Difference between revisions of "User:Shawndouglas/sandbox/sublevel1"

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While the research, analysis, and processing of cannabis has been ongoing for centuries<ref name="DeitchHemp03">{{cite book |title=Hemp – American History Revisited |author=Deitch, R. |publisher=Algora Publishing |location=New York City |year=2003 |pages=232 |isbn=9780875862262}}</ref>, it wasn't until 1896 that Wood ''et al.'' conducted one of the first documented chemical experiments to determine the constituents of cannabis. Several years later, the researchers were able to correctly identify the extracted and isolated cannabinol from the exuded resin of Indian hemp as C<sub>21</sub>H<sub>26</sub>O<sub>2</sub>.<ref name="WoodCann1899">{{cite journal |title=III.—Cannabinol. Part I |journal=Journal of the Chemical Society, Transactions |author=Wood, T.B.; Newton Spivey, W.T.; Easterfield, T.H. |volume=75 |pages=30–36 |year=1899 |doi=10.1039/CT8997500020}}</ref> As of mid-2018, somewhere between 104 upwards to more than 140 of the more than 750 constituents of ''Cannabis sativa'' have been identified as cannabinoids<ref name="RadwanIso15">{{cite journal |title=Isolation and pharmacological evaluation of minor cannabinoids from high-potency ''Cannabis sativa'' |journal=Journal of Natural Products |author=Radwan, M.M.; ElSohly, M.A.; El-Alfy, A.T. et al. |volume=78 |issue=6 |pages=1271-6 |year=2015 |doi=10.1021/acs.jnatprod.5b00065 |pmid=26000707 |pmc=PMC4880513}}</ref><ref name="SolymosiCanna17">{{cite journal |title=''Cannabis'': A Treasure Trove or Pandora's Box? |journal=Mini-Reviews in Medicinal Chemistry |author=Solymosi, K.; Köfalvi, A. |volume=17 |pages=1123–91 |year=2017 |doi=10.2174/1389557516666161004162133}}</ref><ref name="MudgeChemo18">{{cite journal |title=Chemometric Analysis of Cannabinoids: Chemotaxonomy and Domestication Syndrome |journal=Scientific Reports |author=Mudge, E.M.; Murch, S.J.; Brown, P.N. |volume=8 |at=13090 |year=2018 |doi=10.1038/s41598-018-31120-2}}</ref>, "a class of diverse chemical compounds that act on cannabinoid receptors in cells that modulate neurotransmitter release in the brain."<ref name="WHOTheHealth16">{{cite book |url=https://www.who.int/publications/i/item/9789241510240 |title=The health and social effects of nonmedical cannabis use |author=World Health Organization |editor=Hall, W.; Renström, M.; Poznyak, V |publisher=World Health Organization |pages=95 |year=2016 |isbn=978921510240}}</ref>
[[File:IBM 1130 (16758008839).jpg|right|thumb|IBM 1130 desk-sized computer from the mid-1960s and '70s]]Computers in the laboratory are not a recent phenomenon. The mid-1960s saw clinical laboratory computerization become increasingly popular<ref name="KriegClinical74">{{cite book |chapter=Chapter 30: Clinical Laboratory Computerization |title=Clinical Diagnosis by Laboratory Methods |author=Krieg, A.F. |editor=Davidsohn, I.; Henry, J.B. |publisher=W.B. Saunders Company |pages=1340–58 |year=1974 |isbn=0721629229}}</ref><ref name="FlynnComputer65">{{cite book |chapter=Computer-assisted processing of bio-chemical test data |title=Progress in Medical Computing |author=Flynn, F.V. |editor=Atkins, H.J.B. |publisher=Blackwell Science Ltd |page=46 |year=1965 |isbn=0632001801}}</ref><ref name="WilliamsTheUse64">{{cite journal |title=The Use of Data Processing and Automation in Clinical Pathology |journal=Military Medicine |author=Williams, G.Z. |volume=129 |issue=6 |pages=502–9 |year=1964 |doi=10.1093/milmed/129.6.502}}</ref><ref name="HicksRoutine66">{{cite journal |title=Routine Use of a Small Digital Computer in the Clinical Laboratory |journal=JAMA |author=Hicks, G.P.; Gieschen, M.M.; Slack, W.V. et al. |volume=196 |issue=11 |pages=973–78 |year=1966 |doi=10.1001/jama.1966.03100240107021}}</ref><ref name="StraumfjordElectronic67">{{cite journal |title=Electronic Data Processing System for Clinical Laboratories: A System Used for All Laboratory Sections |journal=American Journal of Clinical Pathology |author=Straumfjord, J.V.; Spraberry, M.N.; Biggs, H.G.; Noto, T.A. |volume=47 |issue=5_ts |pages=661–76 |year=1967 |doi=10.1093/ajcp/47.5_ts.661}}</ref>, though that enthusiasm was often based on the potential of the computers themselves rather than their actual capabilities.<ref name="KriegClinical74" /> Researchers imagined potentials such as automatic specimen label generation, daily log and report management, instrument interfacing and data processing, results comparisons, and time management tools. It would take time for some of those potentials to be realized.<ref name="KriegClinical74" />


