Hi everyone,
I’ve been exploring the exciting possibilities of closed-loop research – where automated systems can iteratively experiment based on a defined goal. It’s fascinating to see how we can move beyond manual experimentation.
At UniteLabs, we’re tackling a key challenge in this area: making different lab instruments and software communicate seamlessly. To achieve this, we build and utilize SiLA2 compliant connectors. This standardization allows us to centralize communication, enabling interaction with diverse lab equipment using just a few lines of Python code.
We’re excited to announce our Lab Automation Challenge for SLAS Europe 2025, where participants can experience this firsthand by developing a Python method to optimize a dye mixing process. This challenge will demonstrate how, when your instruments speak a common language and are easily controlled through a unified Python interface, you can truly focus on the scientific problem rather than integration complexities. We provide some boilerplate code and an execution/simulation environment to test different approaches like Bayesian optimization, DoE, grid search, or just by tweaking the number of samples/channels per iteration. 
What are your biggest challenges when trying to implement more automation in your lab workflows, particularly around instrument communication and control? We’d love to hear your thoughts!
We are setting up a Hamilton Microlab STAR and a BMG Labtech PheraSTAR plate reader at the event (Thanks Hamilton and BMG for providing us with the instruments!) and run the submission live during the event.
You can learn more and register for the challenge here
Looking forward to seeing some innovative solutions!
