Using R-shiny as a data reviewing and validation tool in clinical trials, 9/22/2018 Page 1
Using R-shiny as a data
reviewing and validation tool
in clinical trialsMarkus Niederstrasser, Novartis Pharma K.K.
Using R-shiny as a data reviewing and validation tool in clinical trials, 9/22/2018 Page 2
Disclaimer
The opinions expressed in this presentation
and on the following slides are solely those
of the presenter and not necessarily those of Novartis.
Novartis does not guarantee the accuracy or reliability
of the information provided herein.
Using R-shiny as a data reviewing and validation tool in clinical trials, 9/22/2018 Page 3
• Introduction
• Goals
• Requirements
• Software / Libraries
• Server / Client Setup
• Prototype demonstration
• Summary
• Questions
Agenda
Using R-shiny as a data reviewing and validation tool in clinical trials, 9/22/2018 Page 4
• Traditionally SAS has been widely used for statistical analysis
and reporting during the entire clinical drug development
cycle in the industry.
• Especially during the trial execution phase reviewing,
validating and reporting of "work in progress data“ is often
needed (for example DMCs, SMRs)
• Such time consuming tasks consists mainly of examining data
within the table viewer, and running short code parts in SAS
to select, group or summarize data for further investigations
and reporting.
Introduction
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• Relieve the burden of repetitive programming for such
set of deliverables
• Interactive data exploration
• Increase speed
• Have an easier access in terms of creation, usage and
sharing of data/results
Goals
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• Able to deal with "work in progress data”
• Reproducibility of results
• User friendly interface (point and click, self explaining)
• Provide multi user access
• Web based (Easy to install)
• Fast response time
• Export functionality (Results, Code)
Requirements
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Software/Libraries
• R - is an open source programming language and software
environment for statistical computing and graphics. The R
language is widely used among statisticians and data miners for
developing statistical software and data analysis.
https://en.wikipedia.org/wiki/R_(programming_language)
• Shiny library - is an open source R package that provides an
elegant and powerful web framework for building web
applications using R. Shiny helps to turn analyses into interactive
web applications without requiring HTML, CSS, or JavaScript
knowledge. https://www.rstudio.com/products/shiny
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Software/Libraries
• Haven Library - is an R package to facilitate the transfer of data
between R and SAS, SPSS, and Stata
• data.table - is an R package that provides an enhanced version of
data frames (for improved speed and code syntax)
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Server/Client Setup
Web client
R/Shiny Server
Unix file server
selection logic an data
Tables/Reports
Provides SAS DatasetsSettings
SAS code
Imports
Exports
Exports
UserInteracts
R/Shiny
reporting
programs
Insta
lls
Developer
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Prototype demonstration
Example of general review tool (R code 700 lines)
ADaM: ADAE
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Prototype demonstration
Example of general review tool (R code 700 lines)
ADaM: ADLB
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Prototype demonstration
Example of an enhanced AE report (R code 250 lines)
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Prototype demonstrationExample of an enhanced AE report (R code 250 lines)
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Prototype demonstration
Example of an enhance LB report (R code 250 lines)
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Prototype demonstrationExample of an enhance LB report (R code 250 lines)
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Summary
• R/shiny for presentation/exploration of SAS
data could be a useful additional tool during
the trial execution Phase! (DMCs, self
validation, acceptance checks)
• Development for the local/server based R
shiny server is quite fast and straightforward .
Applications in R can be small and very
flexible
• Could be a easy to use counterpart for the
validation of standardized outputs
• Could be used as generator for prototype SAS
code / Macro calls of a reporting system
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Questions
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