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DATABASICS
A PUBLICATION SUPPORTED BY AND FOR THE MEMBERS OFTHE SOCIETY FOR CLINICAL DATA MANAGEMENT, INC
TO ADVANCE EXCELLENCE
IN THE MANAGEMENT
OF CLINICAL DATA
Volume 24 | Issue 2 / 2018 Summer
This Issue2Letter from the Chair
3Letter from the Editor
4Virtual Clinical Trials – An Overview by Appalla VenkataPrabhakar
9DIY (Do It Yourself) – Make A Data Sandwich To Save Time (A Case Study) by Debu Moni Baru
13SCDM 2018 EMEA Leadership Forum, 30-31 May 2018: Key Takeaways, Reflections & Observations
2 DATA BASICS 2018 Summer
LetterFrom the Chair
Shannon Labout
Dear SCDM Community,
It is difficult to believe that we have finished half of 2018 already, but my calendar reminds me that this is true! I hope you are each having a productive year as we all strive to provide value to patients through the development of new therapies and treatments.
Throughout the first half of this year we have been talking about disruptive changes, and how technological advances are driving the discipline of clinical data management to evolve beyond traditional practices and into more of a data science role. SCDM is committed to leading this evolution, and to continue to provide innovative best practices, education and training, and certification to support you in your day-to-day activities and in your professional growth.
Over the past quarter we have made significant progress, some of it “behind the scenes” and not yet publicly visible. I’d
like to thank our volunteers for moving the Society forward in the following ways during that time:
• Nearing finalization of the first seven updated GCDMP chapters based on scientific literature review (watch for upcoming webinars
to introduce these new chapters).• Well-attended European Leadership Forum in London on May 30-31.
53 Data Management leaders from 34 companies tackled the topics of incoming data protection regulations and their impact on CDM, eSource
and their interpretation. • Successful conference in China, with more than 140 attendees, 30 presen-
tations and 4 Sponsors. Highlights included a presentation from the CFDA by Qing Wang on Education and Training for Clinical Data Management, as well as
the FDA with Ron Fitzmartin leading the conversation on the FDA’s Data Standards Strategy and Action Plan.
• Progress toward making the CCDM exam more globally convenient and accessible with our new online platform. We are currently in the process of testing a new online
CCDM platform, allowing you to take the CCDM exam wherever and whenever you want.• Working with regional Steering Committees around the world to offer local opportunities
for networking, education and events in Europe, India, China, and Japan. Most recently, we enjoyed hosting a single-day event in Bengaluru, India on 16 June.
Are you wondering how you can get involved? The best way is to just do it! Many of our committees are still looking for new members - find a team that looks interesting and join in. Register for a
conference. Sign up to present a webinar. Volunteer to help research and write the next GCDMP chapter. There are many ways you can get involved to learn from and network with your peers, contribute your
knowledge and experience, and help us advance our profession together.
So far, 2018 has been a landmark year for SCDM. Join me as we finish the year strong and prepare the Society and our membership for the next stage in our evolution.
Shannon
Shannon Labout Chair Interim Chief Standards Officer & Vice President of Education CDISC
Linda King Vice Chair
Jaime Baldner Past Chair Manager, Clinical Data Management Genentech
Jonathan R. Andrus Treasurer COO & CDO Clinical Ink
Jennifer Price Secretary Director, Clinical Solutions BioClinica
Carrie Zhang Trustee CEO eClinwise, Panacea Technology Co.
Michael Goedde Trustee Vice President Clinical Database and Statistical Programming PAREXEL International
Arshad Mohammed Trustee Senior Director, CDM IQVIA
Peter Stokman Trustee Global Clinical Data Sciences Lead Bayer
Reza Rostami Trustee Assistant Director, Quality Assurance and Regulatory Compliance Duke Clinical Research Institute
Sanjay Bhardwaj Trustee Global Head, Data & Analytics Management Biogen
Deepak Kallubundi Trustee Clinical Functional Service Provider and Analytics – Associate Director Chiltern
2018 SCDM Board of Trustees
3 DATA BASICS 2018 Summer
Letter From the Editor DearColleagues,
AsIreadShannon’sletterfromtheChairaboutalloftheprogressSCDMhasmadethisyear,Iwasamazedandproudtobeamember.IrememberwhenI joinedSCDMmany years’ ago, theGCDMPwas in its infancyand I tookabeta version of the CCDM exam. Now the GCDMP continues to evolve withnewchaptersbasedonscientificliteratureandtheCCDMexamwillsoonbeexpandedsothatitcanbetakenglobally.Thatisprogress.Thatischange.
But somehow despite the change, there are some principals that remainfundamentaltothedatamanagementdisciplinesuchasmanualreview.Thispoint isaddressed this issue’ssecondarticle,byDebuMoniBaruah,“DIY-HowtoMakeaDataSandwichtoSaveTime(ACaseStudy),”whichreviewstheever-presentneedformanualreviewinsomecircumstancesandhowtoavoidtraditionalmanualreviewmethodsbyusingitasimplifiedandefficient“datasandwichmodel.”Theleadarticle,“VirtualClinicalTrialsanOverview,”byAppallaVenkataPrabhakardelves intoanewerapproach forconductingvirtual clinical trials (also known as site-less or direct-to-patient trials) byusingtechnologieslikemobileapps,monitoringdevices,sensors,wearablesand online social engagement platforms. The benefits, risks, regulatorychallengesaswellasresultsofearlyadoptersareexplored.
And to conclude this quarters’ issue, there is an insightful summary ofkey takeaways, reflections and observations from the “SCDM 2018 EMEALeadership Forum” which was held 30–31 May 2018. Fifty-three DataManagement leaders from34companiesconvened todiscuss the futureofdatamanagement.Sometopicswere:
•EvolutionofCDMintotheclinicaldatasciencesdiscipline
•Commonchallengesandhowtocreateopportunities tocollaborateandidentifysynergiesacrossorganizations
•DiscussionofeSource&newdataprotectionregulations
•Newtechnologiesandhowtohandlethem
•Risk-based monitoring, centralized monitoring and new data cleaningstrategies
Itisclearfromthissummarythatprogressandchangeareuponusandthatweasdatamanagementprofessionalsneedtobenimbleanddriveprocessesforchange. It isessential forus tostay rooted in the fundamentalsofdatamanagementbutalsocontinuetoadvanceforward,adaptandgrowtogetherasadisciplineaswellasforourownprofessionaldevelopment.
