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==History== |
==History== |
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Cloud laboratories were built on advancements made in laboratory automation in the 1990s. In the early 1990s, the modularity project of the Consortium of Automated Analytical Laboratory Systems worked to define standards by which biotechnology manufacturers could produce products that could be integrated into automated systems.<ref name="Salit Guenther Kramer Griesmeyer pp. 361A–367A">{{cite journal | last1=Salit | first1=Marc L. | last2=Guenther | first2=Franklin R. | last3=Kramer | first3=Gary W. | last4=Griesmeyer | first4=J. Michael | title=Integrating Automated Systems With Modular Architecture | journal=Analytical Chemistry | publisher=American Chemical Society (ACS) | volume=66 | issue=6 | date=Mar 15, 1994 | issn=0003-2700 | doi=10.1021/ac00078a727 | pages=361A–367A}}</ref> In 1996, the National Committee for Clinical Laboratory Standards (now the [[Clinical and Laboratory Standards Institute]]) proposed laboratory automation standards that aimed to enable consumers of laboratory technology to purchase hardware and software from different vendors and connect them to each other seamlessly.<ref name="SAGE Publications 1998 pp. 93–93">{{cite journal | title=A Report of the NCCLS Area Committee on Automation 4th Quarter of 1998 | journal= |
Cloud laboratories were built on advancements made in laboratory automation in the 1990s. In the early 1990s, the modularity project of the Consortium of Automated Analytical Laboratory Systems worked to define standards by which biotechnology manufacturers could produce products that could be integrated into automated systems.<ref name="Salit Guenther Kramer Griesmeyer pp. 361A–367A">{{cite journal | last1=Salit | first1=Marc L. | last2=Guenther | first2=Franklin R. | last3=Kramer | first3=Gary W. | last4=Griesmeyer | first4=J. Michael | title=Integrating Automated Systems With Modular Architecture | journal=Analytical Chemistry | publisher=American Chemical Society (ACS) | volume=66 | issue=6 | date=Mar 15, 1994 | issn=0003-2700 | doi=10.1021/ac00078a727 | pages=361A–367A}}</ref> In 1996, the National Committee for Clinical Laboratory Standards (now the [[Clinical and Laboratory Standards Institute]]) proposed laboratory automation standards that aimed to enable consumers of laboratory technology to purchase hardware and software from different vendors and connect them to each other seamlessly.<ref name="SAGE Publications 1998 pp. 93–93">{{cite journal | title=A Report of the NCCLS Area Committee on Automation 4th Quarter of 1998 | journal=Journal of the Association for Laboratory Automation | publisher=SAGE Publications | volume=3 | issue=6 | year=1998 | issn=1535-5535 | doi=10.1177/221106829800300618 | pages=93| s2cid=208147539 }}</ref> The Committee launched five subcommittees in 1997 and released standardization protocols to guide product development through the early 2000s.<ref name=AUTO5>{{cite report |title= AUTO5A.Laboratory Automation: Electromechanical Interfaces; Approved Standard| publisher=Clinical and Laboratory Standards Institute |date=2001}}</ref><ref name="Hawker Schlank pp. 746–750">{{cite journal | last1=Hawker | first1=Charles D | last2=Schlank | first2=Marc R | title=Development of Standards for Laboratory Automation | journal=Clinical Chemistry | publisher=Oxford University Press (OUP) | volume=46 | issue=5 | date=Apr 1, 2000 | issn=0009-9147 | doi=10.1093/clinchem/46.5.746 | pages=746–750| pmid=10794772 }}</ref> |
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These early developments in interoperability led to early examples of lab automation using cloud infrastructure, such as the Robot Scientist "[[Robot Scientist|Adam]]" in 2009. This robot encapsulated and connected all the laboratory equipment necessary to perform microbial batch experiments.<ref name="King Rowland Oliver Young pp. 85–89">{{cite journal | last1=King | first1=Ross D. | last2=Rowland | first2=Jem | last3=Oliver | first3=Stephen G. | last4=Young | first4=Michael | last5=Aubrey | first5=Wayne | last6=Byrne | first6=Emma | last7=Liakata | first7=Maria | last8=Markham | first8=Magdalena | last9=Pir | first9=Pinar | last10=Soldatova | first10=Larisa N. | last11=Sparkes | first11=Andrew | last12=Whelan | first12=Kenneth E. | last13=Clare | first13=Amanda | title=The Automation of Science | journal=Science | publisher=American Association for the Advancement of Science (AAAS) | volume=324 | issue=5923 | date=Apr 3, 2009 | issn=0036-8075 | doi=10.1126/science.1165620 | pages=85–89 | pmid=19342587 | bibcode=2009Sci...324...85K | s2cid=14948753 | url=https://www.research.manchester.ac.uk/portal/en/publications/the-automation-of-science(953b64bb-8e2a-4434-8820-4c0c23fe602d).html | access-date=June 13, 2022 | archive-date=September 10, 2022 | archive-url=https://web.archive.org/web/20220910192813/https://www.research.manchester.ac.uk/portal/en/publications/the-automation-of-science%28953b64bb-8e2a-4434-8820-4c0c23fe602d%29.html | url-status=live }}</ref> |
