elements of laboratory technology management

A Publication of the Institute for Laboratory Automation - note: since the ILA suspended operations in 2015, this document can be distributed freely.

Elements of Laboratory Technology Management

© 2014 Institute for Laboratory Automation, Groton, MA, All Rights Reserved

Elements of Laboratory TechnologyManagement

A Unique Approach to Understanding Laboratory Technology Management & Application



© 2014 Institute for Laboratory Automation, Groton MA All Rights Reserved

A Publication of the

http://www.InstituteLabAuto.org

Work Functions in Laboratory Operations

© 2014, Institute for Laboratory Automation, Groton, MA, All Rights Reserved

Topics


1. Introduction ........................................................................................................4

2. Moving from Lab Functions and Requirements to Solutions ........................5

3. What is Laboratory Automation? ....................................................................7 TheILADefinition .......................................................................................7 Why “Process” is Important .........................................................................8

4. The Elements of Laboratory Technology Management .................................10 Management Issues ......................................................................................11 Classes of Lab Automation Implementations ..............................................14 Computer Controlled Experiments ...................................................15 Computer Assisted Lab Work ...........................................................16 ScientificManufacturing-ProductionSystems ...............................16 Experimental Methods .................................................................................17 LabSpecificTechnologies ...........................................................................18 Information Technology ...............................................................................18 Systems Integration ......................................................................................19

5. Skill Requirements for Working with Lab Technologies ...............................27

To the reader,

Most of what is presented in this document will be new material. Many of the topics could cov-er volumes, and may eventually, however rather than prepare a huge tome we opted for some-thing that could be read in one sitting so that the reader could easily absorb the basic structure of what we are doing, think about it, and make use of it, instead of preparing something that if printed could double as a coffee table.

This is a work-in-progress and will likely remain that way for the foreseeable future as systems develop, change and evolve, and the concepts presented here adapt to that reality. Our hope is that it will cause you to think a bit about how you manage laboratory technologies and improve the results you obtain from systems planning and implementation.

Sincerely yours,

Joe Liscouski Executive DirectorInstitute for

LaboratoryAutomationGroton, MA978.732.5122

[email protected] Institute is a 501(c)3non-profitorganization.

Note: the ILA suspended its operations in 2015. If you care to contact the author, you can do via: • telephone: 978-732-5122 • email: [email protected]



Thisdiscussionislessaboutspecifictechnologiesthanitisabouttheabilitytouseadvancedlaboratorytechnologies effectively. “Effectively” means that product and technologies are used successfully to ad-dresses needs in your lab, and that they improve the lab’s ability to function. If it doesn’t do that, you’ve wasted your money. If the technology in question hasn’t been deployed according to a plan your funded projects may not achieve everything they could.

The available technologies should result in the transformation of lab work from a labor intensive effort to one that is intellectually intensive – making the most effective use of people and resources.

People come to the subject of laboratory automation from widely differing perspectives. To some it’s about robotics, to others it’s about laboratory informatics, and others view it as data acquisition and analysis. It all depends on what your interests are, and more importantly what your immediate needs are.

Peoplebeganworkinginthisfieldinthe1940sand1950s,withtheworkfocusedonanalogelectronicstoimproveinstrumentation–thiswasthefirstphaseoflabautomation.Mostnotably,atleastinmyexperi-ence, were the development of scanning spectrophotometers and process chromatographs. People, who firstencounteredthisequipment,didn’tthinkmuchofitandconsideredthistheworldasit’salwaysbeen.Others who had to deal with products like the Spectronic 201(asingle-beammanualspectrophotometer)and used it to develop visible spectra one wavelength measurement at a time, appreciated the automation of scanning instruments.

Mercury switches and timers triggered by cams on a rotating shaft provided chromatograph’s with the abilitytoautomaticallytakesamples,actuatebackflushvalves,andtakecareofotherfunctionswithoutoperator intervention. This left the analyst with the task of measuring peaks, developing calibration curves and performing calculations, at least until data systems became available.

Thedirectionoflaboratoryautomationchangedsignificantlywhencomputerchipsbecameavailable.Inthe1960scompaniessuchasPerkin-Elmerwereexperimentingwiththeuseofcomputersystemsfordataacquisition as precursors to commercial products. The availability of general purpose computers such as thePDP-8andPDP-12series(alongwiththeLab8e)fromDigitalEquipment,withothermodelsavailablefrom other vendors, made it possible for researchers to connect their instruments to computers and carry out experiments. The development of microprocessors from Intel (4004, 8008) led to the evolution of “in-telligent”laboratoryequipmentrangingfromprocessor-controlledstirringhot-platestochromatographicintegrators.

As experimenters learned to use these systems, their application rapidly progressed from data acquisition, to interactive control of the experiments, with data storage, analysis, and reporting. Today the product set available for laboratory applications include data acquisition systems, laboratory information management systems,electroniclaboratorynotebooks,laboratoryrobotics,andspecializedcomponentstohelpresearch-ers, scientists and technicians apply modern technologies to their work.

There is a lot of technology available, the question is: how do you go about using it? As we use it we have toavoidasignificantpotentialproblem:thefamiliaritywithusingcomputersystemsinourdailylivesmaycause us to assume they are doing what we need them to do without questioning how it gets done. “The vendor knows what they are doing” is a poor reason for not testing and evaluating control parameters to make sure they are suitable and appropriate for your work.

1. Introduction

1 The Spectronic 20 was developed by Bausch & Lomb in 1954 and is currently owned and marketed in updated versions by ThermoFisher


Before we can begin to understand the application of the tools and technologies that are available, we have toknowwhatwewanttoaccomplish;specificallywhatproblemswewanttosolve.Wecandividelabora-tory functions into two broad classes: management and work execution.

The following graphics give a breakdown of activities within labs. You can add to them based on your own experience.

Management functions:

2. Moving from Lab Functions and Requirements to Solutions


Work Execution Functions:

Vendors have been developing products to address these work areas, and there are a lot of products avail-able. Many of them are point solutions: products that are focused on one aspect of work without an effort to integrate them with others. That isn’t surprising since there isn’t an architectural basis for integration aside fromspecifichardwaresystems(Firewire,USB)orvendorspecificsoftwaresystems(officeproductsuites).Anotherissueinscientificworkisthatthevendormayonlybeinterestedinaparticularproblemwithmostof the emphasis on an instrument or technique. They may provide the software needed to support their hardware, with data transfer and integration left to the user.

Asyouworkthroughthisdocumentyou’llfindamapofmanagementresponsibilitiesandtechnologies.How do you connect the above map of functions to the technologies? Applying software and hardware solutions to your labs needs requires planning – the days of purchasing point solutions to problems is past, lab managers need to think more broadly about product usage and how components of lab software systems work together. The point of this document is to help you understand what you need to think about.

Given those summaries of lab activities, how do we apply the available technologies to improve lab opera-tions? Most of this work can be placed under the heading of Laboratory Automation, so we’ll begin by looking at what that is.


3. What is Laboratory Automation?

Thisisn’tatrivialquestion,youranswermaydependonthefieldyouareworkingin,yourexperienceandcurrent interests. To some it is robotics, to others it is Laboratory Information Management Systems (or theirclinicalcounterpartLaboratoryInformationSystems-LIS).ElectronicLabNotebooksandinstrumentdata systems are additional elements noted. These are examples of product classes and technologies used in labautomation,buttheydon’tdefinethefield.Wikipedia2providesthefollowingasadefinition:

“Laboratory automation is a multi-disciplinary strategy to research, develop, optimize and capital-ize on technologies in the laboratory that enable new and improved processes. Laboratory automa-tion 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 labora-tory instruments, devices, software algorithms, and methodologies used to enable, expedite and increase the efficiency and effectiveness of scientific research in laboratories.”

2 http://en.wikipedia.org/wiki/Laboratory_automation 3 R.D. McDowall, Anal. Chem., 65 (1993) 896A

McDowall3providesthefollowingdefinition:

“Apparatus, instrumentation, communications or computer applications designed to mechanize or automate the whole or specific portions of the analytical process in order for a laboratory to provide timely and quality information to an organization”

Thosedefinitionsemphasizesequipmentandproducts,andthatiswheretypicalapproachestolabautoma-tion and the work we are doing part company. Products and technologies are important, but what is more importantisfiguringouthowtousethemeffectively.Thelackofconsistentsuccessintheapplicationoflab automation technologies, we believe, stems from this focus on technologies and equipment – “what will thisproductdoformylab?”-ratherthanmethodologiesfordeterminingwhatisneededandhowtoimple-ment solutions.

Havingausefuldefinitioniscrucialsincehowweapproachtheworkdependsonhowweseethefieldde-veloping.ThedefinitiontheInstitutebasesitsworkonisthis:

Lab Automation is the PROCESS of• Determiningneeds&requirements• Planningproject/programs• Evaluatingproductsandtechnologies• Developing&implementingprojects

…according to a SET OF METHODOLOGIESthatRESULTSINSUCCESSFULSYSTEMSthat

• increaseproductivity• improvetheeffectiveness/efficiencyoflaboratoryoperations• reduceoperatingcosts,and• providehigherqualitydata.

The definition this guide is based on:


Thefieldincludestheuseofdataacquisition,analysis,robotics,samplepreparation,laboratoryinformatics,information technology & computer science, a wide range of technologies and products from widely vary-ing disciplines, used in the implementation of projects.

