Management of experimental workflows in robotic cultivation platforms

In the last decades, robotic cultivation facilities combined with automated execution of workflows have drastically increased the speed of research in biotechnology. In this work, we present the design and deployment of a digital infrastructure for robotic cultivation platforms. We implement a Workflow Management System, using Directed Acyclic Graphs, based on the open-source platform Apache Airflow to increase traceability and the automated execution of experiments. We demonstrate the integration and automation of experimental workflows in a laboratory environment with a heterogeneous device landscape including liquid handling stations, parallel cultivation systems, and mobile robots. The feasibility of our approach is assessed in parallel E. coli fed-batch cultivations with glucose oscillations in which different elastin-like proteins are produced. We show that the use of workflow management systems in robotic cultivation platforms increases automation, robustness and traceability of experimental data.

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Publication Details

Journal
SLAS TECHNOLOGY
Published
2024-10-31
DOI
https://doi.org/10.1016/j.slast.2024.100214
Citations
2
Primary Topic
Scientific Computing and Data Management
Type
article
Field-Weighted Citation Impact
2.10
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article

Management of experimental workflows in robotic cultivation platforms

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Scientific Computing and Data Management
2.10
article

Management of experimental workflows in robotic cultivation platforms

Peter B. Neubauer, Mariano Nicolás Cruz Bournazou, Ernesto Martínez, Lucas Kaspersetz, Britta Englert, Fabian Krah
article en
2 citations

Abstract

In the last decades, robotic cultivation facilities combined with automated execution of workflows have drastically increased the speed of research in biotechnology. In this work, we present the design and deployment of a digital infrastructure for robotic cultivation platforms. We implement a Workflow Management System, using Directed Acyclic Graphs, based on the open-source platform Apache Airflow to increase traceability and the automated execution of experiments. We demonstrate the integration and automation of experimental workflows in a laboratory environment with a heterogeneous device landscape including liquid handling stations, parallel cultivation systems, and mobile robots. The feasibility of our approach is assessed in parallel E. coli fed-batch cultivations with glucose oscillations in which different elastin-like proteins are produced. We show that the use of workflow management systems in robotic cultivation platforms increases automation, robustness and traceability of experimental data.

SLAS TECHNOLOGYVol. 29(6)
Technische Universität Berlin (DE)
Zero hunger
Openalex Percentile: Top 8%
Scientific Computing and Data Management
2.10
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