Arvind Kothandaraman, general manager of PerkinElmer’s professional diagnostics department, explores how automation in the lab enables molecular monitoring.
For decades, automation has played an important role in shaping the way people in different industries and jobs work. However, its current and future implications are especially acute in the lab.
Artificial intelligence (AI), machine learning (ML), and robotics have been in the lab for years, but these automation technologies are becoming more and more important in the era of COVID-19. From 2021, diagnostic labs will continue to adopt automation, especially in the move towards widespread monitoring. Second, the advances made by the lab will contribute to a wide range of efforts in the global scientific community that will lead to new and improved ways to detect diseases, develop treatments and discover preventative measures.
Since the early applications in the lab, automation, especially mechanical automation, has helped improve the work of lab personnel. Aside from the many iterations, many lab procedures are difficult and error-prone when performed manually. For this reason, it is not uncommon to see a high percentage of burnouts in the population of lab employees responsible for this task. However, if technicians have access to self-contained, fully automated equipment and workflows, the result is higher laboratory throughput and minimal manual effort associated with this task. In addition, manual testing tends to be sensitive to person-to-person and laboratory-to-laboratory variability, so mechanical automation has long been used to maintain sample integrity and reduce errors. Has been done.
In addition to the mechanical automation common in today’s diagnostic and reference laboratories, there is a broad view of software products that automate the back-end tasks of diagnostic laboratories. These to avoid the tedious and time-consuming tasks associated with test analysis, as well as the operational aspects of lab management such as inventory, purchasing, coding, and billing software platforms backed by AI, ML, or robotic process automation. Processes can be accelerated, often by lab leaders within established specific parameters. The advent of cloud and cloud-based platforms has taken a step towards eliminating the burden of traditional lab management and monitoring. These have proven to be of great value in an increasingly remote and socially distant world.
Decades ago, the lab environment we know today may have been unimaginable. And automation is likely to continue to exceed our expectations, so it’s not just about making your lab work more efficient, effective, and safe. In fact, it may change the nature of the laboratory work itself very well.
Automation 2.0 and next generation monitoring
As society continues to face COVID-19, automation tools and technologies will enable a new era of diagnostic testing and screening, enabling laboratories to monitor outbreaks of infectious diseases at the community and population levels. For example, a research lab at Rutgers University in New Jersey used automation to develop a test in the state that dramatically extended the COVID-19 test. At the time, a typical hospital could process 20 to 30 samples a day, but this technology has shown the potential to process tens of thousands of samples in the same period.
Over the next few years, similar advances in machine lab automation will enable diagnostic labs to respond in real time to ever-increasing test demands, especially as more routine screening programs are adopted. Also, take a look at next-generation lab equipment with technologies that enable improved connectivity. This makes wireless or remote management the norm in small private labs.
For other experimental software, automation continues to show impressive strengths in data analysis. Automation provides insights that help researchers better understand how disease develops and spreads in the human body by aggregating and analyzing a treasure trove of information created by current test programs. Helps to produce. Only with this knowledge can pharmaceutical companies begin developing drugs and treatments that can control the disease and ideally treat it. One day, automation could even move beyond the retrospective approach to diagnostics into the field of predictive analysis.
We don’t yet know how far automation will go in the field of diagnostics, but one thing is certain: these technologies will stay here. The laboratories that continue to adopt all forms of automation are those that will flourish after 2021.
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