The Experts below are selected from a list of 4632 Experts worldwide ranked by ideXlab platform
P M Alves - One of the best experts on this subject based on the ideXlab platform.
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Bioprocess Development for canine adenovirus type 2 vectors
Gene Therapy, 2013Co-Authors: P Fernandes, C Peixoto, V M Santiago, E J Kremer, A S Coroadinha, P M AlvesAbstract:Canine adenovirus type 2 (CAV-2) vectors overcome many of the clinical immunogenic concerns related to vectors derived from human adenoviruses (AdVs). In addition, CAV-2 vectors preferentially transduce neurons with an efficient traffic via axons to afferent regions when injected into the brain. To meet the need for preclinical and possibly clinical uses, scalable and robust production processes are required. CAV-2 vectors are currently produced in E1-transcomplementing dog kidney (DK) cells, which might raise obstacles in regulatory approval for clinical grade material production. In this study, a GMP-compliant Bioprocess was developed. An MDCK-E1 cell line, developed by our group, was grown in scalable stirred tank bioreactors, using serum-free medium, and used to produce CAV-2 vectors that were afterwards purified using column chromatographic steps. Vectors produced in MDCK-E1 cells were identical to those produced in DK cells as assessed by SDS-PAGE and dynamic light scatering measurements (diameter and Zeta potential). Productivities of ∼10^9 infectious particles (IP) ml^−1 and 2 × 10^3 IP per cell were possible. A downstream process using technologies transferable to process scales was developed, yielding 63% global recovery. The total particles to IP ratio in the purified product (
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Bioprocess Development for canine adenovirus type 2 vectors
Gene Therapy, 2013Co-Authors: P Fernandes, C Peixoto, V M Santiago, E J Kremer, A S Coroadinha, P M AlvesAbstract:Canine adenovirus type 2 (CAV-2) vectors overcome many of the clinical immunogenic concerns related to vectors derived from human adenoviruses (AdVs). In addition, CAV-2 vectors preferentially transduce neurons with an efficient traffic via axons to afferent regions when injected into the brain. To meet the need for preclinical and possibly clinical uses, scalable and robust production processes are required. CAV-2 vectors are currently produced in E1-transcomplementing dog kidney (DK) cells, which might raise obstacles in regulatory approval for clinical grade material production. In this study, a GMP-compliant Bioprocess was developed. An MDCK-E1 cell line, developed by our group, was grown in scalable stirred tank bioreactors, using serum-free medium, and used to produce CAV-2 vectors that were afterwards purified using column chromatographic steps. Vectors produced in MDCK-E1 cells were identical to those produced in DK cells as assessed by SDS-PAGE and dynamic light scatering measurements (diameter and Zeta potential). Productivities of ∼10(9) infectious particles (IP) ml(-1) and 2 × 10(3) IP per cell were possible. A downstream process using technologies transferable to process scales was developed, yielding 63% global recovery. The total particles to IP ratio in the purified product (<20:1) was within the limits specified by the regulatory authorities for AdV vectors. These results constitute a step toward a scalable process for CAV-2 vector production compliant with clinical material specifications.
Peter Neubauer - One of the best experts on this subject based on the ideXlab platform.
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Accelerated Bioprocess Development of Endopolygalacturonase-Production with Saccharomyces cerevisiae Using Multivariate Prediction in a 48 Mini-Bioreactor Automated Platform.
Bioengineering, 2018Co-Authors: Annina Sawatzki, Peter Neubauer, Sebastian Hans, Harini Narayanan, Benjamin Haby, Niels Krausch, Michael Sokolov, Florian Glauche, Sebastian Riedel, Mariano Nicolas Cruz BournazouAbstract:Mini-bioreactor systems enabling automatized operation of numerous parallel cultivations are a promising alternative to accelerate and optimize Bioprocess Development allowing for sophisticated cultivation experiments in high throughput. These include fed-batch and continuous cultivations with multiple options of process control and sample analysis which deliver valuable screening tools for industrial production. However, the model-based methods needed to operate these robotic facilities efficiently considering the complexity of biological processes are missing. We present an automated experiment facility that integrates online data handling, visualization and treatment using multivariate analysis approaches to design and operate dynamical experimental campaigns in up to 48 mini-bioreactors (8–12 mL) in parallel. In this study, the characterization of Saccharomyces cerevisiae AH22 secreting recombinant endopolygalacturonase is performed, running and comparing 16 experimental conditions in triplicate. Data-driven multivariate methods were developed to allow for fast, automated decision making as well as online predictive data analysis regarding endopolygalacturonase production. Using dynamic process information, a cultivation with abnormal behavior could be detected by principal component analysis as well as two clusters of similarly behaving cultivations, later classified according to the feeding rate. By decision tree analysis, cultivation conditions leading to an optimal recombinant product formation could be identified automatically. The developed method is easily adaptable to different strains and cultivation strategies, and suitable for automatized process Development reducing the experimental times and costs.
