艾昆纬-数字化转型：临床试验的新时代 Digital Transformation A New Era for Clinical Trials 2024

IQVIA

WhitePaper

DigitalTransformation:

ANewEraforClinicalTrials

NATALIAKOTCHIE,SeniorVicePresident,AppliedDataScienceCenter

CHRISTINALARSEN,Director,Innovation,DataSciences,Safety&MedicalRAJNEESHPATIL,VicePresident,DigitalStrategy&Innovation

SABRINASTEFFEN,VicePresident,HeadofInnovation&DataStrategyforDataSciences,Safety&Medical

Tableofcontents

Introduction3

Technologytrendsinclinicaldevelopment3

Designandplanning:Reducing‘whitespace’6

Earlyiterativeplanningandbenchmarking6

Real-timescenarioplanning7

Demandforreal-timedatafordecision-making7

Needforincreasedsitesupport7

Dataflowanddigitization,enablingfasterinsights8

Callforcommondatamodelsandstandards9

Remainingbottlenecks:‘Collaborationtax’andtheneedforindustry-wideadoption9

Conclusion9

References10

Abouttheauthors11

Introduction

Digitaltransformationishappeningallaroundineverydaylife.Smartphones,watchesandlaptopsconnectandsyncseamlessly;AI-drivenecommerceimprovesconsumer

experiencesforshopping,streamingentertainment

andsocialmedia.Intheretailsectorinparticular,digital

transformationisaddingvalueforcustomers.Operational

processesarebeingsuccessfullystandardized.One

exampleistheuseofstock-keepingunits(SKUs)that

appearasbarcodesorquickresponse(QR)codeson

retailproductlabels.Theseenableretailerstomanagethesupplychainandstockingprocess,increasing

productavailabilityforconsumers.Digitalbankinghasdisruptedtraditionalbankingmodelsbyimplementingstandardizationandcommondefinitions,improving

speed,qualityandgovernanceofinteractions,all

translatingintoabetterend-userexperience.

Theever-increasingcomplexityofclinicaltrialsimpedesefficiency.Asinotherindustries,digitaltransformation—includingdigitization,automationandartificial

intelligence/machinelearning—isimprovingefficiency,enhancingpatientexperiencesandunlockingcrucial

insightsacrosshealthcare.Electronicschedulingis

increasinglyavailableforhealth-relatedappointments,

withpatientportalsenablinghealthinformationtobe

self-managed.IntegrationofAIismakingclinicaltrials

moreaccessible,personalizedandtransparent,fosteringpatient-centrictrialenvironmentsandaccelerating

developmentofnewtherapies.

Overall,digitaltransformationhaspotentialtohelp

clinicaltrialtechnologiestobefutureready,bringing

valuetostakeholdersfrompatientsandsitestosponsorcompaniesandCROs.AuthoredbyIQVIAexperts,

thiswhitepaperprovidesahigh-leveloverviewofkey

elementstoconsiderwhendeployingdigitalcapabilitiesinclinicaltrials.

Technologytrendsinclinicaldevelopment

Currenttechnology-enabledtrendsinclinicaldevelopmentinclude:

•Improvingdecisionmaking,enablingfaster,evidence-baseddecisions

•OptimizingR&Dandclinicaltrials,whichincludes

useofdigitalizationandAI/MLinassetidentification,indicationprioritization,studydesignandplanning

andpatientenrollment;patient-centrictrialprocessesusingtelemedicine,wearables,sensorsanddevices;andreducingthepatientandsiteburdeninvolvedinclinicalresearch

•Enhanceddatacollectionandanalysis,including

remotedatacollectionandreviewwithaccessto

sourcedata;centralizedmonitoringofsiteandclinicaldataprocesses;andelectroniccaptureofdatathroughpatient-generateddatamechanisms,suchasePRO

•Streamliningprocesses/collaboration,involving

automationoftrialadministrativetaskstoimproveefficiencyandcompliance;processautomationto

reviewclinicaldatasignalsforearlyidentificationofrisks;andcollaborativedevelopmentofalgorithms

•Creatinginteroperableecosystemsbyimproving

integrationsbetweenclinicalsystemstooptimize

clinicalworkflows;usingcloud-basedplatformsfordatasharingandcollaborationbetweensponsors,

researchers,sitesandCROs;andenablingenhancedsponsoroversight.

|3

DIGITALTRANSFORMATIONDEFINITIONS

Digitalrepresentsusertouchpointsanddataassetsgeneratedfromsystems,computers,andapplications.Examplesofdigital

approachesincludehealth-relatedapps,

electronicdatacapture,wearables,sensors,devices,andoperationalclinicalsystems,

eConsent,ePRO,eCOA,andconnecteddevices.

