For Drug Discovery Research, Laboratory Automation Needs to Be Flexible

July 8, 2022

Contributed Commentary by Ryan Bernhardt and Rob Harkness  

July 8, 2022 | Today, scientists who want to implement automation in their laboratories should choose an infrastructure that can provide long-term flexibility for their teams. Most drug discovery labs currently use some form of automation, but they do not always have the most adaptable systems, proving costly over time. Additionally, drug discovery and development teams are under increasing pressure to accelerate their workflows and get more therapeutic candidates into clinical trials. The ability to increase productivity with automation is essential to make that vision possible. Similarly, flexibility is critical for researchers to change workflows and take on new priorities quickly.  

Lab automation has evolved from simple machines designed to move sample tubes and plates between instruments to sophisticated systems that can dispense tiny quantities of liquid, transport samples between labs, and capture minute details in real-time. This evolution yields tangible benefits to the research process, and scientists now have more flexible schedules. They can also dedicate more time to designing new experiments and analyzing data that could yield the next blockbuster drug.  

Recent innovations offer even greater flexibility than what was possible a decade ago, though decisions about where and how to install equipment in the lab are far from mundane. Scientists can now experiment with various floor plans and instrument layouts to build more functional labs for their teams. Although automation is far more affordable than it used to be, it is still a significant investment for many labs. Understandably, the focus is often on identifying a vendor and buying the right blend of equipment and software. Questions about automation infrastructure flexibility, adaptability, and operability emerge only after the systems are installed and in use.  

The planning stage should include conversations about the flexibility of automation to help ensure the long-term utility of these systems. There is a plethora of solutions available to help scientists get the most benefit from their systems. For instance, mobile robots–a relatively recent entrant to the automation space–expand on the strengths of their robotic arm predecessors. Today's robots use internal sensors to navigate independently around people and instruments while performing various simple but essential tasks in the lab. They also streamline the automation setup since the robots do not require bolting in place.  

In practice, scientists can break up workflows and run the robots across multiple workstations, floors, or even campuses. Teams can task them to move samples and reagents through designated routes, safely working around equipment and people. They can even assign robots to work exclusively on tasks and equipment for specific experiments. Upgrading mobile robots can also eliminate the need for fixed track-based systems and conveyor belts, where spatial flexibility may be more important than overall throughput. This approach also allows scientists to fully automate workflows within a more traditional laboratory setting with additional flexibility in placing instruments.  

Another option for scientists seeking more flexible mechanisms for moving samples and plates is the dockless cart. These carts can supplant older systems for transporting labware–like conveyor belts and mobile robots–which require laborious setup procedures. Dockless carts come equipped with camera-guided systems, allowing them to navigate around the lab and effortlessly integrate with any platform as needed. They are powered by internal hydraulic systems that eliminate the need for physical docks, fixed hardware, or tubing. The vision-based positioning system enables dynamic integration with robotic arms upon docking without human intervention to teach or refine labware positions.  

Automation software has also come a long way over the years. Gone are the clunky legacy systems that required significant programming expertise. Today, scheduling and orchestration software offers drag-and-drop functionalities to support a range of experiments in the lab. With minimal training, scientists can integrate instruments into complex workflows that run with little to no oversight. It is a simple task to swap virtually any lab instrument in and out of the workflow depending on the experiment's needs or the desire to run experiments around the clock. These systems can monitor lab conditions, flag errors and sample problems, and generate detailed audit trails for regulatory submissions. Importantly, scientists can use the exact solutions whether they need to run many experiments on a few samples or a few experiments on thousands of samples.  

Automation should be intuitive and convenient; otherwise, scientists may be less inclined to use these systems in the lab. Flexibility is not always the first thing that comes to mind when considering lab infrastructure. Still, it is a crucial consideration for teams serious about keeping up with the rapid drug research and development pace.  

Ryan Bernhardt is Chief Commercial Officer at Biosero, a lab automation software provider. Previously, he worked at Eli Lilly and Company–as part of the Discovery Automation Research and Technologies Group–where he led a team of automation engineers and scientists. He holds a bachelor’s degree in chemistry from Marian University in Indianapolis. He can be reached at

Rob Harkness, Ph.D., is Managing Director UK/EU at Biosero. Rob has over 20 years of experience delivering laboratory automation solutions to the Life Science and Consumer Products business sectors, fulfilling several distinct roles and responsibilities during this time. He is responsible for the European organization and works closely alongside the Biosero commercial team to deliver solutions that labs need today. Rob also serves as a Director for the Standards in Laboratory Automation consortium, an effort from within the industry to create and drive open system communication and data standards adoption. He can be reached at