Scientist operating automated lab equipment in a sterile environment for enhanced lab automation.

The Process of Integrating Lab Automation

Lessons learned from more than two decades of automating labs

Written byCarola Schmidt andAlexandra Blancke Soares
| 5 min read
Register for free to listen to this article
Listen with Speechify
0:00
5:00

What comes to mind when you think about lab automation? A standalone pipetting workstation? An automated plate washer? A simple thermal cycler? Or do you imagine a full-scale robotic platform integrating several instruments serving multiple workflows at once? 

Lab automation, in all its forms, has transformed the way we conduct science. Who would still enjoy manually shuttling PCR tubes between water baths when that time could be better spent analyzing data, planning the next experiment, or just taking a well-earned break? Still, we often hesitate to automate tasks for a variety of reasons: 

Lab manager academy logo

Lab Quality Management Certificate

The Lab Quality Management certificate is more than training—it’s a professional advantage.

Gain critical skills and IACET-approved CEUs that make a measurable difference.

  • because we enjoy doing them, 
  • we don’t trust an automated system to produce the same quality data, 
  • we think we are losing control over our processes, or 
  • because we are afraid of being replaced by a machine. 

But this choice might be made for us in the near future. Sample volumes continue to grow and must be processed within shorter periods of time, while skilled staff become increasingly scarce as more colleagues approach retirement. Today’s technologies already produce enormous amounts of data that are impossible for a human alone to organize and analyze. 

Lab automation does not refer to just hardware but includes software and IT structures that enable automated evaluation and rule-based decision-making where necessary. Automation will become a necessity not just to increase efficiency, but to just maintain quality and consistency at scale. 

In this article, we share practical insights based on experience integrating automation into diverse lab environments. These insights can help you understand the common challenges and overlooked details, and equip you with strategies to ensure your system becomes more than just another machine. 

Integrate, not just automate

When the decision to introduce automation has been made, there is often a misconception that automation equals improvement. An automated system is only as good as its integration into the lab’s processes and infrastructure. Simply installing a robotic system will not guarantee smoother workflows, faster results, or less manual labor. It can have the opposite outcome if a system is not properly planned, validated, and supported. 

Interested in lab tools and techniques?

Subscribe to our free Lab Tools & Techniques Newsletter.

Is the form not loading? If you use an ad blocker or browser privacy features, try turning them off and refresh the page.

By subscribing, you agree to receive email related to Lab Manager content and products. You may unsubscribe at any time.

The process of transferring a manual workflow into an automated one will require a shift in the way we think about experiments. Try not to be too stuck in the way you used to do things. Instead, be open to challenge your protocols. For example, do you really need to run your assay in tubes, or could you transfer it to a more automation-friendly multi-well plate? An invested and experienced integration provider who understands your science and desired outcome will help you navigate these questions. 

There’s no shortage of integration providers on the market, so consider which option best fits your needs. Brand-agnostic automation providers may suit you if you know exactly what you want, while vendors focused on their own instruments and workflows often offer more centralized support for their technology. Choosing between these models depends on your lab’s priorities and what is most important to you: flexibility, speed, validation, or in-depth application knowledge and centralized support.

The human factor 

Automation will not eliminate the human factor from the equation, and a system can only be as good as the people operating it. It’s important to make sure your staff is well prepared, not just to operate the system but to understand and adapt to it. It is vital to include everyone throughout the whole process of implementing automation, starting at the planning phase. Only then will people feel part of the process and grow trust in how automation will benefit their daily work. 

Many labs rely too heavily on a single automation expert. If that person leaves—especially without notice—once-utilized systems can quickly become idle. This leads to wasted investment in both equipment and the time spent developing workflows. Don’t miss the opportunity to encourage everyone in your lab to familiarize themselves with your new system. This will not only ensure smooth operation in the long run but also keep staff engaged and up to date with the latest technology. 

