CDISC Migraon - Cytel · • Target Structure flexible, not restricted to SDTM • Data Driven...

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CDISC Migra+on PhUSE 2010 ‐ Berlin 47 of the top 50 biopharmaceu+cal firms use Cytel soFware to design, simulate and analyze their clinical studies. Source: The Pharm Exec 50—the world’s top 50 pharmaceutical companies according to PHARMACEUTICAL EXECUTIVE 1

Transcript of CDISC Migraon - Cytel · • Target Structure flexible, not restricted to SDTM • Data Driven...

Page 1: CDISC Migraon - Cytel · • Target Structure flexible, not restricted to SDTM • Data Driven approach – the logic resides in data – Logic stored in mapping descripon datasets.

CDISCMigra+on

PhUSE2010‐Berlin

47ofthetop50biopharmaceu+calfirmsuseCytelsoFwaretodesign,simulateandanalyzetheirclinicalstudies.

Source: The Pharm Exec 50—the world’s top 50 pharmaceutical companies according to PHARMACEUTICAL EXECUTIVE

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Presentation Objectives

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•  Introduc+ons•  CDISCMigra+onStrategies

•  BenefitsofDeployingaMigra+onU+lity

•  Ques+ons&Answers

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CytelPresenters Title

IrvingDark VicePresident,ClinicalResearchServices

JimNigrelli PrincipalSta+s+calProgrammer

AjaySathe CEO,CytelIndia

Introductions

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CDISC Experience

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•  Converteddatafrommorethan50trialstoSDTMcompliantdatasets

•  Prac+celeaderswithextensiveCDISCexperience•  RecentFDAApprovalusingdatamigratedtoCDISCbyCytel

•  LicensedWebSDM™forcheckingSDTMcompliance

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CDISCMIGRATIONSTRATEGIES

IrvingDark,VicePresidentClinicalResearchServices

JimNigrelli,PrincipalSta+s+calProgrammer

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Migration practices – Key components

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GapAnalysisTrialDesignAnnotatedCRFsDataMigra+onDefine.xmlQCWebSDM™

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GAP Analysis

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•  Itemiza+onandevalua+onoffilestosupportmigra+onac+vi+es

•  Ini+atedpriortocommencingmigra+onac+vi+es•  Documentinventory

•  ReconcilesampleCRFsversussourcedata

•  Comparisonofprotocolamendments/versionsagainstCRFversions

•  Advantages:–  Proac+veapproachratherthanreac+ve–  Clarifiesthescopeandchallengesofmigra+onac+vi+es

–  Iden+fiesdifferencesindatacollec+onformats

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Trial Design

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•  Domainthatcontainsaclearrepresenta+onofthedesignofaclinicaltrial–  CreatedpriortoCRFannota+onanddatamigra+on

–  Experienceneededtocreatethetrialdesigndataset:•  SDTMTrialDesignConcepts

•  Experiencewithkeyclinicaldocuments(e.g.Protocol,SAP,DataSets,CSR)

–  Examples:•  Standardiza+onacrossstudies•  Iden+fyingtrialARMSandtrialVISITS

•  Plannedperprotocolversusactual

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CRF Annotation

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•  TheannotatedCRFprovidesthemigra+onteamwithaclearpresenta+onofSDTMvariables

•  CompletedfollowingtheGAPanalysisandpriortomigra+on•  ExperienceneededtocreatetheannotatedCRF:

–  KnowledgeoftheSDTMImplementa+onGuideandMetadataSubmissionGuidelines(chapter4–GuidelinesforAnnota+ngCRFs)

–  Standarddatamanagementprinciples

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Data Migration

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•  CurrentlyusingSASprogramstomigratedata:–  UseSASandExcel–  Mappingspecifica+onsgenerated(Excel)

–  SASMacrostoassistinstandardizingthemigra+onprocess(e.g.ISOdateconversion,SDTMtemplates,ControlTerminologyLook‐ups)

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DEFINE.XML

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•  Metadatadescribingtheformatandcontentofthedatasets