I hope you enjoy this issue and will consider sharing your knowledge andexperienceinafutureissueofDataBasics.
Bestwishesasweandourdisciplinecontinuetoevolve!
Michelle Nusser-Meany
Editorial Board
Stacie T. Grinnon, MS, [email protected]
Lynda L. Hunter, CCDMPRA Health [email protected]
Elizabeth [email protected]
Nadia [email protected]
Arshad MohammedPublications Committee Board LiaisonIQVIA [email protected]
Claudine Moore, CCDM
Michelle Nusser-Meany, CCDMEditorMutare Life [email protected]
Sanet Olivier, CCDMPublication Committee [email protected]
Derek Petersen, [email protected]
Margarita Strand, CCDMGilead Sciences, [email protected]
Janet Welsh, [email protected]
4 DATA BASICS 2018 Summer
Virtual Clinical Trials – An Overview By Appalla Venkata Prabhakar
Theclinicaltrialprocessplaysanessentialbutexpensiveroleindrugdiscoverybyeffectivelydemonstrating efficacy and safety of a pharmaceutical compound. Analysts’ estimates arethatonly1outof10drugsthatstartstheclinical trialprocessesaregrantedFDAapproval.
Consideringthattheaveragecostofdevelopingandbringinganoveldrugtomarketcomestoaround$2.6billion12,andthetimeinvestedintoasingleprojectcantotalupto12years,thecostofrunningclinicaltrialscanbeprohibitiveandincrediblychallenging—particularlyincasewherethepatientpoolissmallorgeographicallydispersed.
Despite the time, money and effort spent over last few years the number of new molecules reaching the markethasbeenlow.Asthetraditionaldrugdiscoveryprocesscontinuestogrowincostandcomplexity,theemergenceofdisruptivetechnologiescombinedwithapowerfulpushtowardspatient-centricityinclinicaltrialsisgrowingstronger.Insuchachallengingenvironment,pharmaceuticalcompaniesare looking forways toachieveasustainableR&DmodelthatlowerscostsandmaximizeROI.Thus,enterstheconceptof‘VirtualTrials’.
VirtualTrialsofferotherbenefitswhich includesspeedand increasedquality. Italsohelpsustobuildourstudiessmartly,whichinturnwouldhelpusminimizeprotocolamendments,enablingustobringsaferandmoreeffectivetherapiestopatientsinneed.Withafocusonremotemonitoringandpatientengagement,VirtualTrials,alsoknownas‘Site-less’or‘Direct-to-Patient’clinicaltrials,havethepotentialtoimpactthemostperennialproblems—likepatientrecruitmentandretention. Inaddition to thesheerconvenience forpatients,site-less trials teardowngeographicbarriers,openingtrialstoamuchwiderandpotentiallymorediverseandrepresentativepatientpopulation.
WHAT ARE VIRTUAL TRIALS?
Virtualclinicaltrialsarearelativelynewmethodofcollectingsafetyandefficacydatafromhumantrialparticipantsfrom study start-up through execution to follow-up, by taking full advantage of technologies like mobile apps,monitoringdevices,sensors,wearables,andonlinesocialengagementplatformstoconducteachstageofclinicaltrialfromthecomfortofapatient’shome.InoneofthesurveyscarriedoutbyValidicin2016,itwasfoundthat64%ofresearchershaveuseddigitalhealthtoolsintheirclinicaltrials,and97%plantousethesetoolsinnext5years1,13.
TRADITIONAL CLINICAL TRIAL CHALLENGES
87% of patients some
what willing to participate
49% of enrolled patients drop out
before study completion.
~11% sites in any global clinical trial
fail to enroll a patient.
80% of trials delayed due to
enrollment
$8 million revenue loss/day
due to enrollment delay
48% of sites fail to meet enrollment
goals
40% of P-III trial patients become
disengaged and drop out of the study.
70% of patients live > 2hrs
from clinical site
Reference: https://lehub.sanofi.com/en/innovation-en/sanofi-launches-digital-clinical-trials-to-improve-recruitment-and-reduce-trial-times/
5 DATA BASICS 2018 Summer
Virtual Clinical Trials – An Overview
Continued
EARLY ADOPTERS OF VIRTUAL TRIALS
• REMOTE (Research on Electronic Monitoring of Overactive Bladder Treatment Experience) Clinical Trial
•Pfizerpioneeredthevirtualclinicaltrial(REMOTE)in20117.Itwasthefirstrandomizedclinicaltrialusingwebandsmartphone-basedpatientrecruitment,enrollmentandcollectionofstudydatawithoutrequiringpatientstovisitphysicalstudysite.
•Thisstudywasdesignedtotestthesafetyandefficacyofnoveltreatmentstrategyforoveractivebladder.•ThemainobjectiveofthistrialwastocomparevirtualapproachtoconventionalPhase-IVstudytodetermineif
virtualtrialdesignwouldbefeasibletoconductfuturetrials.•Oneofthemajorchallengesfacedinthistrialwaspatientrecruitment,sincemostofthemembersoftheirtarget
patientgroupwereolder.Thetrialwashaltedin20125.
• VERKKO Clinical Trial
•In2015,Sanoficonductedavirtualdiabetestrial(VERKKO)inEurope2.•Nodrugwastestedinthistrial.•Mainobjectiveofthistrialwastotest3Gcapabilityofawirelessglucometer.•FirstclinicaltrialusingeICF(ElectronicInformedConsent)approvedbyEuropeanRegulatoryagencies.•Coordinationtimeforthestudywas66%lessthanconventionalsite-basedstudyusingsimilarstudyprotocoland
complianceimprovedby18%.3
•97%retentionrateandwascompleted30%fasterthanthetraditionaltrial2.•Patient’ssatisfactionsurveyscoreof4.62outof5.3
BENEFITS, RISKS AND CHALLENGES OF VIRTUAL TRIALS
Benefits
•LowerCosts -VirtualTrialscancosthalfasmuchperparticipantcomparedtoasite-basedtrial.
•PatientCentricApproach -Virtually or remotely conducted clinical trials represent a patient centered approach to the pharmaceutical
research. -Maximizespatienteligibilityandpotentialenrollmentinastudy. -ElectronicHealthRecordscanhelpidentifytargetedtrialsubjects -Onlinepatientsupportnetworkscouldbeusedtoraiseawarenessoftrialsanddirectlyrecruitsubjects.
