Nutzung von Sensor Spots zur Bestimmung der Gelöstsauerstoffkonzentration in Single-use Systemen im Labormassstab

Einleitung: Der wirtschaftlich gewinnbringende Einsatz biotechnologischer Verfahren setzt eine explizite Kenntnis des verwendeten Systems voraus. Für aerobe Kultivierungen bedeutet dies insbesondere die Überwachung und Optimierung der Gelöstsauerstoffkonzentration im Bioreaktor. Dies gilt sowohl für die zunehmend an Bedeutung gewinnenden Single-Use Systeme als auch für klassische Bioreaktoren, wobei sich für erstere durch ihre besonderen Eigenschaften Chancen und Herausforderungen ergeben. Einsatzgebiete: Der Einsatz klassischer Messsonden in Single-Use Systemen widerspricht dem zugrundeliegenden out of the box Konzept und erhöht gleichzeitig den Aufwand in Vorbereitung und das Risiko einer Kontamination. Für Systeme wie Schüttelkolben oder Bagreaktoren ist der Einsatz dieser Messsonden aus geometrischen und strömungstechnischen Gründen zudem wenig sinnvoll. In diesem Anwendungsfeld (Laborbioreaktoren im Milliliter- und Litermaßstab) bieten Sensor Spots eine einfache und vielversprechende Alternative zur Sauerstoffüberwachung. In der vorliegenden Posterpräsentation wird der Einsatz von Sensor Spots zur Bestimmung des volumenbe-zogenen Sauerstoffübergangskoeffizienten (kLa-Wert) in verschiedenen Systemen (beispielsweise in Thomson Optimum Growth™ Schüttelkolben oder TubeSpin® Bioreaktoren) illustriert. Im Fokus steht dabei die Optimierung der Prozessparameter für pflanzliche und tierische Zellkulturen. Anwendungsbeispiele: Den Abschluss dieser Posterpräsentation bildet die Vorstellung verschiedener Auswertungsmöglichkeiten sowie die Demonstration der Einsatzmöglichkeiten unter verschiedenen Gesichtspunkten. Die Anwendung wird am Beispiel einer Kultivierungsstudie für CHO (Chinese Hamster Ovary) Zellen demonstriert

Advanced numerical characterization of a wave-mixed bioreactor used in the biopharmaceutical industry

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Cultivation of CHO Cells in Thomson Optimum Growth™ Shake Flasks and Scale-up

In biotechnology, the usage of shaking flasks in upstream processing is widely common due to the easy handling. Frequent applications are process screening and optimization. Thereby, the focus lies mostly on a homogeneous and fast distribution of substrates and gases whilst power consumption and shearing force are meant to be kept low, which ideally results in high biomass concentrations and product titers. For characterization purposes, the mixing time and the oxygen mass transfer coefficient (kLa) were measured in 5 L and 500 mL Thomson Optimal Growth™ shaking flasks, using the de-colorization or the dynamic gassing-out method, respectively. Those geometrical optimized bioreactors are promising higher space-time yields compared to the predominant Erlenmeyer-shake flask design. According to the results of the procedural experiments, CHO (Chinese hamster ovary) cells were cultivated at selected, auspicious parameter combinations. The effectiveness of the predetermined parameters was evaluated and a scale-up method elaborated. The results can be summarized as follows: The key parameter for all experimental setups is the shaking rate. In contrast, the filling volume showed to have a more ambiguous role. Modeling results in the 500 mL flasks showed no significant influence of the filling volume to the maximal cell density, in contrast to the 5L flask (both shaken at 50 mm throw). The highest viable cell density (up to 4.8∙10⁶ cells mL⁻¹) was reached using the 500 mL flask with high shaking rates at 50 mm shaking diameter. Thereby, a µmax of 0.038 h-1 was achieved that correlates with a td of less than 19 h. All in all, the highest µmax of 0.055 h⁻¹ was reached during the scale-up process, whereby higher viable cell densities were reached compared to the batch cultivations using the same parameter settings. In addition to the experiments performed to date, simulations with computational fluid dynamics and experimental determination of specific power consumption rates are already in progress, increasing the range of applicability and the validity of the proposed model correlations

