Our research group at UCL Biochemical Engineering is deeply committed to democratizing synthetic biology through open-source automation. We are pioneering efforts to develop accessible, user-friendly automation platforms that facilitate high-throughput biological experiments. By combining the principles of open-source development with cutting-edge automation technology, we aim to make advanced synthetic biology techniques accessible to a broader community.


Traditional laboratory work in synthetic biology can be labor-intensive and error-prone. Automation has the potential to revolutionize the field by improving efficiency, reducing errors, and enabling more complex experiments. However, proprietary automation systems often come with prohibitive costs and limitations on customization. Our work in open-source automation seeks to break down these barriers, allowing for greater collaboration, innovation, and inclusivity in the field.

Techniques and Tools

To deliver on our commitment to open-source automation, we employ a multi-faceted approach:

  • Open Hardware: Designing and sharing lab automation hardware that can be easily replicated or customized.
  • Open-Source Software: Developing software platforms that are compatible with a range of lab equipment, offering user-friendly interfaces for experiment design and data analysis.
  • Community Collaboration: Actively engaging with the global synthetic biology community to share knowledge, tools, and best practices.
  • Data Analytics: Leveraging the power of big data and machine learning algorithms to optimize automated workflows and analyze experimental results.


The utility of our open-source automation platforms is far-reaching, encompassing areas such as:

  • High-Throughput Screening: Enabling the rapid testing of thousands of biological samples for applications like drug discovery or metabolic engineering.
  • Reproducibility: Providing standardized, automated workflows that improve the reliability and reproducibility of experiments.
  • Educational Outreach: Making advanced synthetic biology experiments more accessible to educational institutions with limited resources.
  • Crowdsourced Research: Facilitating collaborative projects that leverage the collective skills and resources of the global scientific community.