1. Shakul Hameed
FDA Data Standards: An Update

2. Overview
 Background on FDA Regulatory Submissions
 Challenge and Vision
 Data Standards
- Exchange Standards
- Terminology Standards
 The Janus Initiative

3. Background on FDA Regulatory Submissions
 FDA receives an enormous and growing amount of
data in a variety of regulatory submissions.
 For the last two years (2008 and 2009), FDA has
received 11,980 eCTD new applications and 1,44,778
eCTD Sequences
 The volume and complexity of drug-related information
submitted to FDA for regulatory review enormously
increasing.

4. Number of eCTD submission (2008-2009)

5. eCTD submission (2005-2009)

6. Original IND’s and Amendments

7. Original NDA’s and Amendments

8. How Regulatory Submissions are Processed in FDA

9. Submission Reviewing tools used by FDA
 Applications used by Reviewers and PMs:
- DARRTS (Document Archiving, Reporting &
Regulatory Tracking System)
- Global Submit Review (eCTD Review Tool)
- Adobe Acrobat, MS Office products
- Other specialized applications (various statistical
programs, JMP, etc)

10. The Challenge
 The FDA receives massive amounts of Regulatory data
(clinical research data)
–in extremely disparate formats
–using a variety of proprietary standards
 This makes it extremely difficult for reviewer to review the
submissions.

11. The Challenge
 Lack of data standards leads to:
– Creates delays and inefficiency in review process
– Increases variability in quality of reviews
– Reduces transparency and predictability
– Each reviewer is creating their own code to answer
a standard review question

12. The Challenge

13. Standardization needs to speak a common “Language”
Study #2 –dmg.xpt
Study #1 –demog.xpt Study #3 – axd222.xpt
Study #4 – dmgph.xpt

14. The Vision
 FDA has been working towards a standardized approach to
capture, receive, and analyze study data
 Standardization of study data is vital to integrate pre-
marketing study data and post-marketing safety data to
improve public health and patient safety
 Central to this vision is the creation of an enterprise data
infrastructure (Janus) within FDA to improve the
management of all structured scientific data

15. Data Standards
 Data standards can be divided into two categories:
–Exchange standards
–Terminology standards

16. Exchange Standards
 Exchange standards provide a consistent way to
exchange information.
 Exchange standards help ensure that the sending and
the receiving systems both understand unambiguously
what information is being exchanged
 For example, Structured Product Labeling (SPL) is an
exchange of product labeling information.
 Study data tabulation Model (SDTM) for exchange of
clinical study data this model was developed by CDISC.

17. Exchange Standards

18. Terminology Standards
 Terminology standards provide a consistent way to describe concepts.
- For example, the Unique Ingredient Identifiers (UNII),
developed by the FDA, provides a consistent way to describe
substances in foods and drugs.
- Vocabulary developed National Institute of Cancer to describe
terminology related to cancer.

19. Exchange and Terminology
 To develop these data standards, FDA is closely working
with HL7

20. Objectives of Data Standards
 Develop well-defined, publicly available data standards
 Ensure that data is submitted according to publicized standards
 Develop Advanced review tools so that reviewers can use
standardized data efficiently and effectively

21. The Janus Initiative
 Janus n : (Roman mythology)
 The Roman god of doorways,
passages and beginnings;
is depicted with two faces on
opposite sides of his head,
one looking towards the past
and the other looking towards
the future.

22. What is Janus?
 Collection of smart, interoperable databases
- clinical study database
- nonclinical study database
- other scientific databases
 Enterprise program* (project not a specific software application) this
would help FDA
- To enhance scientific computing
- To improve scientific knowledge
- To take regulatory decisions

23. Janus Solutions Components

24. Janus Solutions Components

25. FDA Target Flow for Future Submission Review

26. Current state of FDA Submission Review Process

27. FDA Target State of Submission Review Process

28. What will Janus do?
 Answer questions regulatory review and research
questions e.g., how many women have been enrolled in a
particular HIV drug study
 Provide common platform for mining data
- Across product types
- Across applications
- Across product lifecycle