Lab automation isn’t about stuff, but how we use stuff. The “process” consideration is central to what we do. To quote Frank Zenie4 (one of the founders of Zymark) “you don’t automate a thing, you automate a process”.Youdon’tautomateaninstrument,youautomatetheprocessofusingone.Auto-samplersareagood example of successful automation: they address the process of selecting a sample vial, withdrawing fluid,positioninganeedleintoaninjectionport,injectingthesample,preparingthesyringeforthenextinjection, and indexing the sample vials when needed.

A number of people have studied the structure of science and the relationship between disciplines. Lab au-tomation is less about science and more about how the work of science is done. Before lab automation can be considered for a project, the underlying science has to be done; the process that automation is going to be appliedtohastoexistfirst.Italsohastobetherightprocessforconsideration.Thisisapointthatneedsattention.

Ifyouaregoingtospendresourcesonaproject,youhavetomakesureyouhaveawell-characterizedpro-cess and that the process is both optimal and suitable for automation. This means:

• Thattheprocessiswelldocumented,peoplethatusetheprocesshavebeeninterviewedandtheirworkmonitoredtodetermineanyshort-cuts,work-arounds,orothervariationsfromthecurrent documentation. Differences between the published process and the one actually in use canhaveasignificantimpactonthesuccessofaparticularprojectdesign.

• Theprocess’s“readinessforautomation”hasbeendetermined.Theequipmentusedissuitablefor automation or the changes needed to make it suitable are known, and can be done at reason-able cost. Any impact on warranties has been determined and found to be acceptable.

• Ifseveralprocessoptionsexist(e.g.:differenttestprotocolsforthesametestquestion)theyare evaluated for their ability to meet the science needs and their ability to be successfully implemented. Other options, such as outsourcing, should be considered to make the best use of resources;isitmorecost-effectivetooutsourceorautomate?

Lab process work on different levels:

• High-levelprocesseswhichaddressthelabsreasonforexistenceandcoverthemechanicsofhow the lab functions, and,

• Lower-levelprocesseswhichaddressindividualfunctionsinthelab

Thisprocessviewisimportantwhenweconsiderproductsandtechnologies–theproductshavetofittheprocess which is the basis for product requirements. Discussions about Laboratory Information Manage-mentSystems(LIMS)andElectronicLaboratoryNotebooks(ELNs)areoneexample.Thequestionsaboutthese two technologies usually include:

• WhichdoIneed,ordoIneedboth?• DoesanELNreplaceaLIMS?

Why “process” is important

4 Mr. Zenie often introduced robotics courses at Zymark with that statement


…aswellasothers.Thesequestionsreflectbothvendorinfluenceandalackofunderstandingofthetechnologies and their application. Some differentiate the two types of technology based on “structured (LIMS)”vs“unstructured(ELNs)”data.LIMScomewithawell-defined,extensible,databasestructure.ELNsareviewedasunstructuredsinceyoucanputalmostanythingintoanELNandorganizethecontentsasyouseefit.Butthisreallydoesn’tworkeither,since,asauserImightconsiderthecontentsalongwithan index as having a structure. This is more of an information technology approach rather than one that ad-dresses lab needs. An understanding of lab processes is needed to resolve most issues.

LIMSarewell-definedentities5 and the only one of the two to carry an objective, industry standard descrip-tion. LIMS are also designed to manage a process: that of a testing laboratory (analytical, physical, envi-ronmental, clinical – where they are referred to a LIS, etc.) in a wide variety of industries. The lab behav-ior process model is essentially the same across industries and disciplines. Basically, if you are a testing/service lab and need to manage samples, test results, and answer questions about the status of testing on a larger scale than what you can hold in your head6 , a LIMS is a good answer.

ThereisnostandardizeddefinitionofanELN(note:asofthetimethisworkwaswritten,2012,anASTMcommitteeisconsideringaguidetolaboratoryinformaticsthatincludesadefinitionofELNs).GiventhecurrenthypeaboutELNs,anyproductwiththatdesignationisgoingtogetnoticed.Letsavoidthetermandreplace it with a set of descriptions that addresses functionality:

1. Scripted execution systems – those that guide an analyst in the conduct of an procedure (pro-cess), Velquest (now owned by Accelrys) products and the scripting notebook (vendors descrip-tion) function in LabWare LIMS, and others, are examples.

2. Journal / diary systems – those that provide a record of laboratory work, a word processing sys-temmightfillthisneedalthoughthereareproductswithfeaturesspecificallydesignedtoassistlab work.

3.Application/disciplinespecificrecordkeepingsystems–therearethosedesignedforbiology,chemistry, mathematics and other areas that contain features that allow you to record data and textinavarietyofformsthataregearedtowardtheneedsofspecificareasofscience.

Thisisnotanexhaustivelistofformsorfunctionality,butitissufficienttomakeapoint.Thefirst,scriptedexecution,isdesignedaroundaprocess,ormorespecifically,designedtogivetheuseramechanismtodescribe the sequential steps in a process so that they can be repeated under strict controls. These do not replace a LIMS but can be used synergistically with one, or with software that duplicates LIMS capabilities (some have suggested ERP systems – Enterprise Resource Planning – as a substitute).

The other two types are repositories of lab information: equations, data, details of procedures, etc. There is no general underlying process as there is with LIMS. They can provide a researcher with a means of describing experiments, collecting data, doing analysis, etc. which you can correctly view as a process, but itisoneuniquetothatresearcherorlab.Itisn’tonebasedonanygeneralizedindustrymodelasweseeintesting labs.

Why is this important? Because it illustrates something fundamental: process dictates needs, and needs set requirementsforproductsandtechnology.The“doweneedaLIMSorELN”questionismeaninglesswith-out an understanding the processes that operate in your laboratory.

5ASTME1578-06StandardGuideforLaboratoryInformationManagementSystems6 not a recommended methodology


From the standpoint of equipment, laboratories are often a collection of instruments, computer systems, sample preparation stations, and other test/measurement facilities. One goal frequently stated by lab manag-ers is that “ideally we’d like all this integrated”. The purpose of integration is to streamline the operations, reducehumanlabor,andhaveamoreefficientwayofdoingwork.Whatareyouintegrating:theequipmentand systems used to execute one or more processes. Without a thorough evaluation of the processes in the lab, there is no basis for integration.

Thisiswhytheanswerto“WhatisLaboratoryAutomation?”issoimportant.Onedefinitioncanleadtopurchasing products and limiting the scope of automation to individual tasks. Another will take you through an evaluation of how your lab works, how you want it to work, and produce a framework for getting you there.

If lab automation is a process, we need to look at the elements that can be used to make that process work. That is the subject of this section.

Thefirstthingthatisneededisastructurethatbothshowshowelementsoflabautomationrelatetoeachother,andactsasaguideforsomeonecomingintothefield.Thatstructurealsoservesasaframeworkfororganizingknowledgeaboutthefield.Themajorelementsofthestructureareshownbelow.

There is an inevitability to the use of automation technologies in labs. Vendors are putting chips and programmed intelligence into every product with goals of making them easier to use, reducing the role of human judgment (which can lead to an accumulation of errors in tasks like pippetting), and increasing their capabilitywhilereducingtheamountofworkpeoplehavetodotogetthingsdone.Noneofthesearenega-tives, aside from one point: if we don’t understand how these systems are working and haven’t planned for theiruse,wewon’tgetthemostbenefitfromthemandwemaybeacceptingresultsfromsystemsblindlywithout really questioning their suitability and the results they produce. One of the main points of our work isthattheuseofautomationtechnologiesshouldbeplannedandmanaged.Thatbringsustothefirstmajorelement: management issues shown on the next page.

The Role of Processes in Integration

4. The Elements of Laboratory Technology Management


Why is this important?



Thefirstthingweneedtoaddressiswhothe“management”is.Unlessthelabisjustyou,therearelayersofmanagementanddependingonthesizeoftheorganizationwhatI’mgoingtodescribemaycoverseveralpeople or one.

“Senior Management”, aside from reviewing and approving programs (programs are efforts that cover multiple projects) is responsible for setting the policies and practices that govern the conduct of laboratory programs. This is part of an overall architecture for managing lab operations, and has two components as shown below (this will be given a light treatment in this piece, and covered in more detail elsewhere). The idea of senior management setting guidelines for policies and practices may be new to you.

Before the incorporation of informatics into labs, senior management’s involvement wasn’t necessary, howeverthestorageofintellectualpropertyinelectronicmediahasmadeasignificantchangeinlabwork:labsusedtobeisolatedfromtherestoftheorganizationwithformalcontactmadethroughthedeliveryofresults, reports and presentations. The desire for more effective, streamlined, and integrated information technology operations, and the development of information technology support groups, means that the labs arenowpartofthecorporatepicture.Inorganizationsthathavemultiplelabs,moreefficientuseofre-sources results in a desire to reduce duplication of work. You might easily justify two labs having their own spectrophotometers, but duplicate LIMS doing the same thing is going to require some explaining.