•HigherEngagement&Retention -Morethan40%ofPhaseIIItrialsubjectsbecomedisengagedanddropoutofatypicalclinicaltrial.Elimination
oftheneedforfrequenttraveltostudysiteandautomatingdatacollectionincreasespatientengagementandretention.
-Virtualtrialdesignshavedemonstratedhigherpatientengagementduringthelifecycleofastudy
•FasterDecisions -Decisiontoterminatedrugdevelopmentcouldbetakenfaster,thusimprovingpatientsafetyandreducingcoston
failedtrials. -Remotemonitoringcapabilitiesfacilitatesadaptiveclinicaltrialapproach,allowingimprovementsintrialdesign
basedonaccumulatingdata.
•QualityData -Patientdrivendatacollection -Higherqualitydatawithimprovedtechnologyanddirectdatainputsorimports
6 DATA BASICS 2018 Summer
Virtual Clinical Trials – An Overview
Continued
Risks & Challenges
Followingaresomerisksandchallenges,andanidealvirtualtrialsolutionwillneedinnovativesolutionsforeachofthese.
•Riskofdatatheftthroughonlineinformationsharingbystudyparticipants.•Potentialdifficultyinpatientparticipationduetolackofin-personsupport.•Selectionofaspecificsetofpatientswithspecificsymptomsthroughonlineenrollment.•Federalregulationsmaycreatepotentialchallengesfordatacollection&storageinsomeregionsanddatatransfer
acrossregions.•Recruitmentandretentionofpatientswithlowcomputerliteracymayimpactthetrialdatacollectionanditsquality.•Ascertainingthevalidityofdatacollectedinvirtualtrials.•Clinicaldatamanagementwouldneedadifferentapproachinvirtualtrials.
Some Situations Where Virtual Trials May Not Be Used
•PhaseItrials,asit’sthefirsttimeadrughasbeenusedinhuman,andsubjectsneedtobeintenselyobservedforensuringsafety.
•Uncertainsafetyprofileanddiseasestates.•Acuteproblemslikestroke.•Complexdrugregimensthatmayincludein-patientcare.•Pediatricstudies.
REGULATORY UPDATE6
FDAlaunchedthePre-certpilotprogramonJuly27,2018asapartoftheAgency’sDigitalHealthInnovationActionPlan. The plan outlines the agency’s vision for fostering digital health innovation while continuing to protect andpromote public health by providing clarity on medical software provisions of federal legislation passed in 2016(21stCenturyCures),addingexpertisetothedigitalhealthunit,andinitiatingtheFDAPre-certpilotprogram.
FDA’sPre-certpilotprogramisintendedtoinformatailoredapproachtowarddigitalhealthtechnologybylookingatthesoftwaredeveloperordigitalhealthtechnologydeveloper,ratherthanprimarilyattheproduct.
ThegoalofthisnewapproachisfortheFDAtodeterminewhetherthecompanymeetsqualitystandardsafterreviewingsystemsforsoftwaredesign,validationandmaintenance,andifso,topre-certifythecompany.
Withtheinformationgleanedthroughthepilotprogram,theagencyhopestodeterminekeymetricsandperformanceindicatorsforpre-certificationandidentifywaysthatpre-certifiedcompaniescouldpotentiallysubmitlessinformationtotheFDAthaniscurrentlyrequiredbeforemarketinganewdigitalhealthtoolaspartofaformalprogram.
FDA isalsoconsidering,aspartof thepilotprogram,whetherandhow,pre-certifiedcompaniesmaynothave tosubmitaproductforpremarketreviewinsomecases.
VIRTUAL TRIAL SOLUTION PROVIDERS
AnumberoftechnologyprovidershaveproductsandservicestosupportVirtualTrials.Inaddition,wehaverecentlyseenaleadingContractResearchOrganizationshowcasingtheirvirtualtrialsolution.Areferencedocumentforsuchproviderscanbefoundhere:https://digital.hbs.edu/innovation-disruption/software-enabled-clinical-trials/
THE ROAD AHEAD
VirtualClinicaltrialsareheretostayeitherintheirentiretyoraselementsofamoreconventionalmodel.Therearesubstantialbenefitsforallpatients,investigatorsandsponsors.Patientengagementismostimportantforrecruitment,retentionanddataquality,andshouldbethoroughlyconsideredforstudieswithandwithoutface-to-faceinteractions.Regulatoryauthoritiesaresupportiveofthisinnovativeapproachifthefundamentalpatientrights,confidentiality,andsafetyarenotcompromised.However,thesuitabilityofvirtualtrialsneedstobeassessedoncasetocase-by-casebasis.
Virtualtrialswouldaugmentratherthanreplacetraditionalstudypracticesandworkflows.Virtualizingaspectsofthestudymaybeleveragedwhenthecircumstancescallforit,likehowcentralizedremotemonitoringisbeingadoptedbystudyoversightteamstoday.Similarly,VirtualTrialscouldbeusedforrescuestudieswheretraditionalmodelshavefailed.Furthermore,withtheriseofnewsoftwaretoolsthatmakeresearchfaster,cheaper,andmoreaccessible,andwithaforward-lookingFDAdigitalhealthteam,thetimeisnowforaclinicaltrialparadigmshift.
REFERENCES
1 Software Enabled Clinical Trials – Andrea Coravos., Digital Initiative, April 3, 2018.
2. Sanofi Bets on Virtual Clinical Trials: Center Watch Online., Monday, March13, 2017.
3. The Clinical Trail of the Future, Pharma Times Magazine – October 2016.
4. Incorporating Site-Less Clinical Trials into Drug Development: A Framework for Action, Clinical Therapeutics/Volume 39, Number 5, 2017.
5. Virtual Clinical Trials – A Complete Remote Concept: Blog - https://globalhealthtrainingcentre.tghn.org/community/blogs/post/14744/2017/08/virtual-clinical-trials-a-complete-remote-concept/
6. https://www.fda.gov/NewsEvents/Newsroom/PressAnnouncements/ucm577480.htm
7. Virtual Clinical Trials: The Future of Patient Engagement? Applied Clinical Trials, Jul 12, 2016.
8. Re-Engineering Clinical Trials, Best Practices for Streamlining the Development Process – Peter Schuler and Brendan M. Buckley.
