CDISC Implementation Strategies: Lessons Learned & Future Directions MBC Biostats & Data Management Committee 12 March 2008 Kathleen Greene & A. Brooke.

CDISC Implementation Strategies: Lessons Learned & Future DirectionsMBC Biostats & Data Management Committee

12 March 2008Kathleen Greene & A. Brooke Hinkson,BioMedical Operations, Genzyme Corporation

Agenda Take you on a journey through time to reflect on

Genzyme’s CDISC implementation strategies We will travel

Back in time to “The Past” Through “The Present” Into “The Future”

Questions & Comments

The Past: 2003-2006

Past Environment

Early SDTM Efforts

Introduction to SDTM Submissions

Outsourced end stage SDTM conversion submitted to FDA

Data Operations Submission Datasets: SDTM-like datasets

Create SDTM-like datasets from raw EDC data Data collection: Define new CRF standards

Incorporate SDTM variables into eCRFs

July 2005 First SDTM Submission Motive: Desire to comply with eCTD

Guidance Timeline: September 04 – April 2005

Provided listing CRTs and SDTM datasets to FDA SDTM datasets & define.xml never used by FDA

reviewers Outsourced:

Performed end-stage conversion (mapping & creation of SDTM datasets)

Created define.xml & annotated CRFs Scope: 41 domains; 28 SUPPQUALS

Submissions Lessons Learned First SDTM submission effort required significant

amount of unanticipated Genzyme effort Valuable lessons regarding implementing SDTM

Detailed knowledge of the study data Mapping exercise required cross functional team

Interpretation of standard There are implementation choices; no universal way all

companies should implement SDTM

Implementation standards Genzyme needs to create implementation standards and

governance of the standards

SDTM Flight Attempts Submission datasets:

• Create SDTM-like datasets from raw EDC dataData collection: Define new CRF standards

•Incorporate SDTM variables into CRFs

Why Attempts FizzledDatasets Initiative must be cross-functional

Change cannot be made in isolation; must have up and downstream agreement on new processes and deliverables

Did not have infrastructure to work with fully compliant SDTM datasets Conflicts with project timelines

Data Collection Competing with other initiatives

New version of Clintrial, EDC implementations, M&A’s Push submission requirements upstream

ODM

ODM Experiences Electronic Submissions

define.xml: submit case report tabulation metadata to FDA

Metadata Driven Study Authoring Begin establishing libraries of proprietary

and non-proprietary eCRFs Create vendor extensions to ODM

Generate visualizations that mirror EDCvendor’s application user interface & functionality

Import Genzyme defined ODM into vendorstudy architect tools

ODM Lessons Learned Metadata Driven Study Authoring

Make decisions regarding horizontal/vertical specifications

Successfully exchange study metadata (forms and workflow) with EDC vendors

Need infrastructure to successfully utilize tool Limited reusability of individual study CRF builds

across programs Not just anyone should define studies using the tool

Study modeler should have strong understanding of database design and CDISC SDTM & ODM

The Present: 2007 - 2008

Present Environment

Caption: The scaffolding took longer to assemble than the rocket

May 2007 Second SDTM Submission Motive: FDA requested SDTM for all domains

Jan 07 negotiated DM, AE & all SUPPQUALS Timeline: October 2006 – March 2007

Provided listing CRTs, CSR and CRFs to FDA in March May provided DM, AE, SUPPQUALS, define.xml and

annotated CRFs Descriptive documentation of our mapping process

SDTM datasets and define.xml were used by FDA medical reviewer for safety review

Outsourced: Performed end stage conversion (mapping & creation of

SDTM datasets) Created define.xml

Scope: 2 domains & 2 SUPPQUALS

Lessons Learned FDA requesting SDTM now!! Applied lessons learned from 1st experience to 2nd

project Weekly cross-functional meeting with vendor

Output failed WebSDM validation Validation failures identified at Genzyme We need to incorporate our submission requirements

upstream in data collection Not efficient implementation strategy to convert data to

SDTM so late in the clinical data lifecycle Creating extra work for stat. programming, stats. and esub

End stage conversion is expensive!!

CDISC Roadmap

CDISC Roadmap Purpose To present a clear and complete picture of:

Where CDISC standards fit into the entire clinical data lifecycle

What activities must occur to integrate the standards into the processes and sub-processes within each lifecycle stage

Provide a common language and reference for further dialog, planning, design, and implementation of CDISC Standards.

Series of Initiatives Build a Complete CDISC Standards ImplementationData Flow #1: Late-Stage

Conversion

Data Flow #2: Mid-Stage Conversion

Data Flow #4: CDISC Standards inin Trial Design

Provide SDTM data to FDA

Data Flow #3: Standards in Collection,Processing & Storage

Submit (as SDTM) the collected data on which analysis is based

Collect, process & store data according to standards

Extend standards-based metadata-driven data flow further upstream into trial design

Data Flow Strategy Meet regulatory current requests and soon-

to-be requirements as soon as possible Integrate CDISC standards more broadly and

deeply into business processes Develop clinical data based upon CDISC

standards instead of converting the data to CDISC standards

Fully gain operational efficiencies from the use of standards

Metadata Repository Currently being defined Manage data about the data Serves as a central hub for automation of upstream

and downstream processes and tools i.e. protocol & CRF development, SAS TLF programming

Enforces standards Improves efficiency of process flow Enables reusability

Data Standards Team & Governance Data Standards Team is essential to

successfully implement CDISC standards Data Standards Team will develop,

implement, maintain, educate, communicate and govern the standards globally Standards cannot be viewed as optional

Implementation of data standards includes process changes, technology modifications and more subject matter expertise

Interim Initiatives

Triage Team Charter An interim committee to provide guidance

and support to a select number of studies for mapping & programming SDTM datasets Focus on end & mid-stage conversion activities Will not be involved with attempts to implement

standards at the protocol, CRF or database design lifecycle phases

Will be replaced by the global cross-functional governance body implemented as part of CDISC Roadmap Project

Triage InitiativeTriage Team*

Stat Programming (4) Data Management (4) CDDS (4)Biostats (4)

Project Specialists (1)

Initiative began Q4 07 will go through 2008 Completed 2 reviews so far Anticipate conducting 10 reviews in Q2 & Q3, with

additional studies to be determined in Q4 Currently considering expanding scope to include

review of CRF and database design

*Include Clinical, Coding, IT & RA as needed

Triage Lessons Learned Process works!

Highlights importance of cross-functional communication

Need additional cross-functional resources to support initiative

Need to operationalize training for new projects going through triage reviews

Implementation questions: obtain outside guidance, when needed

Parallel Efforts Converge

2008

Phase I: CDISC Roadmap

Phase II: Design Phase

CRF Standards

Triage Review

Phase III: Implementation

Participation in Standards Activities CDASH HIMSS SDTM Device Sub Team ADaM Working Group WebSDM User Group FDA ODM Pilot HL7 (Q2 2008) CDISC User Networks (BACUN)

The Future: 2009 & Beyond

Future Environment Visions is evolving Established standards and governance Adoption of a growing list of commercially

available standards based products Process improvements enabled by

technological advances Technological and operational infrastructure

to support a metadata driven end-to-end clinical data lifecycle

Sample Future Capabilities Ability to collect, store, analyze/report,

compile/submit data to FDA according to SDTM, in conjunction with other CDISC standards

Ability to integrate other, non-CDISC, standards ODM XML based interchanges of clinical data with

vendors (i.e. EDC vendors, labs, FDA, etc.) Metadata based protocol writing tools that establish

the framework for collection, analysis & reporting at the inception of the study design

Questions

email:

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