scholarly journals Automated bioprocess feedback operation in a high throughput facility via the integration of a mobile robotic lab assistant

2022 ◽  
Author(s):  
Lucas Kaspersetz ◽  
Saskia Waldburger ◽  
M.-Therese Schermeyer ◽  
Sebastian L. Riedel ◽  
Sebsatian Gross ◽  
...  

Biotechnological processes development is challenging due to the sheer variety of process parameters. For efficient upstream development parallel cultivation systems have proven to reduce costs and associated timelines successfully, while offering excellent process control. However, the degree of automation of such small scale systems is comparably low and necessary sample analysis requires manual steps. Although the subsequent analysis can be performed in a high-throughput manner, the integration of analytic devices remains challenging. Especially, when cultivation and analysis laboratories are spatially separated. Mobile robots offer a potential solution, but the implementation in research laboratories is not widely adopted. Our approach demonstrates the integration of a small scale cultivation system into a liquid handling station for an automated sample procedure. The samples are transferred via a mobile robotic lab assistant and subsequently analysed by a high-throughput analyzer. The process data is stored in a centralized database. The mobile robotic workflow guarantees a flexible solution for device integration and facilitates automation. Restrictions regarding spatial separation of devices are circumvented, enabling a modular platform throughout different laboratories. The presented cultivation platform is evaluated based on industrial relevant E. coli BW25113 high cell density fed-batch cultivation. Here its suitability for accelerating bioprocess development is proven. The necessary magnesium addition for reaching high cell densities in mineral salt medium is automated via a feedback operation loop. The feedback operation loop demonstrates the possibility for advanced control options. This study sets the foundation for a fully integrated facility with different cultivation scales sharing the same data infrastructure, where the mobile robotic lab assistant physically connects the devices.

Fermentation ◽  
2021 ◽  
Vol 7 (2) ◽  
pp. 62
Author(s):  
Konstantins Dubencovs ◽  
Janis Liepins ◽  
Arturs Suleiko ◽  
Anastasija Suleiko ◽  
Reinis Vangravs ◽  
...  

The Kluyveromyces marxianus yeast recently has gained considerable attention due to its applicability in high-value-added product manufacturing. In order to intensify the biosynthesis rate of a target product, reaching high biomass concentrations in the reaction medium is mandatory. Fed-batch processes are an attractive and efficient way how to achieve high cell densities. However, depending on the physiology of the particular microbial strain, an optimal media composition should be used to avoid by-product synthesis and, subsequently, a decrease in overall process effi-ciency. Thus, the aim of the present study was to optimise the synthetic growth medium and feeding solution compositions (in terms of carbon, nitrogen, phosphorous, magnesium, and calcium concentrations) for high cell density K. marxianus fed‑batch cultivations. Additionally, the biomass yields from the vitamin mixture and other macro/microelements were identified. A model predictive control algorithm was successfully applied for a fed-batch cultivation control. Biomass growth and substrate consumption kinetics were compared with the mathematical model predictions. Finally, 2‑phenylethanol biosynthesis was induced and its productivity was estimated. The determined optimal macronutrient ratio for K. marxianus biomass growth was identified as C:N:P = 1:0.07:0.011. The maximal attained yeast biomass concentration was close to 70 g·L-1 and the 2-PE biosynthesis rate was 0.372 g·L−1·h−1, with a yield of 74% from 2-phenylalanine.


Processes ◽  
2021 ◽  
Vol 9 (4) ◽  
pp. 575
Author(s):  
Jelena Ochs ◽  
Ferdinand Biermann ◽  
Tobias Piotrowski ◽  
Frederik Erkens ◽  
Bastian Nießing ◽  
...  

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.


2019 ◽  
Vol 338 ◽  
pp. 72-80 ◽  
Author(s):  
L. Silvester ◽  
F. Ramos ◽  
J. Thuriot-Roukos ◽  
S. Heyte ◽  
M. Araque ◽  
...  

