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.
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.
Advanced therapeutic medicinal products (ATMPs) have emerged as novel therapies for untreatable diseases, generating the need for large volumes of high‐quality, clinically‐compliant GMP cells to replace costly, high‐risk and limited scale manual expansion processes. We present the design of a fully automated, robot‐assisted platform incorporating the use of multiliter stirred tank bioreactors for scalable production of adherent human stem cells. The design addresses a needle‐to‐needle closed process incorporating automated bone marrow collection, cell isolation, expansion, and collection into cryovials for patient delivery. AUTOSTEM, a modular, adaptable, fully closed system ensures no direct operator interaction with biological material; all commands are performed through a graphic interface. Seeding of source material, process monitoring, feeding, sampling, harvesting and cryopreservation are automated within the closed platform, comprising two clean room levels enabling both open and closed processes. A bioprocess based on human MSCs expanded on microcarriers was used for proof of concept. Utilizing equivalent culture parameters, the AUTOSTEM robot‐assisted platform successfully performed cell expansion at the liter scale, generating results comparable to manual production, while maintaining cell quality postprocessing.
The automation of cell production processes demands strict requirements with regard to sterility, reliability, and flexibility. Robots work in such environments as transporting devices for a huge variety of disposables, e.g., cell plates, tubes, cassettes, and other objects. Therefore, the blades of their grippers must be designed to hold all of these different materials in a stable, gentle manner, and in defined positions, which means that the blades require complex geometries. Furthermore, they should have as few edges as possible, so as to be easy to clean. In this report, we demonstrate how these requirements can be met by producing stainless steel robot grippers by additive manufacturing.
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