Robots in the lab

How do robots help scientists with their work every day in the lab?
26 February 2014

Interview with 

Neil Bargh, TAP Biosystems

Lab_Robot.jpg

A robot in action in the lab

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Neil Bargh who works in research and development for TAP Biosystems explains to the Lab robotaudience at the Cambridge Science Centre how he develops robots for use in the lab and how difficult it is for robots to model the human hand....

Chris - Neil, you make robots to work in the laboratory. So, tell us about them. What do you actually do?

Neil - Our systems do all kinds of different processes in laboratories. We've been making systems for about 20 years doing processing bottles or flasks like these. These are called T-flasks. They hold about 600 ml of liquid. It's about a pint.

Chris - Do you put beer in them then? Is that what you're doing?

Neil - We've had ideas of such things.

Chris - You do fermentation.

Neil - Yes, we do. These are used to grow cells in, all kinds of cells - animal cells, maybe insect cells and the reason that that's done is to help with pharmaceutical research. Now all around the world, there are thousands of biologists and part of their job is to look after their cells. So, once every few days, they'll need to get a collection of these flasks, take them out of an incubator, unscrew the caps, empty the contents of the liquid in there. Basically, give their cells some more food. The cells grow in the flask and eventually, the cells run out of space. So then, you have to take the cells out to the flask, put them into a new flask to give them some more space to grow and keep them happy. Now, the cells grow at a certain rate and sometimes they need to be like fed and watered at the weekend, so people have to then work the weekend to keep looking after their cells.

Chris - That's what graduate students are for, isn't it?

Neil - It is exactly, but once people mature, get older, they don't like spending their weekends going into the lab to do these jobs and that's where some of our systems come in. Our systems can automate the whole process so that scientists can actually use their time more valuably rather than doing the jobs of unscrewing caps and pouring pipetting liquids.

Chris - Isn't it true though that the volumes of liquids that we're testing in laboratories, for many of the modern tests like DNA tests and things are really, really small, and we're doing many, many hundreds of test tubes all in a row all at once and humans are not terribly good at remembering where they got to? You might make a mistake on the 89th tube and they think, "Was it the 88th or 89th? I better start again." Isn't a robot better than that?

Neil - Very much, so. Many years ago, people used to do all of their work in test tubes. As time progressed, we ended up with things like this. This is a plate with 1,536 wells in it. Each well is about a millimetre square and about 5 millimetres deep. To access that, you need some small pipette tips. So in this box, there are 384 pipette tips. So, we make systems that can pipette 384 samples at a time from plates like this into other plates like that for performing experiments on mass.

Chris - Any questions so far about how we can build robots to speed up research in the laboratory?

Ginny - Well, I've got one on the email from Steve Lamble who says, "Why is this technology not used in Amazon warehouses? This was something that was big in the news recently. We're still asking humans to run around with trollies to pick things up." Sounds like the kind of thing, I mean, on a bigger scale, but similar to what you're talking about.

Neil - Yes and actually, I'm surprised that they wouldn't use automated systems in the Amazon warehouse because many warehousing systems are automated. We made a system for the UK Biobank which is for storage of biological samples they're stored at minus 80 degrees. There's potentially millions of samples. The robot is actually working at about minus 20 degrees, but that's an example of an automated warehousing system.

Chris - So, unlike the employees at Amazon who were complaining last year about conditions, robots don't complain. I suppose that's one big bonus, isn't it?

Neil - Indeed. They can work 24 hours a day, 7 days a week without stopping. They need some maintenance but that's of the benefits of automation is that they can work round the clock.

Dave - Is it part of the reason why that's going to be very difficult because there's lots of different objects in the warehouse and you're saying that robots are not that good at dealing with newer, unexpected situations.

Neil - It's certainly a significant factor. Whenever we are looking at a new application, we try and standardise the things that need to be handled and handled as few different components as possible and even try and design the things that we need to handle to make them suitable for robotic application. So, I think you're right, the size and shapes of the packages will be a big factor and if they were to try and automate it, they'd probably need to standardise on a small set of different size boxes.

Chris - So, do people come to you and say, "This is our laboratory. We want you to design us a robot that will do things in our laboratory" or do you make systems and then people buy them and design their lab around your system?

Neil - It's a bit of both. Quite often, we're looking to develop new systems so we talk to people and say, "What is it that you do in your working life and where are the real problems? Where do you spend all of your time?" And so, having those discussions, we identify that people spend a lot of their time doing fairly mundane tasks. We think, well, if we can help with that task, is that worthwhile? And in some of the applications like the automation of cell culture, there's a variety of benefits. It's not just about say, a labour-saving action. When humans perform an operation, there's always some variability from one person to the next person, or what happens on Friday afternoon is often different to what happens on Monday morning, whereas a robot will perform the same task, pretty much identically every time it performs it. So then, you get more consistency of how the cells are actually growing in the flask. Robots also don't introduce contamination. So, that's quite a problem when you're trying to do cell culture, making sure everything stays sterile. There's bacteria everywhere. It's very easy to contaminate samples, but robots can't inherently contaminate it.