ManagementIssues


Some programs succeed and others fail. Among the reasons often cited for failure is the lack of manage-ment involvement and oversight, and usually stated that way without clarifying what that involvement should be. Senior managements role is to make sure that programs are conducted in a way that:

• Arecommonacrossalllabs,sothatallprogramsareconductedaccordingtothesamesetofguidelines,

• Leadtosuccessfulresults,thatarewell-designed,supportable,andcanbeupgraded,

• Areconsistentwithgoodprojectmanagementpractices,

• Thatarewelldocumented,and

• Areconductedinawaythatallowstheresultstobereusedelsewhereinthecompany.

Theitemsthatneedtobeaddressedareshowninthefigureonthefollowingpage,we’renotgoingtocoverthem in any detail here, but will in a future publication.


Lab Managers are responsible for understanding how their lab needs to operate in order to meet the labs goals. Before automation became a factor, lab management’s primary concern was managing people and helping them get their work done. People did the work. In the early stages of lab automation the technolo-giesweretreatedasadd-onsthatassistedpeopleingettingworkdone.Labmanagersneedtomovebeyondthat mindset and look at changing roles for people as automation systems get the work done and people plan for and manage those systems. As a result, lab managers need to take on the role of technology planners in addition to managing people. The implementation of those plans may be carried out by others (Lab Auto-mationEngineers,ITspecialists),butdefiningtheobjectivesandhowthelabwillfunctionwithacombina-tionofpeopleandsystemsissquarelyinthelapoflabmanagementusingworkflowmodelstodefinethetechnologies and products suitable for their work.

When work in lab automation began, it was usually the effort one or two individuals in a lab or company. Today we need a cooperative effort including management, lab staff, IT support, and if available, Lab Au-tomation Engineers. One of the reasons for establishing policies and practices is to enable people to work together, so they are working from the same set of ground rules and expectations. Problems can occur when differentgroupshaveconflictingsetsofpriorities,asinthecaseoflabsandITsupport.

At one point, lab computing only affected the lab systems, but today labs share resources with other groups and IT is faced with making sure that work in one place doesn’t adversely impact another. Most issues around elements such as networks and security can be handled through network design and bridges to iso-late network segments when necessary. More often problems are likely to occur in the choice and mainte-


nanceofproducts,andthepoliciesITsetsuptoprovidecost-effectivesupport.Operatingsystemupgradesare one place issues can occur if those changes cause products used in lab work to break because the vendor is slow in responding to OS changes. Another place that issues can occur is in product selection; IT may wanttominimizethenumberofvendorsithastodealwithandpreferproductsthatusethesamedatabasesystem as is used elsewhere. That policy may adversely limit the products that the lab can choose from. From the labs perspective, they need the best products in order to get their work done, from the IT groups they see it as driving up support costs. The way to avoid these issues, and others, is for senior managers to determinetheprioritiesandkeeptheinter-departmentpoliticsoutofthediscussion.

The Classes of Lab Automation Implementation will be covered next. There are three classes:

• Computer-controlled experiments, including command & control, robotics, etc., for exampe: datacollectioninhigh-energyphysics,LabViewimplementedsystems,instrumentcontrol,androbotics. These are systems where the computer is an integral part of the experiment doing data collection and/or experiment control

• Computer-assisted lab work/experiments (work could be done without a computer, but ma-chines/softwareimprovetheprocess):chromatographydatasystems,ELNsusedfordocumenta-tion, classic LIMS,

• Scientific manufacturing – production systems: High Throughput Screening, lights out lab automation,ProcessAnalyticalTechnologies,andQbD–qualitybydesign-initiatives

Classes of Lab Automation Implementa-tion


This is where the second phase of laboratory automation began: when people began using digital comput-ers with connections to their instrumentation. We moved in stages from simple data acquisition, acquiring a few points to show that we can accurately represent voltages from the equipment, to collecting multiple data streams over time and storing the results on disks. The next step consisted of automatically collecting the data, processing it, storing it, and reporting results from equipment such as chromatographs, spectrophotom-eters, and other devices.

Softwaredevelopmentmovedfromassemblylanguageprogramming,tohigher-levellanguages,tospecial-izedsystemsthatprovideagraphicalinterfacetotheprogrammer.ProductslikeLabVIEW7 allow the de-veloper to use block diagrams to describe the programming and processing that had to be done, and provide theuserwithanattractiveuser-interfacewithwhichtowork.Thisisafarcryfromembeddingmachinelanguage programming in the BASIC language code as was done in some earlier PC systems.

Robots are another example of this class of work, where computers control the movement of equipment and materials through a process that prepare samples for analysis, and may include the analysis itself.

While commercial products have overtaken much of the work of interfacing / data acquisition / processing andinsomecasestheinstruments-computercombinationarealmostindistinguishablefromtheinstrumentsthemselves , the ability to deal with instrument interfacing and programming is still an essential skill set for those working in research and applications where commercial systems have yet to be developed.

It’s interesting that people often look at modern laboratory instrumentation and say that everything has gone digital. That’s far from the case. They may point to a single pan balance or thermometer with the digitalreadoutasexamplesofa“digital”instrument,notrealizingthatthepackagingcontainssensors,A/Dconverters, and computer control systems to manage the device and its communications. The appearance ofa“digital”devicemaskswhatisgoingoninside-westillneedtounderstandthetransitionfromthereal,analog, world into digital data.

There is a difference between work that can be done by computer and work that has to be done by comput-er; we just looked at the latter case. There’s a lot of work that goes on in laboratories that could be done, that in fact was done, by people that in today’s labs we prefer to do by automated systems.

The management of samples in a testing laboratory used to be done by people logging samples in and keep-ing record books of work that has been done and has to be done. That work today is covered by a LIMS (or


Computer Controlled Experiments

7LabViewisaproductofNationalInstruments(www.ni.com),similarproductsareavailablefromotherven-dors

Computer-assisted lab work /experiments


LIS in the clinical world). The analysis of instrumental data used to be done by hand and is now more com-monly done by instrument data systems that are faster, more accurate, and permit more complex analysis at lower-cost.

Youmightconsiderthatrobotsfitinthiscategory.Thattheyaresimplydoingworkthatcouldbedonemanually, and in fact had been. The reason I don’t consider robots here is that in many cases the equipment used for the robots is different than the equipment that’s used by human beings. So the two really aren’t in-terchangeable. If the LIMS or instrument data system were down, people could pick up the work; that may notbethecaseifarobotwereoff-line.It’sasmallpointandyoucangoeitherwayonthis.

The key element is that the use of computers, and if you prefer robotics, is an option and not a requirement; an option that improves productivity, reduces cost, and provides better quality and more consistent data.

This isn’t so much a new category as it is a formal recognition that much of what goes on in laboratory work mirrors work that’s done in manufacturing, the major difference is that lab works products are data, information and knowledge; some work in quality control is so routine that it matches assembly line work of the 1960s. The work in this category is going to expand as a natural consequence of increasing automa-tion; it’s a fact of life and something we need to address. If this is the direction things are going to go, then we need to do it right.

Recognizingthispointhassignificantconsequences.Ratherthanjustlettingthingsevolvewecantakeadvantage of the situation and drive situations that are appropriate for this level of automation into useful practice. This means

• convertinglaboratorymethodstofullyautomatedsystems

• deliberatelydesigningequipmentandcontrol/acquisition/processingsystemstomeettheneedsof this kind of application

• trainingpeopletoworkamorecomplexenvironmentthantheyhadbeen

• buildingtheautomationinfrastructure(interfacinganddatastandards)thatisneededtomakethesesystemsrealizableandeffectivewithouttakingonsignificantcost.

In short it means opening up another dimension to laboratory work, a natural evolution of work practices. If you look in the direction things are going where large sample volume processing is necessary, for example highthroughputscreening,itissimplyareflectionofreality.

If we look at quality control applications and manufacturing processes we basically see one production process (QC) layered on another (production), where ultimately the two merge into continuous production and testing. This is a logical conclusion to work described by process analytical technologies and quality by design.

This doesn’t diminish the science used in laboratory work, but adds a level of sophistication that hasn’t been widely dealt with: thinking beyond the basic science process to its implementation in a continuous automat-ed system. This is a much more complex undertaking since data will be created at a high rate and we want to be sure that this is high quality data and not just the production of junk at a high rate.

Scientific manufacturing – production systems


This type of thinking is not limited to quality control work. It can be readily applied to research as well, whereeconomicalhigh-volumeexperimentscanbeusedtosupportstatisticalexperimentaldesignmethod-ologies, more exhaustive sample processing, as well as today’s screening applications in life sciences. It is also readily applied to environmental monitoring and regulatory evaluations.

Whilethiskindofthinkingmaybenewtoscientificapplicationsitisn’tnewtechnology.Workthathasbeendone in automated manufacturing can serve as a template for the work that has to be done in laboratory process automation.

I’dliketotakeamomentandlookatthefirsttwobulletsinthissegment.Ifyougavefourlabsamethoddescription and asked them to automate it, you’d get varied implementations of four groups doing the same thing independently. If we are going to turn lab automation into the useful tool it can be, we need to take a different approach: cooperative development of automated systems.

In order to be useful, a description of a fully automated system needs more that a method description. It needsequipmentlists,sourcecode,etc.insufficientdetailthatyoucanpurchasetheequipmentneededandput the system together expecting it work. In reality we can do better than that. In a given industry, where labs are doing the same testing on the same types of samples, we should be able to have them come together and designate and test automated systems to meet the need. Once that is done, vendors can pick up the description and be able to build products suitable to carry out the analysis or test. The problem labs face is getting the work done at reasonable cost. If there isn’t a competitive advantage to having a unique test, cooperatesothatstandardizedmodulesfortestingcanbedeveloped.

