According to CDISC: SDTM provides a standard for organizing and formatting data to streamline processes in collection, management, analysis and reporting. Implementing SDTM supports data aggregation and warehousing; fosters mining and reuse; facilitates sharing; helps perform due diligence and other important data review activities; and improves the regulatory review and approval process.
SDTM is one of the required standards for data submission to FDA (U.S.) and PMDA (Japan).
![](https://raw.githubusercontent.com/pharmaverse/sdtmchecks/main/man/figures/logo_em.png)
Contains data check functions to identify SDTM issues that are generalizable, actionable, and meaningful for analysis
![](https://github.com/pharmaverse/datacutr/raw/main/man/figures/logo.png)
Applying a datacut to SDTM
Upcoming packages for consideration
The following are being worked up towards open sourcing to be considered for later inclusion into the pharmaverse - we felt important to share here in case others are working in a similar space and would be interested to collaborate with the respective developers.
![](https://user-images.githubusercontent.com/82581364/133067114-65f89b9c-be77-4a85-8d78-bd6229c24921.png)
SDTM mapping algorithms via R functions OPEN SOURCE RELEASE EXPECTED IN 2024 Contact Ram Ganapathy (ganapar1@gene.com)
In addition, a collaboration of 7 companies is being formed to tackle “Open Source test data generation” for SDTM mapping via an R package. it would be focused on test data from EDC systems that is needed to test SDTM mapping.