Advances in bioscientific research : strategies to facilitate automation of processes and to improve bioanalytical parameters

Abstract

Bioscientific research in academic settings faces the challenge of addressing increasingly complex questions using advanced methods while ensuring reproducibility. Many processes are subject to variability introduced by the influence of researchers, which can compromise the reproducibility of scientific results. While large pharmaceutical and diagnostic laboratories have benefited from automated processes and highquality bioanalytical parameters for decades, the implementation of automation in academic research remains insufficient due to the unique challenges these laboratories are facing. Unsuitable systems and insufficiently trained researchers are contributing factors to this situation. The aim of this thesis is to develop strategies that enable academic research laboratories to improve their bioanalytical data through the use of laboratory automation. The key challenges are related to flexibility in laboratory processes, as researchers, projects and methods are often time-limited and require easy adaptability. Furthermore, existing equipment needs to be usable, both, manually and automatically, and automated workflows should be achievable without extensive method development. Additionally, supporting researchers in tasks that remain manual is essential to reduce random errors. To meet these requirements, multiple strategies were approached, targeting several aspects simultaneously, with the aim to reach as many bioscientific laboratories as possible. The first strategy involves the development of an automation system based on a robotic arm with a mobile base, capable of automating various processes due to its multifunctionality. The system's features include a plate gripper, a camera, a conventional electronic pipette, and an operating finger for physical tasks in the laboratory. Using fiducial markers, the system can interact with existing equipment, read-out displays, and digitally store measured values. Furthermore, it was shown that the automation of pipetting tasks ─ such as the Bradford assay ─ using conventional laboratory tools like single-channel electronic pipettes, leads to improved bioanalytical parameters more easily than using professional pipetting robots. A second strategy involved the development of a guide to assist researchers in adopting laboratory automation in academic research institutions. This guide provides personalized orientation and offers clarity on the automation potential of individual laboratories. The third strategy focused on the development of a voice assistant for scientific laboratories, which supports tasks such as performing calculations, reading protocols aloud, and controlling laboratory devices via voice commands. In summary, the developed strategies aim to standardize laboratory processes, leading to an improvement in the quality of experimental data while reducing errors in manual tasks by relieving researchers.