Why do labs need to embrace automation, and what should they consider before implementing it?
Before the COVID-19 pandemic, staffing shortages already posed significant challenges. During the pandemic, lab automation became integral to handle the rapidly increasing surge of samples, establishing a “new normal” for scientists and lab technicians who had to depend on automated data management systems for accurate reporting and sample traceability.
In the post-pandemic era, rising healthcare costs and a heightened focus on developing advanced medicines will further increase reliance on automation in drug discovery and development. Automation offers numerous benefits, especially in the face of ongoing staffing shortages. It significantly reduces human error and enhances efficiency, allowing scientists to dedicate more time to more valuable tasks such as research and innovation, where their expertise is crucial.
A mindset shift is essential for fully embracing and adapting to automated tools and instruments. Lab leaders must consider several factors, including training, for reassurance that automation will not replace human jobs but rather redirect efforts toward critical areas of research and innovation, and the establishment of efficient protocols for resolving queries.
Beyond continuous communication around automation’s benefits, scalability must also be a key consideration during implementation. Sample volumes often vary based on specific scenarios, necessitating that automation be flexible and adaptable enough to provide tailored solutions for different needs. This is particularly important in a period of clinical laboratory consolidation, which is requiring scalable automation solutions for labs as their volumes change. For example, Revvity’s EUROIMMUN offers a range of immunofluorescence test (IFT) platforms, including the IF Sprinter for small and medium sample volumes, Sprinter XL for medium to high volumes, and EUROLabWorkstation, the highest volume IFT processor available in the world, which is designed to serve the largest lab operations. Additionally, UNIQO 160, a new fully automated IFT solution with integrated sample preparation and imaging capabilities, is ideal for medium-sized laboratories. Finally, for newborn screening (NBS), Revvity provides solutions such as the GSP instrument and the VICTOR2 D instrument (combined with the DELFIA Trio), which cater to both high and low throughput requirements, respectively.
What are some examples of what we can do today because of automation that we couldn't do just a few years ago?
Automation never operates in isolation. Effective automation in laboratory workflows requires seamless integration of associated software, reagents, consumables and relevant instruments, often connecting to a LIMS (laboratory information management system). These components work together to connect and streamline multiple steps within the lab’s workflow, significantly reducing manual workloads.
For example, the UNIQO 160, the automated IFT system for autoimmune disease diagnostics, integrates seven workflows into a single system. It alleviates many common laboratory challenges by reducing hands-on time and creating efficiencies through end-to-end automation, including automated barcode scanning and sample assignment.
For research-use next generation sequencing (NGS) sample preparation, the BioQule system is designed to simplify the isolation of nucleic acids and the generation and quantitation of NGS libraries, even for operators without prior automation experience. It automatically measures library concentrations, streamlining the quality control process.
Another example is the Auto-Pure 2400 liquid handler for latent tuberculosis (TB) detection, which offers excellent sensitivity and specificity while enabling efficient lab workflows. With less than 10 minutes of hands-on time required, the automated workflow makes previously labor-intensive tasks, such as PBMC isolation and normalization, both quick and straightforward.
What role has artificial intelligence played in this evolution? What will it play down the road?
AI is playing a critical role in driving innovation, particularly by reducing time-consuming, repetitive tasks that were historically performed by humans. For instance, in prostate biopsy imaging, where 10-12 samples are typically analyzed, most results are negative. With AI, negative results with similar patterns are filtered out, allowing pathologists to focus more specifically on those results that indicate potential positives. Another example is that when UNIQO 160 generates fluorescence images and proposes test result interpretations, scientists are still needed to validate and sign off on these results.
These processes require precise differentiation between high-quality results and problematic ones. With proper training, AI will become increasingly adept at distinguishing results based on their quality. Rule-based decisions regarding cut-off ranges, quality control results, calibrations, and reference standards are now routine in medical labs, helping to filter out subpar samples. By eliminating the need for manual intervention, the potential for human-related errors is substantially reduced.
As a global leader in NBS, Revvity has screened approximately 800 million babies for life-threatening diseases across 110 countries cumulatively. The process begins in the hospital after delivery with a heel prick where blood is captured on specialized paper cards. These cards are then sent to laboratories performing NBS tests where automation plays a crucial role, followed by confirmatory testing. In order to identify inborn illnesses early enough to initiate potentially life-saving intervention, samples in the U.S. are typically processed within five days after birth.
We are developing an AI-integrated method for our dried blood spot (DBS) cards, particularly for optical reading. The DBS cards are manually marked with important information immediately after a baby’s birth, which needs to be entered into the LIMS and processed promptly. AI will swiftly capture this information, enabling much faster interpretation than previously possible, identifying inconsistencies or errors, and therefore saving valuable time.
Looking ahead, we anticipate that AI will suggest reflex testing based on initial test results, which could shorten the diagnostic journey and improve diagnostic quality. With AI-enabled faster operations, we expect enhanced accuracy and throughput, enabling clinical laboratories to support clinicians to make critical, time-sensitive decisions around the clock.
Revvity's purpose is to expand the boundaries of human potential through science. Why is automation essential in achieving this?
Revvity has undergone a significant transformation, bringing together the ecosystem needed to realize the promise of precision medicine. The foundation of precision medicine lies in a deeper understanding of both the disease and the patient, including how the patient will respond to specific treatments.
Diagnostic testing is key to this improved patient characterization, critically relying on the interrogation of a broader range of biomarkers and conducting more specialized testing across various samples. In order to handle this increase in testing procedures, automation will play an important role in delivering timely results (e.g., through multiplexing) in an economically viable manner. Additionally, automation not only saves time but also minimizes human errors.
In essence, automation seamlessly integrates modular steps, creating a much more efficient workflow from screening to treatment.