These early developments in interoperability led to early examples of lab automation using cloud infrastructure, such as the Robot Scientist "[[Robot Scientist|Adam]]" in 2009. This robot encapsulated and connected all the laboratory equipment necessary to perform microbial batch experiments.<ref name="King Rowland Oliver Young pp. 85–89">{{cite journal | last1=King | first1=Ross D. | last2=Rowland | first2=Jem | last3=Oliver | first3=Stephen G. | last4=Young | first4=Michael | last5=Aubrey | first5=Wayne | last6=Byrne | first6=Emma | last7=Liakata | first7=Maria | last8=Markham | first8=Magdalena | last9=Pir | first9=Pinar | last10=Soldatova | first10=Larisa N. | last11=Sparkes | first11=Andrew | last12=Whelan | first12=Kenneth E. | last13=Clare | first13=Amanda | title=The Automation of Science | journal=Science | publisher=American Association for the Advancement of Science (AAAS) | volume=324 | issue=5923 | date=Apr 3, 2009 | issn=0036-8075 | doi=10.1126/science.1165620 | pages=85–89 | pmid=19342587 | bibcode=2009Sci...324...85K | s2cid=14948753 | url=https://www.research.manchester.ac.uk/portal/en/publications/the-automation-of-science(953b64bb-8e2a-4434-8820-4c0c23fe602d).html | access-date=June 13, 2022 | archive-date=September 10, 2022 | archive-url=https://web.archive.org/web/20220910192813/https://www.research.manchester.ac.uk/portal/en/publications/the-automation-of-science%28953b64bb-8e2a-4434-8820-4c0c23fe602d%29.html | url-status=live }}</ref> |
Revision as of 02:41, 30 September 2022
A cloud laboratory is a heavily automated, centralized research laboratory where scientists can run an experiment from a computer in a remote location.[1][2][3] Cloud laboratories offer the execution of life science research experiments as a service, allowing researchers to retain full control over experimental design.[4][5][6] Users create experimental protocols through a high-level API and the experiment is executed in the cloud laboratory, with no need for the user to be involved.[1][6]
Cloud labs reduce variability in experimental execution, as the code can be interrogated, analyzed, and executed repeatedly.[2] They democratize access to expensive laboratory equipment while standardizing experimental execution, which could potentially help address the replication crisis[5][7][8]—what might before have been described in a paper as "mix the samples" is replaced by instructions for a specified machine to mix at a specified rpm rate for a specified time, with relevant factors such as the ambient temperature logged.[9] They also reduce costs by sharing capital costs across many users, by running experiments in parallel, and reducing instrument downtime.[8] Finally, they facilitate collaboration by making it easier to share protocols, data, and data processing methods through the cloud.[7]
Infrastructure
Cloud labs utilize common scientific techniques including DNA sequencing and genotyping, high-performance liquid chromatography (HPLC), protein extraction, plate reading, upstream bioprocessing, and western blotting.[3][4][10][11] Users begin by signing up and logging in to the web-based software interface.[6] Researchers submit their protocols via a dedicated web application or through an API, and when the order arrives at the laboratory, human operators set up the experiment and transfer plates from machine to machine. Data is automatically uploaded to the cloud lab via an API where users can access and analyze it. Users can review controls, machine settings, and reagents used.[10] Multiple experiments can be run in parallel, 24 hours a day.[4][12][13]
A true cloud lab is defined by five criteria:[14][15][16]
- Users must be able to conduct experiments on-demand at any time from any location, all through a computer interface.
