Automation in Laboratory: A Comprehensive Guide

Introduction to Laboratory Automation

Laboratory automation began with an AutoAnalyzer in 1957 which increased sample speed from human level to about 150 samples per hour.[1]

It has snowballed into robotics, internet of things(IOT) devices in the lab, and software solutions that can handle absurd amounts of data. These solutions only raise the bar for patient care and time to market, which is great for consumers.

Types of Laboratory Automation

Good laboratory automation involves a wide variety of technologies. It includes pre-analysis automation, streamlining sample preparation and handling; analytical automation, which enhances the efficiency of testing and analysis; and post-analytical automation, which focuses on data management and reporting.

Total laboratory automation (TLA) integrates all these stages into a seamless workflow, while subtotal automation targets specific processes. Stand-alone automation systems operate independently, whereas integrated systems connect multiple devices and software for cohesive operation.

Assumptions: Considerations in Implementing Lab Automation

Starting with a good ROI analysis is important when implementing automation in the lab.

Sherri L. Bassner, PhD has a fantastic article about this on LabManager.com.[2]

She starts with the standard ROI formula

ROI = (gain from investment-cost of investment) / cost of investment * 100

And goes on to emphasize the power of assumptions in this calculations. Making sure that your assumptions are valid is the most crucial step since you have to use assumptions for both cost and gain in each scenario. You should also include a range for all variables that allows for worst-case calculation. As always, build confidence with reasonable projections and make sure that worst case still meets acceptable ROI standards.

Other important things to consider are integration with existing workflows, as some products come with IT challenges or require special training for technicians, supervisors, and sometimes even the C-level. The last thing to consider is that more custom solutions will probably need more maintenance and engineering than canned solutions, which might be okay with your labs workload, but it does depend on your workload.

Key Components of Laboratory Automation Systems

Most laboratory automation systems are made of many components that work together as one to streamline tedious laboratory processes. Implementing effective automation solutions will also depend on your lab and budget. The following are common (and not-so-common) laboratory automation systems:

1. Robotics and automated equipment

2. Software algorithms and control systems (LIMS/LIS)

3. Data management and analysis tools

4. Sample storage and retrieval systems

5. Transportation systems (e.g., conveyor belts, robotic arms)

Budget and Benefits

The benefits that automation brings to clinical labs are noticeable in the bottom line numbers. Although the barrier to entry is higher for some automation solutions, there are solutions for any budget that are turnkey and produce results immediately…

This allows supervisors and technicians to focus on more critical aspects of their work and improves:

1. Safety for laboratory personnel

2. Cost-effectiveness and resource efficiency

3. Turnaround times and throughput

4. Reduced human error and variability

5. Traceability and documentation

Applications of Laboratory Automation

On the more fantastical side of things, total laboratory automation(TLA) for high throughput clinical labs, r&d labs, or life science laboratories normally requires very custom solutions pieced together from many vendors. These solutions would require expert opinions which LabQCpro is not equipped to give out.

On the more practical side, there are software solutions for every type of lab that we can compile for you from real reviews on software sales sites here [3]. These solutions work out of the box for clinical laboratories, diagnostic labs, pharmaceutical r&d sites, and life science labs alike. The workflows for all of these labs are very different and finding a tailored solution for your lab is especially important. These solutions can automate everything from inventory management, data entry, or even data collection.

AI / Emerging Trends in Laboratory Automation

AI is making large strides in laboratory technology and diagnostics. By far the most promising aspect is predictive analytics. [4]

NIH talks about this comprehensively about the demand growth for being able to pin-point bottlenecks, forecast from past data, and make data driven decisions with less human intervention. These have the ability to completely revolutionize patient care.

Using predictive analytics is best when mixed with other forms of cutting edge automation. Cloud based solutions and remote access to the lab allows for a more flexible workforce which is important with the staffing issues facing clinical laboratories across America.

Lastly, IoT (Internet of Things) in laboratory settings should make strides in the next decade, with modern electronics and wifi connectivity (network-wise) becoming more viable than ever in the workplace.

Case Studies: Successful Implementation of Lab Automation

There are many examples of laboratory automation with massive success, and although every case study may not similar to these, it is still important to recognize growth of the industry as a whole.

Metagenomi: Using a highly custom solution from multiple vendors and Biosero's “Green Button Go Scheduler” solution, Metagenomi was able to increase operational efficiency to a point where they had automated the identification of millions of Cas-associated proteins and CRISPR loci. [5]

E.Gulbja Laboratory: A more vendor-centric approach, utilizing NovaticLab's NOVAFlex Archiver and NOVAMove Porter, E.Gulbja Laboratory was able to reduce sample retrieval time from 10 minutes to 30 seconds, which saved an estimated 20 hours of labor daily. [6]

DeepCure: Using AI, DeepCure had automated synthesis and purification direction, which had streamlined what used to be multiple reaction steps that soaked up tons of resources. [5]

Future Outlook for Laboratory Automation

The future of laboratory will probably involve more privacy improvements than anything.

With any improvements in tech, in any industry, privacy concerns grow with innovation because more data is needed to move forward in more scenarios than not. The entire industry will probably see a rise in privacy concerns as it grows technologically. [7]

There are already solutions involving synthetic data that are improving the data that is needed to make better decisions faster while still enabling data sharing for research.

Conclusion

Laboratory automation has transformed scientific research and diagnostics, enhancing efficiency, accuracy, and safety. Through the integration of advanced technologies—robotics, AI, and IoT—laboratories can now streamline processes, minimize human errors, and boost overall productivity. As technology progresses, the future of laboratory automation promises even greater innovations and improvements in patient care.

References and Further Reading

1. https://www.researchgate.net/publication/283350569_Analytical_continuous_flow_systems_where_two_worlds_collide_from_gravimetry_and_test_tubes_to_flow_systems_to_fia_to_sia_to_pat_and_from_orsat_to_control_room_to_pat_to_tap

2. https://www.labmanager.com/building-a-successful-business-case-around-an-roi-calculation-30659

3. https://www.capterra.com/medical-lab-software/

4. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10766873/#:~:text=Predictive analytics is a prominent,laboratory results%2C and clinical outcomes.

5. https://biosero.com/three-customer-success-stories-that-illustrate-the-lab-automation-continuum/

6. https://novaticlab.com/novaticlab-case-study-a-success-story-with-e-gulbja-laboratory/

7. https://www.weforum.org/agenda/2024/06/top-10-emerging-technologies-of-2024-impact-world/