Thischangeslabautomationfrombuild-it-from-scratchmentalitytotheconnectionofstandardizedauto-mated components into a functioning system.

There is relatively little that can be said about Experimental Methods at this point. Aside from the clinical industry, not enough work has been done to give really good examples of systems that have been designed as automated systems that can be purchased, installed in a lab and expected to function8. There are some examplesincludingELIZAroboticsanalysissystemsfromCaliperLifeSciencesandPressurizedLiquidExtraction Systems from Fluid Management Systems. Most laboratory methods are designed with the as-sumption that people will be doing the work.

Experimental Methods


8 Having a data system connected to, or in control of a technique is not the same as full automation. For example there are automated Karl Fisher systems (water analysis), but they only address the titration and not the sample preparation. A vendor can only take things so far in commercial products unless labs describe a larger role for auto-mation-onethatwillvarybyapplication-andthatisthepoint,weneedthedescriptionofthatlargercontext.


What we need to begin doing is looking at the development of automated methods as a distinct task simi-lartothepublishedmanualmethodsbyASTM,USP,EPA,etc.withthedifferencethatautomationisnotviewed as mimicking human actions (develop a robotics system for example that mimics the actions of a person)butassystemsthatsupportthesciencebutareawell-designedandoptimizedproductionprocesses;ascientificmanufacturingimplementationthatincludesthematingtoinformaticssystems.Weneedtothink“bigger”,notlimitingourvisiontojusttheimmediatetaskbutlookingathowitfitsintolab-wideoperations.

Thenexttwosections,LabSpecificTechnologiesandInformationTechnology,areforthepurposesofthisnote, easily understood and well covered elsewhere. There is one point that needs to be made with respect to information technologies: while lab managers do not need to understand the implementation details of the technologies they do need to be aware of the potential they offer in the development of a structure for lab automation implementations. Management is responsible for lab automation planning and that includes choosing the best technologies; managers have to manage the “big picture” of how technologies are used to meet their labs purpose.

Inparticular,theroleofclient-serversystemsandvirtualization,sincetheyofferdesignalternativesthatim-pact the choice of products and the options for managing technology. This is one area where good relation-ships with IT departments are essential. We’ll be addressing the information technologies in more detail in other publications.

Lab Specific Technologies and Information Technology


For more information about lab specific technologies, please see: “Computerized Systems in the Modern Laboratory: A Practical Guide” -- http://tinyurl.com/n9atcht



Systems Integration is another area that has been dealt with at length in other areas (John Triggs: theinte-gratedlab.com,and,LabManagerMagazine“IntegratingSystems”9 ). Many of the points noted above, particularly in the management sections, demand attention to integration to develop systems that work well. When systems are planned, they need to be done with an eye toward integrating the components, something that today’s technologies are not up to as yet, aside from those built around microplates and clinical chemis-tryapplications.Thisisn’tgoingtohappenmagicallynorisittheprovinceofvendorstodefineit.Thisisarealmthattheusercommunityhastoaddressbydefiningthestandardsandthepolicybasisforintegration.The planning that managers have to do as part of technology management has to be done with an under-standingoftheroleintegrationplaysandspecifysolutionsthatleadtowell-designedintegratedsystems.TheconceptsbehindScientificManufacturingdependonit,justasintegrationisrequiredinanyefficientproduction process.

Systems Integration

9“IntegratingSystems”,J.Liscouski,LabManagerMagazine,Jan/Feb2012,Vol7,No.1,pgs26-29



The purpose of integration in the lab is to make it easier to connect systems; for example, pass results from a chromatography data system to a Laboratory Information Management System (LIMS) or Electronic LaboratoryNotebook(ELN)andthenontoothergroups.Theresultsofthisabilitytointegratesystemsinclude:

• Smootherworkflow–lessmanualeffort,avoidingduplicationofdataentry,thisissomethingthat people are striving for and accomplishing in production environments including manufac-turing, video production and graphics design,

• Easier path for meeting regulatory requirements – integrated systems, with integration built in by vendors, results in systems that are easier to validate and maintain,

• Reduced cost of development and support,• Reduction in duplication of records, better data management,• Moreflexibility–aswe’lldiscussbelow,integratedsystemsbuiltonmodularcomponentswill

make it easier to upgrade/update systems, and meet changing requirements.

The inability to integrate systems and components through vendor provided mechanisms results in higher development and support costs, increased regulatory burden, and reduced likelihood that projects will be successful.

Phrases like “integrated system” are used so commonly that it seems as though there should be and instant recognition of what they are. The words may bring a concept to mind, but do we have the same concept in mind? For the sake of this discussion that concept has the following characteristics:

• A given piece of information is entered once, and then is available throughout the system, restricted only by access privileges. The word “system” is the summation of all the information handling equipment in the lab. It may extend beyond the lab if process connections to other departments are needed.

• The movement of materials (sample prep for example) and data / information is continuous from the start of a process through to the end of that process without the need for human effort. The sequence doesn’t have to wait for someone to do a manual portion of the process in order for it to continue, aside from policy conditions that require checks, reviews, and approvals before subsequent steps are taken.

An integrated system should result in a better place for people to work. People wouldn’t be used as a means of achieving repetitive work. Doing so results in two problems: people get bored and make mistakes (some minor, some not, both of which contribute to variability in results), and, the progress of work (pro-ductivity) is dependant on human effort which may limit the number of hours that a process can operate. It is also a bad way of using intelligent, educated personnel.

Forthosewhoarenewtothefield,we’vebeenatthisforalongtime,withnotasmuchtoshowforitaswe’dexpect,particularlywhencomparedtootherfieldsthathaveseenaninfusionofcomputertech-nologies. During the 1980’s the pages of Analytical Chemistry saw the initial ideas that would shape the development of automation in chemistry. Dr. Ray Dessy’s (then at Virginia Polytechnical Institute) articles on LIMS, robotics, networking, and instrument data systems, laid out the promise and expectation for elec-tronicsystemsusedtoacquireandmanagetheflowofdataandinformationthroughoutthelab.

The purpose of integration in the lab is to make it easier to connect systems.

A Brief Historical Note

What is an Integrated System in the laboratory?


Thatconcept-thecomputerintegratedlab-wasthebasisofworkbyinstrumentandcomputervendors,resultinginproof-of-conceptdisplaysandexhibitsatPITTCONandothertradeshows.After30+yearswearestillwaitingforthatpotentialtoberealized,andwemaynotbemuchclosertodaythanwewerethen.Whatwehaveseenisanincreaseinthesophisticationofthetoolsavailableforlabwork,client-serverchro-matography systems, electronic lab notebooks – in their varied forms, are just two. In each case we keep running into the same problem, the ability to connect things into working systems. The result is the use of productspecificcode,work-aroundstomovingandparsingdatastreams.Thesearefixes,notsolutions.Solutionsrequirecarefuldesignnotjustfortheshort-term-what-do-we-need-todaybutlongtermrobustdesigns that permit graceful upgrades and improvements without the need to start over from scratch.

Every day the scientists and technicians in your labs are working to produce the knowledge, information, and data [ K / I / D ] your company depends upon to meet its goals.

That K / I / D is recorded in notebooks and electronic systems. How well are those systems going to sup-portyourneedforaccesstoday,tomorrow,oroverthenext20+years?Thisistheminimummostcompa-nies require for guaranteed access to data.

The systems being put in place to manage laboratory K / I / D are complex. Most lab data management sys-tems(LaboratoryInformationManagementSystems-LIMS,ElectronicLabNotebooks-ELNs,andsomeinstrument data systems) are a combination of four separate products: hardware, operating system, database management system, and the application you and your staff uses. Each from a different company, each with its own product life cycle. Which means that changes can occur at any of those levels, asynchronously, without consideration for the impact they have on your ability to work.

Lab managers are usually trained in the sciences and personnel aspects of laboratory management. They are rarely trained in technology management and planning for laboratory robotics and informatics – the tools used today to get laboratory work done and manage the results. The consequences of inadequate planning canbesignificant:

“In January 2006, the FBI ended the LIMS project, and in March 2006 the FBI and [the vendor] agreed to terminate the contract for the convenience of the government. The FBI agreed to pay a settlement of $523,932 to the company in addition to the money already spent on developing the system and obtaining hardware. Therefore, the FBI spent a total of $1,380,151 on the project. With only the hardware usable, the FBI lost $1,175,015 on the unsuccessful LIMS project.” OIG Audit Report 06-33

Other examples of problems in projects:

• A “2006 ALA Survey on Industrial Laboratory Automation” published in the August 2007 edi-tion of the Journal of the Association for Laboratory Automation posed the following question: MyCompany/Organization’sSeniorManagementFeelsitsInvestmentinLaboratoryAutoma-tionHas:Succeededindeliveringtheexpectedbenefits(56%),producedmixedresults(43%),hasnotdeliveredtheexpectedbenefits(1%).44% failed to fully realize expectations.

• “Asthestatisticsshowthat60%ofallLIMSprojectshavefailedtohavea100%success-fulgo-live..”andthisisreportedin: http://www.scientific-computing.com/features/feature.php?feature_id=132.