- The cloud laboratory must enable a user to digitally replicate the experience of standing in a traditional laboratory and manually operating instruments. It must allow users to specify all aspects of their experiments remotely without lead time, additional software, or outside experts
- Users must have on-demand access to all the instruments needed to perform their experiment, rendering a physical laboratory unnecessary.
- Users must be able to perform sample preparation, as well as storage and handling, from a remote setting.
- Users must be able to script and connect multiple experiments, and conduct data analysis, using a single standardized computer interface.
Using a cloud laboratory vs. high-throughput experimentation
High-throughput experimentation involves increasing throughput by scaling up the number of experiments that can be run in parallel using a common sample form factor and technique.[17][18] When space or materials are limited, minor factors must be assigned to progressively smaller fractions to increase the number of replicates.[19] Cloud labs, on the other hand, do not fundamentally scale up a single experiment but rather increase the number of types of experiments that can be run in parallel.[20] For example, with a cloud lab, a scientist could simultaneously attempt dozens of different purification methods that each uses completely unique equipment sets.[15]
HTE work cells can sometimes be accessed remotely to trigger a run on a library or digitally monitor a run. However, this remote monitoring or screen triggering does not impact the development that must take place in advance of a run.[17] Often with HTE, scientists must group samples into libraries that use the same or very similar form factor containers such that the work cell can more easily traffic and address each sample in an integrated manner.[17] Therefore, scientists need to standardize sample form factors of samples and handle the sample prep offline of the work cell. Cloud labs can work with samples in hundreds or even thousands of unique containers, providing additional flexibility relative to traditional labs (even those that are using HTE), and allowing processing of a larger number of samples.[15]
Cloud labs are intended to replace the driver of traditional lab work by offering scientists the capability to conduct the same type of work they would typically perform in a traditional lab, except unrestricted by time and laboratory space.[21][22]
History
Cloud laboratories were built on advancements made in laboratory automation in the 1990s. In the early 1990s, the modularity project of the Consortium of Automated Analytical Laboratory Systems worked to define standards by which biotechnology manufacturers could produce products that could be integrated into automated systems.[23] In 1996, the National Committee for Clinical Laboratory Standards (now the Clinical and Laboratory Standards Institute) proposed laboratory automation standards that aimed to enable consumers of laboratory technology to purchase hardware and software from different vendors and connect them to each other seamlessly.[24] The Committee launched five subcommittees in 1997 and released standardization protocols to guide product development through the early 2000s.[25][26]
These early developments in interoperability led to early examples of lab automation using cloud infrastructure, such as the Robot Scientist "Adam" in 2009. This robot encapsulated and connected all the laboratory equipment necessary to perform microbial batch experiments.[27]
In 2010, D. J. Kleinbaum and Brian Frezza founded antiviral developer Emerald Therapeutics. To simplify laboratory testing, the group wrote centralized management software for their collection of scientific instruments and a database to store all metadata and results.[28][3]
In 2012, Transcriptic founded a robotic cloud laboratory for on-demand scientific research, which performed select tasks including DNA cloning remotely.[29]
In 2014, Emerald Therapeutics spun out the Emerald Cloud Lab to fully replace the need for a traditional lab environment, enabling scientists from around the world to perform all necessary activities, from experimental design to data acquisition and analysis.[30]
Carnegie Mellon University's Mellon College of Science is building the world's first academic cloud laboratory on their campus.[31] The 20,000 square foot laboratory will be completed in 2023 and offer access to CMU researchers and eventually to other schools and life-sciences startups in Pittsburgh.[32][3]
Risks
Easy access to sophisticated labs can be a potential biosecurity or bioterrorism threat. Filippa Lentzos, an expert in biological risk and biosecurity, said "there are some pretty crazy people out there ... Barriers are coming down if you want to deliberately do something harmful". Cloud labs say that they review all scheduled experiments and can flag or reject any that appear illegal or dangerous, and that detailed record-keeping makes monitoring what is done easier than in a traditional laboratory.[9]
References
- ^ a b Jessop-Fabre, Mathew M; Sonnenschein, Nikolaus (Feb 11, 2019). "Improving Reproducibility in Synthetic Biology". Frontiers in Bioengineering and Biotechnology. 7. Frontiers Media SA: 18. doi:10.3389/fbioe.2019.00018. ISSN 2296-4185. PMC 6378554. PMID 30805337.
