Automation of Experimental Workflows for High Throughput Robotic Cultivations

• Published in: Computer Aided Chemical Engineering Vol. 53; pp. 2971 - 2976
• Main Authors: Kaspersetz, Lucas, Schröder-Kleeberg, Fabian, Mione, Federico M., Martinez, Ernesto C., Neubauer, Peter, Cruz-Bournazou, Mariano Nicolas
• Format: Book Chapter
• Language: English
• Published: 2024
• Subjects: directed acyclic graphs; reproducibility; workflow automation; workflow automation; reproducibility; directed acyclic graphs
• ISBN: 9780443288241; 0443288240
• ISSN: 1570-7946
• DOI: 10.1016/B978-0-443-28824-1.50496-8

Robotic cultivation platforms optimally operated with computational tools can serve as generators of high-information content data. However, the generated data should be accompanied with the executed workflows to enable reproducibility of experiments. Workflow management systems support data provenance and enable traceability of experimental workflows. In contrast to production environments with highly standardized structures and strict operating regimes, integration of workflows in robotic experimental facilities is often challenging. The challenges are due to proprietary interfaces, rapidly changing objectives, and lack of adequate representation of the implemented workflows which prevents their interoperability and automated metadata capture. In this work, we present the design and implementation of a digital infrastructure with a workflow management system as the top layer. The execution of experimental workflows is automated using Apache Airflow enabling to manage all necessary steps for fed-batch cultivations, including sampling, sample transport by a mobile robot, feed additions, data collection, storage in a SQL database and model fitting. Thus, the generated experimental data can be accompanied with the executed workflows, facilitating transparency, and sharing of experimental protocols.