1. Leveraging R and Shiny for Point and Click ADaM Analysis
Ian Fleming and Fred Hofstetter
NJ CDISC User Group
January 2015

2. Agenda Lifecycle of a TFL The Promise of Standards
Overview of the Tool
ADaM Viewer Demonstration
Q&A

3. Lifecycle of a TFL

4. How does Pharma get here?

5. How do we get to a TFL? Protocol/Analysis Plan Data Collection
Protocol – Design and Endpoints
Analysis Plan – Details about the analysis
Data Collection
Case Report Forms
Collection of Data at sites in data capture systems
SDTM/ADaM
SDTM: Collection of raw data in data sets
ADaM: Creation of analysis data in data sets
TFL
Programmed Tables, figures, and listings
Included in study report or Integrated Summary

6. Extensive Process
Transitions from one form to another require significant effort
Significant amount of single use programs
Use of “Validated Systems”
Typically SAS Macro based infrastructure
Company specific infrastructure

7. The Promise of Standards
CDISC formed in 1997
“to develop and support global, platform-independent data standards that enable information system interoperability to improve medical research and related areas of healthcare.”

8. Jetpacks

9. Fundamental Question
Why hasn’t standards adoption brought the levels of efficiency that we were expecting
Tools?
The standards?
The Industry?
How do we explore the cause?

10. Rapid Prototyping Originated in manufacturing
Facilitates real world testing of solutions
Development occurs through iteration
De-facto standard methodology for web development

11. Rapid Prototyping
Design
Prototype
Test
Collect Feedback
Improve

12. The ADaM Viewer

13. Motivations Proof of Concept for Rapid Prototyping methodology
The ability to build standard tools off of ADaM data
The feasibility of R and Shiny for this type of work

14. Brainstorming Requirements
Ability to read in ADaM submission transport files
Ability to produce minimal set of standard summaries
Point and click interface – no end user programming required
No install needed
FREE!

15. CDISC Tools Lots of tools for some standards
CDASH (EDC systems, standard CRFs, etc.)
ODM (in/out from different data collection systems)
SDTM (validation, data visualization tools)

16. ADaM

17. Technology Options SAS? Java? R? Need license(s)
No quick/easy point and click without other tools
Extensive knowledge of SAS stack needed
Java?
Lot of coding
Steep skill set R?

18. R Early History – 1990 Ross Ihaka and Robert Gentleman
Department of Statistics at the University of Auckland
Open source statistical analysis software based on S programming language
Package based
Functional specific extensions

19. R: Early History
If you want to know more…

20. Shiny Web application framework for R Package installed in R
Interactive data analysis with real time code execution based on user input
Web technology without having to know web technology
Minimal Infrastructure requirements

21. Fully functional prototype
3 weeks later…
Prototyping complete
Fully functional prototype
Ability to read in ADaM submission transport files 
Ability to produce standard types of summaries
Point and click interface 
No install needed 

22. Demonstration

23. Results Rapid Prototyping  Standard tool for ADaM Analysis 
3 weeks from concept to full prototype
2 resources working in their spare time
Standard tool for ADaM Analysis 
Consistently create results across any ADaM data
R and Shiny 
Very easy to create and deploy

24. Additional Benefits
Ability for non-technical people to look at analyses
Removing roadblocks to data
Ad-hoc confirmation of current analyses
Easily extendable
Easily accessible
Low/No cost

25. Summary Rapid prototyping is a valuable tool
Next step: incorporate into our development process and interactions with users
R provides tools and packages for quick and powerful application development
Next step: how can we leverage this on a larger scale?
Able to produce easy point and click analysis for ADaM
Next step: Options for a universally available solution?

26. Questions