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Accelerated Bioprocess Development of Endopolygalacturonase-Production with Saccharomyces cerevisiae Using Multivariate Prediction in a 48 Mini-Bioreactor Automated Platform
2018Co-Authors: Annina Sawatzki, Peter Neubauer, Sebastian Hans, Harini Narayanan, Benjamin Haby, Niels Krausch, Michael Sokolov, Florian Glauche, Mariano Nicolas Cruz BournazouAbstract:Mini-bioreactor systems enabling automatized operation of numerous parallel cultivations have been used to accelerate and optimize Bioprocess Development. As implementation of fed-batch conditions, multiple options of process control and sample analysis are possible, these systems represent valuable screening tools for large-scale production. However, the dynamic behavior of cultivations has not yet been considered regarding data evaluation and decision making during high-throughput screening in mini-bioreactors. In this study, the characterization of Saccharomyces cerevisiae AH22 secreting recombinant endopolygalacturonase is performed in 48 parallel fed-batch cultivations regarding 16 experimental conditions. Automated parallel process control, frequent sampling and analysis were implemented. Data-driven multivariate methods were developed to allow for fast, automated decision making as well as online predictive data analysis regarding endopolygalacturonase production. Using dynamic process information, a cultivation with abnormal behavior could be detected by principal component analysis as well as two clusters of similarly behaving cultivations, later classified according to the feeding rate. By decision tree analysis, cultivation conditions leading to an optimal recombinant product formation could be identified automatically. The developed method is easily adaptable and suitable for automatized process Development reducing the experimental times and costs.
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Scale-up Bioprocess Development for production of the antibiotic valinomycin in Escherichia coli based on consistent fed-batch cultivations
Microbial Cell Factories, 2015Co-Authors: Jian Li, Jennifer Jaitzig, Ping Lu, Roderich D Süssmuth, Peter NeubauerAbstract:Background Heterologous production of natural products in Escherichia coli has emerged as an attractive strategy to obtain molecules of interest. Although technically feasible most of them are still constrained to laboratory scale production. Therefore, it is necessary to develop reasonable scale-up strategies for Bioprocesses aiming at the overproduction of targeted natural products under industrial scale conditions. To this end, we used the production of the antibiotic valinomycin in E. coli as a model system for scalable Bioprocess Development based on consistent fed-batch cultivations. Results In this work, the glucose limited fed-batch strategy based on pure mineral salt medium was used throughout all scales for valinomycin production. The optimal glucose feed rate was initially detected by the use of a biocatalytically controlled glucose release (EnBase® technology) in parallel cultivations in 24-well plates with continuous monitoring of pH and dissolved oxygen. These results were confirmed in shake flasks, where the accumulation of valinomycin was highest when the specific growth rate decreased below 0.1 h^−1. This correlation was also observed for high cell density fed-batch cultivations in a lab-scale bioreactor. The bioreactor fermentation produced valinomycin with titers of more than 2 mg L^−1 based on the feeding of a concentrated glucose solution. Valinomycin production was not affected by oscillating conditions (i.e. glucose and oxygen) in a scale-down two-compartment reactor, which could mimic similar situations in industrial bioreactors, suggesting that the process is very robust and a scaling of the process to a larger industrial scale appears a realistic scenario. Conclusions Valinomycin production was scaled up from mL volumes to 10 L with consistent use of the fed-batch technology. This work presents a robust and reliable approach for scalable Bioprocess Development and represents an example for the consistent Development of a process for a heterologously expressed natural product towards the industrial scale.
