H. Lundbeck A/S 10 Apr 2023 1

STDM generation in Lundbeck - From Source to Target

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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

?