M.Sc.

Nießing, Bastian

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  • Publication
    Techno-Economic Analysis of Automated iPSC Production
    ( 2021-01-28)
    Nießing, Bastian
    ;
    Kiesel, Raphael
    ;
    Herbst, Laura
    ;
    Schmitt, Robert H.
    Induced pluripotent stem cells (iPSC) open up the unique perspective of manufacturing cell products for drug development and regenerative medicine in tissue-, disease- and patient-specific forms. iPSC can be multiplied almost without restriction and differentiated into cell types of all organs. The basis for clinical use of iPSC is a high number of cells (approximately 7 × 107 cells per treatment), which must be produced cost-effectively while maintaining reproducible and high quality. Compared to manual cell production, the automation of cell production offers a unique chance of reliable reproducibility of cells in addition to cost reduction and increased throughput. StemCellFactory is a prototype for a fully automated production of iPSC. However, in addition to the already tested functionality of the system, it must be shown that this automation brings necessary economic advantages. This paper presents that fully automated stem cell production offers economic advantages in addition to increased throughput and better quality. First, biological and technological basics for a fully automated production of iPSC are presented. Second, the basics for profitability calculation are presented. Third, profitability of both manual and automated production are calculated. Finally, different scenarios effecting the profitability of manual and automated production are compared.
  • Publication
    High-Speed-Mikroskopie - Mikroskopieren in Bewegung
    ( 2021)
    Janning, Kai
    ;
    Nießing, Bastian
    ;
    König, Niels orcid-logo
    ;
    Schmitt, Robert H.
    Mit einer schnellen Digitalisierung der Proben und einer parallel stattfindenden Bildauswertung kann automatisierte Mikroskopie für Analytik und Qualitätskontrollen beschleunigt und effizienter werden. Moderne High-Speed-Mikroskope, über welche die Autoren hier berichten, vereinen hohe Aufnahmegeschwindigkeiten mit intelligenter Software für individuelle Auswertungen.
  • Publication
    High-Speed-Mikroskopie
    ( 2021)
    Janning, Kai
    ;
    Nießing, Bastian
    ;
    Schmitt, Robert H.
    Um die Mikroskopie für die Analytik und die Qualitätskontrollen in der Zellkultur effizient zu automatisieren, ist eine schnelle Digitalisierung der Proben und eine parallele Bildauswertung erforderlich.
  • Publication
    Automating Laboratory Processes by Connecting Biotech and Robotic Devices - an Overview of the Current Challenges, Existing Solutions and Ongoing Developments
    ( 2021)
    Biermann, Ferdinand
    ;
    Mathews, Julius
    ;
    Nießing, Bastian
    ;
    König, Niels orcid-logo
    ;
    Schmitt, Robert H.
    The constantly growing interest and range of applications of advanced cell, gene and regenerative therapies raise the need for efficient production of biological material and novel treatment technologies. Many of the production and manipulation processes of such materials are still manual and, therefore, need to be transferred to a fully automated execution. Developers of such systems face several challenges, one of which is mechanical and communication interfaces in biotechnological devices. In the present state, many devices are still designed for manual use and rarely provide a connection to external software for receiving commands and sending data. However, a trend towards automation on the device market is clearly visible, and the communication protocol, Open Platform Communications Data Access (OPC DA), seems to become established as a standard in biotech devices. A rising number of vendors offer software for device control and automated processing, some of which even allow the integration of devices from multiple manufacturers. The high, application-specific need in functionalities, flexibility and adaptivity makes it difficult to find the best solution and, in many cases, leads to the creation of new custom-designed software. This report shall give an overview of existing technologies, devices and software for laboratory automation of biotechnological processes. Furthermore, it presents an outlook for possible future developments and standardizations.
