Standardizing Robotics and Automation in the Lab

Advances in computing and technological development in robotics are helping drive labs in to the world of automation. We often come across terms such as "Lab of the Future" and "Smart Lab" – but what do these actually mean? 

We recently spoke to Dr Patrick Courtney, member of the Board of Directors of SiLA (Standards in Laboratory Automation) to learn more about the value of implementing laboratory robotics and automation. Patrick defines some of the key terms used in the field, explains why pharma is so well-suited to automation, and discusses current and future industry trends.

Laura Lansdowne (LL): Could you tell us more about the Standardization in Lab Automation (SiLA) consortium, their history and mission?

PC: SiLA exists to facilitate experimental science by providing open IT communication standards in the laboratory. This means enabling all those great lab instruments to communicate together better, managing data is easier and work less frustrating, making it easier to run a laboratory and improving collaboration between scientists.

The consortium is established as a non-profit membership organization, bringing together lab users and suppliers. This means that the standards are driven by the lab community and available at no cost. It has 30 core members, users and suppliers as well as some 2000 personal members. 

The idea grew out of internal initiatives in some large pharma companies and opened up to the community when it was realized that this is how it could be of most value. The first iteration was used to build a number of large integrated systems and brought many benefits to their operators. In summer 2018 we released SiLA2. This is updated and based on more modern technologies, supporting wireless for example. And we have an alliance with an open data standard called AnIML (Analytical Information Markup Language) from the ANSI standards committee in the US and which is already used by many vendors.

The community is now using it to build work-cells and bring more suppliers and users on board. We’re finding that it is being enthusiastically embraced by startups – who want to save effort in developing interfaces and focus on the innovative aspects – and by academic groups who are integrating devices to create novel systems for life science research.

LL: Could you touch on the economic value of implementing robotics and automation into the laboratory?

PC: Robotics and automation has brought great benefits in areas such as manufacturing; improving throughput and quality, and reducing cost. Robotics people talk about the "3 Ds": dull, dangerous and dirty, where robots can be most useful. We certainly have all these in the lab – in fact we can add a further ‘D’: delicate. Handling fragile cells and tiny quantities of liquids are delicate tasks that have traditionally required human skill but with considerable variability and cost. The ability of laboratory robots to perform liquid handling has been a startling success and has enabled the high-throughput screens that would simply not have been possible using manual pipetting. In the clinical lab, routine blood tests have reached a low price point thanks to the high degree of automation used.

While the benefits – productivity, turn-around time and quality, reduction in errors and lost samples – have are not always very rigorously quantified, there is some useful literature starting to appear which is well worth studying.

The problem of reproducibility in science has also been much discussed recently and robotics and automation have a role to play here, especially when it allows protocols to be more fully documented and shared. 

LL: Can you explain what is meant be the term smart lab?

PC: This term has been used to describe a lab that is much more interconnected than it is today, and does not rely on post-it notes and USB sticks. The manufacturing industry is rapidly adopting new technologies to support production, in this context they talk about ‘industry 4.0’, exploiting technologies such as wireless tags, internet of things, cloud computing, smarter robots, machine learning and so on.

These technologies are developing rapidly, opening up new possibilities in quality and productivity, and also ease of use. So, digitizing the lab is not just about the result data, but also the operations. This will allow more efficient planning and process optimization, as well as areas new to the lab such as simulation and modeling, along with visualization for better communication between staff and the technology.

It’s a fast-changing scheme and no-one has all the answers right now. So, within SiLA we’ve been organizing workshops at the ELRIG conference to bring people together to discuss the smart lab and artificial intelligence (AI).

But the smart lab not just about technology. It goes hand-in-hand with organizational innovations such as “lean” with an emphasis on the communication, training and a focus on real value-added activities. And this is valid for both routine and research labs.

LL: What makes pharma so suitable for automation? 

PC: The pharmaceutical industry has the advantage over other sectors that there is a shared understanding of the process of getting a new drug to market, thanks in part to the regulatory environment. Of course, drug development is still very challenging, time consuming and expensive, and to many not very efficient. So, the role of automation has been clearly articulated and is well established in areas such as screening. Moreover, the industry has a highly trained workforce, and high labor costs also encourage openness to the use of automation.

The rise of personalized medicine and cell therapies will also call on robotics and automation in order to deliver on the promise at a reasonable cost.

LL: Can you give any specific examples of "success stories"?

PC: Pharmaceutical companies such as GSK and AstraZeneca have spoken eloquently on the advantages they have seen from investing in robotics. AstraZeneca have been re-tooling with a new site in Cambridge UK and have gained some great insights on working with suppliers to secure and share the benefits. Meanwhile suppliers such as PAA have been doing very well providing integrated systems, as have the more classic robotics suppliers like Analytik Jena and Tecan, and startups like UniteLabs and cubuslab, all SiLA-members.

Another significant success story has been the take-up of DNA sequencing which has become highly automated and found application in all sorts of areas as the price has come down – from cancer therapy, to ecology and archaeology.

For the smart connected lab, it is still early days. SiLA2 is starting to be rolled out so we can expect new success stories which will be reported during the 2019 SLAS Annual Conference in Washington, DC this February.

LL: How close are we to achieving the lab of the future? Do you think it will happen? 

PC: New facilities are being built by the large users to facilitate collaboration and which take the opportunity to re-think lab layout and informatics. Some examples of open innovation labs are the Materials Innovation Factory with Unilever and Liverpool University, and the ROAR (Centre for Rapid Online Analysis of Reactions) at Imperial College London which scientists are using now. And it’s worth mentioning the SmartLAB Innovation Network in Germany which has been experimenting with new lab furniture design and smart glasses.

However, these are expensive initiatives and the technology is changing all the time, so the lab of the future is always going to seem to be just around the corner.

We are also seeing the establishment of cloud lab approaches, like Transcriptic and Synthace, where you can upload experimental protocols and download results. But it’s really the next generation of scientists that will push it through.

LL: Could you highlight some of the current and future industry trends?

PC: We’re seeing a lot of interest in the topics of personalized medicines and cell therapies such as CAR-T cell. For the lab, this means widening use of techniques such as next generation sequencing (NGS) and CRISPR, as well as organ-on-a-chip.

In terms of robotics, there is increased interest in collaborative robotics, which will allow robots to work alongside bench scientists without harm – there are some great products coming out such as the Andrew Alliance robot. AI is another hot topic in the lab with the hope that data lakes can be mined for new insights. However, this will require tighter integration with lab systems, something SiLA can help with. Looking further in to the future we may start to see more autonomous robotic scientists, planning and executing experiments in the manner described by Prof. Ross King and colleagues.

These exciting developments should help all of us working in the lab to become more productive while gaining new scientific insights. 

Patrick Courtney was speaking with Laura Elizabeth Lansdowne, Science Writer for Technology Networks.