- OpenRBQM/OpenRBQM.github.io OpenRBQM Homepage
- OpenRBQM/gsm.digitpref NA
- OpenRBQM/cluster NA
- OpenRBQM/gsm.ae Adverse Events Plugin
- OpenRBQM/gsm.query Query Data Plugin
- OpenRBQM/openrbqm Collection of R Packages designed for Risk Based Quality Management
- OpenRBQM/PhuseConnect25 Materials for OpenRBQM Workshop
- OpenRBQM/gsm.pd Protocol Deviations gsm Plugin
- Gilead-BioStats/gsm Good Statistical Monitoring R Package
- Gilead-BioStats/clindata Synthetic Data for testing and development
- Gilead-BioStats/gsm.app NA
- Gilead-BioStats/gsm.viz web-based data viz for risk-based monitoring
- Gilead-BioStats/qcthat A quality control framework for R packages used in Clinical Trials
- Gilead-BioStats/gsm.datasim NA
- Gilead-BioStats/gsm.mapping Data mapping framework for {gsm}
- Gilead-BioStats/gsm.dash NA
- Gilead-BioStats/gsm.kri NA
- Gilead-BioStats/gsm.reporting NA
- Gilead-BioStats/gsm.qc Quality Control Tests and documentation for the {gsm} suite of R packages
- Gilead-BioStats/gsm.core The Good Statistical Monitoring or ‘gsm’ suite of R packages provides a framework for statistical data monitoring. ‘gsm.core’ provides the analytics framework for constructing metrics, and the utility functions to run workflows.
Packages
Overview
The OpenRBQM framework is designed to provide a robust and flexible solution for risk-based quality management. It includes a variety of packages that help streamline processes and ensure compliance with industry standards.
Packages
Articles
OpenRBQM
- Intro to OpenRBQM
- Data Model Overview