Creating datasets and tables, listings and graphs (TLGs) for analyzing clinical trials data with R, such that in the final stage the code, datasets and TLGs can be submitted to the health authorities, is a multifaceted problem. We have been working on a number of R packages to create an R-based analysis environment that can be used for exploratory and regulatory analysis of clinical trials data. These projects include: table creation (open source http://github.com/Roche/rtables); random data generation; querying CDISC standards; TLG creation; a pipeline for specifying and producing data and TLG deliverables (with logs, automation, titles and footnotes, etc.); a modular shiny-based exploratory framework that provides dynamic encodings, variable-based filtering, and R-code generation for the displayed outputs. The maturity of these projects varies, but the workflow and analysis environment as a whole can be demonstrated nicely. In this talk, we would like to generate interest in collaboration in order to make these projects more general and with the final goal of open-sourcing some of them.
Adrian Waddell
Roche
Analyzing Clinical Trials Data with R
Creating datasets and tables, listings and graphs (TLGs) for analyzing clinical trials data with R, such that in the final stage the code, datasets and TLGs can be submitted to the health authorities, is a multifaceted problem. We have been working on a number of R packages to create an R-based analysis environment that can be used for exploratory and regulatory analysis of clinical trials data. These projects include table creation (open source http//github.com/Roche/rtables); random data generation; querying CDISC standards; TLG creation; a pipeline for specifying and producing data and TLG deliverables (with logs, automation, titles and footnotes, etc.); a modular shiny-based exploratory framework that provides dynamic encodings, variable-based filtering, and R-code generation for the displayed outputs. The maturity of these projects varies, but the workflow and analysis environment as a whole can be demonstrated nicely. In this talk, we would like to generate interest in collaboration in order to make these projects more general and with the final goal of open-sourcing some of them.