Chris - Can't your robots catch computer viruses?

Neil - We try to avoid that, yeah.

Chris - What sort of software do they run on then? How do you programme them?

Neil - There's a variety of different software packages at different levels. So usually, there's a system PC that's running Windows and that then would talk to say, the arm that's got its own controller in, that's sort of coordinating the manipulation of each of each joints to move the pieces around.

Chris - What about actually making those movements though because I have a hand and the most powerful feature of my hand is the fact that I can make my thumb meet the ends of each of my digits. Is that something that's very easy to replicate?

Neil - Not at all. I think generally as humans, we underestimate how amazingly sophisticated our bodies are. So, when you grab something with your hand, you've got an amazing sense of touch in all of your fingers and that feedback with your eyes means that you can look to an object and pick it up. And you don't even think about it. Whereas with a robotic system, on a robotic system that doesn't have a lot of sensory feedback, we might not know that if we picked up a bottle, and it had a missing cap, we might not know that. And then we try to process that and things would go wrong. So, we do have to have a certain amount of sensors on the system.  But relatively, most robot grippers are pretty clumsy compared to our hands.

Chris - Any questions first before we - we've just got one question here.

Jack - My name is Jack and I'm from Comberton. How much would it cost to like make and design one of these robots?

Neil - It depends on the sophistication of the system, but usually, it's millions of pounds of development effort.

Chris - How much pocket money do you get? It depends on how many chores he does? You need a robot for that.

Bea - Hi. My name is Bea and I'm from Cambridge. I was wondering, to what level can these systems be used for pattern recognition within the lab environment? So currently, as you explained, they're doing some mechanical tasks, but when it gets to sort of say, analysing 900 different samples, they might provide a sort of speed of processing that is much quicker and help narrow down the amount of samples that say, people working in the lab would have, to take further.

Neil - Yes, so I think that's more related to say, a vision system and analysis of say a photograph. So, as an example, it might be trying to recognise cancerous cells from non-cancerous cells, and that might be a very good application for helping that kind of activity in a lab. There are quite a lot of robotic systems that do have integrated vision systems on them. An example would be in PCB construction, your printed circuit boards inside phones. There are circuit boards with tiny components on and in the assembly of those, those components are presented to the robot, the robot picks them up with a little tiny suction cup. It'll move it to a camera, the camera looks at it, decides where exactly it is and sets the orientation of it, for them to be able to accurately place it onto the PCB.

Ginny - I've got a question here from Dominic in Cambridge. He says, "Why have robots been used in factory production lines for so many years, but seem to be very slow to appear in people's homes? Where's our robot to do the chores?"

Neil - Yes, if only we have those robots in our homes. I think, a lot to do with the economics of it. So, in industrial processes where there's the same task to be done over and over again, so if you think about car production lines where, if you're making one car a minute then having a robot that can do the same spot welds all the time is a very efficient way of applying a robot to a process because it's the same process whereas in a house, the household chores of washing up and doing the hoovering, dusting the cobwebs, they're very varied and everybody's houses are very different. So, in terms of robots, there are vacuums that will sort of bump around, hoovering the carpet, what does it do on the stairs? It gets stuck.

Chris - They defeated the Daleks didn't they, in the stairs. I tell you what we do want. We want an ironing robot. That's what we want, a robot to do ironing.

Neil - No, but then there's other solutions. It would be much better to have clothes that don't need ironing. So, that would be say, an engineer's approach to solving the problem.

Chris - Have you and Blaise got together to see if his speech recognition could be plumbed in to your robots so that you could actually end up with a robot that would do as you told it?

Neil - No, we haven't but it would be very useful because sometimes in developing systems, you can see something bad is going to occur. If only you could shout, "Stop now!"

Chris - Can you list one of such example?

Neil -  Well, these flasks, they're quite brittle material and sometimes in developing the systems, you leave a flask in a place where it shouldn't be. The robot, the system knows where everything is, but if you open an incubator door and you decide to start moving flasks, and you take the flask out, have a look at it, think that's very interesting and put it back, if the system doesn't know that, it can quite easily just smash one of these flasks completely inside another flask. So it would basically one flask right inside another.

Chris - Whoops! Especially if there's ebola in there or something. That could nasty, couldn't it?

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