understanding the potential of share

Restricted © Business & Decision Life Sciences 2016 All rights reserved.

InnovionUnderstanding the potential of Share: a visual business case and technical use casePeter Van Reusel, CDISC E3C Chair


Agenda

Introduction

Specify by Browsing

Metadata-driven Process

Call to Action


Provides input to the operational strategy and feasibility of clinical research studiesParticipates in defining the key components of the clinical protocolsData review, analysis and interpretationAnalyze emerging safety profile of the drugEnsure appropriateness of the chosen subject populationAssesses the performance of techniques used for endpoint measures

Establishing an objective framework for conducting an investigationPlacing data and theory on an equal scientific footingDesigning data production through experimentationQuantifying the influence of chanceEstimating systematic and random effectsCombining theory and data using formal methods

The Responsibilities ofClinicians & Statisticians

DataStandardsExperts!

!Clinicians

Statisticians


Updates over time (MAY 2016)

BRIDGv3.0

BRIDGv2.2

ADaMv2.1

ADaM IGv1.0

BRIDGv1.1.1

BRIDGv2.0

BRIDGv2.1

SDTMv1.2

SDTM IGv3.1.2

CDASHv1.0

ODMv1.1

SDTMv1.0

SDTM IGv3.1

ODMv1.2

BRIDGv3.0.1

BRIDGv3.0.2

BRIDGv3.0.3

ProtocolModelv1.0

ADaM Val.

Checksv1.0

ODMv1.3.1

SDTMv1.1

SDTM IGv3.1.1

ODMv1.2.1

Define.xmlv1.0

ADaMv2.0

ODMv1.3

20092002 2010200820052003 2004

/

Content Standards

Technical Standards

Semantics

Therapeutic Areas

2006 2007

BRIDGv1.0

BRIDGv1.1


Updates over time (MAY 2016)

BRIDGv3.0.1

BRIDGv3.0.2

BRIDGv3.0.3

ProtocolModelv1.0

ADaM Val.

Checksv1.0

ODMv1.3.1

20122011 20132010

Alzheimerv1.0

SENDv3.0

SDTMv3.1.2Am.1

ADaM Val.

Checksv1.1

CDASHv1.1

SDM.XMLv1.0

Pain

Tuberculosis

Devices

BRIDGv3.1

BRIDGv3.2

PRM Toolsetv1.0

CDASH UGv1.0

SDTM v1.3SDTM IG

v3.1.3

ADaMVal. Checks

v1.2

Parkinson’sDisease

Virology v1.0

2014

SDTMv1.4

SDTM IGv3.2

Alzheimerv1.1

Asthma

PKD

Define.xml v2.0

CDASH v1.2

ADaM MD Guide

CDASH E2BSAE IG

SDTM Associated Persons IG

v1.0

ODMv1.3.2

2015

Content Standards

Technical Standards

Semantics

Therapeutic Areas

2016

SEND IG v3.1

ProtocolConceptGuide

ADaM IG v1.1

Multiple Sclerosis

DiabetesQT Studies

Cardiovascular

Influenza

BRIDG v4.0

Dataset-xml v1.0

ADaM IG v2.0

CDASH v2.0

Breast cancer v1.0

Traumatic Brain Injury

COPD

CTR-XML v1.0

CDASH v1.2

PROTOCOL.XML1.0

Diabetic Kidney Disease v1.0

Define.xml IG Validation

SEND IG v3.1

SEND DART V1.0

Define.xmlv2.1

ADaM IG v1.2ADaM IG 2.0

SDTM IG v3.4 Batch 1

BRIDG UG v2

SDTM Device IG v2.0

Dyslepidemia

Schizophrenia

ADaM OCCDS V1.0ADaM Validation

Checks V1.3

Analysis Results Metadata v1.0

Hepatitis C

SDTM Pharmacogenomics

IG v1.0

SDTM DeviceSubmission Pilot

SDTM v1.5SDTM IG v3.3

RDF UG v1.0

RDF RG v1.0

Virology v2.0

…


Overview of CDISC Models (JUL 2016)