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Scale-up Bioprocess Development for production of the antibiotic valinomycin in Escherichia coli based on consistent fed-batch cultivations
Microbial Cell Factories, 2015Co-Authors: Jennifer Jaitzig, Roderich D Süssmuth, Peter NeubauerAbstract:Heterologous production of natural products in Escherichia coli has emerged as an attractive strategy to obtain molecules of interest. Although technically feasible most of them are still constrained to laboratory scale production. Therefore, it is necessary to develop reasonable scale-up strategies for Bioprocesses aiming at the overproduction of targeted natural products under industrial scale conditions. To this end, we used the production of the antibiotic valinomycin in E. coli as a model system for scalable Bioprocess Development based on consistent fed-batch cultivations. In this work, the glucose limited fed-batch strategy based on pure mineral salt medium was used throughout all scales for valinomycin production. The optimal glucose feed rate was initially detected by the use of a biocatalytically controlled glucose release (EnBase® technology) in parallel cultivations in 24-well plates with continuous monitoring of pH and dissolved oxygen. These results were confirmed in shake flasks, where the accumulation of valinomycin was highest when the specific growth rate decreased below 0.1 h−1. This correlation was also observed for high cell density fed-batch cultivations in a lab-scale bioreactor. The bioreactor fermentation produced valinomycin with titers of more than 2 mg L−1 based on the feeding of a concentrated glucose solution. Valinomycin production was not affected by oscillating conditions (i.e. glucose and oxygen) in a scale-down two-compartment reactor, which could mimic similar situations in industrial bioreactors, suggesting that the process is very robust and a scaling of the process to a larger industrial scale appears a realistic scenario. Valinomycin production was scaled up from mL volumes to 10 L with consistent use of the fed-batch technology. This work presents a robust and reliable approach for scalable Bioprocess Development and represents an example for the consistent Development of a process for a heterologously expressed natural product towards the industrial scale.
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Robotic platform for parallelized cultivation and monitoring of microbial growth parameters in microwell plates.
Journal of Laboratory Automation, 2014Co-Authors: Andreas Knepper, Florian Glauche, Michael Heiser, Peter NeubauerAbstract:The enormous variation possibilities of Bioprocesses challenge process Development to fix a commercial process with respect to costs and time. Although some cultivation systems and some devices for unit operations combine the latest technology on miniaturization, parallelization, and sensing, the degree of automation in upstream and downstream Bioprocess Development is still limited to single steps. We aim to face this challenge by an interdisciplinary approach to significantly shorten Development times and costs. As a first step, we scaled down analytical assays to the microliter scale and created automated procedures for starting the cultivation and monitoring the optical density (OD), pH, concentrations of glucose and acetate in the culture medium, and product formation in fed-batch cultures in the 96-well format. Then, the separate measurements of pH, OD, and concentrations of acetate and glucose were combined to one method. This method enables automated process monitoring at dedicated intervals (e.g., also during the night). By this approach, we managed to increase the information content of cultivations in 96-microwell plates, thus turning them into a suitable tool for high-throughput Bioprocess Development. Here, we present the flowcharts as well as cultivation data of our automation approach.
P Fernandes - One of the best experts on this subject based on the ideXlab platform.
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Bioprocess Development for canine adenovirus type 2 vectors
Gene Therapy, 2013Co-Authors: P Fernandes, C Peixoto, V M Santiago, E J Kremer, A S Coroadinha, P M AlvesAbstract:Canine adenovirus type 2 (CAV-2) vectors overcome many of the clinical immunogenic concerns related to vectors derived from human adenoviruses (AdVs). In addition, CAV-2 vectors preferentially transduce neurons with an efficient traffic via axons to afferent regions when injected into the brain. To meet the need for preclinical and possibly clinical uses, scalable and robust production processes are required. CAV-2 vectors are currently produced in E1-transcomplementing dog kidney (DK) cells, which might raise obstacles in regulatory approval for clinical grade material production. In this study, a GMP-compliant Bioprocess was developed. An MDCK-E1 cell line, developed by our group, was grown in scalable stirred tank bioreactors, using serum-free medium, and used to produce CAV-2 vectors that were afterwards purified using column chromatographic steps. Vectors produced in MDCK-E1 cells were identical to those produced in DK cells as assessed by SDS-PAGE and dynamic light scatering measurements (diameter and Zeta potential). Productivities of ∼10^9 infectious particles (IP) ml^−1 and 2 × 10^3 IP per cell were possible. A downstream process using technologies transferable to process scales was developed, yielding 63% global recovery. The total particles to IP ratio in the purified product (