It's not all or nothing

Do you dream of fully automating your lab so that none of the tedious work has to be done manually anymore? Or would you rather keep everything the way it is because you consider your processes too complex to automate? There is a middle ground, and often, it is the best way to approach automation. Many processes benefit from selective automation by targeting the most repetitive or error-prone steps — those that offer the greatest value or cost savings to the lab.  Consult your staff to identify the most tedious tasks, workflow bottlenecks, and areas they’re comfortable automating. At the same time, prioritize parts of the process that offer the greatest cost benefit, and distinguish between must-have, nice-to-have, and can-wait features. A clear understanding of the role of each functionality in the process protects your investment and ensures future growth. An experienced integration expert who understands your application will help you identify the bottlenecks and vital components and make sure you adhere to your financial plan.  

Trust the process

Giving up control can be difficult for many scientists because most of us have been trained and have spent years following and developing predominantly manual protocols. Automation shifts some of that control over to the automated system, but it does not completely take it away from the user. Well-designed systems have built-in error handling, rule-based decision-making, run reports, and offer options for guided user intervention. Embedded software allows the operator to add individual rules to check quality based on their experience and expertise. It gives full operational control over any experiments to the system while minimizing the occurrence of missed results and checkpoints. 

Modern software allows us to implement both breakpoints for human result evaluation and branchpoints for simple rules—or more complex AI-based decision-making based on measurement results. With a suitable IT setup, you could even enable 24/7 operation even when human decision-making is involved. Even if the machine makes a mistake, the user can interpret the errors and act on them to maintain oversight. Make sure that error-handling is a priority during the training you receive from your automation provider.

Sample management

One of the benefits that automation provides is sample management that is less prone to accidental mislabeling, mixing up samples, or accidentally losing a tube in the depths of a fridge. While automated barcode labeling and reading, as well as inventory tracking, are standard processes, some labs might require more sophisticated sample tracking and handling. You may want to flag certain samples for a rerun or an alternative processing based on a previous measurement. Implementing either automated rule-based decision-making or manual intervention often requires additional efforts in programming your system. While this might require some initial high-effort work, it will benefit your processes long-term. 

To handle the increasing amount of sample data, many labs utilize well-established laboratory information management systems (LIMS), which should be able to facilitate direct or indirect communication with their lab automation systems. Sample data and handling instructions should be delivered in a format that the automated system can interpret and act on. Similarly, information about the processed sample and measurement results must be fed back into the LIMS in a suitable format. It is worth investing time and resources, with support from your integration provider, to make sure these systems are seamlessly integrated. 

A case for lab automation: democratizing science and healthcare by doing more with less

Moving away from the practicalities of implementing automation, we want to highlight a sometimes-overlooked aspect of how automation can lead to improvements if done right. As we adopt more advanced systems, we also need to ensure that they remain accessible and adaptable to labs with different levels of resources. Modular and scalable systems can enable broader access to higher throughput sample handling in research, pre-clinical, and clinical fields, reducing disparities between well-funded and under-resourced labs. 

Automation has the potential to make high-quality research, diagnostics, and treatments more affordable and accessible. Personalized medicine is the future, but it is more resource-intensive. To ensure patient access to personalized medicine, not just for the most privileged among us, automation can help reduce the cost per sample and support wider population screening. 

Final words

Automation has become essential for many labs. But it only creates value when it is well integrated, adapted to workflows, and embraced by the people who work with it. Automation needs to enable labs to keep up with growing demands and help them meet the challenges ahead—by doing more with less, and doing it better. 

About the Authors

  • Carola Schmidt is the global head of technology, platforms at Revvity. She has more than 25 years of experience in workflow improvement and process optimization in the medical and life science fields. Her focus encompasses the entire workflow, including hardware and software components. She has multiple patents and published papers on the optimization of processes.

    View Full Profile
  • Alexandra Blancke Soares is the senior application scientist at Revvity. In her role, Alexandra helps customers bring their lab automation endeavors to life. She is an expert in workstation design and the realization of workflows. Her aspiration is to make lab automation more accessible and lower the barriers for its implementation in labs worldwide.

    View Full Profile

Related Topics

Loading Next Article...
Loading Next Article...

CURRENT ISSUE - May/June 2025

The Benefits, Business Case, And Planning Strategies Behind Lab Digitalization

Joining Processes And Software For a Streamlined, Quality-First Laboratory

Lab Manager May/June 2025 Cover Image