Lab automation refers to the automation of laboratory equipment, instruments, or software, such that they facilitate scientific tasks with a low amount of manual labor or interaction from staff or technicians. At present, lab automation has been introduced at different levels, including automated hand tools, inventory software, and automated cell culture systems. 1
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Brief History of Laboratory Automation
Laboratory automation can be traced back to 1875 when devices for automatic washing of filtration residues on filter paper were described. In 1894, the first automatic burette was developed for laboratories to perform recurring titrations. The same year, an automatic pipette was designed to conduct the Babcock milk test. It must be noted that these automations were more proprietary and not widely used.2
During World War I, the tremendous need for gas analysis urged the development of the first commercially automated laboratory equipment. In 1929, the first laboratory-based automated titration system was commercialized. This equipment used a photocell to identify the color change in the solution due to the change in pH.3
World War II also boosted innovative automation solutions because of the imbalance regarding high demands for goods relevant to the war and the limited qualified workforce. During this period, a semi-automated distillation apparatus was developed. Furthermore, a motor-driven syringe was introduced in 1948 to deliver the titrant.
Technological advancements played a crucial role in expanding laboratory automation for scientific research. For instance, microprocessor technology enabled the development of programmed sequences for controlling the motors and valves, which led to the creation of fully automatic pipetting systems. In medical laboratories, automation was applied in the mid-1950s, and robotics in the 1970s. Dr. Masahide Sasaki, a Japanese Chemist, was the first to set up a fully automated laboratory.4
Benefits of Laboratory Automation
Scientists believe that lab automation is an unexplored avenue that could transform scientific research. Automation in laboratories saves valuable time for researchers. Instead of performing assays and conducting technical repeats, which is a repetitive and time-consuming process, implementing robotics to carry out these works enabled scientists to focus on more complex experimental work.
The availability of high-quality cells has enabled the development of automated systems, such as AUTOSTEM, StemCellFactory, and StemCellDiscovery. These systems automated the manual stages of stem cell seeding, culture, colony selection, quality assessment, and harvesting. This automatic generation of high-quality cells in increased quantities has significantly accelerated clinical and pharma research.
Robots like plate-washers (e.g., RapidWash™ high-speed microplate washer by Hudson Robotics) that can efficiently wash cell plates in around 30 seconds enable technicians to focus on important scientific experiments. The use of inventory software saves time and physical space. This software helps categorize research stocks and helps to dispose of out-of-date products. Some of the other benefits of lab automation are discussed below:
Reproducibility:
Reproducibility is one of the significant concerns of academic research, which is associated with economic implications and public trust in science. An increase in the use of automation throughout research laboratories presumably enhances reproducibility in scientific research. Automation can improve reproducibility by removing variations that could occur during the manual performance of the experimental protocol.5
Experimental Success Rates:
In the case of cell-based or microbial experiments that are susceptible to contamination due to handling processes, automation can reduce manual handling steps and, thereby, increase the experimental success rate. Automation in the laboratory enables a greater rate of experimental output with higher accuracy with minimal human intervention. It is important to note that automation provides a higher level of precision in reagent dispensing, which contributes to experimental success.
Safety:
Many scientific experiments entail using dangerous reagents and manual manipulation of these could endanger the handler. The use of automated machinery during these experiments could be beneficial.
Lab automation at Karolinska University Hospital, Sweden
Video Credit: ABB Robotics/YouTube.com
Challenges of Automation in the Laboratory
Automation in the laboratory triggers the need to understand the caveats of using automated tools. In addition to knowledge gaps, the lack of resources has withheld the use of automation in small-scale laboratories. Short-term research funds limit an individual researcher’s ability to develop lab automation. Some other limitations of laboratory automation are discussed below:
Incorrect Application:
Incorrect application of automation could result in a rapid propagation of errors. For instance, if a machine is not calibrated properly, it could lead to the generation of a large number and quantity of incorrect products. Variations in input materials in different laboratories would produce different results, thereby hampering reproducibility.
Obsolescence:
Automation in the laboratory is expensive, and most of these technologies cannot be used for a prolonged period due to the obsolescence of materials or the availability of newer and more effective replacements. The rapid advances in hardware and software design quickly render laboratory equipment obsolete. For instance, introducing new thermostable polymerases made a whole generation of Polymerase Chain Reaction machinery obsolete.6
Workforce Impact:
Automation in laboratories has both positive and negative impacts in the context of the workforce, particularly for long-term workers in clinical laboratory settings. Automation cannot replace researchers in laboratories due to their planning and creativity skills.7 However, researchers recruited to perform repetitive manual tasks are more likely to be replaced with the popularity of this technology.
Innovation Inhibition:
Automation can inhibit creativity in experimental processes by limiting opportunities for altering experimental protocols.