• The Standish Report (1995) on project failures (looking at Enterprise Resource Planning [ERP] implementations–similarinscopetoLIMS&ElectronicLabNotebooks)showsthatoverhalfwillfail,31.1%ofprojectswillbecanceledbeforetheyevergetcompleted.Furtherresultsindicate52.7%ofprojectswillcostover189%oftheiroriginalestimates.

The Cost of the Lack of Progress


We’ve received a number of emails discussing the results of improperly managing projects, all have re-questedthatanyidentificationbekeptconfidential.Amongthemare:

• ALIMScustomerwasgivenaprecisefixed-pricequotesomewherearound$90,000andthengothitwithseveral$100,000inextrasafterthecontractwassigned–contributedanonymously.

• AmajorpharmacompanysomeyearsbackthatimplementedaLIMSwithalotofcustomiza-tion that was generally considered to be successful, until it came time to upgrade. They couldn’t doit,andwentbacktosquareoneandpurchasedanothersystem--contributedanonymously.

• Reportsofroboticssystemfailurestotalingover$700,000.• Exampleswherevendorsareusingcustomersitesastest-bedsforsoftwaredevelopment.• A set of 3 labs that were trying to use the same system [to reduce cost] for different types of labs withdifferentrequirements-$500,000spentbeforetheprojectwascancelled.

In addition to those costs, there are the costs of missed opportunities, project delays, departmental & em-ployee frustration, and the fact that the problems you wanted to solve are still sitting there.

The causes for failures are varied, but most include factors that could have been avoided by making sure those involved were properly trained:

• poor planning, unrealistic goals (in part because the features needed to make systems work together aren’t there)

• inadequatespecifications,includingregulatorycompliancerequirements• project management problems• scope creep• lack of experienced resources

The lack of features that permit the easy development of integrated systems can also be added to that list. That missing element causes projects to balloon in scope, requiring people to take on work that they may notbeproperlypreparedfor,orprojectsthatarenottechnicallyfeasible,somethingdevelopersdon’trealizeuntil they are deeply involved in the work.

The method people use to achieve integration today results in cost overruns, project failures and systems thatcan’tbeupgradedormodifiedwithoutsignificantriskofdamagingtheintegrityoftheexistingsystem.One individual reported that his company’s survey of customers found that systems were integrated in ways thatpreventedupgradesorupdates;thecodingwasspecifictoaparticularversionofsoftware,andanychanges could result in scraping the current system and starting over.

Onewayofachieving“integration”issimilartointegratinghouseholdwiringbyhard-wiringallthelamps,appliances, TV’s, etc. to the electrical cables. Everything is integrated, but change isn’t possible without shutting off the power to everything, going to the wall and making the wiring changes, and then repairing the walls and turning things back on. When we think of integrating systems, that’s not the model we’re con-sidering – but from the comments we’ve received, it is the way people are implementing software. We’re looking for the ability to connect things in ways that permit change, like the wiring in most households – plugandun-plug.

That level of compatibility and integration results from the development of standards for power distribution andforconnections:thedesignofplugsandsocketsforspecificvoltages,phasing,andpolaritysothattheright type of power is supplied to the right devices.


There are other examples of the ability to connect systems:

• UniversalSerialBus(USB)–thesameconnectorcanbeusedtoconnectacomputertostorage,a camera, scanner, printer, communications, etc.

• Modular telephone jacks and tone dialing allow for the telephone systems we have today – we couldn’thavethelevelofsophisticationwehavenowifwereliedonrotarydialsandhard-wired phones.

These are just a few examples of component connections that can lead to systems integration. When we consider integrating systems in the lab, we need to look at connectivity and modularity (allowing us to make changes without tearing the entire system apart) as goals.

The lab systems we have today are not built for integration system wide. They are built by vendors and developers to accomplish a set of tasks, connections to other systems is either not considered, or avoided for competitive reasons. If we want to consider the possibility of building integrated systems there are at least fiveelementsthatareneeded:

1. Education2.UserCommunityCommitment3.Standards–fileformatandmessaging/interconnect4. Modular Components5. Stable Operating System Environment

Facilities with integrated systems are built by people trained to do it. This has been discussed within the concepts of Laboratory Automation Engineering published in the Journal of the Association for Laboratory Automation10.

The educational issues don’t stop there. Laboratory management need to understand their role in technolo-gy management. It isn’t enough to understand the science and how to manage people as was the case thirty or forty years ago. Managers have to understand how the work gets done and the technology used to do it. Theeffectiveuse/miss-useoftechnologiescanhaveasbiganimpactonproductivityasanythingelse.Thescience also has to be adjusted for advanced lab technologies. Method development should be done with an eye toward method execution – can this technique be automated?

Vendors and developers aren’t going to provide the facilities needed for integration unless the user com-munity demands them. Suppliers are going to have to spend resources in order to meet the demands for integration and they aren’t going to do this unless there is a clear market need and users force them to meet thatneed.Ifwecontinuewith“businessasusual”practicesofforcefittingthingstogetherandnotbeingsatisfiedwiththeresult,whereistheincentiveforvendorstospenddevelopmentmoney?Thechoicescome down to these: you only purchase products that meet your needs for integration, you spend resources trying to integrate systems that aren’t designed for it, or, your labs continue to operate as they have for the last 30 years – with incremental improvements.

Buildingsystemsthatcanbeintegrateddependupontwoelementsinparticular:standardizedfileformatsand messaging/interconnect systems that permit one vendor’s software package to communicate with an-other’s.

What do we need to build integrat-ed systems?

1. Education

10 “Are you a Laboratory Automation Engineer”, J. Liscouski, JALA 2006;11:157–162, also available in an ex-pandedversionathttp://www.institutelabauto.org/downloads/RULAEdnld.htm

2. User Community Commitment

3. Standards


File Format Standards

Buildingsystemsthatcanbeintegrateddependupontwoelementsinparticular:standardizedfileformatsand messaging/interconnect systems that permit one vendor’s software package to communicate with an-other’s.

Theoutputofaninstrumentshouldbepackagedinanindustrystandardizedfileformatthatallowsittobeusedwithanyappropriateapplication.Thestructureofthatfileformatshouldbepublishedandincludethe instrument output plus other relevant information such as date, time, instrument ID, sample ID read via barcode or other mechanism, instrument parameters, etc. Digital cameras have a similar set up for their raw datafiles:thepixeldataandthecamerametadatathattellsyoueverythingaboutthecamerausedtotaketheshot.

In the 1990’s the Analytical Instrument Association (now the Analytical and Life Science Systems Associa-tion) had a program underway to develop a set of standards for chromatography and mass spectrometry. The program made progress and was turned over to the ASTM where it is currently stalled. It was a good firstattempt.Therewereseveralproblemswithitthatbearnoting.Thefirst point is found in the name of the standard – Analytical Data Interchange Standard. It was viewed as a means of transferring data betweeninstrumentsystems,andservedasasecondaryfileformat,withtheinstrumentvendorsbeingtheprimary format. This has regulatory implications since the FDA requires storage of the primary data and thattheprimarydataisusedtosupportsubmissions.Italsomeansthatfileshavetobeconvertedbetweenformats as it moves between systems.

Ideally, the standard format would be THE format for an instrumental technique. Data collected from an instrument would be in that format and be implemented and used by each vendor. In fact, it would be feasible to have a circuit board in an instrument that would function as a network node. It would collect andstoreinstrumentdataandforwardittoanothercomputerforlong-termstorage,analysisandreporting,thus separating data collection and use. A similar situation currently exists with instrument vendors that use networked data collection modules. The issue is further complicated by the nature of analytical work. A datafileismeaninglesswithoutit’sassociatedreferencematerial:standards,calibrationfiles,etc.,thatareusedtodevelopcalibrationcurvesandevaluatequalitativeandquantitativeresults.Whilefileformatstan-dardsareessential,soisasecond-orderdescription:samplesetdescriptor’sthatprovidesacontextforeachsample’sdatafile–asamplesetmightbeasampletrayinanautosampler,thedescriptorwouldbealistofthe tray’s contents (standards, sample ID, etc.). Work is underway for the development another standard forlaboratorydata:ASTMWK23265-NewSpecificationforAnalyticalInformationMarkupLanguage(http://www.astm.org/DATABASE.CART/WORKITEMS/WK23265.htm ); it’s description indicates that it doestakethecontextofthesample-it’srelationshiptoothersamplesinarunortray-intoaccountaspartof the standard description.

The second issue with the AIA’s program was that it was vendor driven with little user participation. The transfer to the ASTM should have resolved this but by that point user interest waned. People had to buy systems and they couldn’t wait for standards to be developed and implemented. The transition from propri-etaryfileformatstostandardizedformatshastobeaddressedinanystandardsprogram. The third issue is standards testing. Before you ask a customer to commit their work to a vendor’s imple-mentationofastandard,theyshouldhavetheassurance,throughanindependentthird-party,thatthingswork as expected.


4. Modular Systems

Theparagraphabovenotesthatvendorshavetoassumethattheirsoftwaremayberunninginastand-aloneenvironment in order to ensure that all of the needed facilities are available to meet the users needs. This canleadtoduplicationoffunctions.Amulti-userinstrumentdatasystemandaLIMSbothhaveaneedfor sample login. If both systems exist in the lab, you’ll have two sample login systems. The issue can be compoundedbeyondthatwiththeadditionofmoremulti-instrumentpackages.