Content Standards

Technical Standards

Semantics

Therapeutic Areas

UpcomingPROTOCOL DEFINE.XML ODM THERAPEUTICAREAS

ADaMSDTMCDASH

BRIDG

SEND

SHARE

XML TECH

PROTOCOL v1.0 (JAN 2010)PRM TOOLSET v1.0 (APR 2012)PROTOCOL CONCEPTS GUIDE (AUG 2014)

CDASH v1.0 (OCT 2008)CDASH v1.1 (JAN2011)CDASH UG v1.0 (APR 2012)CDASH E2B SAE IG (NOV 2013)CDASH v1.2 (AUG 2014)CDASH v2.0 (DEC 2014)

BRIDG v1.0 (JUN 2007)BRIDG v1.1 (OCT 2007)BRIDG v1.1.1 (FEB 2008)BRIDG v2.0 (JUN 2008)BRIDG v2.1 (OCT 2008)BRIDG v2.2 (MAY 2009)BRIDG v3.0 (OCT 2009)BRIDG v3.0.1 (FEB 2010)BRIDG v3.0.2 (AUG 2010)BRIDG v3.0.3 (DEC 2010)BRIDG v3.1 (FEB 2012)BRIDG v3.2 (SEP 2012)BRIDG v4.0 (NOV 2014)BRIDG UG v2.0 (MAR 2015)

SDTM v1.0 + SDTM IG v3.1(JUL 2004)SDTM v1.1 + SDTM IG v3.1.1(DEC2014)SDTM v1.2 + SDTM IG v3.1.2(NOV 2008)SDTM IG v3.1.2 + AMENDMENT 1(DEC 2011)SDTM MEDICAL DEVICES v1.0(DEC 2012)SDTM ASSOCIATED PERSONS IG v1.0 (DEC 2013)SDTM v1.4 + SDTM IG v3.2(DEC 2013)SDTM QRS SUPPLEMENTS (PERIODIC)SDTM PHARMACOGENOMICS IG v1.0 (MAY 2015)

DEFINE.XML v1.0 (FEB 2005)DEFINE.XML v2.0 (MAR 2013)DATASET-XML v1 (APR 2014)CTR-XML v1.0 (MAR 2016)DEFINE.XML IG VALIDATION(NOV 2014)DEFINE.XML v2.1 (2016)

SDTM v1.5 + SDTM IG v3.3(MAY 2014 – DEC 2015)SDTM DEVICE IG v2.0(FEB 2015)SDTM IG v3.4 Batch 1 (Q1 2016)

SDM.XML v1.0 (SEP 2011)RDF RG v1.0 (JUN 2015)RDF UG v1.0 (JUL 2015)PROTOCOL.XML (Q3 2016)

ODM v1.1 (APR 2002)ODM v1.2 (JAN 2004)ODM v1.2.1 (JAN 2005)ODM v1.3 (DEC 2006)ODM v1.3.1 (FEB 2012)ODM v1.3.2 (MAR 2013)

ADaM v2.0 (AUG 2006)ADaM v2.21 + ADaM IG(DEC 2009)ADaM VALIDATION CHECKSv1.0 (SEP 2010)ADaM VALIDATION CHECKSv1.1 (JUL 2011)ADaM VALIDATION CHECKSv1.2 (JUL 2012)Analysis Results Metadata v1.0(JAN 2015)ADaM OCCDS v1.0 (JUL 2015)ADaM VALIDATION CHECKSv1.3 (MAR 2015)ADaM IG v1.1 (FEB 2016)

