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BioSamplr: An open source, low cost automated sampling system for bioreactors
John P Efromson1, Shuai Li2, Michael D Lynch1
1Department of Biomedical Engineering, Duke University, United States.
This study introduces the BioSamplr, an affordable, open-source automated bioreactor sampling system. It enhances experimental reproducibility and reduces manual labor, making advanced sampling accessible to more labs.
Area of Science:
- Biotechnology
- Bioprocess Engineering
- Laboratory Automation
Background:
- Manual bioreactor sampling is labor-intensive, prone to errors, and limits continuous monitoring.
- Existing automated sampling systems are often expensive and complex, hindering accessibility for smaller laboratories.
- There is a need for cost-effective and user-friendly automated sampling solutions to improve bioprocess research.
Purpose of the Study:
- To design, build, and validate a low-cost, open-source automated bioreactor sampling system.
- To demonstrate the system's capability for reproducible, aseptic, and time-efficient sample collection.
- To provide an accessible automated sampling solution for laboratories with limited resources.
Main Methods:
- Development of the BioSamplr using affordable, 3D-printed components and a Raspberry Pi controller.
- Implementation of wireless control for automated sample collection at user-defined intervals.
- Integration of a cooling system for sample preservation and data logging capabilities.
Main Results:
- The BioSamplr successfully performed automated sampling from bioreactors with high reproducibility.
- The system demonstrated reduced hands-on time and enabled 24-hour sampling capabilities.
- The low-cost design and open-source nature significantly enhance accessibility for various research settings.
Conclusions:
- The BioSamplr offers a viable, cost-effective alternative to expensive commercial autosamplers.
- This automated system improves bioreactor experiment efficiency, reproducibility, and aseptic handling.
- The open-source platform facilitates wider adoption and potential for further customization in bioprocess monitoring.
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