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Cardiac Tissue Engineering as Use Case to Connect Biomedical Research Laboratories to an Emerging Global Data
Markus Suhr1, Nadine Umbach1,2, Tim Meyer3,2
1Department of Medical Informatics, University Medical Center Göttingen, Göttingen, Germany.
This study introduces a digital data management system to improve asset traceability and experiment reproducibility in cardiac tissue engineering research. The system enhances data capture and documentation for automated lab processes.
Area of Science:
- Biomedical Engineering
- Pharmacology
- Toxicology
Background:
- Cardiac tissue engineering and experimental applications are key technologies at the Institute of Pharmacology and Toxicology in Göttingen.
- Current data capture and documentation practices in academic research labs, including this institute, can be improved with modern digital research methods.
Purpose of the Study:
- To propose and prototypically deploy a data management system concept for enhancing lab processes.
- To enable traceability of assets and reproducibility of assays and results within a research setting.
- To lay the foundation for increased automation in laboratory processes through a comprehensive information system infrastructure.
Main Methods:
- Development of a data management system concept.
- Prototypical deployment of the system integrating existing electronic lab notebooks and experiment result databases.
- Creation of a custom portal and integration component to connect disparate data sources.
- Exploration of connecting routine experimental work to a universal data infrastructure.
Main Results:
- A prototypically deployed data management system enabling asset traceability.
- Improved reproducibility of published assays and results.
- Integration of existing electronic lab notebook and experiment result databases with a new research data management system.
- Demonstration of a custom portal and integration component for data connectivity.
Conclusions:
- The proposed data management system concept and its prototype provide a foundation for advancing digital research methods in a biomedical setting.
- The developed integration tools facilitate the connection of routine experimental work to a universal data infrastructure.
- Implementing such systems is crucial for improving data integrity, reproducibility, and automation in research laboratories.
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