Early Bioprocess Development Research Articles

Mass spectrometry-based multi-attribute method for mutation analysis in the early development of therapeutic proteins

The early intervention is essential, and later development cannot compensate for this initial generation of an antibody drug. Especially for sequence variants (SVs), should cause concern during the early bioprocess development. The advancement of bioprocess development is paralleled by development of state-of-the-art analytical methods that will provide further information. In the present study, a mass spectrometry (MS)-based multi-attribute method (MAM) was used to simultaneously monitor the SVs and other quality attributes in the early bioprocess development of ofatumumab, and a sequence variant (SV) was detected by a subunit-based MAM. Subsequently, the variant was further identified by MS/MS and confirmed by adding a synthetic peptide. Furthermore, the content of the SV was detected via DNA sequencing. The levels of the variant (T175A mutant) in the light chain were demonstrate to be nearly consistent at the DNA and protein levels, suggesting that the mutation may have negligible effect on both the transcriptional and translational levels. Collectively, these results indicate that broad-spectrum, rapid, and accurate platform such as MS-based MAM should be implemented to quality control for the early development of therapeutic proteins, it will also be important to establish an effective and integrated MAM to control SVs during therapeutic proteins development.

Microscale Perfusion-Based Cultivation for Pichia pastoris Clone Screening Enables Accelerated and Optimized Recombinant Protein Production Processes.

Pichia pastoris has emerged in the past years as a promising host for recombinant protein and biopharmaceutical production. In the establishment of high cell density fed-batch biomanufacturing, screening phase and early bioprocess development (based on microplates and shake flasks) still represent a bottleneck due to high-cost and time-consuming procedures as well as low experiment complexity. In the present work, a screening protocol developed for P. pastoris clone selection is implemented in a multiplexed microfluidic device with 15 μL cultivation chambers able to operate in perfusion mode and monitor dissolved oxygen content in the culture in a non-invasive way. The setup allowed us to establish carbon-limited conditions and evaluate strain responses to different input variables. Results from micro-scale perfusion cultures are then compared with 1L fed-batch fermentation. The best producer in terms of titer and productivity is rapidly identified after 12 h from inoculation and the results confirmed by lab-scale fermentation. Moreover, the physiological analyses of the strains under different conditions suggested how more complex experimental conditions are achievable despite the relatively easy, straight-forward, and cost-effective experimental setup. Implementation and standardization of these micro-scale protocols could reduce the demand for lab-scale bioreactor cultivations thus accelerating the development of protein production processes.

Study on mixing characteristics in shaken microwell systems

Shaken microwell plates are widely used for early bioprocess development as they allow a large number of experiments to be performed in parallel by using small amount of materials. Despite their widespread use, microwell plates have not been characterised from an engineering viewpoint. In this study, mixing time measurements were carried out in two wells of square and cylindrical cross sections for small orbital diameter shaker, do = 3 mm, commonly used in commercial microwell platforms (i.e. ThermoMixer) and compared against measurements obtained in lab scale reactors for larger orbital diameters. The Dual Indicator System for Mixing Time (DISMT) method was employed for all the operating conditions investigated, and a range of rotational speeds was identified where mixing is less effective due to reduced free surface oscillation. An effective scaling parameter between microwell platforms and lab scale reactors was identified based on the natural frequency of the system, which depends only on fill volume, size and cross section of the reactor.

Polymer-based controlled-release fed-batch microtiter plate \u2013 diminishing the gap between early process development and production conditions