SEND IG v3.0 (MAY 2011)SEND IG v3.1 (JUL 2016)SEND DART v1.0 AUG 2016

CDISC SHARE

HEALTHCARE LINK

ALZHEIMER v1.0 (SEP 2011)PAIN (JUN 2012)TUBERCULOSIS (JUN 2012)PARKINSON’S DISEASE(OCT 2012)VIROLOGY v1.0 (NOV 2012)DEVICES (DEC 2012)PKD (FEB 2013)ALZHEIMER v2.0ASTHMA v1.0MULTIPLE SCLEROSIS(MAY 2014)DIABETES (AUG 2014)CARDIOVASCULAR v1.0 (OCT 2014)INFLUENZA v1.0 (NOV 2014)QT STUDIES v1.0 (DEC 2014)HEPATITIS C v1.0 (MAY 2015)DISLIPIDEMIA v1.0 (JUN 2015)SCHIZOPHRENIA v1.0 (JUN 2015)VIROLOGY v2.0 (SEP 2015)TRAUMATIC BRAIN INJURY v1.0(DEC 2015)ADaM SUPPLEMENT TO DIABETES(DEC 2015)COPD v1.0 (JAN 2016)TUBERCULOSIS v2.0 (FEB 2016)BREAST CANCER v1.0 (MAY 2016)

ADaM IG v1.2 (Q1 2016)ADaM IG v2.0 (Q4 2016)

SHARE API PILOT (Q2 2016)

DIABETIC KIDNEY DISEASE v1.0(Q1 2016)RHEUMATOID ARTHRITIS (Q2 2016)CV IMAGING v1.0 (Q2 2016)PROSTATE CANCER v1.0(Q3 2016)MAJOR DEPRESSIVE DISORDER(Q3 2016)GENERAL ANXIETY DISORDER v1.0(Q3 2016)BI-POLAR DISORDER v1.0 (Q3 2016)SOLID ORGAN (KIDNEY) TRANSPLANT (Q3 2016)


Agenda

Introduction

Specify by Browsing


Call to Action


Visualizing Metadata Today


Analysis Results



Analysis Dataset




ADaM Define.xml



SDTM Define.xml and aCRF


Current MDRs represent metadata in a tabular format

Current Metadata Repository


Current MDRs represent metadata in a tabular format

Current Metadata Repository

Clunky

No Benefits

Confusing

Boring

Not userfriendly


DISCLAIMER NOTEThe following is not a software demonstration

Sole purpose is to illustrate


WelcomeLogin:

Password:

SIGN IN >>

Bkush

************


AEAdverseEvents

EXExposure

CMConcomittantMedication

MHMedicalHistory

VSVital Signs

ListingsTables Figures

LBLaboratoryTest Results

Enter your search here

SDTMDOMAINSDTM VariableValue Level MetadataControlled TerminologyComputational algorithm

ADaMDOMAINADaM VariableADaM ParametersControlled TerminologyComputational algorithm

CDASHDOMAINCDASH VariableValue Level MetadataControlled Terminology

DATACOLLECTION

ANALYSISSHOPPING CART

End Points





Graphical Approaches to the Analysis of Safety Data from Clinical Trials”. Amit, et. al.

From “Graphical Approaches to the Analysis of Safety Data from Clinical Trials”. Amit, et. al.

Figures

x

Distribution of maximum LFT values by treatment.

Panel of LFT shift from baseline to maximum by treatment

LFT Patient profiles

Most Frequent On Therapy Adverse Events

Mean Change from Baseline in QTc by time and treatment.

Distribution of ASAT by time and treatment

Cumulative distribution (with SEs) of time to first AE of special interest


DATACOLLECTION



SAMPLE TEMPLATE


AEAdverseEvents

EXExposure

CMConcomittantMedication

MHMedicalHistory

VSVital Signs

ListingsTables Figures

LBLaboratoryTest Results





DATACOLLECTION


End Points




CDASHDOMAINCDASH VariableValue Level MetadataControlled Terminology Listings

Listing 2.4 Current Cancer History – All Treated Patients Experiencing Critical Events

Listing 2.5 Prior and Concomitant Medication – All Treated Patients Experiencing Critical Events

x

Listing 4.1 Adverse Event Listing. All Pre-Treatment Adverse Events – All Treated Patients Experiencing …

Listing 4.2 Adverse Event Listing. Treatment Emergent Adverse Events – All Treated Patients Experiencing …

Listing 4.3 Adverse Event Listing. Serious Treatment Emergent Adverse Events – All Treated Patients ..

