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Laboratory automation is a multi-disciplinary strategy to research, develop, optimize and capitalize on technologies in the laboratory that enable new and improved processes. Laboratory automation professionals are academic, commercial and government researchers, scientists and engineers who conduct research and develop new technologies to increase productivity, elevate experimental data quality, reduce lab process cycle times, or enable experimentation that otherwise would be impossible.

The most widely known application of laboratory automation technology is laboratory robotics. More generally, the field of laboratory automation comprises many different automated laboratory instruments, devices (the most common being autosamplers), software algorithms, and methodologies used to enable, expedite and increase the efficiency and effectiveness of scientific research in laboratories.

The application of technology in today's laboratories is required to achieve timely progress and remain competitive. Laboratories devoted to activities such as high-throughput screening, combinatorial chemistry, automated clinical and analytical testing, diagnostics, large scale biorepositories, and many others, would not exist without advancements in laboratory automation.

Some universities offer entire programs that focus on lab technologies. For example, Indiana University-Purdue University at Indianapolis offers a graduate program devoted to Laboratory Informatics. Also, the Keck Graduate Institute in California offers a graduate degree with an emphasis on development of assays, instrumentation and data analysis tools required for clinical diagnostics, high-throughput screening, genotyping, microarray technologies, proteomics, imaging and other applications.

Contents

HistoryEdit

At least since 1875 there have been reports of automated devices for scientific investigation.[1] 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 which had become more and more complex.

Automation was spreading in laboratories steadily 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.[2][3] In 1993, Dr. Rod Markin at the University of Nebraska Medical Center created one of the world's first clinical automated laboratory management systems.[4] 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,[5][6] which later evolved into an area committee of the Clinical and Laboratory Standards Institute.[7] 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 undeniable success of Dr. Sasaki laboratory and others of the kind, the multi-million dollar cost of such laboratories has prevented most laboratories to adopt it.[8] This is all more difficult because usually devices made by different manufactures cannot communicate with each other. However, recent advances based on the use of scripting languages like Autoit have made it possible the integration of equipment from different manufacturers.[9] Using this approach, many low-cost electronic devices, including open-source devices,[10] become compatible to common laboratory instruments.

Low-cost laboratory automationEdit

A large obstacle to the implementation of automation in laboratories has been its high cost. Many laboratory instruments are very expensive. This is justifiable in many cases, as such equipment can perform very specific tasks employing cutting-edge technology. However, there are devices employed in the laboratory that are not highly-technological but still are very expensive. This is the case of many automated devices, which perform tasks that could easily be done by simple and low-cost devices like simple robotic arms,[11][12][13] universal (open-source) electronic modules,[14][15] or 3D printers.

So far, using such low-cost devices together with laboratory equipment was considered to be very difficult. However, it has been demonstrated that such low cost devices can substitute without problems the standard machines used in laboratory.[11] It can be anticipated that more laboratories will take advantage of this new reality as low-cost automation is very attractive for laboratories.

The technology that enables the integration of any machine regardless of their brand is scripting, more specifically, scripting involving the control of mouse clicks and keyboard entries, like AutoIt. By timing clicks and keyboard inputs, different software interfaces controlling different devices can be perfectly synchronized.[9][16]

Benchtop automationEdit

Benchtop automation consists in the use of machines of reduced size compared to large automation units found in the most resource-rich laboratories. Benchtop automation are often flexible, meaning that they can deal with many different tasks. Since many laboratories do not need to employ full-scale automation, benchtop automation can be an attractive solution for them. Also, the low-cost devices presented in the previous subsection could easily be employed as benchtop solutions in many cases.

Laboratory automationEdit

Automation is the use of control systems and information technologies to reduce the need for human work in the production of goods and services.

Laboratory automation is the use of instrument and specimen processing equipment to perform clinical assay with only minimal involvement from the technologist.

