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Generate synthetic ADaM (Analysis Data Model) datasets from real
clinical trial data. synadam preserves the structure of
real ADaM datasets (column names, relationships, ranges) while removing
identifiable patient information — enabling development and testing of
analysis pipelines without access to real data.
generate_study_config() scans your ADaM directory and
infers dataset types and column roles automatically.Install from GitHub:
# install.packages("remotes")
remotes::install_github("Novartis/synadam")library(synadam)
# 1. Auto-generate a YAML config from your ADaM directory. The config is
# written into output_dir, alongside where the synthetic data will land.
yaml_path <- generate_study_config(
adam_dir = "/path/to/adam_data/",
output_dir = "./syn_data",
seed = 42
)
# 2. Review the generated YAML, then simulate
simulate_study(yaml_path)Synthetic datasets are saved as individual .rds files
(e.g., syn_adsl.rds, syn_adlb.rds) in the
output directory.
For a full walkthrough including manual configuration and per-dataset control:
vignette("synadam", package = "synadam")Contributions are welcome! Please open an issue or submit a pull request on GitHub.
This package is licensed under the MIT License. See LICENSE for details.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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