Environmental Impact:
The environmental impact of laboratory automation depends on the life span of the equipment, disposal, and recycling scope. Automation designed with the single-use plastic principle generates greater volumes of plastic waste that has a detrimental effect on the environment.8
Current Landscape of Laboratory Automation
The key drivers of lab automation are globalization, collaboration, and advancements and implementations of robotics and software in the laboratory.9 The enhancement in quality and quantity of lab automation is also dependent on individual researchers, funders, research institutions, and automation developers. Automation engineers play a crucial role in connecting researchers with automation.
Currently, most life science research laboratories have introduced robotics and cybernetics. It has been observed that the terms ‘robot’ or ‘robotic’ have often been interchangeable with automation since the 1990s. A wide scale of automation, i.e., from simple to complex automation, has been applied in laboratories for scientific, particularly biology research.
Many software-based technologies that include image-based and data-mining tools have revolutionized scientific research. Although a classification system for industrial automation has been developed, no such system for laboratory automation equipment is available.
One key difference between automation in academic bioresearch facilities and industrial environments is that automation equipment is not completely required to replace manual handling tasks.
Generally, the majority of equipment used in scientific laboratories is expensive. Typically, high-level automated equipment is procured through pooled resources of the parent organization or wider research community. They are often referred to as biofoundries.10 The advent and increase in academic biofoundries are expected to rapidly grow in the coming years, expand existing facilities, and find new ones.7
The mid-range level automation items that enhance the accuracy and reproducibility of laboratory research dominate the equipment budgets. However, these items require a significant amount of manual manipulation before and after the machine's use.
A new automation variant, namely the cloud lab, has been developed that provides researchers with remote access to heavily automated protocols. This is a pay-per-experiment service.11
Some of the leading lab automation companies are TTP Labtech, Andrew Alliance, Integra Biosciences, Opentrons, and Hudson Robotics. Formulatrix’s rover system is being developed to autonomously transfer microwell plates between processing modules. This technology is basically linked to the concept of robotics used in warehouses. A recent software developed by Synthace can link robotics from different manufacturers in one promising and flexible laboratory-based platform.
References and Further Reading
- Mohammed, O. et al. (2023). Recent advancements in laboratory automation technology and their impact on scientific research and laboratory procedures. International journal of health sciences, 7(S1), pp. 3043–3052. doi.org/10.53730/ijhs.v7nS1.14680
- Yeo, C. & Ng, W. (2018). Automation and productivity in the clinical laboratory: experience of a tertiary healthcare facility. Singapore Medical Journal, 59(11), pp. 597–601. doi.org/10.11622/smedj.2018136
- Olsen, K. (2012). The first 110 years of laboratory automation: technologies, applications, and the creative scientist. Journal of Laboratory Automation, [online] 17(6), pp. 469–480. doi.org/10.1177/2211068212455631
- Tomar, R. (1999). Total Laboratory Automation and Diagnostic Immunology. Clinical and Diagnostic Laboratory Immunology, 6(3), pp. 293–294. doi.org/10.1128/cdli.6.3.293-294.1999
- Moutsatsou, P., et al. (2019). Automation in cell and gene therapy manufacturing: from past to future. Biotechnology Letters, 41(11), pp.1245–1253. doi.org/10.1007/s10529-019-02732-z
- Hawker, C.D., et al. (2018) Automation in the Clinical Laboratory. In: Tietz Textbook of Clinical Chemistry and Molecular Diagnostics, 6th Edn, eds N. Rifai, A. R. Horvath, and C. T. Wittwer (Philadelphia, PA: Elsevier Inc), pp. 370.e1–370.e24. doi.org/10.1016/B978-0-323-35921-4.00026-0
- Holland, I. & Davies, J.A. (2020). Automation in the Life Science Research Laboratory. Frontiers in Bioengineering and Biotechnology, 8, p. 571777. doi.org/10.3389/fbioe.2020.571777
- Howes, L. (2019). Can Laboratories Move Away from Single-Use Plastic? ACS Central Science, 5(12), pp.1904–1906. doi.org/10.1021/acscentsci.9b01249
- Jennings, C. (2013). The Opportunities and Challenges behind Lab Automation. Available at: https://www.srgtalent.com/blog/the-opportunities-and-challenges-behind-lab-automation. (Assessed on January 9, 2023.)
- Kitney, R., et al. (2019). Enabling the Advanced Bioeconomy through Public Policy Supporting Biofoundries and Engineering Biology. Trends in Biotechnology, 37(9), pp. 917–920. doi.org/10.1016/j.tibtech.2019.03.017
- Segal, M. (2019). An operating system for the biology lab. Nature. 573, pp. S112–S113. doi.org/10.1038/d41586-019-02875-z
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