BackgroundFed-batch conditions are advantageous for industrial cultivations as they avoid unfavorable phenomena appearing in batch cultivations. Those are for example the formation of overflow metabolites, catabolite repression, oxygen limitation or inhibition due to elevated osmotic concentrations. For both, the early bioprocess development and the optimization of existing bioprocesses, small-scale reaction vessels are applied to ensure high throughput, low costs and prompt results. However, most conventional small-scale procedures work in batch operation mode, which stands in contrast to fed-batch conditions in large-scale bioprocesses. Extensive expenditure for installations and operation accompany almost all cultivation systems in the market allowing fed-batch conditions in small-scale. An alternative, more cost efficient enzymatic glucose release system is strongly influenced by environmental conditions. To overcome these issues, this study investigates a polymer-based fed-batch system for controlled substrate release in microtiter plates.ResultsImmobilizing a solid silicone matrix with embedded glucose crystals at the bottom of each well of a microtiter plate is a suitable technique for implementing fed-batch conditions in microtiter plates. The results showed that the glucose release rate depends on the osmotic concentration, the pH and the temperature of the medium. Moreover, the applied nitrogen source proved to influence the glucose release rate. A new developed mathematical tool predicts the glucose release for various media conditions. The two model organisms E. coli and H. polymorpha were cultivated in the fed-batch microtiter plate to investigate the general applicability for microbial systems. Online monitoring of the oxygen transfer rate and offline analysis of substrate, product, biomass and pH confirmed that fed-batch conditions are comparable to large-scale cultivations. Furthermore, due to fed-batch conditions in microtiter plates, product formation could be enhanced by the factor 245 compared to batch cultivations.ConclusionsThe polymer-based fed-batch microtiter plate represents a sophisticated and cost efficient system to mimic typical industrial fed-batch conditions in small-scale. Thus, a more reliable strain screening and early process development can be performed. A systematical scale-down with low expenditure of work, time and money is possible.

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

High throughput automated microbial bioreactor system used for clone selection and rapid scale-down process optimization.

High throughput automated fermentation systems have become a useful tool in early bioprocess development. In this study, we investigated a 24 x 15 mL single use microbioreactor system, ambr 15f, designed for microbial culture. We compared the fed‐batch growth and production capabilities of this system for two Escherichia coli strains, BL21 (DE3) and MC4100, and two industrially relevant molecules, hGH and scFv. In addition, different carbon sources were tested using bolus, linear or exponential feeding strategies, showing the capacity of the ambr 15f system to handle automated feeding. We used power per unit volume (P/V) as a scale criterion to compare the ambr 15f with 1 L stirred bioreactors which were previously scaled‐up to 20 L with a different biological system, thus showing a potential 1,300 fold scale comparability in terms of both growth and product yield. By exposing the cells grown in the ambr 15f system to a level of shear expected in an industrial centrifuge, we determined that the cells are as robust as those from a bench scale bioreactor. These results provide evidence that the ambr 15f system is an efficient high throughput microbial system that can be used for strain and molecule selection as well as rapid scale‐up. © 2017 The Authors Biotechnology Progress published by Wiley Periodicals, Inc. on behalf of American Institute of Chemical Engineers Biotechnol. Prog., 34:58–68, 2018

Simplex-based optimization of numerical and categorical inputs in early bioprocess development: Case studies in HT chromatography.

Bioprocess development studies often involve the investigation of numerical and categorical inputs via the adoption of Design of Experiments (DoE) techniques. An attractive alternative is the deployment of a grid compatible Simplex variant which has been shown to yield optima rapidly and consistently. In this work, the method is combined with dummy variables and it is deployed in three case studies wherein spaces are comprised of both categorical and numerical inputs, a situation intractable by traditional Simplex methods. The first study employs in silico data and lays out the dummy variable methodology. The latter two employ experimental data from chromatography based studies performed with the filter-plate and miniature column High Throughput (HT) techniques. The solute of interest in the former case study was a monoclonal antibody whereas the latter dealt with the separation of a binary system of model proteins. The implemented approach prevented the stranding of the Simplex method at local optima, due to the arbitrary handling of the categorical inputs, and allowed for the concurrent optimization of numerical and categorical, multilevel and/or dichotomous, inputs. The deployment of the Simplex method, combined with dummy variables, was therefore entirely successful in identifying and characterizing global optima in all three case studies. The Simplex-based method was further shown to be of equivalent efficiency to a DoE-based approach, represented here by D-Optimal designs. Such an approach failed, however, to both capture trends and identify optima, and led to poor operating conditions. It is suggested that the Simplex-variant is suited to development activities involving numerical and categorical inputs in early bioprocess development.