9. https://blog.andreacoravos.com/software-enabled-clinical-trials-8da53f4cd271
10. Will Virtual Clinical Trials Revolutionize the Pharma Industry?: https://www.mdconnectinc.com/medical-marketing-insights/virtual-clinical-trials-pharma-industry
11. Incorporating Site-less Clinical Trials into Drug Development: A Framework for Action. Clinical Therapeutics, Volume 39, Issue 5, May 2017, Pages 1064-1076.
12. Virtual Clinical Trials – Can Remote Trials Change the Clinical Trail Landscape? - https://xtalks.com/virtual-clinical-trials-1/
13. Survey: 64 percent of clinical trials execs have used digital technology, 97 percent plan to. Mobihealth News., September 22, 2016 : http://www.mobihealthnews.com/content/survey-64-percent-clinical-trial-execs-have-used-digital-technology-97-percent-plan
7 DATA BASICS 2018 Summer
Virtual Clinical Trials – An Overview
Continued
ABOUT THE AUTHOR:
Appalla VenkataprabhakarGroup Head, Clinical Database DeliveryNovartis
Appalla Venkataprabhakar is a Group Head of Clinical Database Delivery at Novartis. He has more than 21 years of experience in Pharmaceutical and CRO industry. He is an active member of SCDM India Steering Committee. His area of interest includes Statistics, Clinical Data Management, Data Analytics and People Management.
8 Return to CoverDATA BASICS 2018 Summer
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9 DATA BASICS 2018 Summer
ABSTRACT
Whenprogrammaticdatareviewcannotbeemployedduetolackofresourcesortimethensavetimebymakinga‘DataSandwich’.Thisisdonebyappendingandsortingdatasets-asimpleDIY-proventobetimesavingandefficientcomparedtothetraditionalmanualreviewprocesses.Inthiscasestudy,weexploretheavenuesofeliminatinglengthymanualdatareviewinclinicaldatamanagementanddiscussthesimplicityandefficiencyofthe“SandwichModel”comparedtoothercontemporarymanualdatareviewapproaches.
BACKGROUND
Itisundeniablethatclinicaldatamanagersarestillreviewingdataladenspreadsheetsmanually,spendingamajoramountoftheirproductivehours.Manualdatareview(datareviewprocesswithlittleornoprogrammaticassistance)inClinicalDataManagement,isalwayshighlyresourceintensiveanderrorprone.The“SandwichModel”needsnoexpensivetechnologyorskillsandcanbeadoptedbyanyoneforalmostanykindofmanualreviewprocess.
HOW TO AVOID MANUAL DATA REVIEW
Thesuccessofprogrammaticadoptionofdatareview largelydependsonthepresenceofunique identifiers in thetargeteddatasets.ThiscanbeaddressedduringCRFdesignbyaddingfieldstotheCRFtocapturecorrespondingrecords linkingbothdatasets.Forexample,addingfields in theconcomitantmedication (CM) form tocapture thecorresponding AEs and/or Medical Histories (MH) form or record identifiers (form/record number) creates therequireduniqueidentifiers(e.g.,AECRForrecordnumberwhichisunique)andcommoninboththeforms,(i.e.,AEandCMforms).Thisapproachhasmultipleadvantages:
1.ItsavesDataEntry(DE)time.ItwasobservedinacasestudyconductedinasandboxenvironmentofaCDMSsystemthatselectingtheAEtermsandformnumbersfromalistofvaluesontheCMformtakes22%lesstimethanpopulatingtheindicationfieldbytyping.
2.RemovesthechanceoftypographicalerrorswhichmaycauseDEdifferencesbetweenboththeformentries.
3.PromptstheDEpersontoaddthecorrespondingdata(reducesmissingdataoccurrences).
DATA SANDWICH MODEL: DO IT YOURSELF
DataSandwichmodelshouldbeusedwhenthereisnootherwaytoreviewdataprogrammatically(e.g.,lackofuniqueidentifiersduetoCRFdesignconventionsorlimitationsofCDMSsystems).Thismethodpositionsdatafrommultiplesources(datasets)neartoitsclosestmatchbasedonthecategoryofrelationship.Forexample–ifyouwanttovalidatethe data consistency between an exposure form collecting the infusion information for which administration wasadjusted due to an adverse event vs. the corresponding adverse event data then the sandwiching can be done asshowninTable 1.
Table 1:SandwichofExposure(Infusion)andAEData
Source Subjid Start Date End Date Reason Adjusted/Ae
Infusion 100001 10-Feb-17 11-Feb-17 ADVERSEEVENT
AE 100001 11-Feb-17 12-Feb-17 RASH
Infusion 100002 12-Feb-18 13-Feb-18 ADVERSEEVENT
AE 100002 12-Feb-18 14-Feb-18 HYPERTENSION
Infusion 100003 17-Feb-18 18-Feb-18 ADVERSEEVENT
AE 100003 19-Feb-18 20-Feb-18 HEADACHE
AEDatawasappendedwithExposure(Infusion)dataandsortedbyStartDateandthenEndDate.
DIY (Do It Yourself) – Make a Data Sandwich to Save Time (A Case Study)By Debu Moni Baruah
10 DATA BASICS 2018 Summer
Table 2:SandwichofAE,CMandMHData
Source Subjid AE/ Indication/MH CM AE/CM/MH
Start DateAE/CM/MH
End Date
CM Given (Yes/No)/ Indication
CM 100001 Fever Paracetamol 27-Jan-2014 03-Feb-2014
CM 100001 Fever Paracetamol 27-Jan-2015 03-Feb-2015
MH 100001 Fever 27-Jan-2015 03-Feb-2015 Yes
CM 100001 Fever Paracetamol 14-Jan-2017 03-Feb-2017
AE 100001 Fever 24-Jan-2017 14-Feb-2017 Yes
MH 100001 Headache 27-Jan-2016 03-Feb-2016 Yes
AE 100001 Headache 24-Jan-2017 14-Feb-2017 Yes
CM 100001 Headache Paracetamol 27-Jan-2017 03-Feb-2017
Table 2 is the appended and sorted output (data sandwich) developed using the datasets of AE, CM and MH. Thedatasetsareappendedbasedonheadertypes(allstartdatesinonecolumn,AEterm,MHtermandIndicationfromtheCMforminonecolumn,enddatesinonecolumn)andsortedintheorderofterms,StartDateandEndDate.Fortheeaseofreview,eachgroupwasgivenacolourcode.Appendingandsortingbroughtmatchingdatapointsneartoeachother(eventhoughthereweretypos–Fevar,Headache)andhenceaidsinquickerreview.