Listing 4.4 Adverse Event Listing. Serious Treatment Emergent Adverse Events Related To Study Drug …

Listing 2.6 Physical Examination at Screening – All Treated Patients Experiencing Critical Events

Listing 3.1 Reference Chemotherapy and Concomitant Chemotherapies – All Treated Patients Experiencing ..

Listing 4.5 Adverse Event Listing. Serious Treatment Emergent Adverse Events Related To Treatment


DATACOLLECTION



SAMPLE TEMPLATE





Domain VariablesADaM Computational Algorithm

ADAE One record per subject per adverse event, per date

Dataset Description

x

Domain Variables Computational AlgorithmSDTMRelated metadata: Domain VariablesCDASH

Filter active: ADAE Domain

DCM Figures ListingsTables

DATACOLLECTION






ADaM Computational Algorithm


Filter active: ADAE Variables

Domain Variables

ADAE

Domain LabelName Computational Algorithm

ADAE

ADAE

ADAE

ADAE

ADAE

ADAE

ADAE

ADAE

USUBJID

SUBJID

SITEID

DOSEAONU

DOSEAEON

COUNTRY

ASTTM

ASTDT

AETERM

Unique Subject Identifier

subject identifier for the study

Study Site identifier

Study Drug Dose at AE Onset Units

Study Drug Dose at AE Onset

Country

Analysis Start Time

ADAE.DOSEAEONU

ADAE.DOSEAEON

ADAE.ASTTM

ADAE.ASTDT

Reported Term for the Adverse Events

Analysis Start Time

x

Filter active: ADAE Domain


DATACOLLECTION






ADaM


Filter active: ADEA Computation..

Domain Variables Computational Algorithm

Reference Description

ADAE.AENDT Equals to % SDTM_DATE_VARIABLE % transformed into %DATE_NUMERIC_FORMAT% when length (%SDTM_DATE_VARIABLE%) > 9

x

ADAE.ADURN Equals to ADAE.AENDT – ADAE.ASTDT + 1.

ADAE.DOSEAEON Equals to EX.EXDOSE where the numeric version of EX.EXSTDTC <= ASTDT <= the Numeric version of EX.EXENDTC.

ADAE.DOSEAEONU Equals to EX.EXDOSU where the numeric version of EX.EXSTDTC<= ASTDT <= the Numeric version of EX.EXENDTC.

ADAE.DOSEAEON Equals to ‘’DAYS’’ADAE.DOSEAEON

Filter active: ADAE Variables


DATACOLLECTION






ADaM

Domain Computational AlgorithmSDTMRelated metadata: DomainCDASHDCM Figures ListingsTables

Domain Variables Computational Algorithm

Reference Description

xADAE.DOSEAEON

Equals to EX.EXDOSE where the numeric version of EX.EXSTDTC <= ASTDT <= the Numeric version of EX.EXENDTC.

Filter active: DOSEAEON

AESTDTC

EXDOSE

EXTDTC

EXENDTC

Start date/Time of Adverse Event

Dose per administration Derived

CRF

CRF Perm

Name Label Origin Role Core

Start date/Time of treatment

End date/Time of treatment

CRF

Record Qualifier

Timing

Timing

Timing

Exp

Exp

Exp

x

Variables

AE

AE

EX

EX

AESTDAT

AESTIM Start Time

Dose

Units

Domain Name Question

EXAMONT

EXAMONTU

Start Date

x

EX

EX

EX

EXENDAT

EXENTIM

EXSTDAT

End Date

End Time

Start Date

Variables

DATACOLLECTION



DATACOLLECTION




ANALYSISDomain VariablesADaM Computational Algorithm

Domain Variables Computational AlgorithmSDTMRelated metadata: Domain VariablesCDASHFigures ListingsTables

