The failed promise of lab automation
- Set multichannel pipette volume to 100μL
- Pick up tips with multichannel
- Aspirate liquid from position A1-H1
- Dispense liquids into new plate: positions A1-H1
- Mix sample to assumed homogeneity, approximately ten times
- Eject tips in to waste bin
- Repeat the process but for positions A2-H2 into new plate A2-H2…
Does that sound familiar? Actually, it’s what we spend a lot of our time as scientists doing…rather than thinking about new science.
There are a lot of repetitive liquid handling actions in modern biology and to make progress we are expected to pipette carefully, rapidly and with provenance (e.g. record where we pipette to). Occasionally, the cycle breaks, you make an error, I know I have. This means you have to skip a row, start again, mark the data as lost, lose time, stay late etc. My frustration is palpable.
At the various sites I have been at, this is also the case with nearly all the scientists I’ve had the pleasure of working with. As humans, we can’t avoid making such mistakes when performing mundane tasks. Our minds yearn for more than just repetitive action. So why is it that in biology, we have highly educated people performing tasks, that in many other industries would no longer be done by human! Shouldn’t a liquid handling robot be doing this for us?
There are lots of fantastic liquid handling hardware on the market, hardware that is great at moving liquids around, and yet a lot of them are:
i) Purchased but unused as they take almost as long to program as it would take to do by hand i.e. no time cost-benefit;
ii) The liquid handler is specifically used for a single task only, although it has wider capability;
iii) No one knows how to use it or has the time to learn.
This has led to what I like to call, the failed promise of lab automation and has given rise to the infamous laboratory automation graveyards you can probably find in your laboratories now (try the cupboards or the corner where no one works….).
So what? Why should we care about how little flexible automation equipment is used within the industry?
Well, as scientists, we should be spending our time managing innovation, exploring experimental results, planning, and be thinking of ways of accelerating the science we do by increasing our lab team’s productivity. All of this has the potential to save the industry huge amounts of time and money. How do we do this? Well, we enable our scientists with the means of flexibly automating laboratory hardware with ease.
This is what Antha delivers.
Antha, for me, is a tool that I can use to run my everyday experiments in the lab across multiple liquid handlers using Antha as a single common language.
Antha is seamless and intuitive. I can use Antha to wire up complex liquid handling actions with little effort and I don’t even have to think about what position my liquid in plate 1 needs to go in to. All I have to do is enter parameter values that describe my experiment, such as, do I want to add 50uL or 100uL of stop solution to my ELISA assay. Using Antha is as easy as setting up the parameters required for running a particular washing cycle on your washing machine or altering the account setting for your Gmail account. Antha only gives you the information you need to care about, it handles the rest!
In my experience, using Antha to build my experimental protocols reduces my planning time tremendously, in some cases by 90%. It stores the exact experimental protocols in the Antha job queue, which my colleagues and clients can run on their own devices and frees me up to work on more mission-critical science. Antha lets scientists finally leverage the automation capabilities available.
So why not brush off the dust from your liquid handler and let Antha deliver the promise of lab automation – seamless, beautiful and intuitive!
Machine Learning: It’s All About the Data
How to build a strong data foundation for machine learning applications.
Synthace Unveils First Life Sciences R&D Cloud Addressing Complexity, Speed & Reproducibility for Scientists
First ever no-code platform lowers barriers to automated biological experimentation and insight sharing.