AI SDTM mapping (R for ML, Python, TensorFlow for DL)

Development repo for pilot3 submission to FDA - ADaM

De-identifying CDISC SDTM data by Phuse rules using SAS

A dashboard to visualize what datasets were used to create each of the clinical trial datasets

Unit conversion, verification with Unified Code for Units of Measure (Python)

Code for the CDISC {admiral} hackathon, Feb 2023. The objective of this hackathon is to develop ADaM datasets in R using the ADaM in R Asset Library {admiral} and other Pharmaverse packages.

R-based framework for automated CDISC SDTM validation — an open alternative to Pinnacle 21 with configurable rules, documented checks, and full test coverage.

caAdapter provides model mapping, data mapping and transformation services among data sources like HL7 and Regulatory Data Sets.

R scripts to process clinical trial data using the CDISC SDTM and ADaM standards. It automates the transformation of raw clinical data into structured SDTM datasets (e.g., DM, AE, VS domains) and analysis-ready ADaM datasets (ADSL, ADAE, ADVS). The project includes statistical summaries, descriptive analytics, and viz

DXT-packaged MCP server for the CDISC Library (discovery, Biomedical Concepts, SDTM Dataset Specializations)

A hands-on R training for clinical SAS programmers — learn to transition from SAS to R through 7 interactive modules covering data manipulation, SDTM programming, and QC reporting.

CDIS data standardization with SAS and R

Python script to download, extract, and organize CDASH, SDTM, SEND, ADaM, and Define-XML standards from NCI EVS.