However, at least in the United States, when it comes to 1. enacting the broad level of testing required to ensure public safety—whether it be medical, recreational, or industrial use of cannabis—and 2. researching and better understanding the pharmacokinetics and pharmacodynamics (medical use and benefit) of cannabinoids in the human population, many have argued that laboratory testing of cannabis is still in its infancy<ref name="HazekampCanna12">{{cite journal |title=Cannabis - from cultivar to chemovar |journal=Drug Testing and Analysis |author=Hazekamp, A.; Fischedick, J.T. |volume=4 |issue=7–8 |pages=660–7 |year=2012 |doi=10.1002/dta.407 |pmid=22362625}}</ref><ref name="BushWorlds15">{{cite web |url=https://www.seattletimes.com/seattle-news/worldrsquos-strongest-weed-potency-testing-challenged/ |title=World’s strongest weed? Potency testing challenged |author=Bush, E. |work=The Seattle Times |publisher=The Seattle Times Company |date=18 February 2015 |accessdate=18 November 2021}}</ref><ref name="RutschQuality15">{{cite web |url=https://www.npr.org/sections/health-shots/2015/03/24/395065699/quality-testing-legal-marijuana-strong-but-not-always-clean |title=Quality-Testing Legal Marijuana: Strong But Not Always Clean |author=Rutsch, P. |work=Shots |publisher=National Public Radio |date=24 March 2015 |accessdate=18 November 2021}}</ref><ref name="KuzdzalUnrav15">{{cite journal |title=Unraveling the Cannabinome |journal=The Analytical Scientist |author=Kuzdzal, S.; Lipps, W. |issue=0915 |year=2015 |url=https://theanalyticalscientist.com/techniques-tools/unraveling-the-cannabinome |accessdate=18 November 2021}}</ref><ref name="CrombieMari16">{{cite web |url=https://www.oregonlive.com/marijuana/2016/07/marijuana_labs_prepping_for_st.html |title=Marijuana labs prepping for regulation and oversight; no lab licenses issued yet |author=Crombie, N. |work=The Oregonian |publisher=Oregon Live LLC |date=25 July 2016 |accessdate=18 November 2021}}</ref><ref name="KuzdzalACloser16">{{cite web |url=https://www.ssi.shimadzu.com/sites/ssi.shimadzu.com/files/Industry/Literature/Shimadzu_Whitepaper_Emerging_Cannabis_Industry.pdf |format=PDF |title=A Closer Look at Cannabis Testing |author=Kuzdzal, S.; Clifford, R.; Winkler, P.; Bankert, W. |publisher=Shimadzu Corporation |date=December 2017 |accessdate=18 November 2021}}</ref> and evidence-based research of marijuana continues to be slow and bogged down in regulation.<ref name="BajajHowThe14">{{cite web |url=https://takingnote.blogs.nytimes.com/2014/07/30/how-the-federal-government-slows-marijuana-research/ |title=How the Federal Government Slows Marijuana Research |author=Bajaj, V. |work=Taking Note: The New York Times |publisher=The New York Times Company |date=30 July 2014 |accessdate=18 November 2021}}</ref><ref name="CheslerGov15">{{cite web |url=https://weedrush.news21.com/government-restrictions-lack-of-funding-slow-progress-on-medical-marijuana-research/ |title=Government restrictions, lack of funding slow progress on medical marijuana research |author=Chesler, J.; Ard, A. |work=News21: America's Weed Rush |publisher=Carnegie Corporation of New York; John S. and James L. Knight Foundation |date=15 August 2015 |accessdate=18 November 2021}}</ref><ref name="WeissTestimony16">{{cite web |url=https://www.hhs.gov/about/agencies/asl/testimony/2016-09/the-state-of-the-science-on-the-therapeutic-potential-of-marijuana-and-cannabinoids/index.html |archiveurl=https://web.archive.org/web/20170504180135/https://www.hhs.gov/about/agencies/asl/testimony/2016-09/the-state-of-the-science-on-the-therapeutic-potential-of-marijuana-and-cannabinoids/index.html |title=Testimony from Susan R.B. Weiss, Ph.D. on The State of the Science on the Therapeutic Potential of Marijuana and Cannabinoids before Judiciary Committee |author=Weiss, S.R.B. |work=ASL Testimony |publisher=U.S. Department of Health & Human Services |date=13 July 2016 |archivedate=04 May 2017 |accessdate=18 November 2021}}</ref><ref name="JosephDEA16">{{cite web |url=https://www.statnews.com/2016/08/10/marijuana-medical-research-dea/ |title=DEA decision keeps major restrictions in place on marijuana research |author=Joseph, A. |work=STAT |publisher=Boston Globe Media |date=10 August 2016 |accessdate=18 November 2021}}</ref><ref name="RudroffMari17">{{cite web |url=https://www.newsweek.com/marijuana-regulation-blocks-vital-ms-research-544886 |title=Marijuana Regulation Blocks Vital Multiple Sclerosis Research |author=Rudroff, T. |work=Newsweek |publisher=IBT Media, Inc |date=21 January 2017 |accessdate=18 November 2021}}</ref> As such, legally researching and analyzing the chemical constituents of cannabis is a complicated task, with much more work to be done.
In 1970, Temple University Medical School's Marion Ball, M.A., an assistant professor in the Department of Medical Physics, conducted a survey of pathology directors in clinical laboratories that were using computers. Asking their opinions about the advantages and disadvantages of computerized systems in the lab, she received responses from directors in 15 U.S. states, as well as from three other countries. Responses included<ref name="BallASurvey70">{{cite journal |title=A Survey of Field Experience in Clinical Laboratory Computerization |journal=Laboratory Medicine |author=Ball, M.J. |volume=1 |issue=11 |pages=25–27, 49–51 |year=1970 |doi=10.1093/labmed/1.11.25}}</ref>:


Regulation and method standardization woes aside, cannabis is also difficult to analyze due to its matrix, and the task becomes even more difficult when it's added to food and other matrix types, requiring established and consistent methods for testing.<ref name="DePalmaChallenges18">{{cite web |url=https://www.labmanager.com/insights/challenges-of-cannabis-contaminant-testing-1928 |title=Challenges of Cannabis Contaminant Testing |author=DePalma, A. |work=Lab Manager |publisher=LabX Media Group |date=10 September 2018 |accessdate=18 November 2021}}</ref><ref name="CummingsGurus18">{{cite |journal |title=Gurus of Pesticide Residue Analysis [The Cannabis Scientist] |journal=The Analytical Scientist |author=Cummings, J. |publisher=Texere Logo Texere Publishing Ltd |issue=0218 |year=2018 |url=https://theanalyticalscientist.com/fileadmin/tas/pdf-versions/TCS_Issue4.pdf |format=PDF}}</ref> Regulators, patients, and the testing industry are all calling for improved standardization of both the production and testing of medical and recreational cannabis. Without proper testing, several issues are bound to arise<ref name="BushWorlds15" /><ref name="RutschQuality15" /><ref name="HazekampCanna12">{{cite journal |title=Cannabis - from cultivar to chemovar |journal=Drug Testing and Analysis |author=Hazekamp, A.; Fischedick, J.T. |volume=4 |issue=7–8 |pages=660–7 |year=2012 |doi=10.1002/dta.407 |pmid=22362625}}</ref><ref name="KuzdzalACloser17">{{cite web |url=https://www.ssi.shimadzu.com/sites/ssi.shimadzu.com/files/Industry/Literature/Shimadzu_Whitepaper_Emerging_Cannabis_Industry.pdf |format=PDF |title=A Closer Look at Cannabis Testing |author=Kuzdzal, S.; Clifford, R.; Winkler, P.; Bankert, W. |publisher=Shimadzu Corporation |date=December 2017 |accessdate=18 November 2020}}</ref><ref name="CassidayTheHighs16">{{cite web |url=https://www.aocs.org/stay-informed/inform-magazine/featured-articles/the-highs-and-lows-of-cannabis-testing-october-2016 |title=The Highs and Lows of Cannabis Testing |author=Cassiday, L. |work=INFORM |publisher=American Oil Chemists' Society |date=October 2016 |accessdate=18 November 2021}}</ref><ref name="CANORMLHow11">{{cite web |url=https://www.canorml.org/business-resources-for-cannabis-brands/how-accurate-is-cannabis-potency-testing/ |title=How Accurate Is Cannabis Potency Testing? |publisher=California NORML |date=21 September 2011 |accessdate=18 November 2021}}</ref>:
<blockquote>''The ability to rapidly prepare cumulative records and then to inspect them for possible errors through analysis trends has been proven to be of tremendous advantage in a number of laboratories. We can prevent errors in our analytical systems, but we are not prepared to prevent errors in the collecting of the sample, the mislabeling of the sample, or the accidental use of an incorrect sample. Thus, the ability to inspect data trends presents the only real tool that we currently have to pick out these kinds of errors.'' - Max E. Chilcote, Ph.D, Meyer Memorial Hospital Division</blockquote>