Digitizationisaboutconvertinganalog

dataintodigitalform(suchasfromapaperdocumenttoaPDFfile).Digitalizationis

aboutusingtechtotransformbusinessprocesses(automatingtasks,etc).

Digitalizationinvolvesusingtechnologytotransformbusinessprocesses.Thisenablesdigitalassetstobemachine-readable,

comprisinganimportantpartofautomation.

Digitaltransformationistheintegrationofdigitaltechnologyintoallareasofa

business,fundamentallychanginghowitoperatesanddeliversvaluetocustomers.

Adigitaloperatingmodelcombines

multipledimensionsthatcollectivelyenabledigitalandtechnologycapabilitiestodeliverdefinedstrategicobjectives.Thisfocuses

onculture,customerjourneys,dataand

analytics,inadditiontothedimensionsofpeople,processandtechnology.

Thebenefitsofdigitalapproachesareillustratedin

Figure1,whichillustrateshow‘digitalnative’companies—wherevaluecreationinproducts,servicesanduserexperienceisbasedondigitaltechnologies—can

outstriptraditionalfirms.Thisisduetothefactthatthevaluethatscaledeliverseventuallytapersoffintraditionaloperatingmodels,butitcanclimbmuchhigherindigitaloperatingmodels.

Figure1:Digitaloperatingmodelstendtooutperformtraditionaloperatingmodels2,3

TraditionaloperatingmodelDigitaloperatingmodel

>

Numbersofusers

ForerunnersofinnovationinthehealthcareecosystemareshowninFigure2.Thesereflectaccelerationin

scientificinnovation,increasinguseofreal-worldevidencetodrivedecision-making,andthefactthatempowered

patientsareengaginginnewways.

“Examplesofdigitalapproaches

includehealth-relatedapps,

electronicdatacapture,wearables,sensors,devices,eConsent,ePRO,eCOA,andconnecteddevices”

4|DigitalTransformation:ANewEraforClinicalTrials

Figure2:Healthcareecosysteminnovationdrivinggrowthandpatientbenefits

Scientificinnovationisaccelerating

Real-worldevidenceisdrivingdecision-making

Empoweredpatientsareengaginginnewways

Innovationdrivers

NOVELTHERAPEUTICS

DIGITALPATIENTENGAGEMENT

TELEHEALTH

DIGITALTHERAPEUTICS

Artificial

DECISIONSUPPORT

MEDICALDEVICES

Intelligence

CLINICALWORKFLOW

REMOTEMONITORING

Pharmacompaniesareincreasinglyembracingdigital

transformationinanefforttounlockvalue(Figure3).

Currently,40-50%ofpharmacompaniesbenefitfromAI,4withtwooutofthreecompaniesplanningtoinvestmoreinIT.5ThesebenefitsincludethefactthatAIcanpredictbiomolecularstructures,6andAI-designedmolecules

recordphaseIsuccessratesof80-90%,comparedwith55-65%forthosesourcedusingtraditionalapproaches.7

Patientrecruitmentcanbeuptotwotimesfasterwhen

dataandpredictivemodelsareused,8anddecentralizedtrialshavebeenshowntoreducetrialcostsby2-3%,withafour-foldreturnoninvestmentusingmobiletechnology,telehealth,in-homevisitsandotherremoteapproaches.9Finally,useofdigitaloutcomemeasuresincreasesvalue

byprovidingpatientbenefits.10

Figure3:Currentpharmaindustryeffortstounlockvaluethroughdigitaltransformation

Decentralizedtrials

Reducetrialscostby2-3%withROIof4xusingmobiletech,telehealth,in-homevisits,etc.

•40-50%ofpharma

companiesbenefitfromAI

•2of3companiesplantoinvestmoreinIT

Successrate

Cost

Drugdiscovery

PhaseIsuccessrateof80-90%forAIdesignedmoleculesvs55-65%forthetraditionalapproach

Target

identification&validation

>

Compoundscreening

Lead

>identification&

optimization

>

Pre-clinicalstudies

>PhaseItrials

>PhaseIItrials

>PhaseIIItrials

>Regulatoryapproval

>Commercialization

Post-

>marketing

studies

>

Digitaloutcomes

Patientbenefitsusingnoveldigitalendpoints:apps,VR,etc.