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Bioprocess Development for canine adenovirus type 2 vectors
Gene Therapy, 2013Co-Authors: P Fernandes, C Peixoto, V M Santiago, E J Kremer, A S Coroadinha, P M AlvesAbstract:Canine adenovirus type 2 (CAV-2) vectors overcome many of the clinical immunogenic concerns related to vectors derived from human adenoviruses (AdVs). In addition, CAV-2 vectors preferentially transduce neurons with an efficient traffic via axons to afferent regions when injected into the brain. To meet the need for preclinical and possibly clinical uses, scalable and robust production processes are required. CAV-2 vectors are currently produced in E1-transcomplementing dog kidney (DK) cells, which might raise obstacles in regulatory approval for clinical grade material production. In this study, a GMP-compliant Bioprocess was developed. An MDCK-E1 cell line, developed by our group, was grown in scalable stirred tank bioreactors, using serum-free medium, and used to produce CAV-2 vectors that were afterwards purified using column chromatographic steps. Vectors produced in MDCK-E1 cells were identical to those produced in DK cells as assessed by SDS-PAGE and dynamic light scatering measurements (diameter and Zeta potential). Productivities of ∼10(9) infectious particles (IP) ml(-1) and 2 × 10(3) IP per cell were possible. A downstream process using technologies transferable to process scales was developed, yielding 63% global recovery. The total particles to IP ratio in the purified product (<20:1) was within the limits specified by the regulatory authorities for AdV vectors. These results constitute a step toward a scalable process for CAV-2 vector production compliant with clinical material specifications.
Spyridon Konstantinidis - One of the best experts on this subject based on the ideXlab platform.
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Simplex-based optimization of numerical and categorical inputs in early Bioprocess Development: Case studies in HT chromatography.
Biotechnology Journal, 2017Co-Authors: Spyridon Konstantinidis, Nigel J. Titchener‐hooker, Ajoy VelayudhanAbstract: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 (mAb) 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 inputs 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.
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Application of simplex-based experimental optimization to challenging Bioprocess Development problems: Case studies in downstream processing.
Biotechnology Progress, 2016Co-Authors: Spyridon Konstantinidis, John P. Welsh, David J. Roush, Ajoy VelayudhanAbstract:The identification of feasible operating conditions during the early stages of Bioprocess Development is implemented frequently through High Throughput (HT) studies. These typically employ techniques based on regression analysis, such as Design of Experiments. In this work, an alternative approach, based on a previously developed variant of the Simplex algorithm, is compared to the conventional regression-based method for three experimental systems involving polishing chromatography and protein refolding. This Simplex algorithm variant was found to be more effective in identifying superior operating conditions, and in fact it reached the global optimum in most cases involving multiple optima. By contrast, the regression-based method often failed to reach the global optimum, and in many cases reached poor operating conditions. The Simplex-based method is further shown to be robust in dealing with noisy experimental data, and requires fewer experiments than regression-based methods to reach favorable operating conditions. The Simplex-variant also lends itself to the use of HT analytical methods, when they are available, which can assist in avoiding analytical bottlenecks. It is suggested that this Simplex-variant is ideally suited to rapid optimization in early-phase process Development. © 2016 American Institute of Chemical Engineers Biotechnol. Prog., 32:404-419, 2016.
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the hybrid experimental simplex algorithm an alternative method for sweet spot identification in early Bioprocess Development case studies in ion exchange chromatography
Analytica Chimica Acta, 2012Co-Authors: Spyridon Konstantinidis, Ajoy Velayudhan, Eva Heldin, Sunil Chhatre, N J TitchenerhookerAbstract: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.
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The simplex algorithm for the rapid identification of operating conditions during early Bioprocess Development: Case studies in FAb' precipitation and multimodal chromatography
Biotechnology and Bioengineering, 2011Co-Authors: Sunil Chhatre, Yuhong Zhou, Spyridon Konstantinidis, S Edwards-parton, Nigel J. Titchener-hookerAbstract: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.
N J Titchenerhooker - One of the best experts on this subject based on the ideXlab platform.
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the hybrid experimental simplex algorithm an alternative method for sweet spot identification in early Bioprocess Development case studies in ion exchange chromatography
Analytica Chimica Acta, 2012Co-Authors: Spyridon Konstantinidis, Ajoy Velayudhan, Eva Heldin, Sunil Chhatre, N J TitchenerhookerAbstract: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.