A semi-automated liquid handling robot with a multi-channel attachment for pipetting samples into an array format.
Scientists use liquid handling robots for programmable tasks such as dispensing reagents into multi-well plates before sequencing.
iStock, zorazhuang

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What Is Lab Automation?

Lab automation is a process that combines common research workflows and technologies such as robotics, computers, and liquid handling instruments.1 Although scientists have turned to automated approaches for over a century, the applications and innovations that enable lab automation continue to evolve with steady advances in high throughput technologies.1,2 Despite everchanging needs and techniques, a common thread in lab automation remains constant; lab automation reduces or eliminates manual research tasks, improving experimental efficiency, accessibility, and reproducibility.2,3

Semi-Automated Versus Fully Automated

Both semi-automated and fully automated workflows reduce manual labor and thus save time while reducing opportunities for human error. However, cost and equipment availability are common lab automation roadblocks for academic researchers.4 To overcome these barriers, scientists need to tailor their automation approach to their application-specific needs.

Scientists select automated tools based on the task type and scale. Researchers who aim to automate a single, repetitive task may use a semi-automated approach that integrates simple robotics and manual work or oversight.3,5 For example, genomics researchers enhance their next generation sequencing workflows with semi-automated liquid handling; scientists manually perform more complex experimental steps in the workflow such as nucleic acid extraction and use liquid handling robots for programmable tasks such as dispensing reagents into multi-well plates before sequencing.5

In contrast to semi-automated approaches, fully automated processes enable hands-off multi-tasking. This incorporates robotics and computer programming at many workflow steps, including reagent transfer, sample preparation, result detection, and sample storage. Fully automated approaches, such as liquid handling workstations, typically integrate single-tasking automation technologies and tools such as pumps, shakers, plate readers, centrifuges, heating blocks, and thermocycling devices.5

Liquid Handling Examples of Lab Automation

Infographic highlighting examples of manual, semi-automated, and fully automated liquid handling technologies (handheld pipettes, pipette assisting devices, and liquid handling workstations).

Liquid handling technologies range from manual tools such as micropipettes, to fully automated systems such as computer operated liquid handling workstations. Semi-automated and fully automated liquid handling solutions enable high throughput, greater accuracy and precision, and less time lost on repetitive tasks.5
The Scientist

How Do Researchers Use Lab Automation?

Liquid handling and microfluidics

Traditional liquid handling robots that manipulate pipettes and receptacles are common examples of lab automation tools.4 However, liquid handlers have historically been expensive and technically complex, requiring specialized technicians for setup and operation, which is inaccessible for many research labs.6 Today, technological advances lead to more commercially available, affordable, and adaptable liquid handlers,4 as well as automated liquid handling alternatives such as microfluidic devices.6

Unlike liquid handling robots, microfluidics allows researchers to control liquids on a microscopic scale. Researchers use microfluidic devices to automate synthetic biology protocols and cell culture methods. Additionally, microfluidic devices such as fragment analysers are increasingly popular for researchers working with nucleic acids and next generation sequencing applications.6

High throughput screening

Scientists typically perform high throughput screening to accelerate and scale up molecular discovery, including drug development. New automated platforms and analytical tools enable academic and industrial researchers to collect and process large amounts of data for high throughput screening assays.7 For example, miniaturization such as laboratory on a chip technology reduces manufacturing costs and lab space requirements for semi-automated bioanalytical assays, allowing scientists to obtain rapid screening rates. In addition, automated microplate-based platforms comprised of multiple computers, operating systems, scheduling software, and a central liquid handling robot enable semi-automated and fully automated compound screening, with greater speed and reproducibility than manual processes.Many automated platforms currently use array-based multi-well formats suitable for a range of high throughput applications, including high density immunoassays and cellular microarrays.6,7


From arrayed immunoassays to blotting-based techniques, lab automation facilitates faster and more reproducible workflows. For example, antibodies can be robotically arrayed by liquid handlers for multi-well formats such as enzyme-linked immunosorbent assays (ELISAs) or spotted on membranes with microfluidic technologies such as soft lithography.7,8 These automated technologies help scientists overcome limitations of conventional immunoassay workflows, reducing sample and antibody waste, accelerating analysis times, and increasing multiplexing capability.8,9

Automated reporting and data management 

Lab automation tools take many forms and serve many functions, including data management microprocessors and computers known as laboratory information systems (LIS) or laboratory information management systems (LIMS). Even before personal computers became widely available, scientists turned to a variety of automation-enabling devices for data reporting and management, such as chart recorders and photocells.1 Today, multifunctioning, programmable, computer-controlled interfaces enable bidirectional data transfer between lab instruments and LIS for machine-readable analytical experiments, including records of process steps and data reports. Additionally, advances in computing power and artificial intelligence make lab automation more accessible by progressing toward the next generation of research technologies—remote labs.10

Remote labs: biofoundries and cloud labs 

Remote research labs such as biofoundries and cloud labs help more scientists implement fully or semi-automated experiments without owning specialized technologies.6 Both biofoundries and cloud labs involve integrated systems where scientists submit experiments and digitally receive readouts. A biofoundry typically includes an extensively automated core lab for a range of applications, largely related to DNA manipulation and synthetic biology. Similarly, a cloud lab is a central, heavily automated facility where researchers can perform experiments by remotely controlling automated equipment.6

Biofoundries usually operate through a service model; researchers schedule experiments in an automated lab and receive digital results along with any relevant process data. A cloud lab offers researchers more freedom, functioning as a robotic lab that the scientist controls from behind a computer through web portals and application programming interfaces (APIs).6,11,12

These remote research spaces are burgeoning options for industrial and academic lab automation, with two current company-run cloud labs based in the US (Emerald Cloud Lab and Strateos, previously Transcriptic) and several non-commercial biofoundries based in Europe, Asia, Oceania, and North America.6,12

  1. Olsen K. The first 110 years of laboratory automation: technologies, applications, and the creative scientist. J Lab Autom. 2012;17(6):469-80.
  2. Reynolds T. What is automation in high-throughput science? NC State University. Accessed October 12, 2023.
  3. Baillargeon P, et al. Design of microplate-compatible illumination panels for a semiautomated benchtop pipetting system. SLAS Technol. 2019;24(4):399-407.
  4. Holland I, Davies JA. Automation in the life science research laboratory. Front Bioeng Biotechnol. 2020;8:571777.
  5. Tegally H, et al. Unlocking the efficiency of genomics laboratories with robotic liquid-handling. BMC Genomics. 2020;21(1):729.
  6. Jessop-Fabre MM, Sonnenschein N. Improving reproducibility in synthetic biology. Front Bioeng Biotechnol. 2019;7:18.
  7. Szymanski P, et al. Adaptation of high-throughput screening in drug discovery-toxicological screening tests. Int J Mol Sci. 2012;13(1):427-52.
  8. Yang C, et al. Advanced design and applications of digital microfluidics in biomedical fields: An update of recent progress. Biosens Bioelectron. [published online: October 01, 2023].
  9. Desire CT, et al. The development of microfluidic-based western blotting: Technical advances and future perspectives. J Chromatogr A. 2023;1691:463813.
  10. Bai J, et al. From platform to knowledge graph: Evolution of laboratory automation. JACS Au. 2022;2(2):292-309.
  11. Groth P, Cox J. Indicators for the use of robotic labs in basic biomedical research: a literature analysis. PeerJ. 2017;5:e3997.
  12. Holowko MB, et al. Building a biofoundry. Synth Biol (Oxf). 2021;6(1):ysaa026.
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