QUICK TIPS:
1.Sortorderplaysavitalrole.Altersortordertofindtheeasiestmatchasrequired(sortbydateandthenbytermorviceversa).
2.Unknowndatesaredifficulttosort.Thesedatescanbeprogrammaticallyconvertedtofirstdayofthemonthandorfirstmonthoftheyear(UNK-JAN-2018=01-JAN-2018;UNK-UNK-2018=01-JAN-2018).Thismakestherestoftherevieweasierandreviewercanstillviewandusetheactualdateenteredtomakeinferences.
3.Filteringdataatsubjectlevelmakesrevieweasier.
THE DATA SANDWICH MODEL: CASE STUDY
Threedatasets-AE,CMandMHwerereviewedforconsistencybyateamoftwovolunteersusingthreedifferentapproaches. The targeted number of rows were set to 100 and the same data rows were used for all the threeapproaches.
Method 1:Datasandwichedmethod.
Method 2:Sidebysidedatadump:Inthismethod,datafromAE,CMandMHweredumpedsidebyside(rowwise).Therewasnorelationshipbetweenthevariables.
Method 3:Datadumpinthreedifferentspreadsheets.
RESULTS:
TheDataSandwichmodel (Method1)proved tobe20%moreefficient thanMethod3and23%moreefficient thanMethod2.ThevolunteersfoundMethod2extremelycumbersomeandconcludedthebelow:
1.Itwasdifficulttomoveleftandrightinonespreadsheethavingallthedataside-by-side.
2.Puttingfiltersinmultipledatapointsandsearchingkeywordstospotthecorrespondingvariablestookmoretimeandwasconfusing(mostofthetimetheymissedremovingthefiltersandassumedthatdatapointsweremissing).
DIY (Do It Yourself) – Make a Data Sandwich to Save Time (A Case Study)
Continued
11 DATA BASICS 2018 Summer
DIY (Do It Yourself) – Make a Data Sandwich to Save Time (A Case Study)
Continued
3.Thevolunteerstooktheleastamountoftimetoreviewthedatasetsusingsandwichmodel.Theyjusthadtofilterthedataoneatatimeatsubjectlevelandscrollthemouseupanddowntoreviewandvalidatetherows.Forsubjectshavingmoredatapointstheyusedkeywordsearchunderfilterstonarrowdownthesearch.
Example:Code to make data sandwich with AE, CM datasets.
proc sql;
create table AEmed_vs_Conmed as
select SITEID label = “Study Site Identifier”,
SUBJID label = “Subject Identifier for the Study”,
“AE” as ORIGIN length = 10 label = “Origin”,
AESPID label = “AE Number”,
AETERM label = “Adverse Event”,
AESTDTC label = “AE Start Date”,
AESPDTC label = “AE End Date”,
ACNOMED label = “Other Action Taken Medication”
from AE
where ACNOMED ne “”
outer union corr
select SITEID label = “Study Site Identifier”,
SUBJID label = “Subject Identifier for the Study”,
“ConMed” as ORIGIN length = 10 label = “Origin”,
CMSpid label = “CM Identifier”,
CMINDC label = “Indication”,
CMTRT label = “Medication”,
CMSTDTC label = “CM Start Date”,
CMSPDTC label = “CM End Date”,
CMONGO as ongo label = “CM ongoing”,
CMAENO label = “AE ID”
from cm
where CMAENO ne ‘’ and SUBJID in (select distinct SUBJID from ae where ACNOMED ne “”)
order by 1,2,3;
quit;
CONCLUSION
As a rule of thumb, any type of manual review method should always be used as the last resort. If the cause ofdiscrepancyispostreviewdatachange,thenmanualreviewprocessescannotefficientlydetectthem.Whereas,incaseofprogrammaticreview,eachchangeindatacausingdiscrepancycanbeflaggedeverytimetheprogrammeruns.Duetothis,programmaticreviewalwaysshouldbethechoiceunlessthestudyistoosmall(entirereviewcanbedoneinashortperiodoftime).However,forinstanceswheremanualreviewistheonlyoptionthenthesandwichmodelcouldbeaneasiersolutionaidingfasterresultwithgreateraccuracy.Itisdoablebyanyoneasitinvolvesonlycopy,pasteandsortingactions.Itallowsreviewerstoperformholisticreviewssinceitbringsalltherequireddatapointstoitsnearestmatchandisalsoverysuitableforsmallsizedstudies.
12 DATA BASICS 2018 Summer
DIY (Do It Yourself) – Make a Data Sandwich to Save Time (A Case Study)
Continued
ACKNOWLEDGEMENT
IwouldliketoexpressmyspecialthanksofgratitudetoSnehaCheriyanathandNithinSrinivasforvolunteeringinthecasestudyandtoAnandhaSatheeshfordevelopingthecode(exampleabove)forAE-CMSandwiching.
ABOUT THE AUTHOR:
Debu Moni Baruah’s (M.Sc., LSSGB) background spans the fields of research and development, sales and marketing, clinical data management, art and culture and freelance inexpensive data visualization solutions. His specific interest is in crafting data visualization processes easy, simplified and propitious. He has earned several industry-acknowledged certificates on data visualization and highly specialized in Microsoft Excel based dashboards. Debu has authored and co-authored over 30 life science and research articles. Recently Debu has successfully facilitated an industry workshop on the topic “A Technology Approach for Data Review” in the SCDM – 1st Single Day Event. Currently Debu is serving as an Associate Manager in Clinical Data Management at Covance.
13 DATA BASICS 2018 Summer
SCDM 2018 EMEA Leadership Forum, 30-31 May 2018 – Key Takeaways, Reflections & Observations What follows are some collected personal notes and observations, in addition to the slides provided by the presenters. The text below may paraphrase what was said by the speakers and during the discussions. The authors attempted to capture the essence of the discussions, but they do not claim 100% accuracy. Nevertheless, these reflections provide useful insight of key developments in the EMEA region for Clinical Data Management.
OPENING KEYNOTE LECTURE
Dawn Anderson,Deloitte
TwobigissuesfacingClinicalDataManagement:
1.Dataproliferation.Tenyearsago:onaverage,therewereabout1milliondatapointsperstudy,andcurrentlythereare1milliondatapointsaday.Therefore,wehavea‘deluge’ofdatafromdifferent(new)sources.Today’schallenge:theinteroperabilityofsystem&datareconciliation.