Whynotbreakdownthefunctionalityinalabanduseonesampleloginmodule?Itissimplyamulti-userdatabase system. If we were to do a functional analysis of the elements needed in a lab with an eye toward eliminating redundancy and duplication, designing components as modules, integration would be a simpler issue.

A modular approach – login module, lab management module, modules for data acquisition, chromato-graphic analysis, spectra analysis, etc. – would provide a more streamlined design, with the ability to upgrade functionality as needed. For example, a new approach to chromatographic peak detection, peak deconvolution, could be integrated into an analysis method without having to reconstruct the entire data system.

When people talk about modular applications, the phrase “LEGO® like” implementation comes up. It is a good illustration of what we’d like to accomplish. The easily connectable blocks and components can be structured in a wide variety of items. All based on a simple standardized connection concept. There are two differences that we need to understand. In LEGOs almost everything connects.. in the lab connections needtomakesense.SecondlyLEGOsisasingle-vendorsolution;unlessyou’reTHEvendorthatisn’tagoodmodel.ALEGOs-likemult-sourcemodel(includingopensource)ofwell-structured,well-designedandsupportedmodulesthatcouldbeconnected/configuredbytheuserwouldbeaninterestingapproachtothe development of integratable systems.

Modularitywouldalsobeofbenefitwhenupgrade/updatingsystems.Withmorefunctionsdistributedover several modules, the amount of testing & validation needed would be reduced. It should also be easier to add functionality. This isn’t some fantasy, this is what systems engineering – Laboratory Automation Engineering–iswhenyoulookattheentirelabenvironmentratherthanimplementingproductstask-by-task in isolation.

The foundation of an integrated system must be a stable operating environment. Operating system upgrades that require changes in applications coding are disruptive and lead to a loss of performance and integrity. It maybenecessarytoforgothebells-and-whistlesofsomecommercialoperatingsystemsinfavorofopensourcesoftwarethatprovidesrequiredstability.Upgradesshouldbeimprovementsinqualityandfunction-alitywherethatchangeinfunctionalityhasaclearbenefittotheuser.

The items noted above are just introductory comments, each could be a healthy document by itself. At somepointthesestepsaregoingtohavetobetaken.Untiltheyare,andtheyresultintoolsyoucanuse,labs – your labs – are going to be committing the results of your work into products and formats you have littlecontrolover.Thatshouldnotbeanacceptablesituation;theuseofproprietaryfileformatsthatlimityour ability to work with your company’s data should end and be replaced with industry standard formats thatgiveyoutheflexibilitytoworkasyouchoose,withwhateverproductsyouneed.

Weneedtobeverydeliberateinhowweapproachthisproblem.Inthefileformatstandardsdiscussionforexample,itwasnotedthatthedatafileforasinglesampleisuselessbyitself.Ifyouhadthefileforachromatogram for instance, you could display it, look at the conditions used to collect it, but interpretation

5. Stable Operating System Environment


requiresdatafromotherfiles,sostandardsforfilesetshavetobedeveloped.Thatwasn’taconsiderationinthe original AIA work on chromatography and mass spec (though it was in work done on Atomic Absorp-tion,EmissionandMassSpectroscopyDataInterchangeSpecificationstandardsfortheArmyCorpsofEngineers, 1995).

ThefirststepinthisprocessisforlabmanagersandITprofessionalstobecomeeducatedinlaboratoryautomation and what it takes to get the job done. The role of management can’t be understated, they have to sign off on the direction work takes and support it for the long haul. The education needs to focus on the management and implementation of automation technologies, not just the underlying science; it is the exclusive focus on the science that leads to the smokestack / silo implementations we have today. The user communities active participation in the process is central to success, and unless that group is educated in the work, the effect of that participation will be limited.

Secondly,weneedtorenewthedevelopmentofindustrystandardfileformats,notjustfromthestand-pointofencapsulatingdatafiles,butformatsthatensurethatthedataisusable.Theinitialfocusforeachtechnique needs to be a review of how laboratory data is used, particularly with the advent of hyphenated techniques,andusethatreviewasabasisfordefiningthelayersofstandardsneededtodevelopauseableproduct. This is a complex undertaking, but worth the effort. If you’re not sure, consider how much your lab’s data is worth and the impact of its loss.

In the short term we need to start pushing vendors – you have the buying power – to develop products with the characteristics needed to allow you to work with and control the results of your lab’s work. Products need to be developed to meet your needs, not the vendors/developers. Product criteria needs to be set with thepointsaboveinmind,notonacompany-by-companybasisbutasacommunity;you’remorelikelytoget results with a community effort.

Overcoming the barriers to the integration of laboratory systems is going to take a change in mindset on the partoflabmanagementandthoseworkinginthelabs.Thatchangewillresultinasignificantchangeinthe way labs work, yielding higher productivity, a better working environment, with an improvement in the return on your company’s investment in your labs operations. Laboratory systems need to be designed to be effective. The points noted here are one basis for that design.

That is a brief tour of what the Elements of Laboratory Technology Management looks like right now. The diagram will change and details will be left to additional layers to keep the structure easy to understand and use.Onethingthatwassacrificedinordertofacilitateclarityistherelationshipbetweentechnologies.Forexample a robotics system might use data acquisition and control components in its operations, which could be noted by a link between those elements.

There is room for added complexity to the map. Someone may ask where “bioinformatics” or some other subjectresides.Thataswellasotherpoints-andthereareanumberofthem-wouldbeaddressedinsuc-cessivelevels,givingtheviewertheabilitytodrill-downtowhateverlevelofdetailtheyneed.Thebestway to view this is an electronic map that can be explored by clicking on subjects for added information and relationships.

The entire diagram is available as a jpeg available through http://www.institutelabauto.org/publications/pubs.htm.

ELTM map summary and added levels


5. Skill Requirements for Working with Lab Technologies

While this subject belongs in the management section above, we needed to wait until the major elements were described before taking up this critical point. In particular, we had to address the idea behind “Scien-tificManufacturing”.

LabAutomationhasanidentityproblem.Manypeopledon’trecognizeitasafield.Itappearstobeacol-lection of products and technologies that people can use as needed. Emphasis has shifted from one technol-ogy to another depending on what is new, hot, interesting, with conferences and papers, until something else comes along. Robotics, LIMS, neural networks, etc., have all had their periods of intense activity; now [2012] the spotlight is on electronic lab notebooks, integration and paperless labs.

Labautomationneedstobeaddressedasamulti-disciplinaryfield,workinginallscientificdisciplines,and including those working in labs, consultants, developers, and those in Information Technology support groups. That means addressing three broad groups of people:

Groups that need to beaddressed by an

e�ective program

Scientists &Technicians(end-users)

Laboratory AutomationEngineers

(designing/implementingend-user systems)

Product / SystemDevelopers

StudentsEmployed or

SeekingEmployment

Working for an end-userorganization, planning

programs/projects speci�c tothat organizations needs

Working for a vendororganization, planningprograms/projects ascommercial products

We’llbeginbyaddressingtheend-users,thelabstaffworkingwiththesystemsonadailybasis.

Discussions concerning lab automation and the use of advanced technologies in lab work are usually done fromthestandpointofthetechnologiesthemselves:whattheyare,whattheydo,benefits,etc.Missingfromthese conversations is an appreciation of the ability of those working in the lab to use these tools, and how they will change the nature of laboratory work.

The application of analog electronic systems to laboratory work began in the early part of the 20th century. For the most part, they made it easier for a scientist to make measurements. Recording spectrophotometers replacedwavelength-by-wavelengthmanualmeasurements,processchromatographsautomatedsampletaking,back-flushvalves,attenuationchanges,etc.Theymadeiteasiertocollectmeasurementsbutdidnotchange the analysts job of data analysis – analysts still had to look at each curve or chromatogram, make judgments, and apply their skills to making sense of the experiment. At this point, scientists were in charge of executing the science, analog electronics made the science easier to deal with.


Whenprocessor-basedsystemswereaddedtothelab’stoolset,thingsmovedinadifferentdirection.Thecomputersdidthedataacquisition,displayandanalysis.Now,partofthesciencewasperformedbya program, the analyst could adjust the behavior of the program by setting numerical parameters. This represents a major departure in the nature of laboratory work – from scientist being completely responsible fortheexecutionoflabprocedures,toallowingacomputer-basedsystemtotakeovercontrolofalloraportion of the work.

For many labs, the use of increasingly sophisticated technologies is just a better way of individuals doing tasks better, faster and with less cost. In others, the technology takes over a task and frees the analyst to do other things. We’ve been in a slow transition from people driving work to technology driving work. As the use of lab technologies moves further into automation, the practice of laboratory work is going to changesubstantiallyuntilwegettothepointwherescientificmanufacturing/productionisthedominantfunction:automationappliedfromsampleacceptancetothefinaltest/experimentalresult.

