h. lundbeck a/s16-jan-141 stdm generation in lundbeck - from source to target
TRANSCRIPT
H. Lundbeck A/S 10 Apr 2023 1
STDM generation in Lundbeck - From Source to Target
H. Lundbeck A/S 10 Apr 2023 2
Agenda
• Background• Architecture & Tools• Design and Implementation of the SDTM
conversion framework• Evaluation• Plan for further delvelopement• Questions/Discussion
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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.
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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
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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
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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
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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
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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)
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Architecture
Rave
Datafax
eDM/eDE
Partners
CROs
ETL ToolSDTM Interface
Reporting Tool
SADS
SOURCE TARGET
SAS-Di Studio
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Design and Implementation
• The shortest distance between two points is a stright line:
A B
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Design and Implementation
• Divide the line into stages:
SOURCE
TARGET
Stage 1 Stage 2 Stage 3 Stage 4
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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
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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
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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
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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)
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Design and Implementation
• Depictured with work-demanded proportions:
SOURCE
TARGET
Stage 1
Stage 2
Stage 3
Stage 4
Define
Apply
Derive
Structure
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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
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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)
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…and some memories
’Computer Charlieer en helt almindelig mand& han ta'r toget ind til City hver daggemmer sit ansigt så godt han ka'bag et slør fra dagens første Havannahan ligner til forveksling alle andre i kupé'ender til gengæld ligner koksgrå lig& sidder pænt på række som på bunden af en gravmens station efter station bare suser forbi’
’I en blågrå kupe’ af C.V. Jørgensen
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Thanks to …
• H. Lundbeck A/S• Nordic CIDSC User Group • Danish Association for Data Managers
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Questions/Discussion
?