  • Publication
    Deep-learning-based multi-class segmentation for automated, non-invasive routine assessment of human pluripotent stem cell culture status
    ( 2021)
    Piotrowski, Tobias
    ;
    Rippel, Oliver
    ;
    Elanzew, Andreas
    ;
    Nießing, Bastian
    ;
    Stucken, Sebastian
    ;
    Jung, Sven
    ;
    König, Niels orcid-logo
    ;
    Haupt, Simone
    ;
    Stappert, Laura
    ;
    Brüstle, Oliver
    ;
    Schmitt, Robert
    ;
    Jonas, Stephan
    Human induced pluripotent stem cells (hiPSCs) are capable of differentiating into a variety of human tissue cells. They offer new opportunities for personalized medicine and drug screening. This requires large quantities of highquality hiPSCs, obtainable only via automated cultivation. One of the major requirements of an automated cultivation is a regular, non-invasive analysis of the cell condition, e.g. by whole-well microscopy. However, despite the urgency of this requirement, there are currently no automatic, image-processing-based solutions for multi-class routine quantification of this nature. This paper describes a method to fully automate the cell state recognition based on phase contrast microscopy and deep-learning. This approach can be used for in process control during an auto mated hiPSC cultivation. The U-Net based algorithm is capable of segmenting important parameters of hiPSC colony formation and can discriminate between the classes hiPSC colony, single cells, differentiated cells and dead cells. The model achieves more accurate results for the classes hiPSC colonies, differentiated cells, single hiPSCs and dead cells than visual estimation by a skilled expert. Furthermore, parameters for each hiPSC colony are derived directly from the classification result such as roundness, size, center of gravity and inclusions of other cells. These parameters provide localized information about the cell state and enable well based treatment of the cell culture in automated processes. Thus, the model can be exploited for routine, non-invasive image analysis during an automated hiPSC cultivation. This facilitates the generation of high quality hiPSC derived products for biomedical purposes.
  • Publication
    Fully Automated Cultivation of Adipose-Derived Stem Cells in the StemCellDiscovery - A Robotic Laboratory for Small-Scale, High-Throughput Cell Production Including Deep Learning-Based Confluence Estimation
    ( 2021)
    Ochs, Jelena
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    Biermann, Ferdinand
    ;
    Piotrowski, Tobias
    ;
    Erkens, Frederik
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    Nießing, Bastian
    ;
    Herbst, Laura
    ;
    König, Niels orcid-logo
    ;
    Schmitt, Robert H.
    Laboratory automation is a key driver in biotechnology and an enabler for powerful new technologies and applications. In particular, in the field of personalized therapies, automation in research and production is a prerequisite for achieving cost efficiency and broad availability of tailored treatments. For this reason, we present the StemCellDiscovery, a fully automated robotic laboratory for the cultivation of human mesenchymal stem cells (hMSCs) in small scale and in parallel. While the system can handle different kinds of adherent cells, here, we focus on the cultivation of adipose-derived hMSCs. The StemCellDiscovery provides an in-line visual quality control for automated confluence estimation, which is realized by combining high-speed microscopy with deep learning-based image processing. We demonstrate the feasibility of the algorithm to detect hMSCs in culture at different densities and calculate confluences based on the resulting image. Furthermore, we show that the StemCellDiscovery is capable of expanding adipose-derived hMSCs in a fully automated manner using the confluence estimation algorithm. In order to estimate the system capacity under high-throughput conditions, we modeled the production environment in a simulation software. The simulations of the production process indicate that the robotic laboratory is capable of handling more than 95 cell culture plates per day.
  • Publication
    Automation, Monitoring, and Standardization of Cell Product Manufacturing
    ( 2020)
    Doulgkeroglou, Meletios-Nikolaos
    ;
    Nubila, Alessia di
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    Niessing, Bastian
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    König, Niels orcid-logo
    ;
    Schmitt, Robert H.
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    Damen, Jackie
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    Szilvassy, Stephen J.
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    Chang, Wing
    ;
    Csontos, Lynn
    ;
    Louis, Sharon
    ;
    Kugelmeier, Patrick
    ;
    Ronfard, Vincent
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    Bayon, Yves
    ;
    Zeugolis, Dimitrios I.