2.Protocolamendments:60%ofstudieshavemorethan1amendment;typicalarethestudiesthatmettheprotocolapprovaldatagoal,butwherethefirstamendmentisafactpriortostudystart.Estimatedcostsofaprotocolamendment:250-450k$.
It’s estimated that 50% of the current trials can be ‘virtual‘ i.e., site-less. In many cases there is no overarchingdata management strategy (per organization, nor per clinical program). It is recommended to actively evolve datamanagementprocesses&comeupwithaplatformapproachtowardsunifieddata.
SESSION 1 – EMEA CDM COMMUNITY PANEL
CDMprofessionalorganizations®ionspresentedtheirmission,vision&activitiestoidentifycommonchallenges&opportunitiestocollaborate&identifysynergies.
FromthediscussionsitbecameclearthatCDMisevolvingveryrapidlyintothenewClinicalDataSciencesdiscipline.Inmanycompanies,CDMisadoptingnewroles:asdataprovidersforRBQMapproaches,leading&hostingCentralData Review as a new CDM activity, leading with strategic visions regarding eSource and new data sources. DataManagementorganizationsappeartohaveahardtimekeepinguporplayinga leadingrole,particularlysince it isdifficulttoreachthefolksworkinginthesenewareas–whomaynothaveanyCDMaffiliation.
Peter Stokman
GlobalClinicalDataSciencesLead,
Bayer(Germany)
Ioannis Karageorgos
ComplianceLead,Bristol-Myers
Squibb(Belgium
Richard Young
VicePresident,VeevaVaultEDC(UK)
Albert Hage
DirectorDataManagement,Astellas(TheNetherlands)
Karim Ouakkas
PrincipalStudyDataManager,
F.Hoffman-LaRoche,Ltd.(Switzerland)
Tanya Du Plessis
AssociateDirector,CDM,GlobalData
Management,IQVIA(SouthAfrica)
Maron Ravi
AssociateDirector,DataManagement
FSP,Parexel,(SouthAfrica)
Irina Sher
VPDataManagement,
BioforumLtd(Israel)
Amir Malka
President&Co-Founder,
BioForumLtd(Israel)
SCDM EMEA STEERING COMMITTEE
14 DATA BASICS 2018 Summer
The discussion led to the insight that with these new developments, it will be difficult if not impossible to playan authoritative role (like with the GCDMP-document), as the areas in which CDM is evolving are very diverse &ledbydifferentauthorities; the folksmostadvanced in their specificarea. Itwassuggested that theprofessionalorganizationscould–collectivelyorinacombinedeffortfacilitateknowledgesharing,e.g.,bysettingupaYouTubechannel,featuringpresentationsofexpertsdescribingapproached(todisseminatebasicknowledge/certification),andorganizingwebcastwiththeseexpertstofacilitatemoreprofoundknowledge(leadingtomoreadvancedcertification).
Asallcompanies/CROsareworkingonthesameissues,commonneedscanbeidentified&harmonizationcanbegreatlysupported.
Since the new activities (like RBM) cross functional boundaries, working together with professional organizationsservingadjacentdisciplines(ACPR,PhUSE,etc.)isindispensable.Inthecontextofprofessionalorganizations,butalsowithincompaniesroleshavetotranscendtheirtraditionalsilos.Thisissomethingwhereprofessionalorganizationscanbeleading.
IntermsofPeople qualification/certification,manyCDMEUleadersrealizethatgenericDMcertificationremainsattractive with service providers which try to put forward the competence of billable resource and individual jobseekers.Atthesametime,itmightrequiresignificantre-design,inordertoappealtomatureDMorganizationswithdeeptechnicalspecializationoftheirworkforce.Itmayalsoneedtobecomemorefocused/granularregardingnewcompetencies/skills(notonlyCertifiedDataManagerbutalsoDataScientist/Analyst,CentralMonitor,BigDataetc.etc.). Significant room for improvement may also exist with Academic Institutions which provide degrees for DataScience/Management.
IntermsofProcess/System qualification,arepeatedregulatoryexpectationistohaveNorms/StandardsforAuditTrailsandAuditTrailReviews-aswellasmorematureRiskAssessmentandRiskManagementtoolkits.
SESSION 2 – eSOURCE & NEW DATA PROTECTION REGULATIONS
Regulatory Perspectives on eSource & Data Protection, Lisbeth Bregnhøj
InspectorswillbelookingattheITaspectsofclinicaltrialsandsponsorsshouldlookatthis,whilespecificallyfocusingonvendorqualificationinspections.
Thecontractistheplacetolaydownrespectiveresponsibilities:
•Regardingvalidation(thesponsorshouldunderstand&agreewiththevalidationprocessthevendorfollowedtovalidatetheirsystems).Thiswillrequire,asaveryminimum,anintimateknowledgeoftheQualityManagementSystemofthesubcontractor-whichcannotbemetbysimpleAuditcertificates.
•Proceduresforthereviewoftheaudittrail
•Firewall/reviewoffirewallsettings
•Restoringfrombackup
•Adequacyofsecuritypatching/planfortestingofsystempenetration
•Planforthehandlingofsecuritybreaches
InDenmark,thereisaconsiderablediscussionsurroundingtheaccessrightsofGCPinspectors,whichmayinterferewithprivacyregulations.Thesuggestionistostudythefindingsofinspectionreports–whichareplacedonlineandtrytounderstandwhyfindingsareconsideredtobeminorormajor.Finally,thenallpartiesshouldreachoutandaskquestions–butnottoooften.
SCDM 2018 EMEA Leadership Forum, 30-31 May 2018 – Key Takeaways, Reflections & Observations
Continued
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SCDM 2018 EMEA Leadership Forum, 30-31 May 2018 – Key Takeaways, Reflections & Observations
Continued
Pharma & CROs are urged to provide feedback on reflection papers/draft guidance documents: contracts witheVendors (Q&Arecentlypublished).The informationonagreedoutputduringandafter the trial,arrangementsondecommissioningofadatabase.
Whenaninspectoragreeswiththerisk-levelingapproach,thatwillbereflectedinwhattheinspectionwillinvestigate.
Electronic health records: expect some level of assessment to establish whether it’s doing what it’s supposed tobe doing. Many countries are moving onto enlarging GxP scope to include EHRs in terms of compliance and CSVexpectations.