Value

Biomolecularstructure

AIeffortlesslypredicts

structureofproteins,DNA,RNA,ligands,ions,etc.

Volume

Patientrecruitment

Upto2xfasterpatient

recruitmentthroughdata&predictivemodels

Speed

|5

Severalpossibleapproachestoderivingmorevalueforthevariousclinicaltrialstakeholdersusingadigitaloperating

modelareillustratedinFigure4.Whiletraditionalapproacheshavefocusedatfunction-specificandcross-functional

levels,digitaltransformationhasafocusoninteroperabilityandintegrationacrosstheenterpriseand,ultimately,acrossthevaluechain.Advancesareshownfromlefttoright,withfunctionalsilosbeingreimaginedasafullyinterconnected

valuenetwork.

Figure4:Potentialwaystoderivemorevalueforclinicaltrialstakeholders

FunctionspecificCross-functionalAcrossenterpriseAcrossvalue-network

>

↓

↓

Traditionalstate

Digitaloperationsstate–interoperabilityandintegrationfocus

Designandplanning:Reducing‘whitespace’

Sponsorsareeagertoreducethe‘whitespace’inclinicaldevelopment,definedasthetimetakentotransition

betweenresearchphasesthataffectscostsandtimelines.Earlyengagementwithsponsors,ideallyasmuchas

12monthsbeforestudystartup,canhelpaddressthis.

Benefitstothesponsorincludehavingtheabilitytomakedata-drivenstudydesigndecisions—suchaseligibility

criteriaandscheduleofactivities—basedonananalysisofkeyparameters,includingpatientandsiteburden,

whileaddressingthepotentialconsequencesofthesedecisionsonpatientrecruitmentandsiteparticipation.

Earlyiterativeplanningandbenchmarking

Usingthistimeforearlyiterativeplanningand

benchmarkingcanimprovedecision-makingand

savetimeatlaterstages.Iteratingondesignideasto

assessmultiplescenarioscanhelpsponsorsunderstandtheimpacttheirchoiceswillhavedownstream,providing

earlyinsightintopotentialoperationalrisksandthe

trade-offstoconsider.Forexample,useoftechnologymightimprovepatientparticipationbutwiththetrade-offofincreasingburdensometasksandaddedcosts

atsitelevel.IQVIAhasalibraryofdesignanalytics

andbenchmarksthatcanbeappliedatvariouspointsthroughoutthedesigndevelopmentcontinuum.Theseanalyticsprovideinsightsthatallowsponsorstomakeinformeddecisionsthatsupportprotocoloptimization.Additionally,protocolscanberapidlyassessedand

scoredforcomplexity,patientburdenandsiteburden,

whichgivessponsorsinsightsintowhichdesignelementsmightleadtooperationalchallenges.

6|DigitalTransformation:ANewEraforClinicalTrials

Earlydesignandoperationalplanningenabletheprotocoltobefinalizedattheearliestpossiblestage.Theremay

beoptionsforstreamlining,forexamplebyfocusingonprimaryandsecondaryendpointsandincludingonly

essentialexploratoryendpoints.Fromadatascience

perspective,itisvitaltotaketimeupfronttoidentify

potentialrisksandtoconsiderthebiostatisticalanalysesthatwillberunattheendofthestudytodetermine

factorsthatinfluencethedatacollectionstrategyanddigitalcapabilityselection.

Real-timescenarioplanning

Real-timescenarioplanningisincreasinglybeingusedforclinicaltrialplanning.Thishistoricallyincludedtheuseoftraditionalstatisticalapproaches,suchasMonteCarlo

simulationsforenrollmentratesandotherscenarios.

IQVIA’sstudyplanningandenrollmentoptimization

platformleveragesexpansive,globalreal-worlddataandAItoquicklybuildoptimalenrollmentstrategies.Itallowssponsorstoexplorearangeofscenarioswithenriched

informationaboutthecountriesunderconsiderationfortheirstudy.UsingcontemporarystatisticalmethodsandAI/MLcapabilities,alternativeoptionsaremodeledbasedontimeandcost,includingquickest,lowestcostand

balancedoptions.Representingafundamentalchange

inhowplanningisconducted,thisuseoftechnologyforscenario-baseddecisionmakingoffersarapid,highly-

accurateapproachtoidentifyingtheoptimalcountryandsiteselection,resultinginaclear,conciseplanthatmeetssponsorobjectives.