We can get a sense of how work will change by looking at the development of manufacturing systems, where we see a transition from manual methods to fully automated production driven by the same issues as labs face: high productivity, lower costs, improved and consistent product quality. The major differ-ence is that in labs, the “product” isn’t a widget, it is data and information. In product manufacturing we also see a reduction in manpower as a goal; in labs it is a shift from manual effort to people spending their effortstounderstanddataandimprovingthescience.Onesignificantbenefitfromashifttoautomationisthatlabstaffwillbeabletore-designlabprocesses–thesciencebehindlabwork–tofunctionbetterinanautomated environment; most of the processes and equipment in place today assume manual labor and are not well designed for automated control.

We’regoingtolookasetofmanufacturingstagesfromthestandpointoffivecriteria:relativeproductioncost,productivity,skillsrequired,productquality,andflexibility.Theprocessunderconsiderationiswood shaping, making moldings for example. The trim you see on wood windows and the framing on cabinet doors are all example of shaping wood as shown below – the illustrations are found in manufactures catalogs.

Development of Manufacturing / Production Stages

Components of Cabinet Door Frames

Christopher Schwarz,Lost Art Press,lostartpress.com

Initially, hand planes, like the one shown below were used to remove wood and form trim components. Multiple passes were needed, each deepening the groves and shaping the word. It took practice, skill and patience to do the work well and avoiding waste. This was the domain of the craftsman, the skilled woodworker.


In terms of our evaluation, the criteria we are looking have the following characteristics (we’llfillinthetableaswegoalong):

The next stage would use electric motor driven routers to shape the wood. Instead of multiple passes with a hand plane, a motor driven set of bits removes material leaving thefinishedproduct.Theroutershownisguidedbyhand.

A variety of cutting bits allow the craftsman to create different shapes. The illustration on the right shows the matching set of bits used to create the rails and stiles that frame cabinet doors with interlocking pieces.

The chart below shows the impact of this equipment on the production criteria. While available for the home woodworker, the use of this equipment implies that the craftsman is going to be producing the shaped wood in quantity, so we are moving above the produc-tion level of a cottage industry. The cost of good quality routers and bits is modest and requires an invest-mentindevelopingskillstousethemeffectively.Usedwell(andsafely)theycanproducegoodproducts;they can also produce a lot of scrap if the individual isn’t properly schooled.


The equipment shown in the next graphic is an example of the next stage in wood shapingproductivity:multi-headednu-merically controlled routers. Instead of onerouter-bitcombinationtherearefour,and the path they follow is directed by computer program so that highly repeat-able and precise cuts can be made.

With multiple heads, the complexity of the product increases.

The chart below shows the impact of this kind of equipment. We’ve moved from the casual woodworker to a production opera-tion–thecostoftheequipmentissignifi-cant, and the operators – both the program designer and machine operator – have to be skilled in the use of the equipment to reduce mistakes and scrap material. The “Less Manual Skill” notation refers to the point that we have moved from the craftsman-woodworkertotheskilledoperator,re-quiring different skill sets than previous production methods. One oftheside-effectsofhigherproductionisthatifyoumakeadesignerror,youcanmakeoff-specproductquickly.


Thefinalstepinourdevelopmentisfullyautomatedassemblylines.Theirinclusioncompletesthechartthat we’ve been developing.


Theentireprocesscanbesummarizedasfollows:

Thattranslatesfairlywellwhenweconsiderlabautomation,movingfrom100%manualworktofullauto-mation:scientificmanufacturing/production.

Note:theimageinthelastcolumnisfromFluidManagementSystems(Watertown,MA)andshowsanautomated extraction system.


What does this mean for lab workers?

Theskillsneededtodayandinthefuturetoworkinamodernlabhavechangedsignificantly,andwillcontinue to change as automation takes hold. We’ve seen these changes occur already. Clinical Chemistry, HighThroughputScreening(HTS),andautomatedbio-assaysusingmicroplatesaresomeexamples.

The discussion here mirrors the development in the woodworking example. We’ll look at the changes in skills using chromatography as an example. The material below is applicable to any laboratory environ-ment, electronics, forensics, physical properties testing, etc. Chromatography is being used because of it’s wide application in lab work.

By“manualmethods”wemean100%manualwork,includinghavingthechromatographicdetectoroutput(ananalogsignal)recordedonastandardstripchartrecorder,thepentracewillbeanalyzedbythehand,eyeandskilloftheanalyst.Theprocessbeginswiththeanalystfindingoutwhatsamplesneedtobeprocessed,findingthosesamples,andpreparingthemforinjectionintotheinstrument.Theinstrumenthadtobesetupfortheanalysiswhichincludedinstallingthepropercolumns,adjustingflowrates,componenttemperatures, and making sure that the instrument was working properly.

As each injection is done, the starting point for the data – a pen trace of the analog signal – is noted on the strip chart. This process is repeated for each sample and reference standard. Depending on the type of analysis, each sample’s data may take up to several feet of chart paper. The recording is a continuous trace andisafaithfulrepresentationofthedetectoroutput,withoutanyfilteringasidefromattenuatoradjustments(range selections to keep the signal recording within the limits of the paper – some peaks may peg the pen atthetopofthechartbecauseoftheirsizeinwhichcasethatdataislost)andelectrical/mechanicalnoisereduction).

When all the injections have been completed, the analyst begins the evaluation of each sample’s data. That includes:

• Inspectingthechromatogramforanomalies,includingpeaksthatweren’texpected(possiblecontaminants), separations that aren’t as clear as they should be, noise, baseline drifts, and any other unusual conditions that would indicate a problem with that sample or the entire run of samples.

• Makingmeasurementsneededforqualitative/quantitativeanalysis

• Developingthecalibrationcurves,and

• Makingthecalculationsneededtocompletetheanalysis.

Theanalysiswouldincludeanyin-processcontrolsamples,andaddressingissueswithproblemsamples.

Thefinalstepwouldbetheadministrativeworkincludingchecksoftheworkbyanotheranalyst,reportingresults, and updating work request lists.

Historically the next major development was the introduction of automated injectors. Instead of the analyst spending the day injecting samples into the instruments injection port, a piece of equipment did it and broughtinthefirstexpansionoftheanalyst’sskillset(oftentheanalysistimewastooshorttoallowtheanalyst to do anything else so the analysts day was spent injecting and waiting). Granted this wasn’t a majorchange,butitwasachange.Itdidrequiretheanalysttoconfirmthatthesamplesandstandardswerein the right order, that the right number of injections per sample were set or duplicate vials were put in the

The analyst using manual methods – quality control lab

Point automa-tion – automation applied to specific tasks


tray(duplicateinjectionswereusedtoconfirmthatproblemsdidn’toccurduringtheinjectionprocess).Theanalysthadtoensurethattheauto-injectorwasconnectedtothestripchartrecordersothattheinjectiontiming mark was made automatically.

Thissimplechangeofaddinganauto-injectortotheprocess,didhaveanimpactontheanalystsskillset.The same held true for the use of automatic integrators, and sample preparation systems; in addition to understanding the science, the lab work took on the added dimension of managing systems, trading labor for systems supervision with a gain of higher productivity.

Theadditionofdatasystemstothesampleanalysisprocesstrain(worklistgeneration-samplepreparation-instrumentanalysissequence)furtherreducedtheamountofworktheanalystdidinsampleanalysisandchanged the nature of the work performed. Starting with the simple integrators and later computer systems, thedatasystemwouldworkwiththeauto-injectortostarttheinstrumentanalysisphaseofwork,acquirethesignal from the detector, convert it to digital form, process that data (peak detection, area and peak height calculations, retention time) and perform the calculations needed for quantitative analysis. Less work with higher productivity.

While systems like this are common in labs today, there are problems and we’ll come to those shortly.

Depending on what is necessary for sample preparation, it may not be much of a stretch to have automated sample prep, injection, data collection, analysis and reporting (with automated updates into a Laboratory InformationManagementSystem-LIMS)performedinasmallfootprintwithequipmentavailabletoday.Onevendorhasanauto-injectionsystemthatiscapableofdissolvingmaterial,extractions,mixing,andbarcode reading (and other functions). Connect that to a chromatograph and data station, with programmed connectiontoaLIMSandyouhavethebasisofanautomatedsamplepreparation-chromatographicsys-tem. There are some issues that have to be noted and addressed.

Thegoalhastobehigh-volume,automatedsampleprocessingwiththegenerationofhigh-qualitydata.Theintent is to reduce the amount of work the analyst has to perform, ideally so that the system can run unat-tended.By“high-quality”itmeansthatyouhaveahighlevelofconfidenceintheresults.Thereismoretothatthantheabilitytodocalculationsforquantitativeanalysisorhavingavalidatedsystem-youhavetovalidate the right system.

Computer systems used in chromatographic analysis can be tuned to control how peaks are detected, what is rejectedanoise,andhowseparationsareidentifiedsothatbaselinescanbeproperlydrawnandpeakareasallocated. The analyst needs to evaluate the impact of these parameters for each analytical procedure and make sure that the proper settings are used.

Thefirstbulletunderthemanualdescriptionnotestheinspectionofthechromatogramforelementsthatdon’tmatchtheexpectationsforawell-characterizedsample:thenumberofpeaksthatshouldbethere,thetype of separations between peaks, etc. This screening of samples has to be applied to every sample whether by human eye or automated system, the latter giving lower labor costs and higher productivity. If we are going to build fully automated production systems we have to be able to describe a screening template that isappliedtoeverysampletoeitherconfirmthatthesamplefitsthestandardcriteriaorhastobenotedforfurtherevaluation.That“furtherevaluation”maybefrustratedbynothavingthedatasystemkeepsuffi-cient data for that evaluation, and require rerunning the sample.

