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Laboratory automation

Process improvement strategy for routine procedures

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Laboratory automation can increase experimental throughput, reduce repetitive manual work, and improve the consistency of laboratory processes. Automated systems may include liquid-handling equipment, autosamplers, analytical instruments, robotic workstations, sample-transport systems and software for controlling instruments and coordinating workflows.

More recently, laboratory automation has been combined with algorithmic experimental planning in self-driving laboratories and other autonomous laboratory systems. These systems use results from automated experiments to select subsequent experiments, creating a closed-loop process in which experimental execution, measurement, analysis and planning are integrated.

History

At least since 1875 there have been reports of automated devices for scientific investigation. These first devices were mostly built by scientists themselves in order to solve problems in the laboratory. After the second world war, companies started to provide automated equipment with greater and greater complexity.

Automation steadily spread in laboratories through the 20th century, but then a revolution took place: in the early 1980s, the first fully automated laboratory was opened by Dr. Masahide Sasaki. In 1993, Dr. Rod Markin at the University of Nebraska Medical Center created one of the world's first clinical automated laboratory management systems. In the mid-1990s, he chaired a standards group called the Clinical Testing Automation Standards Steering Committee (CTASSC) of the American Association for Clinical Chemistry, which later evolved into an area committee of the Clinical and Laboratory Standards Institute. In 2004, the National Institutes of Health (NIH) and more than 300 nationally recognized leaders in academia, industry, government, and the public completed the NIH Roadmap to accelerate medical discovery to improve health. The NIH Roadmap clearly identifies technology development as a mission critical factor in the Molecular Libraries and Imaging Implementation Group (see the first theme – New Pathways to Discovery – at https://web.archive.org/web/20100611171315/http://nihroadmap.nih.gov/).

Despite the success of Dr. Sasaki laboratory and others of the kind, the multi-million dollar cost of such laboratories has prevented adoption by smaller groups. This is all more difficult because devices made by different manufactures often cannot communicate with each other. However, recent advances based on the use of scripting languages like Autoit have made possible the integration of equipment from different manufacturers. Using this approach, many low-cost electronic devices, including open-source devices, become compatible with common laboratory instruments.

Some startups such as Emerald Cloud Lab and Strateos provide on-demand and remote laboratory access on a commercial scale. A 2017 study indicates that these commercial-scale, fully integrated automated laboratories can improve reproducibility and transparency in basic biomedical experiments, and that over nine in ten biomedical papers use methods currently available through these groups.

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