Thefollowingcasewasusedasanexample:theinvestigatorwasabletochangetheCRF.Subsequently,theyrefusedtousethesystemuntilitwasfixed.Thereasonforthiswasthattheyfeltthesystemwasjeopardizingpatientsafety,andthereforedidnotrecruitateam.Furthermore,thesitewasexcludedfromthestudyforunder-recruiting.
Inaddition,itiscommonforinspectorstogotoasitetoinspecttheuser-friendlinessoftheaudittrail.
A Site Perspective, Vivienne van der Walle
Per SCRS study: Protocol complexity has doubled between 2000 and 2015. On average, payments to sites havedecreased,leadingtoanincreaseof‘uncompensatedwork’.Sitesfeeltheytookoverthedataentry(DE)workthatusedtobedonebythecompanies/CROs.Whenaskedwhythesitedoesn’trequestDEsupport,itwasmadeclearthatthesiteshavetofightforarecruitmentandavendormanagementfee,sogettingcompensatedforDEworkisconsideredunlikely.
Thesitesshareaconsiderablefrustrationregardinghelpdesksthatdon’thelpwhenassistanceisneeded;theyjustopenaticket,whichisofnotmuchhelpwhenaninvestigatorismeetingwithasubject.
Regarding electronic medical records: still 90% work with additional paper sources, such as ´Source forms’ and‘Worksheets’.
AccordingtosomeEuropeaninspectors,anysystemwithaserverintheUS(complianttothe2001PatriotAct)isnotGCPcompliant–inwhichcasethedatawasthenmovedtoLondon.
From Creation to Implementation of RBQM, Andy Lawton
Weclaim:allstudiesaredoneaccordingtoGCP,yettherearestillfindingswherethisisnotthecase.CRAsspend30%oftheirtimeimplementingSDV,witha2.5%-onlycorrectionrateforthecombinedCRA/CDMdatacleaningefforts.
Whyarewecollectingnon-criticaldatainthefirstplace?CRAs&DMshavedetailedprocessknowledge,whichiswhatW.EdwardsDemingcalled‘profoundknowledge’.
Randomerrors:cannotbechanged,yet:systematicerrorsaretheerrorsthatmatterandshouldbeaddressed,andthat’swhatRBMisallabout.
Approach to RBM, François Torche, CluePoints, Belgium
ThestatisticaltooldevelopedbyCluePointswasrecommendedbytheFDA.
Testsonfrequency,variability,correlations,etc.areruntocompareapatient,asite&acountrywithallpatients,sites&countries.Resultingrates&p-valueswillsubsequentlybeusedinaglobalrankingprocess.Theoutcomewillbeusedinadatamonitoringtool,withKRIs,aRACTandasignal&actiontracker.Theimportanceofthelatterwasstressedasobviouslydocumentationoffindings&subsequentactionsiscritical.
Exampleswereprovidedwherecleardeviations from theexpecteddistribution (meanoff, lackof variability)weredetected.
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Continued
Implementing RBM, Chris Wells, F. Hoffmann – La Roche, UK
RocheimplementedRBMinallongoingstudies;theprocessofcomparing&analyzingsitesandpatientswitheachother (irrespective of treatment) to detect fraud & falsification (Statistical Monitoring) is completely outsourced.Standardstatisticaloversightassessmentsrunat30,60&90%ofenrollment,lookingforanomaliesin12differentdatacharacteristics.RocheiscurrentlydefiningGlobalRocheQualityToleranceLimits(QTLs),allowingforTA/phase-dependentspecificity,asonesizedoesnotfitall.
BREAKOUT SESSIONS
Inseparategroups,variousdifferenttopicswerediscussed.
1. RBM in CDM, Alison Liddy - ICON PLC
ManyaspectswerediscussedwheretheCDMeffortcouldbeguidedbytherisk-levelingofapertinentstudy,aswellasariskcategorizationofdata(levelsA/B/C;decreasingrelevance).
Theeffortisdescribedinthe(risk-based)datamanagementplan,inwhichtheintensityofdatamanagementcanbedecidedupfront.Theideaistomovefromdatacleaningtodataintegrity,byhavingprofessionalslookingatthedatawhounderstandthem,orbyhavingacross-functionalintegrateddatareviewapproach.
Query Management:independentofrisklevelstudy:queryonlyonce.Trytoonlycollectcriticaldatainthefirstplace;resistthedesiretocollectdata‘justincase’.Incaseofdoubt:refertoICHandanswerthequestionifcollectingtheproposeddatawouldbepartofstandardmedicalpractice?
Creating Edit Checks:UseofStandardECs:ECsarethereinthefirstplacetoalerttheinvestigator.CostofcratingECisnormal,butquerymanagementisexpensive.Itisobviouslynecessarytoquery,butitisfutiletore-query.ECissuesareoftenconsideredDMissues,whichisverymuchasignofsiloedthinking.
eCRF UAT:irrespectiveofstudyrisk,eCRFsshouldworkeverytime.
Study Risk-Leveling: 72-criterialist;basedonRACT:9questions.
Documentation Data Management plan contains risk assessment & categorization, set up single place (issuemanagementsystem)totrackactions.
3. Evolution of CDM/CDR, Pieter Voermans, F. Hoffmann-La Roche, Switzerland
Theperiod todiscuss theevolutionwasset to5years.Thebreakout teamstarted towritedown theirnamesandfunctionsonaflip-chart.Withthepurposetoreviewthisin5yearstoseewhatthechangeswouldbe.Further,weagreedthatthevolumeofdatahandledbyDataManagementwouldincreasedramatically.TheclassicaleCRFdatawillremainbutwillonlybelimitedinvolumecomparedtootherdatasources,likegenomicsandwearables.Tocopewiththisbigdataweshouldexpandourscopeofactivitiesandgainknowledgeontoolslikeartificialintelligenceandmachinelearning.Theconclusionwas:thattheevolutionpathwillbesteepandtheDataManagementcommunityshouldbeontopofthechangesintechnologyandenvironment,tobereadyforthefutureofClinicalDataManagement.
4. eSource, Lisbeth Bregnhøj
Twocaseswerepresented:
1. TLFs
Duringaninspection,itwasdiscoveredbycomparingsourcedataatsitewithdatalistings(providedasexcelintheformatrequestedbytheinspectorspre-inspection)andtheTLFs(Tables-Listings-Figures)oftheCSR(ClinicalStudyReport)thattherewereerrorsintheTLFs.(Seeslidesformoredetails.)