- ^ a b Groth, Paul; Cox, Jessica (Nov 8, 2017). "Indicators for the use of robotic labs in basic biomedical research: a literature analysis". PeerJ. 5: e3997. doi:10.7717/peerj.3997. ISSN 2167-8359. PMC 5681851. PMID 29134146.
- ^ a b c d Arnold C (2022). "Cloud labs: where robots do the research". Nature. 606 (7914): 612–3. doi:10.1038/d41586-022-01618-x. PMID 35697877.
- ^ a b c van der Mersch, Vassili (May 17, 2016). "Exploring the Cloud Laboratory: Advances in Biotech & Science-as-a-Service". Nordic APIs. Archived from the original on January 21, 2022.
- ^ a b Bates, Maxwell; Berliner, Aaron J.; Lachoff, Joe; Jaschke, Paul R.; Groban, Eli S. (Sep 2, 2016). "Wet Lab Accelerator: A Web-Based Application Democratizing Laboratory Automation for Synthetic Biology". ACS Synthetic Biology. 6 (1). American Chemical Society (ACS): 167–171. doi:10.1021/acssynbio.6b00108. ISSN 2161-5063. PMID 27529358.
- ^ a b c "Laboratories in the cloud". Bulletin of the Atomic Scientists. 3 July 2019. Archived from the original on February 4, 2022. Retrieved Dec 9, 2021.
- ^ a b "Robotic Cloud Laboratories Allow Scientists to Work from Home". The New Stack. April 3, 2020. Archived from the original on January 1, 2022. Retrieved Dec 9, 2021.
- ^ a b Wykstra, Stephanie (Jun 30, 2016). "Robotic Cloud Labs May Be One Way to Make Research More Reproducible". Slate Magazine. Archived from the original on May 6, 2022. Retrieved Dec 9, 2021.
- ^ a b Ireland, Tom (11 September 2022). "Cloud labs and remote research aren't the future of science – they're here". The Guardian.
- ^ a b Check Hayden, Erika (Dec 3, 2014). "The automated lab". Nature. 516 (7529): 131–132. Bibcode:2014Natur.516..131C. doi:10.1038/516131a. PMID 25471888. Archived from the original on January 23, 2022. Retrieved Dec 9, 2021.
- ^ "Culture riding virtual R&D wave, latest funding round enables development of cloud bioreactors". Biopharmaceutical Manufacturing, Upstream, Downstream processing news. Nov 12, 2021. Archived from the original on November 15, 2021. Retrieved Dec 9, 2021.
- ^ Mouratidis, Yiannis (Feb 27, 2019). "A Cloud Lab Dedicated To Cancer Drug Discovery". Forbes. Archived from the original on February 28, 2019. Retrieved Dec 9, 2021.
- ^ Segal, Michael (Sep 25, 2019). "An operating system for the biology lab". Nature. 573 (7775): S112–S113. Bibcode:2019Natur.573S.112S. doi:10.1038/d41586-019-02875-z. S2CID 202749446. Archived from the original on October 26, 2021. Retrieved Dec 9, 2021.
- ^ "5 criteria of a true cloud laboratory". Drug Discovery & Development. February 25, 2022. Archived from the original on May 6, 2022. Retrieved Mar 17, 2022.
- ^ a b c "What are the criteria of a true cloud laboratory?". Drug Discovery & Development. March 16, 2022. Archived from the original on May 6, 2022. Retrieved Mar 17, 2022.
- ^ Blackburn, Toby (May 4, 2022). "Accelerating Scientific Research Using the Cloud". In the Lab Enewsletter. Pharmaceutical Technology's in the Lab eNewsletter, May 2022. 17 (5). Archived from the original on May 4, 2022. Retrieved May 5, 2022.
- ^ a b c Shevlin M (2019). "The Evolution of High-Throughput Experimentation in Pharmaceutical Development and Perspectives on the Future". Org Process Res Dev. 23 (6): 1213–1242. doi:10.1021/acs.oprd.9b00140. S2CID 164744152. Archived from the original on 2022-05-09. Retrieved 2022-05-09.
