What Is Lab Automation?
In the medical and life sciences fields, technologies such as robotics, computer vision, and artificial intelligence are being applied to automate a plethora of time-consuming and sensitive laboratory tasks. This technology use case, often referred to as lab automation or laboratory automation, is a critical part of the overall concept of the smart hospital, where advanced technologies are employed to improve the healthcare experience for patients, providers, and staff.
Typically, research and clinical labs that embrace lab automation do so through a combination of laboratory information management systems (LIMS), robotic material handlers, and automated laboratory instruments. Lab automation helps these labs deliver precise, accurate results at scale.
The most basic level of lab automation involves automated laboratory instruments with onboard computing and high-speed networking that allow them to act as connected Internet of Things (IoT) devices. In advanced deployments, these automated instruments are assembled to create workflows operated by additional robotics, control systems, and information management systems. High-performance workstations, edge servers, and on-premise or cloud-based data center resources also help support lab automation and the required operational technology at the edge. Data integration at every step—from the instruments to the servers—allows labs to quickly process and analyze results with centralized visibility into the state of their automated systems.
Ultimately, lab automation helps to lessen the daily workload of researchers and care providers so they can focus on their most high-value work. Basic tasks like loading and unloading samples, conducting PCR tests, or incubation can be handled by automated workstations and instruments. Labs can also use more complex deployments that incorporate additional equipment like conveyors and robotic movers to carry out complex, multipart workflows.
Benefits of Lab Automation
Technology-enhanced lab automation solutions can help clinical and scientific labs maximize productivity and accuracy simultaneously, addressing a need to respond to cost constraints and increased demands for sophisticated testing, while also establishing a platform for future innovation.
Increased Productivity
Automated lab capabilities can run 24 hours a day and often work at a faster pace than human staff. These automated functions allow labs to accomplish more in less time without sacrificing accuracy or precision.
Reproducibility
Lab automation technologies perform with a level of consistency that surpasses what most humans can achieve. Robotic arms and automated instruments perform operations such as pipetting and aliquoting exactly the same way every time, and they always follow the same process. Because of this, results can easily be replicated for verification purposes.
Accuracy and Precision
Like reproducibility, automated lab processes and workflows also help enhance accuracy and precision. Because automation and AI dramatically remove the possibility of human error, there is a much lower likelihood of mistakes, inaccurate measurements, or protocol violations.
Safety
In automated labs, machines can handle dangerous or sensitive materials. This exposes lab staff to less risk.
Challenges of Lab Automation
Despite the benefits of lab automation, introducing new technologies also raises new challenges and concerns that need to be addressed.
Accuracy
Lab staff need to feel confident that their lab automation solutions will perform as expected and deliver precise, accurate results. This concern is only becoming more critical as AI plays an expanded role in complex healthcare and scientific operations.
Costs
Laboratories are seeking ways to improve operations while requiring that instruments do more and cost less. Here, single-CPU configurations can help manufacturers control the cost of materials, increase performance, and deliver better user experiences.
Uptime and Availability
When lab automation systems go down, productivity is dramatically impacted. Thus, minimizing downtime is critical. Integrated computer vision systems enable remote instrument diagnostics, which can help identify and resolve issues earlier and faster.
Security and Manageability
Data security is a top-of-mind concern in the healthcare and life sciences industries. Hardware-enabled security technologies like accelerated data encryption and trusted execution technology can help meet expanding cybersecurity needs for connected lab automation use cases.
Analytics and AI Growth
Modern lab instruments must be able to support increasingly complex analytics and artificial intelligence. These advanced functions introduce new performance requirements for robotics and edge hardware. To control costs, manufacturers are exploring how to deliver advanced capabilities with the right balance of price and performance.
Development
Developing lab automation technologies, both hardware and software, introduces a wide variety of challenges, including price/performance, security, and accuracy. Additionally, manufacturers and software vendors face stringent compliance requirements alongside the need to support and integrate with heterogeneous computing environments at the edge.
Lab Automation Components
A wide range of technologies, provided by a vast network of technology partners, are used to enable lab automation solutions. Principally, robotics and edge IT solutions are required to carry out, manage, and connect lab operations. These devices often integrate with edge hardware and data center and cloud resources for additional processing and centralized visibility. Sophisticated AI algorithms, especially computer vision, and software solutions are used to enable intelligent capabilities and centralized visibility. Network solutions are also employed to connect all devices and edge servers.
Robotics
Devices like robotic arms and robotic movers enable workflow automation for a variety of lab procedures. Automated lab instruments also include robotics components that allow them to function autonomously. These resources work in conjunction with LIMS and edge hardware to perform their tasks intelligently and accurately. Today’s robotics devices are equipped with advanced compute capabilities that allow them to perform complex operations and support AI-enhanced operations.
Edge Hardware
Lab automation solutions often include edge hardware, including edge servers, that power workloads like computer vision or other AI capabilities. Edge hardware for lab environments introduces challenges like size and power constraints, as well as the need for quiet operation.
Software and AI
Lab automation solutions may include a number of software tools, including LIMS, workflow scheduling software, lab informatics, and configuration applications. AI capabilities— enabled by a wide spectrum of ISVs, AI specialists, and device manufacturers—can be deployed throughout the lab, from computer vision to AI-enabled analytics for sample data.
Lab Automation Use Cases
Across both healthcare and life sciences, lab automation technologies are applied to automate a wide variety of tasks, including medical imaging, centrifugation, decapping, recapping, aliquoting, sorting, incubation, labware storage, and colony counting.
Processes and techniques such as PCRs, flow cytometry, cell imaging, analytical chromatography, and pathogen screening can all be automated and enhanced through lab automation technologies.
Modern labs pursue both partial automation, where just a single part of a larger process, task, or instrument is automated, and total workflow automation, where the end-to-end procedure can be carried out without human intervention. Fully automated labs can perform multiple complex operations constantly, allowing them to reach even higher levels of efficiency and precision than partial ones. Modular automation systems provide labs with a great option for flexible and reconfigurable lab automation implementations.
The Future of Lab Automation
AI will continue to play a critical role in lab automation as the technology use case develops. Additionally, labs will continue to become more connected and autonomous as adoption grows and technology advances. The automated, connected lab of the future will further incorporate optimized edge compute and AI capabilities to drive even more accuracy and precision, enable centralized insights, and further improve productivity. Lab staff will see their role evolve to become more focused on their most critical work, while healthcare patients will benefit from faster, more accurate results.