stdm generation in lundbeck from source to target
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STDM generation in Lundbeck - From Source to Target. Agenda. Background Architecture & Tools Design and Implementation of the SDTM conversion framework Evaluation Plan for further delvelopement Questions/Discussion. Background. This is a presentation about:

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agenda
Agenda
  • Background
  • Architecture & Tools
  • Design and Implementation of the SDTM conversion framework
  • Evaluation
  • Plan for further delvelopement
  • Questions/Discussion

H. Lundbeck A/S15-Sep-142

background
Background
  • This is a presentation about:
    • The considerations and experiences Lundbeck has had when implementing their SDTM conversion process
  • This a not a presentation about
    • Hardcore SAS macros
    • A detailed explaination of the SDTM data model.

H. Lundbeck A/S15-Sep-143

background1
Background
  • The SDTM conversion project was initated and developed in 2007-2008 as a part of the Lundbeck eClinical program.
  • Started with one programmer under the supervision of a project lead.
  • Current status: the SDTM conversion process is rolled out in Line of Business (the CDO Department) and involves five programmers and one project manager

H. Lundbeck A/S15-Sep-144

background2
Background
  • The goal was to implement a framework for converting any clinical study data (source) into an SDTM data format (target)
  • Benefits of framework:
    • Extend the use of industry standards (CDISC/SDTM) to the clinical data process flow
    • Eliminate data transformation / alignment both within and across studies and from external sources
    • Enable systematic and extensive use of current and historical data
    • Simplify data interchange with partners and regulatory authorities

H. Lundbeck A/S15-Sep-145

background3
Background
  • Source data from four Rave studies were selected as the basis for the implementation of the framework
    • Lundbeck project LuAA21004, studies 11984A, 11984B and 11985A and Lundbeck project LuAA24530: study 11918A

H. Lundbeck A/S15-Sep-146

background4
Background
  • The experiences from converting the first four studies will lay the basis for a Lundbeck SDTM data model
    • Domain definitions of all domains currently used in the SDTM conversion process
    • Convension rules /Algorithms
    • CDISC/Lundbeck Controlled Terminology

H. Lundbeck A/S15-Sep-147

architecture
Architecture
  • Available tools for the SDTM conversion:
    • Clinical study data (a lot!)
    • An ETL-tool for data manipulation
    • The SDTM Implementation Guidelines version 3.1.1/3.1.2
    • CDISC Controlled Terminology
    • In-house experience of a previously SDTM conversion project (Gaboxadol)

H. Lundbeck A/S15-Sep-148

architecture1

SDTM Interface

Rave

Reporting Tool

Datafax

eDM/eDE

ETL Tool

SOURCE

SAS-Di Studio

CROs

SADS

Partners

Architecture

TARGET

H. Lundbeck A/S15-Sep-149

design and implementation
Design and Implementation
  • The shortest distance between two points is a stright line:

A

B

H. Lundbeck A/S15-Sep-1410

design and implementation1
Design and Implementation
  • Divide the line into stages:

SOURCE

TARGET

Stage 1

Stage 2

Stage 3

Stage 4

H. Lundbeck A/S15-Sep-1411

design and implementation2
Design and Implementation
  • Stage 1(Define):
    • Define the mapping from source to target
      • Annotate CRF according to the SDTM format
    • Implement the mapping
      • Build up data dictionaries (SAS format libraries)

Example

H. Lundbeck A/S15-Sep-1412

design and implementation3
Design and Implementation
  • Stage 2(Apply):
    • Apply the mappings to the source data
      • Apply the SAS user defined formats
    • Set the value of general variables
      • E.g. STUDYID, DOMAIN, VISIT, VISITNUM, VISITDY
        • A SAS macro library

H. Lundbeck A/S15-Sep-1413

design and implementation4
Design and Implementation
  • Stage 3(Derive):
    • Derive standard values based on the original collected result(Relevant for the Findings Observation Class).
      • E.g. the variables --STRESC and STRESN and standard units in –STRESU
    • Derive other values.
      • E.g. the variables --DY, VSTESTCD=BMI, --SEQ

H. Lundbeck A/S15-Sep-1414

design and implementation5
Design and Implementation
  • Stage 4(Structure):
    • Create the final structure on datasets
      • E.g. create the supplemental qualifiers domains.
    • Create the CO (Comments Domain)
    • Create the Trial Design Domains (TI, TE, TV,TS,TA)

H. Lundbeck A/S15-Sep-1415

design and implementation6
Design and Implementation
  • Depictured with work-demanded proportions:

Derive

Define

Stage 3

SOURCE

TARGET

Stage 1

Stage 2

Stage 4

Apply

Structure

H. Lundbeck A/S15-Sep-1416

evaluation
Evaluation
  • Evaluation of the benefits:
    • Extend the use of industry standards (CDISC/SDTM) to the clinical data process flow
    • Eliminate data transformation / alignment both within and across studies and from external sources
    • Enable systematic and extensive use of current and historical data
    • Simplify data interchange with partners and regulatory authorities

H. Lundbeck A/S15-Sep-1417

further development
Further Development
  • Implement the WebSDTM validation checks
  • Development and implementation of a CDASH library
    • Greater transparency in the data flow
  • SDTM knowledge/experience sharing between companies (Network Groups)

H. Lundbeck A/S15-Sep-1418

and some memories
…and some memories

’Computer Charlie

er en helt almindelig mand

& han ta\'r toget ind til City hver dag

gemmer sit ansigt så godt han ka\'

bag et slør fra dagens første Havanna

han ligner til forveksling alle andre i kupé\'en

der til gengæld ligner koksgrå lig

& sidder pænt på række som på bunden af en grav

mens station efter station bare suser forbi’

’I en blågrå kupe’ af C.V. Jørgensen

H. Lundbeck A/S15-Sep-1419

thanks to
Thanks to …
  • H. Lundbeck A/S
  • Nordic CIDSC User Group
  • Danish Association for Data Managers

H. Lundbeck A/S15-Sep-1420

questions discussion
Questions/Discussion

?

H. Lundbeck A/S15-Sep-1421

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