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How automation has unlocked a new era in surveillance

How automation has unlocked a new era in surveillance

Arvind Kothandaraman, general manager, specialty diagnostics at PerkinElmer, examines how automation in the lab enables molecular surveillance. 

For decades, automation has played an important role in shaping how people across industries and job functions do their work. Its current and future impact, however, will be especially profound in the lab. 

While artificial intelligence (AI), machine learning (ML) and robotics have been in laboratories for years, these automation technologies have become increasingly important in the age of COVID-19. In 2021 and beyond, diagnostic labs will continue to embrace automation, particularly in a move toward widespread surveillance. In turn, the advances made by labs will contribute to a broader effort in the global scientific community that leads to new and improved methods of detecting disease, developing therapeutics and discovering preventative measures. 

Automation 1.0

Since its earliest applications in the lab, automation – particularly mechanical automation – has helped improve the jobs of laboratory personnel. Apart from being highly repetitive, many lab procedures can be arduous and error-prone when performed manually. For this reason, it’s not uncommon to see a high rate of burnout among the population of lab employees who are responsible this work. However, when technicians have the option of working with self-contained, fully automated instruments and workflows, the result is often increased lab throughput and a minimal amount of manual labour associated with this work. Furthermore, because manual testing also tends to be susceptible to person-to-person and laboratory-to-laboratory variation, mechanical automation has long been used to maintain sample integrity and reduce error. 

In addition to the mechanical automation that is commonplace in diagnostic and reference laboratories today, there is an expansive landscape of software offerings that automate the back-end work of diagnostic labs as well. To avoid the tedious and time-intensive tasks associated with testing analysis – along with more operational aspects of lab management like inventory, purchasing, coding and billing – software platforms backed by AI, ML or robotic process automation can accelerate these processes and oftentimes within specific parameters established by lab leaders. The advent of the cloud and cloud-based platforms go a step further toward eliminating the burden of traditional lab management and monitoring, which are also proving to be greatly valuable in an increasingly remote and socially distanced world. 

Decades ago, the lab environment that we know today might have been unimaginable. And, as automation is likely to continue exceeding our expectations, it will move beyond making lab work more efficient, effective and safer. In fact, it may very well change the nature of lab work itself.

Automation 2.0 and next-generation surveillance

As society continues to confront COVID-19, automation tools and technologies are enabling a new era of diagnostic testing and screening – helping labs monitor for community- and population-level occurrences of infectious disease. For example, a research lab at Rutgers University in New Jersey harnessed automation to develop a test that dramatically expanded COVID-19 testing in that state. While at the time, a typical hospital was able to process 20 to 30 samples a day, this technology showed potential for processing tens of thousands of samples in the same time span.

In the coming years, similar advances in mechanical lab automation will help diagnostic labs keep pace with ever-increasing testing demands in real-time – especially as more routine screening programs are adopted. We’ll also see future generations of lab instruments outfitted with technologies that allow for increased connectivity, making wireless or remote management the norm—even for smaller private labs.

In terms of other laboratory software, automation will continue to show impressive strength in data analysis. By aggregating and analysing the treasure trove of information that current testing programs have created, automation will help generate insights that help researchers better understand how disease develops in the human body, and how it spreads. Only when armed with this knowledge can pharmaceutical companies begin to develop the drugs and therapeutics with potential to control and ideally cure diseases. One day, automation may even move beyond the retrospective approach to diagnostics and more into the field of predictive analytics. 

While it remains to be seen just how far automation will go in the field of diagnostics, one thing that is certain is that these technologies here to stay. Laboratories that continue to embrace automation in all its forms are those that will thrive in 2021 and beyond. 

Med-Tech Innovation

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