This isn’t just specific to Opentrons, but here’s how I see it: find the biggest pain point with the most impactful result, and you’ll have your primary focus for automation.
In my career, I introduced automation to a lab that previously relied entirely on manual processes. I began by automating portions of common assays, step by step. Now, I must warn you: introducing automation into an established manual workflow is challenging, especially compared to designing automation from the start. Your team may initially struggle to grasp the nuances, like the impact of dead volumes or the importance of scalability. It can be tough to push through this initial resistance, and it’s one reason why automation often goes underutilized.
One great way to start small is by automating serial dilutions for common assays like ELISA, BCA quantifications, Luminex, or MSD plate runs. These assays allow you to showcase automation’s value, demonstrating reproducibility, low CVs, and comparable dead volumes to manual methods.
Where I wouldn’t recommend starting is with 96-head stamping, as the dead volume requirements can be high—up to 15-30mL per reagent in some cases, which may be several times higher than needed for manual methods.
Another effective approach is to let your team use the device for smaller tasks that benefit from repeatability and consistency. As the automation lead, you shape perceptions of these systems, so if you focus the team on a specific powerhouse assay, like ELISA, you can establish norms and SOPs around automation that wouldn’t arise organically in a manual setup.
Other great introductory tasks for automation include aliquoting samples into a 96-deep well format or reformatting from tubes to plates. These are low-hanging fruit, achievable quickly, and serve as foundational steps toward more complex assays.
I’d suggest thinking of automation as a tool, like a multichannel pipette, rather than as an all-or-nothing change. It’s there to boost efficiency and reduce errors. And remember, automated processes are rarely a direct 1:1 replacement for manual methods; there will always be differences. For instance, precision and accuracy are often desirable, but not always essential. Hamilton, for example, has a helpful visual on this, showing that if a reagent isn’t a limiting factor, you might prioritize quick dispenses over precise ones.
While Opentrons is a powerhouse in lab automation, it’s essential to select the right tool for each job. Opentrons excels in assay support but may not be ideal for every type of assay. For ultra-high throughput or clinical testing, I’d recommend Hamilton. For low-volume pipetting, the FAST system is preferable, while Lynx is excellent for rapid normalizations. Trying to force a single system into roles it isn’t designed for can create issues.
Opentrons also offers a strong applications team and plenty of pre-written protocols and methods, so make the most of those. Use these as foundations but don’t take them at face value; often, standard scripts don’t fully meet the specific needs of your lab’s workflows, though they can inspire new applications.
I’d love to hear where you’re planning to start with your robot. Welcome to this exciting journey—taking the first step to make the robots work!