DCM’s

x

SHOPPING CART

DCM

<

<<< >>

ListingsTablesDCM

Domain Variables Computational Algorithm Domain Variables

Figures


Agenda

Introduction

Specify by Browsing


Call to Action


Specification, Execution

SDTMDatasets

ADaMDatasets

ADaMGenerator

TFLGenerator

TFLs

ADaM Standard Macros TFL Standard Macros

ADaM Metadata Analysis Results Metadata



User InteractionMetadataData

Study-Specific Input

Study Input Selector

Metadata-driven Script Generator

Selected TFLsLibrary Metadata

SDTMDatasets

ADaMDatasets

ADaMGenerator

TFLGenerator

TFLs

ADaM Standard Macros TFL Standard Macros


What is a Concept Map

Concept maps = diagram which include “bubbles” representing concepts/ideas/things and labeled arrows that represent the relationships between the concepts/ideas/things.

Advantage = easier to draw and more accessible than more formal modeling diagrams (e.g. UML diagrams)


Concept Map Legend

Type of statistical analysis required for an endpoint

Statistical Concept Computational Algorithm

Algorithm used to calculate some analysis variable or

parameter

SAS ScriptSAS script that implements

a standard, re-usable, computational algorithm

TFL Definition

Type of TFL used to represent some data or analysis results

Document produced within the Clinical Trial

Document

Healthcare Encounter

Administration to or visit with A healthcare facility or

healthcare provider.

Observation Result

A finding obtained by an observation.

A Specification for creating normalized datasets compliant

with CDISC standards.

CDISC DomainVariable

The name and/or label of an attribute when represented

as a column in normalized dataset

A defined point in time.

Time Point

Initiative Procedure

An invasive treatment or Diagnostic procedure.

An activity that administers A product to a subject

Substance Administration

A sample taken from aSubject or existing

Specimen for analysis.

SpecimenProduct

Anything made. Includes drugs and devices.

Terminology

Verbatim terms or vocabularyfrom a codelist or dictionary.

Identifiers and relative timingused to describe a concept

as it relates to the study.

Study Context

An activity with multiple classifications. Often has component sub-activities.

Composite Activity

An activity that takes a Sample for later analysis

Specimen Collection

Assessor

The person or organization that reports ab observation.

Observation

A test, examination, or other activity that gathers

Information about a subject.

Other Activity

An activity not otherwise classified.


Tabulation concept map


Analysis Concept Map


depicted by

presented in

for parameter

calculated using

implemented by

defined as Defined as

meaning that

defined as defined as defined as defined as

meaning that meaning thatcalculated using

equalstaking as input implemented by

using

takes as input

equalsequals

equalsmeaning that

as

asdefined in

specified in

Primary Efficacy Endpoint

TFL

CSR Section

Statistical Analysis Plan

Protocol Mean change from baseline

Table comparing drug and placebo arms on visit 1 seperated by age groups

Temperature PARAMCD

MT.ADVS.CHG

AVAL

BASE

mt_advs_chg,sas

Analysis set Selection Criteria Statistical Method Analysis Sub -Groups Data Handling Rule

