Schmieg, B. / Brandt, N. / Schnepp, V.J. / Radosevic, L. / Gretzinger, S. / Selzer, M. / Hubbuch, J. (2022)

Appl. Sci., 2022, 12, 7728, doi.org/10.3390/app12157728

Abstract: Bioprinting is a method to fabricate 3D models that mimic tissue. Future fields of application
might be in pharmaceutical or medical context. As the number of applicants might vary between
only one patient to manufacturing tissue for high-throughput drug screening, designing a process
will necessitate a high degree of flexibility, robustness, as well as comprehensive monitoring. To
enable quality by design process optimisation for future application, establishing systematic data
storage routines suitable for automated analytical tools is highly desirable as a first step. This
manuscript introduces a workflow for process design, documentation within an electronic lab
notebook and monitoring to supervise the product quality over time or at different locations. Lab
notes, analytical data and corresponding metadata are stored in a systematic hierarchy within the
research data infrastructure Kadi4Mat, which allows for continuous, flexible data structuring and
access management. To support the experimental and analytical workflow, additional features
were implemented to enhance and build upon the functionality provided by Kadi4Mat, including
browser-based file previews and a Python tool for the combined filtering and extraction of data. The
structured research data management with Kadi4Mat enables retrospective data grouping and usage
by process analytical technology tools connecting individual analysis software to machine-readable
data exchange formats.

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