenization pressure conditions ( approximately 400 bar). Observed improvements in the recovery of active HBsAg and reduction of contaminating host lipids were attributed to the low-shear conditions experienced by the HBsAg product and reduced cell fragmentation, which led to lower coextraction of lipids during the detergent step. As a result of the cleaner process stream, the level of product capture during the loading stage of a downstream hydrophobic interaction chromatography stage increased by two-fold leading to a concomitant increase in the chromatography step yield. The lower level of exposure to contaminants is also expected to improve column integrity and lifespan.

High-throughput screening techniques for rapid PEG-based precipitation of IgG4 mAb from clarified cell culture supernatant.

Locating optimal protein precipitation conditions for complex biological feed materials is problematic. This article describes the application of a series of high-throughput platforms for the rapid identification and selection of conditions for the precipitation of an IgG(4) monoclonal antibody (mAb) from a complex feedstock using only microliter quantities of material. The approach uses 96-microwell filter plates combined with high-throughput analytical methods and a method for well volume determination for product quantification. The low material, time and resource requirements facilitated the use of a full factorial Design of Experiments (DoE) for the rapid investigation into how critical parameters impact the IgG(4) precipitation. To aid the DoE, a set of preliminary range-finding studies were conducted first. Data collected through this approach describing Polyethylene Glycol (PEG) precipitation of the IgG(4) as a function of mAb concentration, precipitant concentration, and pH are presented. Response surface diagrams were used to explore interactions between parameters and to inform selection of the most favorable conditions for maximum yield and purification. PEG concentrations required for maximum yield and purity were dependant on the IgG(4) concentration; however, concentrations of 14 to 20% w/v, pH 6.5, gave optimal levels of yield and purity. Application of the high-throughput approach enabled 1,155 conditions to be examined with less than 1 g of material. The level of insights gained over such a short time frame is indicative of the power of microwell experimentation in allowing the rapid identification of appropriate processing conditions for key bioprocess operations.

Application of agent-based system for bioprocess description and process improvement.

Modeling plays an important role in bioprocess development for design and scale-up. Predictive models can also be used in biopharmaceutical manufacturing to assist decision-making either to maintain process consistency or to identify optimal operating conditions. To predict the whole bioprocess performance, the strong interactions present in a processing sequence must be adequately modeled. Traditionally, bioprocess modeling considers process units separately, which makes it difficult to capture the interactions between units. In this work, a systematic framework is developed to analyze the bioprocesses based on a whole process understanding and considering the interactions between process operations. An agent-based approach is adopted to provide a flexible infrastructure for the necessary integration of process models. This enables the prediction of overall process behavior, which can then be applied during process development or once manufacturing has commenced, in both cases leading to the capacity for fast evaluation of process improvement options. The multi-agent system comprises a process knowledge base, process models, and a group of functional agents. In this system, agent components co-operate with each other in performing their tasks. These include the description of the whole process behavior, evaluating process operating conditions, monitoring of the operating processes, predicting critical process performance, and providing guidance to decision-making when coping with process deviations. During process development, the system can be used to evaluate the design space for process operation. During manufacture, the system can be applied to identify abnormal process operation events and then to provide suggestions as to how best to cope with the deviations. In all cases, the function of the system is to ensure an efficient manufacturing process. The implementation of the agent-based approach is illustrated via selected application scenarios, which demonstrate how such a framework may enable the better integration of process operations by providing a plant-wide process description to facilitate process improvement.