Future of Lab Automation

Over the past several decades, automation has become more commonplace in laboratories around the world, with manual processes being replaced by machines in every area of science and technology.

Lab Robot

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The purpose of automation is to improve the quality of processes, remove human error and variation, and ultimately make processes more cost-effective, efficient, and rapid.

Lab automation is expected to continue to infiltrate labs over the coming years, with new technologies being developed and adopted. However, several challenges need to be addressed before lab automation can reach its full potential.

Growth of the lab automation market

Recent reports have valued the total lab automation market at $1027.5 million in 2019. This is expected to grow at a compound annual growth rate (CAGR) of 6% between now and 2025, reaching a value of 1554.94 billion. This rapid growth is being mostly driven by the rising demand for higher accuracy of test results.

Also, advances in available automation technology from some of the industrys major players, such as Siemens AG, Honeywell, and Schimadzu, amongst others, boost the adoption of automated technologies by more laboratories worldwide.

In the US, in particular, there has been increased spending on healthcare, which leads to the improvement of research and development processes, including clinical trials.

The improvement of clinical trials has led to a growing interest in automation, which is being brought in to improve the quality and accuracy of testing protocols. This alone will act as a major driver of lab automation in the coming years.

The Asian Pacific is the region representing the fastest area of growth now and over the next five years. Companies here are making significant advances in available technology, and labs are seeing the value of adding these technologies into their methodologies.

Why automate a lab?

The main reason for adopting automation processes is to improve the accuracy of lab testing. Manual processes rely on human workers, who by their nature are not immune to error and external and internal factors such as tiredness.

Data shows that between 30% and 86% of total pre-analytic errors are attributed to human error. Therefore, in replacing humans with robots, this significant contributor to error can be instantly removed.

In addition, manual processes are far more time consuming than automatic ones, accounting for around 60% of the total time invested in a specimen workflow.

Therefore, replacing manual processes with automated ones allows for testing to occur in a short timeframe with fewer resource allocations.

This has the effect of increasing the efficiency of the testing, making it more cost-effective and allowing labs to reallocate human resources to other areas of the business that are more value-creating.

Developments in lab automation

The establishment of the Laboratory Information Management System (LIMS) is expected to help boost the lab automation market over the coming years.

Recently, major advances have been made in the software that manages lab automation systems, giving users more control and visibility of their workflows and machinery.

LIMS enables researchers to automate their workflows, integrate their instruments, and generate accurate and reliable results with speed and precision. LIMS can also help in tracking data from sequencing that occurs over time and between multiple experiments.

These systems are expected to be commonplace in automated labs of the future. It is also expected that the technology offered by these systems will continue to grow and develop, adding further benefits to introducing lab automation systems.

One particular area of science that is expected to rapidly adopt automation processes over the coming years is the field of molecular biology. Recent research has demonstrated that automated systems are capable of handling delicate biological samples in a way that does not impact the results.

For example, there was initial concern over how the mechanical movements of transporting samples could lead to detectable changes in the results. However, with the improvement of technology and machinery, the impact of mechanical movement is no longer an issue.

For this reason, biological labs are now confident in adding automation to their testing processes.

Finally, future lab automation systems are predicted to develop to be more user-friendly. There is a call for automation systems to be easier to manage, with less training and knowledge needed to operate them.

This will reduce the investment required to get automation systems up and improve the cost-effectiveness. It is expected that software management systems will show rapid improvement over the coming years to meet this need.

Challenges in lab automation

Several challenges need to be overcome before lab automation can reach its full potential. Firstly, the conversion from manual to automated systems requires re-training staff, who are used to working with the samples with their hands, to be able to operate the technological systems instead.

Staff may not always have the same level of expertise when it comes to computer systems, which can present an extra cost and time expense in needing to provide training.

Because of this need to retrain, there is often a learning curve involved when new automated systems are introduced. This means that there is a period while staff are still acquiring skills and knowledge before the system can operate at its full efficiency.

However, while staff are required to learn new skills to operate the new systems, there is also a concern that over time knowledge of how and why methods are conducted in certain ways will be lost.

As human involvement in testing reduces, the underlying knowledge of these tests may be lost, which will present problems when troubleshooting of the automated equipment is called upon

Finally, automated systems are subject to technological glitches. Some mechanical errors are hard to spot and can build up over time, having the effect of reducing the accuracy of the results produced.

Staff need to be thoroughly trained in how to spot these mistakes early to prevent decreases in accuracy and quality.


Further Reading

Last Updated: Mar 20, 2020

Sarah Moore

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Sarah Moore

After studying Psychology and then Neuroscience, Sarah quickly found her enjoyment for researching and writing research papers; turning to a passion to connect ideas with people through writing.


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