Busting common myths about lab automation 

Automation concept

Ernesto Staroswiecki, Senior Manager, R&D, at Beckman Coulter Life Sciences takes readers through common lab automation myths. 

Many clinical and research laboratories today are having to do more with less: faced with ongoing staffing shortages, increased workloads, and budgetary constraints, many laboratory managers are feeling the stress, which is where the benefits of automation can be truly realised for labs in both academia and industry. Such a move can be filled with uncertainties and unknowns; for those with little to no experience with automation in the laboratory, the process can seem too difficult, expensive, and perhaps intimidating to undertake. 

Although laboratory automation has become more mainstream, many myths and misconceptions remain. These misunderstandings about what automation can do and how it can be integrated into laboratory workflows may prevent managers from effectively utilising this technology, so here are the truths behind some common myths about lab automation.

Myth 1: The cost of automation is too big – and my lab is too small

High-throughput screening is far from the only area in which automation is beneficial. Laboratory automation – much like computers – have both evolved over the years and have come down in both cost and size. Decades ago, an entire room was needed for a computer and now it fits in the palm of your hand. Certain automated instruments have similarly become more accessible, with some now able to sit on the benchtop compared to needing an entire corner of a lab with out-of-sight costs. In recent years smaller, more compact products, such as liquid handlers and nucleic acid purification systems, are now commonplace and used in labs both large and small.  

Many automation solutions can perform several different tasks and can be paired with other equipment to automate a range of tasks, such as DNA extraction and sequencing, PCR, and Western blots. Even smaller labs with more limited budgets are now able to utilise automated equipment for daily tasks.  

Improvements in software and user interfaces mean that labs don’t need a dedicated programmer to run the equipment. Often, experiments can be set up from pre-set menus and with a few simple clicks. While some manufacturers offer the ability to create your own code for their devices, most machines can be run with little to no programming knowledge. 

Regardless of laboratory size, there can be long-term savings in the amount of manual time and resources needed to perform everyday tasks, as we’ll highlight below.

Myth 2: Automation will threaten jobs and alienate staff

Fears that automation would usurp workers and result in job loss have existed for centuries. There can be downsides to exclusively relying on human labour to perform many repetitive tasks daily. There is a substantial increase in the risk of hand and shoulder discomfort from constant pipetting, in part due to repeated motions and heavy thumb force1 That can lead to a rise in repetitive use injuries, like carpal tunnel syndrome. 

Ergonomic challenges aside, there is the potential for errors that come with manual workflows. Our minds can wander when we get bored, which can leave even an otherwise precise laboratory worker vulnerable to error. It also can leave technicians vulnerable to injury. It is easy to drop or break a sample when your attention drifts, which can be especially dangerous when processing certain types of samples.  

Automation solutions don’t get distracted, and won’t lose line of thought when, say, someone changes the radio station. Valuable scientists may also become bored and look for more exciting work elsewhere that makes better use of their education and skills. When a well-trained technician or graduate student leaves a lab, they can take with them important knowledge about the details of running experiments, and how to create consistent results. This makes reducing staff turnover even more important. 

By automating those repetitive tasks that can occupy much of a scientist’s workday, you can free them to spend more time working on projects for which they are truly passionate, which can lead to more job satisfaction and potentially reduce the trend of clinical laboratory workforce shortages2. 

Myth 3: Automation interferes with a flexible workflow

Think about what happens when a priority sample comes to your lab today. Do you find yourself scrambling to figure out where to pause your current work to squeeze in the priority request? Worse yet, after you process the rush request, have you found yourself forgetting where you left off in the previous workflow? 

If you perform all of your tasks manually, you may need to stop your initial run partway through, which means losing the reagents and samples with which you have already begun working. 

Automation can do the critical thinking for you: you can program your instruments to help assist you with this process. Perhaps your liquid handler could be programmed to set samples aside in the middle of the process, which would allow you to resume where you left off.  

Just because you have automated a workflow doesn’t mean you are locked into it. There are options to pause and schedule the priority sample, without losing the progress and precious data of the original sample. Depending on the sample and instrument, automation can provide temperature-controlled chambers that can continue to maintain the integrity of the sample as you pause that particular run to prioritise and plan the day.

Myth 4: Physical steps are the only processes to automate

Although pipetting and sequencing may be the processes most obviously amenable to automation, they aren’t the only aspects of a laboratory that can be streamlined. We cannot forget about managing and analysing data. Automation can track logistics, such as adding reagents to a recurring order after a certain amount is used up. This approach can also help create a detailed history of the samples and lot numbers used in each run, so if you experience a recall six months later, you can know exactly what bottle was used for which experiments, and which specimens were affected. 

Data management is also a major area in which automation is often under-utilised. Automating activities such as data loading, cleaning, and integration can both speed up these processes and improve accuracy. Once these information pipelines are programmed, you can have more confidence that your data is flowing to the right place at the right time.

Myth 5: I’ll never be able to trust automation to perform to my standards

It can be challenging to let go of old workflows or ways of thinking, let alone trusting someone – or something – else to do the work you’ve done for years. I’ve noticed many lab professionals sit and watch our automated instruments do the work, double checking that everything is done correctly. 

Despite this double-checking, what I often hear is the amazement that the instrument can do the work with such precision and speed, with often no human involvement needed to get the job done. Robotic systems are able to move with speed and agility without losing focus on the task at hand. These instruments can also work in tight spaces with ease, using programmed precision movement to accomplish the job. 

Automated systems may perform laboratory tasks slightly differently than a human. Take a task like doing a cell wash. A regular lab tech may perform this five times in succession before undertaking an analysis, but an automated system might wash only three times, and with different buffers. Although the processes might be different, it’s the end result (a pure sample ready for examination) that really matters. These results can also be more consistent. A machine can be programmed on these different steps and do it in more uniform fashion, and without the potential for errors. 

Myth 6: I would lose too much time setting up an automated system to make it worthwhile

Implementing automation in a lab can seem like a significant investment, and the returns on that investment may seem like they would take time to recoup. Time spent learning a new system may be a luxury some labs can’t afford, but that short-term loss can’t stand in the way of long-term gains. 

Many of today’s automated systems feature robust user-friendly interfaces that are able to be quickly understood, without the need for coding knowledge or programming skills.  

While learning the system may take a little bit of time in the short-term, think about this long-term statistic example: automating stem cell analysis and transplantation can save the typical lab six hours a week3. That equates to 312 workhour savings a year, which is a big return on investment for a few hours spent learning and adjusting to a new system.

In conclusion

Automating the right tasks can help save time, improve staff morale, decrease job turnover, lower costs, add flexibility, and increase consistency. When all of these details are fully analysed and taken into consideration, you realise how automation can add many long-term benefits to everyday laboratory processes. 

A more automated future for laboratories can mean freeing up scientists to focus on their important work – not the workflow. Researchers will be able to spend their time planning experiments, analysing results, and performing other complex tasks that remain out of reach for many robotic systems. This is the heart of life science—not pipetting or preparing samples—and can immensely help in the journey to the next big breakthrough discovery. 

References

  1. https://www.cdph.ca.gov/Programs/CCDPHP/DEODC/OHB/HESIS/CDPH%20Document%20Library/labwork.pdf 
  2. https://ascls.org/addressing-the-clinical-laboratory-workforce-shortage/ 
  3. https://www.beckman.com/reagents/coulter-flow-cytometry/antibodies-and-kits/aquios/stem/workflow-comparison 

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