| Tongda Che, Laura Frederick, Peng Wan |
In clinical trial analysis, managing complex dataset and code dependencies is crucial for ensuring traceability and
compliance with regulatory guidelines. Traditional methods of tracking these dependencies often require significant
manual effort, leading to potential errors and inefficiencies. This paper presents an innovative R Shiny application
designed to streamline dependency tracking among ADaM (Analysis Data Model) datasets, SAS code, and output
results.
The application provides a dynamic, real-time view of all outputs associated with a given study protocol.
Utilizing log files, it identifies and displays all relevant ADaM datasets and macro programs linked to each output, thereby
enhancing transparency throughout the development process. Additionally, the app uses file timestamps to automatically
flag outdated files, significantly reducing the reducing the risk of errors and improving the accuracy of final outputs. With
integrated API functionality, users can effortlessly rerun any outdated dependency programs with a single
click.
Developed using base R , the Tidyverse, and the Shiny package, this application features a user-friendly
interface for protocol path input and file selection, along with seamless integration with SAS through API connections.
This tool not only enhances compliance with traceability requirements but also optimizes the efficiency of clinical trial
analysis. |