Asthestudyprogresses,real-timedatasupportsplan

revisionsanddevelopmentofnewprojections,helping

studyteamsgetaheadofpotentialchallengesandcoursecorrectasneeded.Usingtechnologytoconductreal-timeanalysescanaccelerateandinformdecision-making,

helpingmeetsponsorneedsforproactive,agileapproachestotheirstudyfeasibilityandenrollmentstrategies.

“Thereisademandfromsponsors tocompleteactivitieswithincreasedspeedandprecision,withcontinuousdataflowtosupportrapiddetectionoftrendsanddecision-making.”

Demandforreal-timedatafordecision-making

Overall,thereisademandfromsponsorstocompleteactivitieswithincreasedspeedandprecision,with

continuousdataflowtosupportrapiddetectionoftrendsanddecision-making.ThisdemandcanbemetbyIQVIA

digitalplatformsandapplicationsthatprovideautomationandconnectivity.Thereisalsoageneralshiftawayfrom

siteentereddata,likeelectronicdatacapture(EDC),infavorofpatientreporteddatafromconnecteddevicesandelectronicclinicaloutcomeassessment(eCOA),

whicheliminateslosttimewaitingfortranscription.Dataintegrationsautomaticallyfeeddatafromalldatasourcesintoadatarepositoryforaggregation.Asdataupdates,

itisautomaticallyconnectedtothedigitaloperationalprocesses,enablingcreationofcontinuously-updatedoversightdashboardsfortrialmanagement.

Digitizationeliminatestheneedformanualreviews,

reconciliationsandlogs,furtherimprovingtheway

dataflowsintheecosystemtoenableimprovementsindownstreamprocesses,suchasqualitymanagement,

compliancereviewofsites,patientsignaldetection,dataqualityissuesanddatamanagement.

|7

Needforincreasedsitesupport

Therehasbeenaproliferationinthenumberofsite-facingtechnologiesinrecentyears.Fromtechnologystrategy

andadoptionperspectives,theseposechallengesforsiteengagementandsiteenablement.Thereisaneedforsitesupportto:

•Reducetheadministrativeburdenforsitesandthus

improvesiteengagementfordocumentmanagementsystems.IQVIAofferselectronicinvestigatorsitefile

implementation,eBindersandeLogs.Thishelpsreducetheburdenofmanagingessentialdocumentsatthe

site,replacingpaperrecordswithdigitalones.

•Simplifycollectionofpatient-generateddataviaDigitalHealthTechnologies:thesensors,wearablesandotherdevicesthathavebeenavailablefor

sometimewithusagefurtherexpandedduringtheCOVID-19pandemic.

•ClarifyaneSourcestrategytohelpmakeavailable

offlinesystemswheredatacanbecollectedinan

asynchronousmannerandflowsintosystemsthroughintegrationmechanisms.

•Implementcentralmonitoringcapabilitiesin

responsetoincreasinguseofremotetechnologiesinclinicaltrials.Digitaltoolsarebeingdeployed,suchasplatformsformonitorsthatprovidemobilesitevisit

reportsandenablemobileinvestigationalproduct

managementthroughsimpleapplicationinterfaces

onhand-helddevicessuchastabletsandphones.Thisishelpingmeetuserswheretheyareinthisdigital

landscape.

Digitalizationofdataflowenablesfasterinsights

DigitalizationisresultinginvastincreasesintheavailabilityofpatientdatafromeSource(datacapturedelectronically),devices,andeCOA.TherearefourkeycomponentsusedatIQVIAtostreamlinedataflow:11

1.Digitization,whichfocusesoncreationofdigitaldataassets.Thiscanbedonebycompletingoperational

processesinadigitalworkflowapplication,suchas

thereviewofdataissues.Digitaldataassetsmay

alsobecreatedbydigitalizationofPDFs,hand-writtennotesandnaturallanguagenarratives,whichcreate

adigitalassetevenwhenamanualprocessisutilized.Thesearetransformedintodigitalassetsthatcanbeformatted,cleaned,andmergedwithotherdata.

2.Centralization,whichinvolvesstoringalldataina

warehouseordatalake,providingasinglerepository

foralldataassets.Thisstepstreamlinesdata

acquisition,appliesrigortodatacleaningandhandling,andeaseseffortsbyteamsacrossanorganizationto

usethesameresourcestosupportdecisions.