Quantification of the oxygen uptake rate in a dissolved oxygen controlled oscillating jet-driven microbioreactor.

BACKGROUNDMicrobioreactors have emerged as a new tool for early bioprocess development. The technology has advanced rapidly in the last decade and obtaining real‐time quantitative data of process variables is nowadays state of the art. In addition, control over process variables has also been achieved. The aim of this study was to build a microbioreactor capable of controlling dissolved oxygen (DO) concentrations and to determine oxygen uptake rate in real time.RESULTSAn oscillating jet driven, membrane‐aerated microbioreactor was developed without comprising any moving parts. Mixing times of ∼7 s, and kLa values of ∼170 h−1 were achieved. DO control was achieved by varying the duty cycle of a solenoid microvalve, which changed the gas mixture in the reactor incubator chamber. The microbioreactor supported Saccharomyces cerevisiae growth over 30 h and cell densities of 6.7 gdcw L−1. Oxygen uptake rates of ∼34 mmol L−1 h−1 were achieved.CONCLUSIONThe results highlight the potential of DO‐controlled microbioreactors to obtain real‐time information on oxygen uptake rate, and by extension on cellular metabolism for a variety of cell types over a broad range of processing conditions. © 2015 The Authors. Journal of Chemical Technology & Biotechnology published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Electromagnetic stirring in a microbioreactor with non-conventional chamber morphology and implementation of multiplexed mixing.

BACKGROUNDMicrobioreactors have emerged as novel tools for early bioprocess development. Mixing lies at the heart of bioreactor operation (at all scales). The successful implementation of micro‐stirring methods is thus central to the further advancement of microbioreactor technology. The aim of this study was to develop a micro‐stirring method that aids robust microbioreactor operation and facilitates cost‐effective parallelization.RESULTSA microbioreactor was developed with a novel micro‐stirring method involving the movement of a magnetic bead by sequenced activation of a ring of electromagnets. The micro‐stirring method offers flexibility in chamber designs, and mixing is demonstrated in cylindrical, diamond and triangular shaped reactor chambers. Mixing was analyzed for different electromagnet on/off sequences; mixing times of 4.5 s, 2.9 s, and 2.5 s were achieved for cylindrical, diamond and triangular shaped chambers, respectively. Ease of micro‐bubble free priming, a typical challenge of cylindrical shaped microbioreactor chambers, was obtained with a diamond‐shaped chamber. Consistent mixing behavior was observed between the constituent reactors in a duplex system.CONCLUSIONA novel stirring method using electromagnetic actuation offering rapid mixing and easy integration with microbioreactors was characterized. The design flexibility gained enables fabrication of chambers suitable for microfluidic operation, and a duplex demonstrator highlights potential for cost‐effective parallelization. Combined with a previously published cassette‐like fabrication of microbioreactors, these advances will facilitate the development of robust and parallelized microbioreactors. © 2015 The Authors. Journal of Chemical Technology & Biotechnology published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Risk-based Process Development of Biosimilars as Part of the Quality by Design Paradigm