Last Observation Carried Forward

DTYPE

LOCFmt_adsl_agegr.sasADSL.AGE

MT.ADSL.AGEGR1

18 to 65; over 65ANOVAVisit 1Efficacy Population

ADSL.EFFFL AVISIT

Visit 1Y

TEMP corresponds to VSSTRESN where VSTESTCD=TEMP

has

has

STUDYID

VISIT

VISITNUM

USUBJID

VSTESTCD

VSORRESU

VSDTC

VSTPT

VSTPTNUM

VSORRES

SUPPVS

VSSTRESC

C25206

C25206 TEMP

temperature

number

C

C42559

Study

number

visit

Temperature test

Temperature measurement

clinical significance

timepoint

stored in has

has

stored in equal to

stored in

stored in

stored in

stored in

stored in

results in

participates in

corresponds to

results in

reports

Subject

Assessor

clinical significance result

result unit

date

code

name

ID

assesses

stored in

equal to

equal to corresponds to stored in

corresponds to stored in

VSTEST

VSSTRESN

stored in

stored in

taken from

has

Can be proven by

Hypothesis

The Tabulation and AnalysisConcept Map will link perfectly

TabulationConcept Map

Analysis Concept Map


Simplified view

Computational Algorithm

Data Collection

Analysis

SDTMADaM

SDTM VLM Value

SDTM VLM Names

SDTM Variables

CDASH Variables

(e) CRFCode values

Analysis Variables

Analysis Datasets

ADaM Parameter Value

ADaM Parameter Names

Analysis Results

TFLs

Endpoints

Code List

Domain

Only Semantic Interoperability can achieve real benefits from clinical data standards.

Colo

r Co

ding


Tabulation Implementation Layer

has

has

STUDYID

VISIT

VISITNUM

USUBJID

VSTEST

VSTESTCD

VSORRESU

VSDTC

VSTPT

VSTPTNUM

VSORRES

SUPPVS

VSSTRESNVSSTRESC

C25206

C25206 TEMP

temperature

number

C

C42559

Study

number

visit

Temperature test



timepoint

stored in

stored in

stored in has

has

stored in equal to

stored in

stored in

stored in

stored in

stored in

results in

participates in

corresponds to

results in

reports

Subject

Assessor


result unit

date

code

name

ID

assesses

stored in

equal to

equal to corresponds to

stored in

stored in

corresponds to

SDTM Variables

Protocol

Controlled Terminology


Analysis Implementation Layer

has

can be proven by

depicted by a

presented in

for parameter

calculated using

implemented by

defined as

meaning that




using

taken as input

equalsequals

equalsmeaning that

as

asdefined in

specified in

Study

hypothesis


TFL

CSR Section




Temperature PARAMCD TEMP

MT.ADVS.CHG

AVAL

BASE

Mt_advs_chg.sas



DTYPE

LOCFMt_adsl_agegr.sasADSL.AGE

MT.ADSL.AGEGR1


ADSL.EFFFL AVISIT

Visit 1Y

SAS Code

Protocol


ADaM Variables

SAP/CSR



Mean change from baseline


Temperature PARAMCD

MT.ADVS.CHG

Mt_adsl_agegr.sas

ADSL.EFFFL AVISIT


Display Table 10-1.01 Primary Endpoint Analysis: ADVS-Temperature - Summary at Visit 1 - LOCF (Efficacy Population)

Analysis Result Dose Response Analysis for ADVS.TEMP changes from baseline

Analysis Parameter(s) PARAMCD = "TEMP"

Analysis Variable(s) CHG (Change from Baseline)

Analysis Reason SPECIFIED IN SAP

Analysis Purpose PRIMARY OUTCOME MEASURE

Data References (incl. Selection Criteria) ADVS [PARAMCD = "TEMP" and AVISIT = "Visit 1" and EFFFL = "Y"]

DocumentationLinear model analysis of CHG for dose response using randomized dose (0mg for placebo; 10mg for low dose; 50mg for high dose) and site group in model. Used PROC GLM in SAS to produce p-value (from Type III SS for treatment dose). SAP Section 10.1.2

Programming Statements

[SAS version 9.2]

proc glm data = ADVS; where EFFFL='Y' and AVISIT='Visit 1' and PARAMCD="TEMP"; class AGEGR1; model CHG = TRTPN AGEGR1;run;

Implementation example:Analysis Results Metadata


Temperature Mean change from baseline

PARAMCD

MT.ADVS.CHG


Mt_adsl_agegr.sas

ADSL.EFFFL AVISIT


Agenda

Introduction

Specify by Browsing


Call to Action


Gap Analysis 1

SDTM

VersionSDTM DomainSDTM VariableCode ListValue Level MetadataComputational AlgorithmData Handling Rules