An overview of drive systems and sealing types in stirred bioreactors used in biotechnological processes

No matter the scale, stirred tank bioreactors are the most commonly used systems in biotechnological production processes. Single-use and reusable systems are supplied by several manufacturers. The type, size, and number of impellers used in these systems have a significant influence on the characteristics and designs of bioreactors. Depending on the desired application, classic shaft-driven systems, bearing-mounted drives, or stirring elements that levitate freely in the vessel may be employed. In systems with drive shafts, process hygiene requirements also affect the type of seal used. For sensitive processes with high hygienic requirements, magnetic-driven stirring systems, which have been the focus of much research in recent years, are recommended. This review provides the reader with an overview of the most common agitation and seal types implemented in stirred bioreactor systems, highlights their advantages and disadvantages, and explains their possible fields of application. Special attention is paid to the development of magnetically driven agitators, which are widely used in reusable systems and are also becoming more and more important in their single-use counterparts

Oxygen mass transfer in biopharmaceutical processes : numerical and experimental approaches

Oxygen supply in aerobic bioprocesses is of crucial importance. For this reason, this paper presents the oxygen demand of different cells and summarizes experimental and numerical possibilities for the determination of oxygen transfer in bioreactors. The focus lies on the volumetric oxygen mass transfer coefficient (kLa) calculation using computational fluid dynamics and state-of-the-art models for surface-aerated and forced-aerated bioreactors. In addition, experimental methods for the determination of the kLa value and the gas bubble size distribution are presented

CFD modelling of a wave-mixed bioreactor with complex geometry and two degrees of freedom motion

Optimizing bioprocesses requires an in-depth understanding, from a bioengineering perspective, of the cultivation systems used. A bioengineering characterization is typically performed via experimental or numerical methods, which are particularly well-established for stirred bioreactors. For unstirred, non-rigid systems such as wave-mixed bioreactors, numerical methods prove to be problematic, as often only simplified geometries and motions can be assumed. In this work, a general approach for the numerical characterization of non-stirred cultivation systems is demonstrated using the CELL-tainer bioreactor with two degree of freedom motion as an example. In a first step, the motion is recorded via motion capturing, and a 3D model of the culture bag geometry is generated via 3D-scanning. Subsequently, the bioreactor is characterized with respect to mixing time, and oxygen transfer rate, as well as specific power input and temporal Kolmogorov length scale distribution. The results demonstrate that the CELL-tainer with two degrees of freedom outperforms classic wave-mixed bioreactors in terms of oxygen transport. In addition, it was shown that in the cell culture version of the CELL-tainer, the critical Kolmogorov length is not surpassed in any simulation

Improvement of HEK293 cell growth by adapting hydrodynamic stress and predicting cell aggregate size distribution

HEK293 is a widely used cell line in the fields of research and industry. It is assumed that these cells are sensitive to hydrodynamic stress. The aim of this research was to use particle image velocimetry validated computational fluid dynamics (CFD) to determine the hydrodynamic stress in both shake flasks, with and without baffles, and in stirred Minifors 2 bioreactors to evaluate its effect on the growth and aggregate size distribution of HEK293 suspension cells. The HEK FreeStyle™ 293-F cell line was cultivated in batch mode at different specific power inputs (from 63 W/m³ to 451 W/m³), whereby approx. 60 W/m³ corresponds to the upper limit, which is what has been typically described in published experiments. In addition to the specific growth rate and maximum viable cell density VCDmax, the cell size distribution over time and cluster size distribution were investigated. The VCDmax of (5.77 ± 0.02) · 10⁶ cells/mL was reached at a specific power input of 233 W/m³ and was 23.8% higher than the value obtained at 63 W/m³ and 7.2% higher than the value obtained at 451 W/m³. No significant change in the cell size distribution could be measured in the investigated range. It was shown that the cell cluster size distribution follows a strict geometric distribution whose free parameter p is linearly dependent on the mean Kolmogorov length scale. Based on the performed experiments, it has been shown that by using CFD-characterised bioreactors, the VCDmax can be increased and the cell aggregate rate can be precisely controlled