In the last few years, several quality by design (QbD) studies demonstrated the benefit of systematic approaches for biopharmaceutical development. However, only very few studies identified biosimilars as a special case of product development. The targeted quality profile of biosimilars is strictly defined by the originator's product characteristic. Moreover, the major source of prior knowledge is the experience with the originator product itself. Processing this information in biosimilar development has a major effect on risk management and process development strategies. The main objective of this contribution is to demonstrate how risk management can facilitate the implementation of QbD in early-stage product development with special emphasis on fitting the reported approaches to biosimilars. Risk assessments were highlighted as important tools to integrate prior knowledge in biosimilar development. The risk assessment process as suggested by the International Conference on Harmonization (ICH Q9) was reviewed and three elements were identified to play a key role in targeted risk assessment approaches: proper understanding of target linkage, risk assessment tool compliance, and criticality threshold value. Adjusting these steps to biosimilar applications helped to address some unique challenges of these products such as a strictly defined quality profile or a lack of process knowledge. This contribution demonstrates the need for tailored risk management approaches for the risk-based development of biosimilars and provides novel tools for the integration of additional knowledge available for these products. The pharmaceutical industry is facing challenges such as profit loss and price competition. Companies are forced to rationalize business models and to cut costs in development as well as manufacturing. These trends recently hinder the implementation of any concepts that do not offer certain financial benefit or promise a long return of investment. Quality by design (QbD) is a concept that is currently struggling for more acceptance from the side of the pharmaceutical industry. To achieve this, the major goals of QbD have to be revisited and QbD tools have to be subsequently developed. This contribution offers an example as to how implement risk management in early-stage biosimilar development as part of the QbD concept. The main goal was to go beyond the conventional QbD workflow and to adjust risk management to the challenges of biosimilar products. Accordingly, instead of using methods like failure mode and effects analysis, recommendations of the ICH Q9 guideline were reviewed and put into practice by creating tailored risk assessment tools. The novelty of this contribution is to report those tailored tools ready-to-use for early bioprocess development of biosimilars along QbD principles.

Multivariate data analysis as a PAT tool for early bioprocess development data

Early development datasets are typically unstructured, incomplete and truncated, yet they are readily available and contain relevant process information which is not extracted using classical data analysis techniques. In this paper, we illustrate the power of multivariate data analysis (MVDA) as a Process Analytical Technology tool to analyze early development data of a PER.C6® cell cultivation process.MVDA increased our understanding of the process studied. Principal component analysis enabled a thorough exploration of the dataset, identifying causes for batch deviations and revealing sensitivity of the process to scale. These findings were previously undetected using traditional univariate analysis. The lack of structure and gaps in the early development datasets made it impossible to fit them to more advanced partial least square regression models. This paper clearly shows that MVDA should be routinely used to analyze early development data to reveal relevant information for later development and scale-up. The value of these early development runs can be greatly enhanced if the experiments are well-structured and accompanied with full process analytics. This up-front investment will result in shorter and more efficient process development paths, resulting in lower overall development costs for new biopharmaceutical products.

The hybrid experimental simplex algorithm – An alternative method for ‘sweet spot’ identification in early bioprocess development: Case studies in ion exchange chromatography

The capacity to locate efficiently a subset of experimental conditions necessary for the identification of an operating envelope is a key objective in many studies. We have shown previously how this can be performed by using the simplex algorithm and this paper now extends the approach by augmenting the established simplex method to form a novel hybrid experimental simplex algorithm (HESA) for identifying ‘sweet spots’ during scouting development studies. The paper describes the new algorithm and illustrates its use in two bioprocessing case studies conducted in a 96-well filter plate format. The first investigates the effect of pH and salt concentration on the binding of green fluorescent protein, isolated from Escherichia coli homogenate, to a weak anion exchange resin and the second examines the impact of salt concentration, pH and initial feed concentration upon the binding capacities of a FAb′, isolated from E. coli lysate, to a strong cation exchange resin. Compared with the established algorithm, HESA was better at delivering valuable information regarding the size, shape and location of operating ‘sweet spots’ that could then be further investigated and optimized with follow up studies. To test how favorably these features of HESA compared with conventional DoE (design of experiments) methods, HESA results were also compared with approaches including response surface modeling experimental designs. The results show that HESA can return ‘sweet spots’ that are equivalently or better defined than those obtained from DoE approaches. At the same time the deployment of HESA to identify bioprocess-relevant operating boundaries was accompanied by comparable experimental costs to those of DoE methods. HESA is therefore a viable and valuable alternative route for identifying ‘sweet spots’ during scouting studies in bioprocess development.

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.