* label claims may not match actual contents;
<blockquote>''There is little argument about whether an operating computer system can be an advantage in a laboratory, but the most critical time is the installation and transition from a "manual" to a "computer" oriented laboratory.'' - Robert L. Habig, Duke University Medical Center</blockquote>
* contaminants may linger, causing illness or even death;
* chemical properties and medicinal benefits of specific strains and their unique cannabinoid-terpene profiles can't be isolated; and
* research on potential therapeutic qualities can't be replicated, hindering scientific progress.


Cannabis testing labs are increasingly common in regions and countries where legalization efforts have reached fruition. In particular, the labs analyzing medical cannabis are vitally important for ensuring the best outcomes of patient health. These labs are responsible for analyzing many of the constituents of cannabis, including cannabinoids, terpenes, and contaminates (e.g., pesticides, solvents, heavy metals, mycotoxins, and microorganisms). The test equipment and methods used for these analyses continue to develop and evolve. Testing for cannabinoids may involve [[chromatography]] methods such as [[high-performance liquid chromatography]] with UV detection (HPLC-UV) or [[supercritical fluid chromatography]] (SFC)<ref name="CassidayTheHighs16" /><ref name="APHLGuide16">{{cite web |url=https://www.aphl.org/aboutAPHL/publications/Documents/EH-Guide-State-Med-Cannabis-052016.pdf |format=PDF |title=Guidance for State Medical Cannabis Testing Programs |author=Association of Public Health Laboratories |pages=35 |date=May 2016 |accessdate=18 November 2021}}</ref>, while terpene analysis requires various forms of specialized [[gas chromatography]].<ref name="CassidayTheHighs16" /><ref name="ShimadzuCLTS">{{cite web |url=https://www.ssi.shimadzu.com/products/literature/life_science/shimadzu_cannabis_brochure.pdf |archiveurl=https://web.archive.org/web/20160327180816/https://www.ssi.shimadzu.com/products/literature/life_science/shimadzu_cannabis_brochure.pdf |format=PDF |title=Cannabis Testing Laboratory Solutions |publisher=Shimadzu Corporation |archivedate=27 March 2016 |accessdate=18 November 2021}}</ref> And heavy metal analysis typically involves some sort of [[inductively coupled plasma mass spectrometry]].<ref name="CassidayTheHighs16" /><ref name="APHLGuide16" /><ref name="ShimadzuCLTS" />
<blockquote>''The most pressing future need for computerization of the laboratory lies in the area of medical diagnosis and guidance of the therapeutic management. This is where the physician's role for the future in the laboratory lies ... We will be gathering vast amounts of information on the health status of many individuals. We can then take advantage of large data processing computers to analyze this information and come up with patterns of disease states.'' - Leonard Jarett, M.D., Barnes Hospital</blockquote>
 