3.Standardization,whichrespondstotheexistenceof

assetsinmultiple,oftenunstructured,formats,suchasdoctors’notes,customerservicetasks,audiofiles

andimages.Theseformatsoftenapplydifferentrules,codesandnamingconventions.Fortheseassetstobecombinedandanalyzedasinglesetofbusinessrulesmustbeappliedbasedonenduserfeedback.

4.Automation,whichusesAI/MLtointerpretthe

dataandstreamlinedataflowandprocessesfrom

acquisitiontofinalanalysis.Thisenablesend-userstoquerydataassetswithdetailedquestionsandfollow-upsthatgeneratenearreal-timeresults.

5.Patienttokenization,whichanonymouslylinks

multipledisparatedatasetstogetheratthepatientlevel,providingmanufacturerswiththemost

comprehensiveviewofthepatientjourneywhilemaintainingaminimumriskofre-identification.

Callforcommondatamodelsandstandards

Clinicalresearchlacksstandarddefinitions,makingit

difficulttocreatescalable,digitaltransformation.There

areincreasingcallsfortheclinicalresearchsectortomovetowardcommondatamodels,buildingonlearningsfrom

8|DigitalTransformation:ANewEraforClinicalTrials

initiativessuchastheClinicalDataInterchangeStandardsConsortium(CDISC)studydatatabulationmodel(SDTM).Therehasalreadybeeninfrastructureinvestmentin

buildingcommondatamodels,aswellasbuildingend-

usertoolstoleveragedatarepositories,butmoreprogressisneeded.

Variousconsortiacontinuetoworkonstandards.

Thestandardscanoffermajorbenefits,including

improveddatacleaninginclinicaldatamanagement.

Somecompaniesarecustomizingthesestandardsto

achieveinnovation.Customizationandstandardizationshouldbebalancedtogaintheadvantagesofboth.

Lookingahead,AI/MLcanbeusedforstandardizedactivities,whilemanualeffortsarefocusedwhere

customizationorcustomAIsolutionsareneeded.

Animportantpieceofdigitaltransformationinvolves

continuousprocessesanddataflowtocreatebetter

insightsandprocesses.Whenthedataisflowingandalloperationalworkisinadigitalapplication,allelements

areconnected,enablingvisibilityintoongoingworkvia

dashboards.OneexampleisIQVIA’sCleanPatientTrackerdashboard,designedtogiveanoverviewofdatacleaningstatus,providinginsightsatproject,country,site,and

subjectlevel.Thisincludesadashboardtorapidlyidentifyissuesandtrends.

Remainingbottlenecks

Severalbottlenecksremain.Clinicaltrialsareincreasing

incomplexity,andtheamountofdatacollectedisrising.Forexample,infunctionaloutsourcingagreementswithmultipleCROs,inefficienciescanarisewhenvarious

elements–suchasdatamanagementorcentralized

monitoring–areeachoutsourcedtoadifferentCRO.Thisapproachrequiresconsiderableeffortforcoordination,

sometimesreferredtoasa‘collaborationtax.’Insome

situations,itcanworkbettertouseafull-serviceCROwithefficientprocessesthatareconnectedfromstarttofinish.Sometimes,creativesolutionsarerequired,suchasAPIsandjointaccessplatforms.

Industry-wideadoptionisanotherchallenge.Progress

isoftenmeasuredintermsoftheabilitytobuildanew

processandputitrapidlyintooperation,withadjustmentsbeingmadelater.Trulyeffectivechangedependson

alteringhowteammemberswork,withcarefulplanningtoreduceriskovertime—anapproachthattakeslongerupfrontandrequirespatience.

Conclusion

Lookingahead,IQVIAwillcontinueadvancingdigitaltransformationforsponsorswithleading-edgeAI/

MLsolutions.Thesesolutions(Figure5)willrapidly

navigatethevastvolumesofvariedindustry-specific

data,improvingclinicaltrialefficiencyandaccelerating

innovation.WithHealthcare-gradeAI,dataanalystswillincreasinglybeabletodiscoverpatternsandconnectionswithinandbetweendatasets,informingidentification

ofthenextbestactionforthetrialprocess.Usingtheseapproaches,dataanalystswillincreasinglybeableto

enhanceefficiencybyunravelingdatacomplexity,drivingactionableoutcomesandenhancingdecision-making.

Digitaloperatingmodelswillprovidecapabilitiesto

helpmeetsponsordemandstominimizethe‘white

space’intheclinicaldevelopmentprocess.Increased

automationandconnectivitywilladvancecontinuously-updatedoversightdashboardsforstudymanagement–protectingpatientsafetywhilepotentiallyreducing

clinicaldevelopmenttimelines.

