Development and Application of a Modular Open-Source Lab Automation System for Biology Research

The challenges faced with bioscience lab protocols encourage the development of automation systems to come alongside technicians. Today’s experiments involve complex protocols with precise actions usually performed manually. Even simpler biologicals can be tedious and error-prone, as was seen during the COVID-19 pandemic and society’s demand for high-volume, rapid analysis. Moreover, reproducibility suffers from excessive variability and insufficient data, while low-income labs remain slow to adopt automation. To approach these challenges and more, we leveraged aspects of the Stanford Biodesign process to develop a modular lab automation system with open-source components. Our system’s modularity minimizes the need for multiple inflexible systems, instead allowing for removing individual components as needed. Modularizing the software architecture enables us to insert artificial intelligence and machine learning models, bringing greater value to our data. Soon, using open-source chatbots such as ChatGPT will assist in converting manual protocol steps to automated functions at a low cost. Combining all of these available, low-cost tools can ultimately bring more democratization and widespread adoption of bioscience automation.