Automation in clinical laboratoryEdit

There are several individual steps in the analysis process as a whole in a laboratory such as:

1. Identifying the patient 2. Getting the correct sample 3. Identifying and proper labeling of the sample 4. Delivery of sample in proper storage condition and within time 5. Preparation of sample for test 6. Sample loading/aspirating 7. Analysis 8. Reporting—Entering the result manually 9. Entering in register

Automation has a lot of benefits for the laboratory personnel. 1. Reduces the workload 2. Reduces turnaround time (Saves time used per analysis) 3. Increases total number of tests done in less time 4. Eliminates repetition and monotony from human life so decreases human error, improves accuracy 5. Improves reproducibility (repeatability) 6. Uses minimum amount of sample and reagent

Companies involved in Lab automationEdit

TranscripticEdit

Transcritpic is commercial provider of robotic cloud platform for life science research. It was founded in 2012 by Max Hodak.

Gingko BioworksEdit

See alsoEdit

ReferencesEdit

  1. ^ Olsen, Kevin (2012-12-01). "The First 110 Years of Laboratory Automation Technologies, Applications, and the Creative Scientist". Journal of Laboratory Automation. 17 (6): 469–480. doi:10.1177/2211068212455631. ISSN 2211-0682. PMID 22893633. 
  2. ^ Felder, Robin A. (2006-04-01). "The Clinical Chemist: Masahide Sasaki, MD, PhD (August 27, 1933–September 23, 2005)". Clinical Chemistry. 52 (4): 791–792. doi:10.1373/clinchem.2006.067686. ISSN 0009-9147. 
  3. ^ Boyd, James (2002-01-18). "Robotic Laboratory Automation". Science. 295 (5554): 517–518. doi:10.1126/science.295.5554.517. ISSN 0036-8075. PMID 11799250. 
  4. ^ LIM Source, a laboratory information management systems resource
  5. ^ Clinical Chemistry 46, No. 5, 2000, pgs. 246-250
  6. ^ Health Management Technology magazine, October 1, 1995
  7. ^ Clinical and Laboratory Standards Institute (formerly NCCLS)
  8. ^ Felder, Robin A (1998-12-01). "Modular workcells: modern methods for laboratory automation". Clinica Chimica Acta. 278 (2): 257–267. doi:10.1016/S0009-8981(98)00151-X. 
  9. ^ a b Carvalho, Matheus C. (2013-08-01). "Integration of Analytical Instruments with Computer Scripting". Journal of Laboratory Automation. 18 (4): 328–333. doi:10.1177/2211068213476288. ISSN 2211-0682. PMID 23413273. 
  10. ^ Pearce, Joshua M. (2014-01-01). Chapter 1 - Introduction to Open-Source Hardware for Science. Boston: Elsevier. pp. 1–11. doi:10.1016/b978-0-12-410462-4.00001-9. ISBN 9780124104624. 
  11. ^ a b Carvalho, Matheus C.; Eyre, Bradley D. (2013-12-01). "A low cost, easy to build, portable, and universal autosampler for liquids". Methods in Oceanography. 8: 23–32. doi:10.1016/j.mio.2014.06.001. 
  12. ^ "Robotics-assisted mass spectrometry assay platform enabled by open-source electronics". Biosensors and Bioelectronics. 64: 260–268. doi:10.1016/j.bios.2014.08.087. 
  13. ^ "Dual robotic arm "production line" mass spectrometry assay guided by multiple Arduino-type microcontrollers". Sensors and Actuators B: Chemical. 239: 608–616. doi:10.1016/j.snb.2016.08.031. 
  14. ^ "Universal electronics for miniature and automated chemical assays". 
  15. ^ "Open hardware: Self-built labware stimulates creativity". Nature. 532: 313. doi:10.1038/532313d. 
  16. ^ Carvalho, Matheus (2017). Practical Laboratory Automation: Made Easy with AutoIt. Wiley VCH. ISBN 978-3-527-34158-0. 

Further readingEdit