clinical-trial-ipd-sim

You can generate synthetic individual patient data (IPD) for clinical trials using a g-formula causal-DAG simulator that aligns simulated data with published trial results while maintaining an explicit causal structure.

Yes, the simulation produces SDTM-style CRFs and ADaM analysis datasets following CDISC standards for data exchange by leveraging the pharmaverse stack for standards compliance.

A causal-DAG simulator uses a g-formula approach to generate synthetic IPD that matches both marginal statistics and joint distributions of published clinical trial results.

Yes, simulating clinical trial IPD with this approach requires R 4.3 or higher along with the pharmaverse stack, including packages like admiral, sdtm.oak, and xportr for CDISC compliance.

Provide an NCT ID along with a protocol document to simulate synthetic IPD that aligns with the published trial results and generates corresponding SDTM and ADaM datasets.

Causal-DAG simulation aligns synthetic IPD with published trial statistics and joint distributions, but requires R 4.3+ and the full pharmaverse stack to execute, which may present an environment setup barrier.