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SCDM 2018 EMEA Leadership Forum, 30-31 May 2018 – Key Takeaways, Reflections & Observations
Continued
Thegroupconcludedthattheoverallrobustnessintheprocesswaslacking.TherootcauseidentifiedintheCAPAdoesnotresideintheSASprogrammingpart,butinthemissingQCoftheCSR,theflawedriskassessment,andorganizationalsiloedthinking.
2. ePROs
An increasing number of trials are inspected where the primary endpoints are based on data collected fromePROs.ThisnaturallyincreasesinspectorfocusonePROdataandgeneratesdeviationsrelatedtoePROs.Oneoftheissuesthatcausesmostcriticaldeviations-andinseveralcaseshavecauseddelaysintheapplicationprocessorexclusionofdata-arearoundtheprocessesforcorrectingdata.
ThegroupconcludedthatePROdataessentiallyisrealdatafromrealpeople.Ingeneralnochangescanbemade;limitanychangestoaminimum,usesubmissionprompts.Thereshouldbeaprocesstocorrectingandchangingerrors,but it is important to document these!Riskmitigationcanbefoundinretraining&re-monitoring.
ThepreferredoptionbyInspectorsisthetimelyandorganizedriskbasedreviewofaudittrailinformation-i.e.,toidentifyquestionnairesfilledoutatinappropriatetimesornotinaccordancetotheprotocolschedule.
SESSION 5. PARTNERS’ SYMPOSIUM
Clinical Ink - Jonathan Andrus
JonathansharedwiththeaudienceinformationaboutwhatClinicalInkprovidestosites,patients,sponsorsandCROs.ThroughtheuseofClinicalInksolutions(CaptureandEngage),siteadherencetoprotocolrequirementsisimprovedbecausedataarecollectedatthetimeofasubject’svisitandrealtimeeditsandlogicareembeddedinthesystemtoguideandprovideinsightintotherequirementsoftheprotocol.Theuseofcapturedrasticallyreducestimespenton transcription and query management and allows site monitors to focus on higher value activity - focusing onsite&patientrelationshipsvs.sourcedocumentverification.Finally,ClinicalInk’sEngagesolutionimprovespatientengagementandadherenceandallowsforcontinualcollaborationwithpatientsbetweenvisitsviathepatient’sownmobiledevice.
Veeva Systems - Hugo Cervantes
HugosharedabriefbackgroundonVeevaandthecloudsolutionsifprovidesfortheLifeSciencesindustry,specificallyVaultEDC.VeevaistransforminghowthelifesciencesindustrycapturesandusesclinicaldatawithVaultEDC,thefirstcloudapplicationforclinicaldatamanagement.VaultEDCisafast,modern,andadaptivesolutionpurpose-builtfortrialprocessestospeedcriticalworkflowsandenablereal-timeaccesstocleandata.Itprovidesasinglesourceoftruthandtheflexibilitytosupporttheincreasedcomplexityoftoday’sclinicaltrials.
SESSION 6: OTHER PERSPECTIVES ON NEW DEVELOPMENTS
Investigator’s Perspective, Vivienne van der Walle, PT&R, the Netherlands
ViviennelikenedRBMtoBMW’sConditionBasedServicecarmonitoringsystem,andconcludedthatthereis(significant)roomforimprovementinRBM.Particularlytheaspectoftrialadministrationincreased,leadingtopressureonpatientcare.Managingmanydifferentsoftwaresystems–andrelatedURLs&passwords–doesnotleadtotheanticipatedbenefits&increasedefficiencies.Thiswasillustratedbytworeallifecasestudies,leadingtotheconclusionthatmuchefficiencycanbegainedifcompanieswouldaligntheirRBMprocesses,wouldincludesitespecificknowledge&bemoretransparent.
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Continued
CRA’s Perspective, Miguel Valenzuela, Bayer, UK
Miguelexplainedtheprocessofriskstrategyconsolidationbeforethestudystartanditsmaintenanceduringstudyconduct, emphasizing flexibility as a mandatory component when working with risk indicators and the continuousprocessofchangemanagement.
Withaclearunderstandingofhowmetricsarecalculatedandtheirdatadefinitions,whilemaintainingaconnectionwithinternaldatareviewprocesses,RBMhasoutstandingadvantages.ThechallengesofimplementingthisapproachatsitesmightberesolvedwithathoroughsiteteameducationonRBMrationaleanditstrueimpactontheirprocesses.
RBMprocessesshouldbecarefullyconsideredinlightoflatesttrends,suchaseSource.
Patient Advocacy Organization’s Perspective, Virgil Simon - The Prostate Net, Spain
Virgil explained the patient perspective on clinical trials and highlighted the fact that although data collection isimportant, keeping the patient population educated, and thus ensuring their engagement, is key to ensuring thesuccessofatrial.Hehighlightedareasintheplanningofaclinicaltrialwherepatientneedsshouldbeconsidered(outreaches/surveys/patientexpectationanalysis/etc).Itwasclearthatpatienttrustintheindustryiskey(trustingtheclinicaltrialprocessandmotivation).Patientsneedtounderstandwhattheyareagreeingtoandtheyneedtofeelthattheirneeds/questions/concernsarebeingunderstood.
CLOSING KEYNOTE LECTURE, TANYA DU PLESSIS, IQVIA, SOUTH AFRICA
It isclear thatwe (DataManagersacrossdifferentorganizations)areall facing thesamequestions/uncertainties.Thereisaclearchangeinthewayrisksarebeingmanaged/identifiedinclinicaltrialdata,andthisisdrivingriskbasedmonitoringandinterlinkedcentralizedmonitoring.Sincethisapproachcallsformorecollaborationacrossfunctionsweasleadersindatamanagementweneedtothinkabouthowourworkforceneedstoadapttothischange.Lastlyalotofthe“new”technologieswehavebeendiscussingasanindustryareactuallyalreadyonourdoorstep.Weneedtomakesurewehavestrategiesinplacetobeableto(atminimum)handleconnecteddevices(e.g.,eCOA,variouslaboratoryanalyses,etc)andthecollectionofdatafromaneSourceapproach.Realignmentwithnewstrategiesindatacleaningandriskplanning,aswellastheaccommodationof“new”technologiesareunavoidable.
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