aimee gott – r consultant [email protected] the rise and rise of graphic expectations...
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Aimee Gott – R [email protected]
Who are Mango?
• Provide data science and analytic implementation services
• Premier providers of R Services in the world today
• Private company founded in 2002• Offices in UK & China• Global Team of ~50 • ISO 9001 Accredited
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Aimee Gott – R [email protected]
My Background
• Trained as a Statistician• Worked at Mango since 2012• Worked on many projects with the Pharma
Industry• Training• Analysis• Application Development• Validation of R
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Aimee Gott – R [email protected]
1970's
• SAS requires hundreds of punch cards• S in its infancy• Graphics usage limited
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Aimee Gott – R [email protected]
1980's
• SAS/GRAPH released• Initial interactive graphics in S-PLUS
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Aimee Gott – R [email protected]
2002
• Mango founded• Started working with Pharma companies using S-
PLUS• R being more widely used, lots of support for
graphics systems
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Aimee Gott – R [email protected]
Late 2000's
• ggplot2 is first released in R• Graphics being widely used• R starting to be used in Pharma, primarily for
graphics
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Aimee Gott – R [email protected]
The iGeneration
• Graphics are everywhere• They have to be clear• They have to look good• They are interactive• Information is easy to access
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Aimee Gott – R [email protected]
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Aimee Gott – R [email protected]
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Aimee Gott – R [email protected]
What is Expected?
• Sophisticated Graphics• Interactive• Interactive documents
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Aimee Gott – R [email protected]
Challenges in Pharma
• Graphics for decision making• Analysis time shrinking• Multi-technology• Graphics must be reproducible?
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Aimee Gott – R [email protected]
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Aimee Gott – R [email protected]
Example 1
• Area: PreClin - FTiH• Challenge: Traceability of Decisions• Solution: Interactive decision chart
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Aimee Gott – R [email protected]
What was the Challenge?
• Teams use their "favourite" way to make a decision
• Difficult to trace what data was used• Difficult to re-generate graphics
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Aimee Gott – R [email protected]
Solutions
• Single solution for presenting data to safety board• Consistent production of informative graphics• Auditable repository of graphics
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Aimee Gott – R [email protected]
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Aimee Gott – R [email protected]
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Aimee Gott – R [email protected]
Example 2
• Area: Trial Reporting• Challenge: Reduced time for reporting, lots of
graphics• Solution: Automated reporting
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Aimee Gott – R [email protected]
Challenge
• Very short timelines for generating reports• Reports contain lots of graphics• Data often changes at the last minute
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Aimee Gott – R [email protected]
Dynamic Reporting in R
• Report + code in one file• Graphics re-generated automatically• Data can be changed and re-run
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Aimee Gott – R [email protected]
Example 3
• Area: Clinical Reporting• Challenge 1: Consistency and quality• Challenge 2: Multiple Tools• Solution: SAS to R link
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Aimee Gott – R [email protected]
Requirements
• High quality graphics• Consistent• Easily reproducible
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Aimee Gott – R [email protected]
Solution
• Interface to R from SAS• R based library of standard graphics
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Aimee Gott – R [email protected]
Example 4
• Major Pharma company in Philadelphia• Challenge: Traceability of interactive graphics• Solution: Built a custom GUI that generates a
script
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Aimee Gott – R [email protected]
Challenges
• Traceability of decisions• Interactive graphics for decision making• Tool for non-programmers
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Aimee Gott – R [email protected]
Code Generating Interface
• Users interact with custom GUI• Graphics updated based on selected options• All code generated for traceability• Graphics completely reproducible• Decision making tracked
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Aimee Gott – R [email protected]
Future Challenges?
• New tools to learn• Better graphical awareness• New coding standards• New tools to validate
• R + shiny apps• JavaScript
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Aimee Gott – R [email protected]
Summary
• Pharma industry leading stats computing• Graphics a huge part of reporting• Many open questions about interactive graphics...