1. The Importance of CDASH
Benjamin Vali, M.S.
Mathematical Statistician
Division of Biometrics III
CDER/OTS/OB
U.S. Food and Drug Administration

2. FDA Disclaimer
This presentation reflects the views of the authors and should not be construed to represent FDA’s views or policies.

3. Outline What do we do? What do we need? What do we get? CDASH
NDA/BLA Statistical Review of Efficacy
What do we need?
All Regulatory Reviewers at FDA/CDER
What do we get?
Current Approaches
CDASH
Focusing on The Best

4. What do we do? Statistical Review of Efficacy for NDA/BLA
Regulation Citation
21 CFR
....Reports of adequate and well-controlled investigations provide the primary basis for determining whether there is "substantial evidence" to support the claims of effectiveness for new drugs.

5. What do we do? Statistical Review of Efficacy for NDA/BLA
These “adequate and well-controlled investigations” pertain to the “Pivotal/Confirmatory” trials (i.e. Phase 3 trials) in a clinical development program
Consequently all aspects of these protocols and corresponding Statistical Analysis Plans (SAPs) need to be pre-specified
including how the clinical data are captured

6. What do we do? Statistical Review of Efficacy for NDA/BLA
Key Analysis Questions to ask during Marketing Application Review:
Are the key results correct?
Programmatically validate all major results during the filing review - IMPORTANT!

7. What do we do? Statistical Review of Efficacy for NDA/BLA
Programmatically validate all major results during the filing review
Reviewer needs
Protocol
SAP
Clinical Study Report (CSR)
Annotated case report form (aCRF)
Tabulation/clinical datasets with corresponding metadata/data definition file (SDTM, define.xml)
Analysis datasets with corresponding metadata/data definition file (ADaM, define.xml)
Reviewers’ guide (e.g., SDRG & ADRG)

8. What do we do? Statistical Review of Efficacy for NDA/BLA
Programmatically validate all major results during the filing review
Two-step process
Independent quality validation of Analysis Dataset Variables
Primary and Key Secondary Endpoints
Additional key subject-level analysis variables (e.g. analysis set flags)
Independent quality validation of Analysis Results
Inferential and/or Descriptive

9. What do we do? Statistical Review of Efficacy for NDA/BLA
Key Analysis Questions to ask during Marketing Application Review:
Are the results consistent?
Similar findings from each clinical study
Not sensitive to different approaches to analysis
Similar across study subgroups
Supported by results from secondary endpoints (which are generally related to primary endpoints)
Conduct further analyses with support and insight from Medical Officer

10. What do we need? All Regulatory Reviewers at FDA/CDER
Metadata
Traceability
Data Standards

11. Why Push for Traceability?
Full transparency for each data point throughout (end-to-end) clinical data lifecycle (from the source “to my computer”)
Need to make sure that the data were captured and analyzed in a way that is consistent with what was pre-specified in the protocol and SAP!

12. The Clinical Data Lifecycle
Source Documents
 Case Report Form (CRF)
 Clinical Database
 Analysis Database
 Tables, Listings, and Figures (TLFs)
 Clinical Study Report (CSR)
 Product Labeling
 Promotional Materials

13. Why Push for Data Standards?
Overall Improved Efficiency Analyzing Data
Consistent data structure
Consistent nomenclature
Analysis-ready
Standardize not only the data
Metadata
Representation of the relationship between data elements
Communication
SDRG and ADRG

14. Traceability vs. Data Standards
MY Regulatory Reviewer Perspective
Traceability is key
Traceability may be even more important than Data Standards (To Me)

15. And I know it is important to you…
Inherent in this principle is a need for traceability to allow an understanding of where an analysis value (whether an analysis result or an analysis variable) came from, i.e., the data’s lineage or relationship between an analysis value and its predecessor(s).
CDISC ADaM v2.1….

16. Traceability vs. Data Standards
What we often see submitted by Applicants
In the creation of standard data for submissions, traceability is (at times), compromised by post-data-capture mapping

17. Current Approaches

18. Approach #1 (Historical/Legacy)
… Legacy CRF  Clinical Database  Analysis Database  TLFs …

19. Approach #2 (Starting Out …)
SDTM
… Legacy CRF  Clinical Database  Analysis Database  TLFs …

20. Approach #3 (Getting Better …)
SDTM ADaM
… Legacy CRF  Clinical Database  Analysis Database  TLFs …

21. Approach #4 (Better and Better …)
SDTM  ADaM
… Legacy CRF  Clinical Database  Analysis Database  TLFs …

22. Approach #5 (Getting There …)
… Legacy CRF  Clinical Database  SDTM  ADaM  TLFs …

23. Approach #6 (The Best)
… CDASH CRF  SDTM  ADaM  TLFs …

24. CDASH CDASH - Clinical Data Acquisition Standards Harmonization
Best facilitates mapping to SDTM and creation of high quality CRF pages
Closest to 1-to-1 mapping in terms of structure, content and format
Pages for 16 out of 25 major SDTM domains are covered
Best Practices for creating other domain pages

25. CDASH Gets it right the first time
Done at data capture stage!
Eliminates the need for more downstream work
Streamlines everything on the Production and Regulatory Review sides
Standards development instituted as early as possible within the clinical data lifecycle
CDASH is the best example of how effective this can be

26. CDASH
The original premise, per DIA Meeting in January 2006, was for efficiency
Motivated by ACRO and FDA – Critical Path
Current Version 1.1 – January 18, 2011
We’ve come a long way since previous versions/previous era
Version 2.0 release imminent
Will begin development of therapeutic area specific CRFs

27. As We Move Forward…
Don’t map for the sake of mapping (i.e., from legacy datasets to SDTM and ADaM)
Approaches #2, #3 and #4
Unnecessary cost (time and money) to applicants
Includes time and money wasted for responding to subsequent Information Requests during the review cycle!
Strive for Approach #6 – no mapping required!

28. As We Move Forward… The principle behind this approach is key
More so than the CDASH standard itself
Implementation is everything!
More so than the content standards in general themselves
Must adhere to CDISC foundational principles

29. As We Move Forward…
Right now we are living during a “transitional” period (i.e., from legacy to standardized data), hence you need to do what you need to do
Don’t pull the e-brake while going at 150 mph
This doesn’t have to happen today
Just eventually…

30. Thank you for your attention!