Figure5:Afuturemodelfordigitaltransformationinclinicaltrials12

Healthcare,lifescience,

AIexpertise

Optimized

AI

models

AIinfra-Bench-

structuremarked

Cleansedandscrubbed

Precision

and

diversity

Domainexpertise

PrivacyandSecurity

Geographiccoverage

Regulatorycompliance

and

AdaptableAI

Unparalleled

quality

healthdata

|9

References

1.EasyM.TransformingClinicalTrialWorkflowswithAI.IQVIAblog.February22,2024.

/blogs/2024/02/transforming-clinical-trial-workflows-with-ai

2.DefinitionsfromonlinesourcesincludingMcKinsey,Accenture,HarvardBusinessSchool,Gartner,MIT

3.IansitiM,LakhaniKR.CompetingintheAgeofAI:StrategyandLeadershipWhenAlgorithmsandNetworksRuntheWorld.Book.2020.

/faculty/Pages/item.aspx?num=56633

4.Bain&Companypressrelease.40%ofpharmaexecutivesarebakingexpectedsavingsfromGenerativeAIinto2024budgets.February12,2024.

/about/media-center/press-releases/2024/40-

of-pharma-executives-are-baking-expected-savings-from-generative-ai-into-2024-budgets/

5.BuntzB.Two-thirdsofpharmacompaniesplantoupITinvestmentsin2024,surveyfinds.DrugDiscover

Trends.December14,2023.

/two-thirds-of-pharma-companies-plan-

to-up-it-investments-in-2024-survey-finds/

6.Googleblog.AlphaFold3predictsthestructureandinteractionsofalloflife’smolecules.May8,2024.

https://blog.google/technology/ai/google-deepmind-isomorphic-alphafold-3-ai-model/

7.JayatungaMKp,AyersM,BruensL,JayanthD,MeierC.HowsuccessfulareAI-discovereddrugsinclinical

trials?Afirstanalysisandemerginglessons.DrugDiscovToday.2024Jun;29(6):104009.doi:10.1016/j.

drudis.2024.104009.Epub2024Apr30.PMID:38692505.

/science/article/pii/

S135964462400134X

8.BuntzB.InsideAmgen’sATOMICstrategytouseMLtoaccelerateclinicaltrials.January24,2024.

/amgen-atomic-clinical-trials-ml/

9.DiMasiJA,SmithZ,Oakley-GirvanI,MackinnonA,CostelloM,TenaertsP,GetzKA.AssessingtheFinancial

ValueofDecentralizedClinicalTrials.TherInnovRegulSci.2023Mar;57(2):209-219.doi:10.1007/s43441-022-00454-5.Epub2022Sep14.PMID:36104654;PMCID:PMC9473466.

/articles/

PMC9473466/

10.DiMasiJA,DirksA,SmithZ,ValentineS,GoldsackJC,MetcalfeT,GrewalU,LeyensL,ConradiU,KarlinD,

MaloneyL,GetzKA,HartogB.Assessingthenetfinancialbenefitsofemployingdigitalendpointsinclinicaltrials.ClinTranslSci.2024Aug;17(8):e13902.doi:10.1111/cts.13902.PMID:39072949;PMCID:PMC11284240.

/39072949/

11.MayerT,SteffenS,JacksonD.ControlYourDataFlow,ControlYourTrial.IQVIAWhitePaper.August2022.

/library/white-papers/control-your-data-flow-control-your-trial

12.IQVIAwebpage.AIYouCanTrust.IntroducingIQVIAHealthcare-GradeAI™.

/

solutions/innovative-models/artificial-intelligence-and-machine-learning

13.IQVIAwebpage.Maketherightconnections.

/about-us/iqvia-connected-intelligence

10|DigitalTransformation:ANewEraforClinicalTrials

Abouttheauthors

NATALIAKOTCHIE

SeniorVicePresident,AppliedDataScienceCenter

NataliaKotchieleadstheIQVIA

AppliedDataScienceCenter(ADSC)forR&DSolutions.TheADSCteam–comprising200+

datascientists,analytic,andfeasibilityexperts,across

NorthandSouthAmerica,Europe,andAsiaPacific–

createsdatainsightsandsupportstheirtranslation

tooperationstodriveimpactonstudies.Priortoher

currentrole,Natalia