Determination of culture design spaces in shaken disposable cultivation systems for CHO suspension cell cultures

Processes involving mammalian cell cultures - especially CHO suspension cells - dominate biopharmaceutical manufacturing. These processes are usually developed in small scale orbitally shaken cultivation systems, and thoroughly characterizing these cultivation systems is crucial to their application in research and the subsequent scale-up to production processes. With the knowledge of process engineering parameters such as oxygen transfer rate, mixing time, and power input, in combination with the demands set by the biological production system, biomass growth and product yields can be anticipated and even increased. However, the available data sources for orbitally shaken cultivation systems are often incomplete and thus not sufficient enough to generate suitable cultivation requirements. Furthermore, process engineering knowledge is inapplicable if it is not linked to the physiological demands of the cells. In the current study, a simple yet comprehensive approach for the characterization and design space prediction of orbitally shaken single-use cultivation systems is presented, including the “classical” Erlenmeyer shake flask, the cylindrical TubeSpin bioreactor and the alternately designed Optimum Growth flask. Cultivations were performed inside and outside the design space to validate the defined culture conditions, so that cultivation success (desired specific growth rates and viable cell densities) could be achieved for each cultivation system

Improved time resolved KPI and strain characterization of multiple hosts in shake flasks using advanced online analytics and data science

Shake flasks remain one of the most widely used cultivation systems in biotechnology, especially for process development (cell line and parameter screening). This can be justified by their ease of use as well as their low investment and running costs. A disadvantage, however, is that cultivations in shake flasks are black box processes with reduced possibilities for recording online data, resulting in a lack of control and time-consuming, manual data analysis. Although different measurement methods have been developed for shake flasks, they lack comparability, especially when changing production organisms. In this study, the use of online backscattered light, dissolved oxygen, and pH data for characterization of animal, plant, and microbial cell culture processes in shake flasks are evaluated and compared. The application of these different online measurement techniques allows key performance indicators (KPIs) to be determined based on online data. This paper evaluates a novel data science workflow to automatically determine KPIs using online data from early development stages without human bias. This enables standardized and cost-effective process-oriented cell line characterization of shake flask cultivations to be performed in accordance with the process analytical technology (PAT) initiative. The comparison showed very good agreement between KPIs determined using offline data, manual techniques, and automatic calculations based on multiple signals of varying strengths with respect to the selected measurement signal

Predictive monitoring of shake flask cultures with online estimated growth models

Simplicity renders shake flasks ideal for strain selection and substrate optimization in biotechnology. Uncertainty during initial experiments may, however, cause adverse growth conditions and mislead conclusions. Using growth models for online predictions of future biomass (BM) and the arrival of critical events like low dissolved oxygen (DO) levels or when to harvest is hence important to optimize protocols. Established knowledge that unfavorable metabolites of growing microorganisms interfere with the substrate suggests that growth dynamics and, as a consequence, the growth model parameters may vary in the course of an experiment. Predictive monitoring of shake flask cultures will therefore benefit from estimating growth model parameters in an online and adaptive manner. This paper evaluates a newly developed particle filter (PF) which is specifically tailored to the requirements of biotechnological shake flask experiments. By combining stationary accuracy with fast adaptation to change the proposed PF estimates time-varying growth model parameters from iteratively measured BM and DO sensor signals in an optimal manner. Such proposition of inferring time varying parameters of Gompertz and Logistic growth models is to our best knowledge novel and here for the first time assessed for predictive monitoring of Escherichia coli (E. coli) shake flask experiments. Assessments that mimic real-time predictions of BM and DO levels under previously untested growth conditions demonstrate the efficacy of the approach. After allowing for an initialization phase where the PF learns appropriate model parameters, we obtain accurate predictions of future BM and DO levels and important temporal characteristics like when to harvest. Statically parameterized growth models that represent the dynamics of a specific setting will in general provide poor characterizations of the dynamics when we change strain or substrate. The proposed approach is thus an important innovation for scientists working on strain characterization and substrate optimization as providing accurate forecasts will improve reproducibility and efficiency in early-stage bioprocess development