    Although regenerative medicine products are at the forefront of scientific research, technological innovation, and clinical translation, their reproducibility and large-scale production are compromised by automation, monitoring, and standardization issues. To overcome these limitations, new technologies at software (e.g., algorithms and artificial intelligence models, combined with imaging software and machine learning techniques) and hardware (e.g., automated liquid handling, automated cell expansion bioreactor systems, automated colony-forming unit counting and characterization units, and scalable cell culture plates) level are under intense investigation. Automation, monitoring and standardization should be considered at the early stages of the developmental cycle of cell products to deliver more robust and effective therapies and treatment plans to the bedside, reducing healthcare expenditure and improving services and patient care.
  • Publication
    Smarte Steuerung flexibler Produktionssysteme. Ein service-orientierter Ansatz zur Automatisierung adaptiver, individueller Prozesse
    ( 2020)
    Hort, Simon orcid-logo
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    Nießing, Bastian
    ;
    Jung, Sven
    ;
    Schmitt, Robert H.
    Um trotz kleiner Stückzahlen kundenindividuelle Produkte effizient herstellen zu können, müssen Produktionssysteme variable Prozesse ausführen und Aufträge optimal einsteuern können. Bei der Umsetzung birgt - neben einer variablen Verkettung der Maschinen - die steuerungsseitige Implementierung große Herausforderungen. Dieser Beitrag stellt sich letzterer Herausforderung und zeigt einen service-orientierten Ansatz zur intelligenten, adaptiven Prozesssteuerung auf.
  • Publication
    The StemCellFactory: A Modular System Integration for Automated Generation and Expansion of Human Induced Pluripotent Stem Cells
    ( 2020)
    Elanzew, Andreas
    ;
    Nießing, Bastian
    ;
    Langendoerfer, Daniel
    ;
    Rippel, Oliver
    ;
    Piotrowski, Tobias
    ;
    Schenk, Friedrich
    ;
    Kulik, Michael
    ;
    Peitz, Michael
    ;
    Breitkreuz, Yannik
    ;
    Jung, Sven
    ;
    Wanek, Paul
    ;
    Stappert, Laura
    ;
    Schmitt, Robert H.
    ;
    Haupt, Simone
    ;
    Zenke, Martin
    ;
    König, Niels orcid-logo
    ;
    Brüstle, Oliver
    While human induced pluripotent stem cells (hiPSCs) provide novel prospects for disease-modeling, the high phenotypic variability seen across different lines demands usage of large hiPSC cohorts to decipher the impact of individual genetic variants. Thus, a much higher grade of parallelization, and throughput in the production of hiPSCs is needed, which can only be achieved by implementing automated solutions for cell reprogramming, and hiPSC expansion. Here, we describe the StemCellFactory, an automated, modular platform covering the entire process of hiPSC production, ranging from adult human fibroblast expansion, Sendai virus-based reprogramming to automated isolation, and parallel expansion of hiPSC clones. We have developed a feeder-free, Sendai virus-mediated reprogramming protocol suitable for cell culture processing via a robotic liquid handling unit that delivers footprint-free hiPSCs within 3 weeks with state-of-the-art efficiencies. Evolving hiPSC colonies are automatically detected, harvested, and clonally propagated in 24-well plates. In order to ensure high fidelity performance, we have implemented a high-speed microscope for in-process quality control, and image-based confluence measurements for automated dilution ratio calculation. This confluence-based splitting approach enables parallel, and individual expansion of hiPSCs in 24-well plates or scale-up in 6-well plates across at least 10 passages. Automatically expanded hiPSCs exhibit normal growth characteristics, and show sustained expression of the pluripotency associated stem cell marker TRA-1-60 over a t least 5 weeks (10 passages). Our set-up enables automated, user-independent expansion of hiPSCs under fully defined conditions, and could be exploited to generate a large number of hiPSC lines for disease modeling, and drug screening at industrial scale, and quality.