Sequential-step automation

Production-level automation: movement to Scientific Manufacturing / Production


Thedataacquiredbythecomputersystemundergoesseverallevelsoffilteringandprocessingbeforeyouseethefinalresults.Thesamplingalgorithmsdon’tgiveusthelevelofdetailintheanalogchromatogram.The visual display of a chromatogram is going to be limited by the data collected and the resolution of the display–thestair-steppingofadigitizedchromatogramisanexampleofthat,ananalogchromatogramisasmooth line. Small details and anomalies that could be evidence of contamination may be missed because of the processing.

In addition, the entire process needs to be continually monitored and evaluated to make sure that it is work-ingproperly.Thisisprocess-levelstatisticalqualitycontrol,anditincludesoptionsforevolutionaryopera-tions updates – small changes to improve process performance. Standard samples have to be run to test the system. If screening templates are used, samples designed to exhibit problems have to be run to trigger thosetemplatestomakesurethatproblemsamplesaredetected.Thesein-processcheckshavetoincludeeveryphaseoftheprocessandbeabletoevaluateallpotentialrisks.Theintentistobuildconfidenceinthedatabybuildingconfidenceinthesystemusedtoproduceit.

The goals of higher productivity can be achieved for sample processing, but in doing so, the work of the an-alyst will change from carrying out a procedure to managing and continuously tuning a system that is doing the work for them. The science has to be well understood, as does the implementation of that science. As weshifttomoreautomation,anduseanalyticaltechniquestomonitorin-processproductionsystems,moreemphasishastobeplacedoncharacterizingalltheassumptionsandpossiblefailurepointsofthetechniqueand building in tests to ensure that the data being used to evaluate and control production process is sound. Duringthedevelopmentoftheprocessdescribedabove,theanalysthastofirstdeterminethesequenceofsteps, demonstrate that they work as expected, and prepare the documentation needed to support the process and guide someone through it’s execution. This includes the details of how the autosampler programming is developed, stored and maintained. The same hold true for the data systems parameters, screening templates and processing routines. This is process engineering.

When the system is being used the analyst has to ensure that the proper programming is loaded into each component and that it is set up and ready for use.

This is a very simple example of what is possible and an illustration of the changes at would occur in the work of lab professionals. The performance of a system such as that described could be doubled by imple-mentingasecondprocessstreamwithoutsignificantlyincreasingtheanalystworkload.

The key element is the skill level of those working in the lab, are they up to it? Much of what has been de-scribed is process engineering, and there are people who are good at that – they work in manufacturing and production. We need to combine process engineering skills with the science. Developing automation teams is one approach, but no matter how you address the idea, those working in labs need an additional layer of skills, beyond what they have been exposed to in formal education settings.


Of the sciences, Clinical Chemistry has moved the furthest into application of lab automation as it could be in a lab, and transformed lab work in the process, moving from lab staff executing procedures manually to managing systems. The following quote from Diana Mass (Associated Laboratory Consultants, formerly: ProfessorandDirectorClinicalLaboratorySciencesProgram,ArizonaStateUniversity-privatecommuni-cations, used with permission) help delineate the difference in lab work styles:

“What I have observed is that automation has replaced some of the routine repetitive steps in performing analysis; however, the individual has to be even more knowledgeable to troubleshoot sophisticated instrumentation. Even if the equipment is simple to operate, the person has to know how to evaluate quality control results and have a quality assurance system in place to ensure quality test information.”

FromMarthaCasassa(LaboratoryDirector,BraintreeRehabilitationHospital,Braintree,Ma-privatecommunications,usedwithpermission)whohasexperienceinbothclinicalandnon-clinicallabs:

“Having a background both clinical (as a Medical Technologist) and non-clinical (Chemistry ma-jor and managing a non-clinical research lab), I can attest to the training/education being differ-ent. I was much more prepared coming through the clinical experience to handle automation and computers and the subsequent troubleshooting and repair necessary as well as the maintenance and upkeep of the systems. During my non-clinical training the emphasis was not so much on theo-ry as practical application in manual methods. I learned assays on some automated equipment, but that education was more to obtain an end-product than to really understand the system and how it produced that product. On the clinical side I learned not only how to get the end-product, but the way it was produced so I could identify issues sooner, produce quality results, and more effectively troubleshoot.”


The bottom line is simple: if people are going to be effective working in modern labs, the need is to under-stand both the science and the way science is done using the tools of lab automation. We have a long way to go before we get there. A joint survey by the ILA and Lab Managers Association11 yielded the following:

• LabAutomationisessentialformostlabs,butnotall• Theskillsetnecessarytoworkwithautomationhaschangedsignificantly• Entry-levelscientistsaregenerallycapableofworkingwiththehardware/software• Entry-leveltechniciansoftenarenot• Ingeneral,applicantsforpositionsarenotwellqualifiedtoworkwithautomation

How well educated in the use of automated systems are those working in the lab? The following text was used earlier in this piece:

The computers did the data acquisition, display and analysis. Now, part of the science was per-formed by a program, the analyst could adjust the behavior of the program by setting numerical parameters.

Nowwe’llfollowthatthoughtdownadifferentpath…

In chromatography, those numerical parameters were used to determine the start and end of a peak, and how baselines were drawn. In some cases, an inappropriate set of parameters would reduce a data set to junk. Do people understand what the parameters are in instrument data systems and how to use them?

In a March 200512 article the author provides the following comment: “Despite a lot of exposure to computerized data handling, however, many practicing chromatog-raphers do not have a good idea of how a stored chromatogram file — a set of data points arrayed in time — gets translated into a set of peaks with quantitative attributes such as area, height, and amount. This installment of “GC Connections” examines the basics of peak identification and quantification.”

Another article13summarizingasessionatthe35thInternationalSymposiumonCapillaryChromatographystated:

“At this point, I noticed that the discussion tipped from an academic recitation of technical needs and possible solutions to a session driven primarily by frustrations. Even today, the instruments are often more sophisticated than the average user, whether he/she is a technician, graduate student, scientist, or principal investigator using chromatography as part of the project. Who is responsible for generating good data? Can the designs be improved to increase data integrity?”

At the European Lab Automation 2012Meeting,oneliquid-handlingequipmentvendor14 gave a presen-tation on how improper calibration and use of liquid handling systems would yield poor data. Discussion with other vendors supported that point, citing poor training as the cause.

Oneoftheproblemsthathasdevelopedis“push-button-science”,ortobemoreprecise,theexecutionoftasks by pushing a button: the sample goes in, push a button to get the measurements, and get a printout. Measurements are being made and those using the equipment don’t understand what is being done, or if it is being done properly – there is a “trust the vendor” or the “vendor is the expert” mindset. Those points run againsttheconceptsofvalidationdescribedbytheFDAandISOorganizations,aswellasothers.Peopleneed to approach equipment with a healthy skepticism, not assuming that it is working but being able to demonstrate that it is working. Trusting the system is based on experience and proof that the system works as expected, not assumptions.

11 See: http://www.institutelabauto.org/research/LMSurvey.html12Hinshaw,J.V.,“FindingaNeedleinaHaystack”,LCGCAsiaPacific,Vol.8Num1,Pgs24-2913 Stevenson R., Gras R., Lee M., “The Future of GC Instrumentation From the 35th International Symposium on Cap-illaryChromatography(ISCC)”,AmericanLaboratory,Sept2011,Vol43Num9,pgs4-8

14 Bradshaw J., “The Importance of Liquid Handling Details and Their Impact on your Assays” ELA 2012, Hamburg, Germany, May 30 2012


Education on the use of current lab systems is sorely needed in today’s working environment. What are the needs going to be in the future as we move from people using equipment in workstations to the integrated workflowsofscientificmanufacturing/productionprocesses?

We need lab personnel that are competent users of modern lab instrumentation systems, robotics, and infor-matics(LIMS,ELNs,SDMS,CDS,etc.)–thetoolsusedtodolabwork.

They should understand the science behind the techniques and how the systems are used in their execution. If a computer system is used to do data capture and processing, that understanding includes:

• howthedatacaptureisaccomplished,• howitisprocessed,• whatthecontrolparametersareandhowthecurrentsetinusewasarrivedat(not“that’swhat

came from the vendor”), and• howtodetectandcorrectproblems.

They should also understand statistical process control so that the behavior of automated systems can be monitored,withpotentialproblemsdetectedandcorrectedbeforetheybecomesignificant.Ratherthansimply being part of the execution of a procedure, they manage the process.

We also need Lab Automation Engineers:

• Capableofplanning,implementing,andsupportinglabsystems

• Capableofdevelopingproductsandtechnologiesforlabwork

This is described in detail in an article titled “Are You a Lab Automation Engineer?” .

This includes not only the people developing systems but those supporting them. We’ve developed a course “R/D Technology for IT Professionals” to assist in their education .

The implementation of lab systems is an engineering program and should be approached in the same man-ner as any systems development activity.

The use of advanced technology products isn’t going to improve until we have people that are fully compe-tent to work with them, understand their limitations, and drive vendors to create better products.

Educational Requirements:

Laboratory Automation Engineers

elements of laboratory technology management

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