- ^ Mennen S (2017). "Practical High-Throughput Experimentation for Chemists". ACS Med Chem Lett. 8 (6): 601–607. doi:10.1021/acsmedchemlett.7b00165. PMC 5467193. PMID 28626518. Archived from the original on 2022-05-09. Retrieved 2022-05-09.
- ^ Shevlin M (2017). "Practical High-Throughput Experimentation for Chemists". ACS Med Chem Lett. 8 (6): 601–607. doi:10.1021/acsmedchemlett.7b00165. PMC 5467193. PMID 28626518.
- ^ "Carnegie Mellon University and Emerald Cloud Lab to Build World's First University Cloud Lab". CMU.edu. Aug 30, 2021. Archived from the original on February 15, 2022. Retrieved Mar 24, 2022.
- ^ "Developing drugs using a lab in the cloud". Manufacturing Chemist. Jul 29, 2021. Archived from the original on September 25, 2021. Retrieved May 9, 2022.
- ^ "Cloud lab solution empowers access of research tech from miles away". Outsourcing Pharma. Aug 26, 2021. Archived from the original on September 22, 2021. Retrieved May 9, 2022.
- ^ Salit, Marc L.; Guenther, Franklin R.; Kramer, Gary W.; Griesmeyer, J. Michael (Mar 15, 1994). "Integrating Automated Systems With Modular Architecture". Analytical Chemistry. 66 (6). American Chemical Society (ACS): 361A–367A. doi:10.1021/ac00078a727. ISSN 0003-2700.
- ^ "A Report of the NCCLS Area Committee on Automation 4th Quarter of 1998". Journal of the Association for Laboratory Automation. 3 (6). SAGE Publications: 93. 1998. doi:10.1177/221106829800300618. ISSN 1535-5535. S2CID 208147539.
- ^ AUTO5A.Laboratory Automation: Electromechanical Interfaces; Approved Standard (Report). Clinical and Laboratory Standards Institute. 2001.
- ^ Hawker, Charles D; Schlank, Marc R (Apr 1, 2000). "Development of Standards for Laboratory Automation". Clinical Chemistry. 46 (5). Oxford University Press (OUP): 746–750. doi:10.1093/clinchem/46.5.746. ISSN 0009-9147. PMID 10794772.
- ^ King, Ross D.; Rowland, Jem; Oliver, Stephen G.; Young, Michael; Aubrey, Wayne; Byrne, Emma; Liakata, Maria; Markham, Magdalena; Pir, Pinar; Soldatova, Larisa N.; Sparkes, Andrew; Whelan, Kenneth E.; Clare, Amanda (Apr 3, 2009). "The Automation of Science". Science. 324 (5923). American Association for the Advancement of Science (AAAS): 85–89. Bibcode:2009Sci...324...85K. doi:10.1126/science.1165620. ISSN 0036-8075. PMID 19342587. S2CID 14948753. Archived from the original on September 10, 2022. Retrieved June 13, 2022.
- ^ Vance, Ashlee (3 July 2014). "Emerald Therapeutics: Biotech Lab for Hire". Bloomberg. Archived from the original on 5 July 2017. Retrieved 30 October 2019.
- ^ "Biotech Startup Transcriptic Receives $1.2M In Seed Funding Led By Google Ventures And FF Angel". TechCrunch. Dec 13, 2012. Archived from the original on December 16, 2012. Retrieved Dec 12, 2012.
- ^ Buhr, Sarah (Jul 8, 2014). "Emerald Cloud Laboratory Is Experimenting With Drugs In The Cloud – TechCrunch". TechCrunch. Archived from the original on September 10, 2022. Retrieved Dec 9, 2021.
- ^ "Carnegie Mellon Gets $150M Grant for Science and Robotics". GovTech. May 27, 2021. Archived from the original on May 9, 2022. Retrieved Dec 9, 2021.
- ^ Castellanos, Sara (Aug 30, 2021). "Carnegie Mellon's Cloud Lab to Automate Labor-Intensive Science Experiments". WSJ. Archived from the original on December 5, 2021. Retrieved Dec 9, 2021.