ADaM

VersionADaM DomainADaM VariableCode ListComputational AlgorithmAnalysis Sub GroupsSAS Code

CDASHStandard

CRF Data Validation RuleData Collection ModuleCRF Template

VersionCDASH DatasetCDASH VariableCompletion GuidelinesImplementation Guidelines

Protocol& SAP

Clinical Study ProtocolStatistical Analysis PlanStatistical Requirements

Statistical Method

Analysis Results

Display Display LayoutFootnoteTitlesAnalysis RuleOutput Specification RuleSAS Code

Clinical Study Report

Clinical Study ReportCSR Section

Industry StandardNo industry Standard

Color CodingNot everything is standardized (yet)


Gap Analysis 2

SDTM Variables

SAS Code

Protocol


ADaM Variables

SAP/CSR



TFL

CSR Section




Temperature PARAMCD

MT.ADVS.CHG

AVAL

Mt_advs_chg,sas



DTYPE


MT.ADSL.AGER1


ADSL.ETTFL AVISIT

Visit 1Y

TEMP VSSTRESN where VSTESTCD=TEMP

BASE

STUDYID

VISIT

VISITNUM

USUBJID

VSTESTCD

VSORRESU

VSDTC

VSTPT

VSTPTNUM

VSORRES

SUPPVS

VSSTRESC

C25206

C25206 TEMP

temperature

number

C

C42559

Study

number

visitTemperature test



timepoint

Subject

Assessor


result unit

date

code

name

ID

VSTEST

VSSTRESN

has

has

VSTESTCDTEMP

stored in has

has

Is stored in Is equal to

stored in

Is stored in

stored in

stored in

stored in

results in

participates in

corresponds to

results in

reportsassesses

stored in

equal to



VSTEST

stored in

stored in

as

depicted by a

presented in

for parameter

calculated using

implemented by

defined as

meaning that



equalstaking as imput implemented by

taken as input

equalsequals

equalsmeaning that

as

defined in

specified in

Corresponds to

taken from

using

has

Can be proven by

Hypothesis

Current metadata is tabular

We need concept metadata


depicted by

presented in

for parameter

calculated using

implemented by

defined as Defined as

meaning that




using

takes as input

equalsequals

equalsmeaning that

as

asdefined in

specified in


TFL

CSR Section




Temperature PARAMCD

MT.ADVS.CHG

AVAL

BASE

mt_advs_chg,sas



DTYPE


MT.ADSL.AGEGR1


ADSL.EFFFL AVISIT

Visit 1Y

TEMP corresponds to VSSTRESN where VSTESTCD=TEMP

has

has

STUDYID

VISIT

VISITNUM

USUBJID

VSTESTCD

VSORRESU

VSDTC

VSTPT

VSTPTNUM

VSORRES

SUPPVS

VSSTRESC

C25206

C25206 TEMP

temperature

number

C

C42559

Study

number

visit

Temperature test



timepoint

stored in has

has

stored in equal to

stored in

stored in

stored in

stored in

stored in

results in

participates in

corresponds to

results in

reports

Subject

Assessor


result unit

date

code

name

ID

assesses

stored in

equal to



VSTEST

VSSTRESN

stored in

stored in

taken from

has

Can be proven by

Hypothesis

BiomedicalConcept Map

AnalysisConcept Map

Analysis concepts aremissing (today)

Gap Analysis 3


Semantic Technology

Conclusion

Clarity Structure Complete Terminology Machine readable Reusable

Impact Assessment

Automation End-to-End

Traceability

Business Outputs

Exports to Support Today’s Process

Is this something the industry wants?Effort is needed on an industry scale

Source: Dave Iberson-Hurst CDISC Standards and the Semantic Web Slides 12th October 2015 PhUSE Annual Conference, Vienna


Thank you


Peter Van Reusel | Managing Director | +32 476 54 59 17 | [email protected]

mailto:[email protected]

understanding the potential of share

Documents