2009 ◽  
Vol 103 (6) ◽  
pp. 1095-1102 ◽  
Author(s):  
Robert Huber ◽  
Marco Scheidle ◽  
Barbara Dittrich ◽  
Doris Klee ◽  
Jochen Büchs

Author(s):  
Nicolás M. Morato ◽  
MyPhuong T. Le ◽  
Dylan T. Holden ◽  
R. Graham Cooks

The Purdue Make It system is a unique automated platform capable of small-scale in situ synthesis, screening small-molecule reactions, and performing direct label-free bioassays. The platform is based on desorption electrospray ionization (DESI), an ambient ionization method that allows for minimal sample workup and is capable of accelerating reactions in secondary droplets, thus conferring unique advantages compared with other high-throughput screening technologies. By combining DESI with liquid handling robotics, the system achieves throughputs of more than 1 sample/s, handling up to 6144 samples in a single run. As little as 100 fmol/spot of analyte is required to perform both initial analysis by mass spectrometry (MS) and further MSn structural characterization. The data obtained are processed using custom software so that results are easily visualized as interactive heatmaps of reaction plates based on the peak intensities of m/ z values of interest. In this paper, we review the system’s capabilities as described in previous publications and demonstrate its utilization in two new high-throughput campaigns: (1) the screening of 188 unique combinatorial reactions (24 reaction types, 188 unique reaction mixtures) to determine reactivity trends and (2) label-free studies of the nicotinamide N-methyltransferase enzyme directly from the bioassay buffer. The system’s versatility holds promise for several future directions, including the collection of secondary droplets containing the products from successful reaction screening measurements, the development of machine learning algorithms using data collected from compound library screening, and the adaption of a variety of relevant bioassays to high-throughput MS.


2012 ◽  
Vol 45 (3) ◽  
pp. 489-495 ◽  
Author(s):  
Clement E. Blanchet ◽  
Alexey V. Zozulya ◽  
Alexey G. Kikhney ◽  
Daniel Franke ◽  
Peter V. Konarev ◽  
...  

A setup is presented for automated high-throughput measurements of small-angle X-ray scattering (SAXS) from macromolecular solutions on the bending-magnet beamline X33 of EMBL at the storage ring DORIS-III (DESY, Hamburg). A new multi-cell compartment allows for rapid switching between in-vacuum and in-air operation, for digital camera assisted control of cell filling and for colour sample illumination. The beamline is equipped with a Pilatus 1 M-W pixel detector for SAXS and a Pilatus 300 k-W for wide-angle scattering (WAXS), and results from the use of the Pilatus detectors for scattering studies are reported. The setup provides a broad resolution range from 100 to 0.36 nm without the necessity of changing the sample-to-detector distance. A new optimized robotic sample changer is installed, permitting rapid and reliable automated sample loading and cell cleaning with a required sample volume of 40 µl. All the devices are fully integrated into the beamline control software system, ensuring fully automated and user-friendly operation (attended, unattended and remote) with a throughput of up to 15 measurements per hour.


2017 ◽  
Vol 06 (04) ◽  
pp. 1750007 ◽  
Author(s):  
Miles D. Cranmer ◽  
Benjamin R. Barsdell ◽  
Danny C. Price ◽  
Jayce Dowell ◽  
Hugh Garsden ◽  
...  

Radio astronomy observatories with high throughput back end instruments require real-time data processing. While computing hardware continues to advance rapidly, development of real-time processing pipelines remains difficult and time-consuming, which can limit scientific productivity. Motivated by this, we have developed Bifrost: an open-source software framework for rapid pipeline development. (a) Bifrost combines a high-level Python interface with highly efficient reconfigurable data transport and a library of computing blocks for CPU and GPU processing. The framework is generalizable, but initially it emphasizes the needs of high-throughput radio astronomy pipelines, such as the ability to process data buffers as if they were continuous streams, the capacity to partition processing into distinct data sequences (e.g. separate observations), and the ability to extract specific intervals from buffered data. Computing blocks in the library are designed for applications such as interferometry, pulsar dedispersion and timing, and transient search pipelines. We describe the design and implementation of the Bifrost framework and demonstrate its use as the backbone in the correlation and beamforming back end of the Long Wavelength Array (LWA) station in the Sevilleta National Wildlife Refuge, NM.


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