Reading about these potentials and opinions today, some 50 years later, we see both clear similarities and definite advances. For example, Habig's statement about transitioning from manual to more automated processes still rings true today: it can be nerve wracking and critical to get the transition right. Conversely, while the systems of decades past weren't able to "prevent errors in the collecting of the sample, the mislabeling of the sample, or the accidental use of an incorrect sample," modern [[laboratory informatics]] systems provide many assurances to sample management in the lab. In many cases, activities such as label generation, reporting, results analysis, [[workflow]] control, test ordering, and broad interoperability are commonplace in modern systems.<ref name="JonesInformatics14">{{cite journal |title=Informatics and the Clinical Laboratory |journal=The Clinical Biochemist Reviews |author=Jones, R.G.; Johnson, O.A.; Batstone, G. |volume=35 |issue=3 |pages=177–92 |year=2014 |pmid=25336763 |pmc=PMC4204239}}</ref> And those systems continue to advance, with [[machine learning]] now finding its way into a few laboratory data management and [[Data analysis|analysis]] workflows.<ref name="BurtonNHS18">{{cite web |url=https://towardsdatascience.com/nhs-laboratories-need-data-science-c93f7983302c |title=NHS Laboratories Need Data Science |author=Burton, R. |work=Towards Data Science |date=19 July 2018 |accessdate=18 November 2021}}</ref><ref name="CuffAugment18">{{cite web |url=https://www.nextplatform.com/2018/06/19/augmenting-pathology-labs-with-big-data-and-machine-learning/ |title=Augmenting Pathology Labs with Big Data and Machine Learning |author=Cuff, J. |work=The Next Platform |date=18 June 2018 |accessdate=18 November 2021}}</ref>
 
We've come a long way since the 1960s, to a point where the question is no longer "can a computerized system help my lab?" but rather "how do I choose and implement an informatics system to help my lab?" What follows is information to help you with that question, while considering the technology, features, security, cost, implementation, and vendor guarantees that come with such a system.


==References==
==References==
{{Reflist|colwidth=30em}}
{{Reflist|colwidth=30em}}

Revision as of 23:32, 21 January 2022

IBM 1130 desk-sized computer from the mid-1960s and '70s

Computers in the laboratory are not a recent phenomenon. The mid-1960s saw clinical laboratory computerization become increasingly popular[1][2][3][4][5], though that enthusiasm was often based on the potential of the computers themselves rather than their actual capabilities.[1] Researchers imagined potentials such as automatic specimen label generation, daily log and report management, instrument interfacing and data processing, results comparisons, and time management tools. It would take time for some of those potentials to be realized.[1]

In 1970, Temple University Medical School's Marion Ball, M.A., an assistant professor in the Department of Medical Physics, conducted a survey of pathology directors in clinical laboratories that were using computers. Asking their opinions about the advantages and disadvantages of computerized systems in the lab, she received responses from directors in 15 U.S. states, as well as from three other countries. Responses included[6]:

The ability to rapidly prepare cumulative records and then to inspect them for possible errors through analysis trends has been proven to be of tremendous advantage in a number of laboratories. We can prevent errors in our analytical systems, but we are not prepared to prevent errors in the collecting of the sample, the mislabeling of the sample, or the accidental use of an incorrect sample. Thus, the ability to inspect data trends presents the only real tool that we currently have to pick out these kinds of errors. - Max E. Chilcote, Ph.D, Meyer Memorial Hospital Division

There is little argument about whether an operating computer system can be an advantage in a laboratory, but the most critical time is the installation and transition from a "manual" to a "computer" oriented laboratory. - Robert L. Habig, Duke University Medical Center

The most pressing future need for computerization of the laboratory lies in the area of medical diagnosis and guidance of the therapeutic management. This is where the physician's role for the future in the laboratory lies ... We will be gathering vast amounts of information on the health status of many individuals. We can then take advantage of large data processing computers to analyze this information and come up with patterns of disease states. - Leonard Jarett, M.D., Barnes Hospital

Reading about these potentials and opinions today, some 50 years later, we see both clear similarities and definite advances. For example, Habig's statement about transitioning from manual to more automated processes still rings true today: it can be nerve wracking and critical to get the transition right. Conversely, while the systems of decades past weren't able to "prevent errors in the collecting of the sample, the mislabeling of the sample, or the accidental use of an incorrect sample," modern laboratory informatics systems provide many assurances to sample management in the lab. In many cases, activities such as label generation, reporting, results analysis, workflow control, test ordering, and broad interoperability are commonplace in modern systems.[7] And those systems continue to advance, with machine learning now finding its way into a few laboratory data management and analysis workflows.[8][9]

We've come a long way since the 1960s, to a point where the question is no longer "can a computerized system help my lab?" but rather "how do I choose and implement an informatics system to help my lab?" What follows is information to help you with that question, while considering the technology, features, security, cost, implementation, and vendor guarantees that come with such a system.

References

  1. 1.0 1.1 1.2 Krieg, A.F. (1974). "Chapter 30: Clinical Laboratory Computerization". In Davidsohn, I.; Henry, J.B.. Clinical Diagnosis by Laboratory Methods. W.B. Saunders Company. pp. 1340–58. ISBN 0721629229. 
  2. Flynn, F.V. (1965). "Computer-assisted processing of bio-chemical test data". In Atkins, H.J.B.. Progress in Medical Computing. Blackwell Science Ltd. p. 46. ISBN 0632001801. 
  3. Williams, G.Z. (1964). "The Use of Data Processing and Automation in Clinical Pathology". Military Medicine 129 (6): 502–9. doi:10.1093/milmed/129.6.502. 
  4. Hicks, G.P.; Gieschen, M.M.; Slack, W.V. et al. (1966). "Routine Use of a Small Digital Computer in the Clinical Laboratory". JAMA 196 (11): 973–78. doi:10.1001/jama.1966.03100240107021. 
  5. Straumfjord, J.V.; Spraberry, M.N.; Biggs, H.G.; Noto, T.A. (1967). "Electronic Data Processing System for Clinical Laboratories: A System Used for All Laboratory Sections". American Journal of Clinical Pathology 47 (5_ts): 661–76. doi:10.1093/ajcp/47.5_ts.661. 
  6. Ball, M.J. (1970). "A Survey of Field Experience in Clinical Laboratory Computerization". Laboratory Medicine 1 (11): 25–27, 49–51. doi:10.1093/labmed/1.11.25. 
  7. Jones, R.G.; Johnson, O.A.; Batstone, G. (2014). "Informatics and the Clinical Laboratory". The Clinical Biochemist Reviews 35 (3): 177–92. PMC PMC4204239. PMID 25336763. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4204239. 
  8. Burton, R. (19 July 2018). "NHS Laboratories Need Data Science". Towards Data Science. https://towardsdatascience.com/nhs-laboratories-need-data-science-c93f7983302c. Retrieved 18 November 2021. 
  9. Cuff, J. (18 June 2018). "Augmenting Pathology Labs with Big Data and Machine Learning". The Next Platform. https://www.nextplatform.com/2018/06/19/augmenting-pathology-labs-with-big-data-and-machine-learning/. Retrieved 18 November 2021.