•  In‐HouseU+lity:–  SASGenerated–  Metadata/Code‐listdriven

–  CRFpagelinks–  Commentsinser+on

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Migration QC

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•  QCofMigra+onofClinicalData

•  Deriva+onofSDTMvariables

•  Genera+onofDefine.xml•  CompliancetoSDTMstandards

•  KeyComponents:–  DataAccountability–  Sourcedatachecks–  Define.xml

–  Addi+onalQCchecks–  SDTMCompliance

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WebSDM™

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•  Datareviewtoolusedtovalidatethecomplianceofdatasetsanddefine.xmltoSDTMstandards

•  Iden+fies:–  Trueerrors–  Datarelatederrors(e.g.start/enddates)–  Falseerrors(e.g.un+l‐lesstestresults)

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BENEFITSOFDEPLOYINGAMIGRATIONUTILITY

AjaySathe,CEOCytelIndia

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Automate – What and how

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•  Metadataapproach

•  Tasksmostamenabletoautoma+on:

–  Mappingofvariables(mappingspecsdocument)

–  MappingCodeGenera+on

–  Valida+ngthemappeddatasets

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Automate – What and how

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•  AccountforallofSourceData•  LoadTargetDatadefini+on(SDTMorother)

•  CreateCustomDomains

•  Defineglobalterminology

•  Definepre‐processinglogic,e.g.,TRANSPOSE•  Supplymappinglogic

–  Talkabouttheseventypesofmappinglogic?

•  Pushthebukon!–  (no,it’snotthatsimple,ofcourse.Verbalexplana+on)

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So, what’s new in this approach?

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•  TargetStructureflexible,notrestrictedtoSDTM

•  DataDrivenapproach–thelogicresidesindata

–  Logicstoredinmappingdescrip+ondatasets.

•  Self‐documen+ng.Generatemappingspecifica+oninparallel

•  Meta‐programming.GenerateSAS®codethatdoesthejob

•  Transforma+ontypes–versa+le&comprehensive–  Automa/c–matchnameandtype–  DataTypeconversion–  RenameVariables–  ValueConversions,usingControlledTerminology–  DateConversions(e.g.ISODATE)–  Concatena/onorParsing/spliHng–  Compute–userdefinedSAS®statements

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The Outputs

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•  AccountforallofSourceData•  MappingSpecifica+onsDocument

•  SAS®codeforMapping

•  MigratedDatasets

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Step 1: Project-level settings

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SelectSDTMVersionhere

Setvariousfolderpathshere

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Step 2: Dataset level settings

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Pickasourcedataset

Pickatargetdataset(inthiscaseSDTM)

Mappingdefini+onbeginstoappear.

No+cethe“WHERE”

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Step 3 – Global controlled terminology

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Loadcontrolledterminologyfroman

Excelfile…

…and/or,addittomappingmetadata

manually

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Step 4 – Mapping the variables

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“Auto”mappingusingsmartrules

Therulesappearhere;Useroverridepossible

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Step 4 – Auto-mapping rules

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“Auto”mappingusingsmartrules

Therulesappearhere;Useroverridepossible

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Step 5 – Mapping the variables

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Selectthedomain

CorrespondingSource&Targetsappear

Usersetspre‐processingandtransforma+onlogic

Mappingsspecsaresaved.Self‐documen+ng!

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Transformation types

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•  Auto

•  Convert Data Types

•  Rename

•  Drop

•  Convert Values

•  Convert ISODate

•  Concatenate

•  Extract

•  Compute (any user-defined SAS® code logic)

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The generated code

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The generated code

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Page 28: CDISC Migraon - Cytel · • Target Structure flexible, not restricted to SDTM • Data Driven approach – the logic resides in data – Logic stored in mapping descripon datasets.

Thankyou.

QuesCons?

Euro/UKcontact:LaurentSpiess,[email protected]:+33673861254

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Innova+onsinAdap+veClinicalTrialDesigns

www.cytel.com

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