Strategies for Implementing CDISC

2 0 1 1 FA L L B I O M E T R I C S W E B I N A R S E R I E S

Strategies for Implementing CDISC

Dec. 13, 2011 Presented by Thomas Kalfas

Thomas Kalfas
 Director, Global Biometrics Technical Operations
 24+ years of technical data management and
biostatistical programming experience in pharma/
biotech/CRO industries
 Member: CDISC IAB/CAB, CDISC SDS and CDISC
Validation teams since 2006
 Focus on technical operations, standards development
and implementation
2011 FALL BIOMETRICS WEBINAR SERIES

CDISC Acronyms/Definitions
3

 ADaM – Analysis Data Model; statistical analysis data
standards
 CDASH – Clinical Data Acquisition Standards Harmonization;
Case Report Form (CRF) standards
 CDISC – Clinical Data Interchange Standardization Consortium;
organization advocating global standards for clinical trial data
 Define Doc aka Define.xml aka CRT-DD – dataset
specifications; a dynamic table of contents for the submission
datasets (SDTM and/or ADaM)
 SDTM – Study Data Tabulation Model; clinical trial data
standards

Objectives
4

 Topics will include a brief review of CDISC,
implementation challenges, and insight into the best
timing for implementation.

 We will not be going in-depth into actual conversions
or creation of specific CDISC domains, but rather
focusing on high-level requirements, issues and
feedback from the FDA, common approaches for
standards implementation, and our recommendations.


Today’s Topics
5

1) Business Justification for CDISC
2) Current CDISC Status
3) Methods for Producing CDISC Deliverables
– Common Errors
– Timing Considerations and Best Methods
– Recommendations

4) Summary


Business Justification for CDISC

“ The Center for Drug Evaluation and Research
(CDER) is strongly encouraging sponsors to
submit data in standard form as a key part of
“
its efforts to continue with advancement of
review efficiency and quality.
-CDER, May 2011


Origins
7

Critical Path Initiative (2004)
 Streamline the submissions/review process, shorten the
review cycles, decrease costs, and allow for easier
data warehousing
 FDA asked sponsors to voluntarily use SDTM and
ADaM standards for the e-submissions
 Powerful tools/software to be developed (based on
these standards) to assist reviewers with their
evaluations


8

FDA encouraging sponsors to continue
the learning curve on CDISC standards

– No submission will be – Ultimately (~1-2 years),
rejected for non- a minimum level of
compliance compliance will be
expected for all
– If compliant, then review submissions, and if not
(after training completed met, then these “CDISC-
and reviewers have like” submissions would
become familiar with be treated as non-CDISC
format/tools) should be or “legacy” data (and
quicker would take much longer
to review)


9

Process Improved Cost Value-
data
efficiencies quality savings added

CDISC


Cost Savings
10

 Estimated 30% clinical trial efficiencies gained (project startup,
cleaning, programming and analysis)
– Potentially reduce the study lifecycle by 8 months resulting in savings of
approximately $9 billion annually
Cycle Time in Months

8 Months
Cycle Time
Reduction/Trial

 Estimated thata restricted implementation of these standards at tail-
end submission stage would decrease the potential return by only 60%
2011 FALL BIOMETRICS WEBINAR SERIES Source: Gartner&CDISC (November 2006))

Current CDISC Status
 FDA Trends
 CDISC Updates
 Premier Research and CDISC


FDA CDISC Trends
12

 Committed to Standards Initiative (2009-2013) and
actively working to “refine and maximize utility of
CDISC standards”
 Both CDER and CBER accepting/requesting SDTM
*and* ADaM formatted datasets since December 2010
 Number of eSubmissions has increased by ~2K per
month since 2010
 CDER now tracking number of submissions (SDTM and
ADaM) on their website

FDA CDISC Trends
13

Source: http://www.accessdata.fda.gov/FDATrack/track?program=cder&id= CDER-
OB-NDAs-BLAs-and-Efficacy-Supplements-with-Electronic-Datasets-Available

CDISC Updates
14

 Working closely with the FDA to:
– Determine “Supp-qual” data needed to be added to main domains
– Have reviewers comfortable with the Implementation Guide (IG)
– Build review automation for standard analysis
 Providing further guidance to the industry to help navigate gray
areas within the standard

 Developing therapeutic standards, i.e., supplements to the IG to
address specific implementations
 Developing a set of Medical Device domain standards
 Discussing/clarifying type/location of derived variables (SDTM
vs. ADaM)

Premier Research and CDISC
15

 Spending more time with our clients discussing the benefits
of early-stage CDISC implementation

 Premier has developed CRF and DB standards in line with
CDASH and SDTM. Use of Premier Standards enables our
operational staff (CRF- and DB-developers and
programmers) to utilize these standards to help realize the
efficiencies anticipated by Gartner in their projections of
industry savings.

