Life sciences research often involves costly and complex procedures that take time away from experiment planning. Lab automation could speed up the process across a range of areas, including drug development, diagnostics, and synthetic biology.
Speed has always been a critical but somewhat elusive goal in life sciences research. While technological advances have led to acceleration in some areas, those in the industry will be familiar with some of the more stubborn statistics: for instance, it typically takes upward of 10 years and a billion dollars to bring a drug to market. But the recent months of the pandemic have brought a renewed push for speed, particularly regarding bringing vaccines and medicines to market sooner and developing diagnostics that are faster, less expensive, and more accurate than ever.
Biopharma and biotech companies, along with academic institutions and governments, are putting greater investment into automated instruments and techniques that speed up workflows, make resources go further, and produce extraordinarily accurate results. Most of all, they make possible a whole new level of research that will position us well for the future.
My specialty is in the design of advanced liquid handlers; my team and I created an instrument that uses soundwaves to cause a specific, tiny quantity of liquid to ‘leap’ from one container to another. An integral part of this level of automation for any instrument is miniaturization—that is, using just a tiny fraction of the samples and reagents that would be needed in a conventional liquid handler. Together, miniaturization and automation allow one to do more with less, and, in the case of using soundwaves to move liquid, the combination produces extremely accurate results. It also saves time, resources, and even money in the reduced quantities of samples and reagents they require.
The lab of the future will incorporate more and more of these technologies. As instruments have become more automated, researchers are spending less time in the lab; an individual can set up an experiment and then go home to remotely initiate and run it. This remarkable level of automation frees up time for other things. Having a machine do the bulk of the work, especially for workflows that are highly complex, allows researchers to put more emphasis on thinking and designing future experiments, and less on logistics.
Not surprisingly, the most intricate processes benefit the most from automation and miniaturization. Genomics work can be incredibly time consuming, and often difficult to do manually. With advanced instruments, cloning methods can be reduced from the microliter to the nanoliter scale, which again saves time, materials and reagents, and money. The same is true for polymerase chain reaction (PCR), which is used in Covid-19 research and diagnostics, among others.
Synthetic biology has some of the most complex workflows, and stands to gain the most from advanced automation. With instruments that automate and miniaturize, the assembly of large DNA molecules in a synthetic biology workflow moves from 12 hours to three hours. In DNA sequencing, pooling together DNA fragments from sample libraries also becomes much faster: transferring each sample takes less than a second using automation, which can reduce the total time from six hours to 12 minutes.
Automation is advancing along many other exciting avenues as well. Robotic transfer of plates and other materials can occur not just within an instrument, but between instruments. This level of choreography will allow even more complex research to be carried out, with researchers monitoring larger experiments from afar. And in this age of remote working, the ability to carry out lab work from home may be especially desirable.
Remote laboratories are popping up all over the world; they allow a researcher to choose compounds online and map out an experiment remotely. The research can then be carried out at a lab anywhere across the globe, with the researcher never stepping foot in a physical lab.
The central feature of moving toward more comprehensive automation is that it will silently handle unprecedented levels of complexity, both during and in preparation for experiments. For instance, machine learning systems can gain knowledge of how various combinations of reagents perform, predict and propose what might work better, see if the reagents are available and even order them, and schedule the synthesis and testing of the new compounds. Researchers are reporting doing more experiments on faster timelines with automation. This again shifts focus from doing and logistics to thinking and designing larger investigations.
An interesting example of the growing confidence in lab automation is Amazon, a company that has long embraced automation for its own business operations—most people have probably seen footage of robots shuffling items back and forth across the warehouse. Amazon has invested heavily in accumulating and optimizing its army of warehouse robots to be smaller, faster, stronger, and smarter. More recently, the company invested in automated lab instruments in both the US and UK to carry out regular Covid-19 PCR tests for its employees. Although it was a large financial investment, doing the testing in-house will end up saving money in the long run—and underscores the company’s commitment to automation, particularly as it moves deeper into its own public healthcare offerings.
For some organizations, the greatest barrier to automation may indeed be cost, particularly as it may seem cheaper to have a graduate student carry out an experiment than an advanced machine. But as mentioned, the miniaturization factor implicit in automation goes a long way in reducing costs for materials, reagents, and other consumables, in addition to the sheer speed of automation.
The reality is that a lot of questions simply can’t be answered in laboratories without automation—this will increasingly cause a divide between those who have taken the plunge and those who haven’t. The need for automation and the benefits derived from it will only be clearer in the future, as experiments become more complex, workflows faster, and researchers more accustomed to mapping out pathways of experiments from their desks, with much less physical involvement.
The bottom line is that automation allows for more efficient and accurate research—it’s already had a very real effect on the speed of developing and bringing life-saving therapies and vaccines to patients, and it will only accelerate in the coming years.
Rich Ellson is Chief Technology Officer and Director of Research at Beckman Coulter Life Sciences. He joined the company in 2019 with the acquisition of Labcyte where he served as Chief Technology Officer, Board Director, and co-founder since 2000. Labcyte was a biotech tools company best known for its acoustic liquid handling instruments that have been drivers for automation and miniaturization. Ellson is also a fellow, prior board member, and active volunteer in the Society for Laboratory Automation and Screening (SLAS).