 Number of early-stage CDISC (SDTM) projects for 2011
has tripled that of 2010 (~40% of our active projects)


Premier Research and CDISC
16

 Spike in requests to add SDTM as a requirement for
existing “legacy” projects
 Also seeing an increase in requests for:
– Early-stage feeds into a ISS/ISE-like datamart
– CDISC training
– Consulting services for implementation of CRF, DB and
programming standards for existing and new clients


Methods for Producing
CDISC Deliverables
 Common Errors
 Timing Considerations and Best Methods
 Recommendations


Common Errors (per FDA)
18

 “SDTM-Like” submissions  Non-compliant define.xml
 Traceability issues  Define doesn’t validate
 Invalid ISO 8601 date format  Required variable not found
 Inconsistent value for standard units  Invalid value for MedDRA Term
 All dates in the SDTM domains must conform to the ISO 8601 format
 Begin Date must be ≤ End Date (e.g., CM or AE start dates that come after
the end dates)
 For a given test, all values of --STRESU should be the same. In some cases -
-TESTCD may not be sufficient to uniquely indentify a test

For a full list, go to:
 http://www.fda.gov/downloads/Drugs/DevelopmentApprovalProcess/Form
sSubmissionRequirements/ElectronicSubmissions/UCM254113.pdf
 http://www.fda.gov/BiologicsBloodVaccines/DevelopmentApprovalProcess/
ucm209163.htm

Common Methods
19

Study Close DB
Start-up Study Conduct Out Lock

Late-Stage
Conversion
Early-Stage Mid-Stage
Implementation Conversion


Common Methods:
Late-Stage Conversion (1)
20

Usually as part of an NDA submission, but now being
requested for individual or groups of studies earlier
than the traditional NDA activities
 Cost-effective? Might seem so, but…
 Compliance issues common as this could take place months
or even years after the study had completed (dependent
on the quality/compliance issues introduced at the protocol
and CRF layers)
 Traceability issues (it is critical that the data is traceable
from the CSR to the analysis datasets to the SDTM
datasets to the raw datasets to the CRFs)

Common Methods:
21

 DB is locked!!!

 Cleaning of DB may not have incorporated all SDTM
compliance checks, e.g., start dates must be less than or
equal to stop dates, etc.
 Aside from the database, what else has been produced
that will now need to be reconciled against the “new”
SDTM datasets? Analysis datasets? TLG’s? ISS/ISE? CSR?

 The further along you are with the study, the more work
necessary to ensure traceability


Common Methods:
22

Need to:
Determine need for standardization of values/units, e.g., labs, and
coding dictionaries (if multiple studies, should have same version of
dictionary)
Completely document steps needed to produce SDTM and
ADaM…you’ll need not just for the conversion, but also for the
Define Docs
Fully assess risk/impact of any review/compliance findings on
downstream deliverables
Documentation is critical (Annotated CRFs, Dataset Specifications,
Code Lists, Change Logs, Define Docs)
Reproduce numbers from your CSR! Need to show that the
analysis/results can be reproduced from SDTM

Common Methods:
23

Need to (continued):
Maintain Change Logs to track programming changes (in addition to
maintenance of your “living” documents, i.e., SDTM Dataset
Specifications -> Define Doc
Reproduce numbers from your CSR! Need to show that the
analysis/results can be reproduced from SDTM
– If significant issues, then need resolution
– If differences can be explained, then consider adding text explanation
to the “Reviewer Notes” portion of the Define Doc

Same as above for your compliance checks, i.e., any oddities need
to be explained in the reviewer notes


Common Methods:
Mid-Stage Conversion
24

Usually as a late CDISC consideration in preparation
for NDA activities
 Same issues/challenges as for the Late-Stage Conversion;
however…

 DB is active, not locked!

 So, while there are most likely still conversion challenges
with non-standard CRF/DB setup, it is now easier to
address compliance/review findings as part of you normal
DM/cleaning processes!


Common Methods:
Early-Stage Implementation (1)
25

Standards compliance from the very start
 Protocol:
– Controlled Terminology, e.g., AE Severity

 CRFs:
– CDASH: for items not covered by SDTM directly, e.g., date
component fields
– SDTM: want to get as close to 100% SDTM compliance as
possible from the CRFs and DB
– Controlled Terminology → reduces the need for additional
programming/mapping/conversions (and QC)


Common Methods:
26

 Database:
– Standard modules
– Standard checks (cleaning and compliance)
– Standardization of values/units, medical coding, etc.

 Programming:
– Still requires thorough documentation (Annotates, Specs,
Define Docs), but development/maintenance is much easier
as standard templates can be used
– Standard programs refine the CDISC-like (both SDTM and
ADaM) datasets into 100% compliant datasets
– Standard programs used to load into ISS/ISE, produce
standard TLGs, etc.

Common Methods:
27

 Efficiencies are realized due to standards adherence

 Traceability is inherent within this process due to a more
traditional SDLC methodology (i.e., specs first, then
development, then validation, then these feed into the next
deliverable, e.g., ADaM, ISS/ISE, and TLGs)

 Value-added: reliance on standards, allows for CDISC
outputs to be produced earlier in the study “life-cycle” and
made available for data warehousing, data mining (as
ISS/ISE) and DSMB/DMC requirements


Summary
 CDISC SDTM & ADaM standards are gaining traction
 Requirements for CDISC datasets getting stronger
 While late- and mid-stage conversions can and will
continue to be done, the FDA cautions against this in
favor of early-stage CDISC standards implementation
 Early-stage implementations of CDISC not only allow
for efficiencies to be realized, but also make value-
added scenarios possible

Webinars Series
29

Listen to past webinars:
▪ The Role of Data Monitoring Committees
Speaker: Ron Kershner, Ph.D.

▪ IVR/IWR…More than just Randomization
Speaker: Ryan Michaud

▪ Streamlining Data Management Start-up
Speaker: Cheryl Silva


Questions?

Thomas Kalfas
Director, Global Biometrics Technical Operations

Telephone: 847.420.2622
thomas.kalfas@premier-research.com


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