Open-source R tooling has made table generation easy, yet interpreting the code and guaranteeing bullet-proof QC can still delay submissions. We present a workflow that fuses {gtsummary} for rapid table building with cards for "automatic" validation, topped by a fully offline, model-agnostic LLM helper. Starting on synthetic CDISC-like data, we create a standard summary table, validate it with {cards}, and ask the LLM-helper to explain each step and result and propose, if necessary, next steps—all without revealing trial data. A descriptive log is generated on the fly, combining code, QC results, and LLM explanations in one auditor-friendly document. When real data arrive, the same script reruns unchanged, delivering submission-ready tables in minutes while boosting clarity and compliance.
Davide Garolini
Roche
LLM-Powered {gtsummary}: QC-Ready Clinical Tables in Minutes
Open-source R tooling has made table generation easy, yet interpreting the code and guaranteeing bullet-proof QC can still delay submissions. We present a workflow that fuses  gtsummary  for rapid table building with cards for "automatic" validation, topped by a fully offline, model-agnostic LLM helper. Starting on synthetic CDISC-like data, we create a standard summary table, validate it with  cards , and ask the LLM-helper to explain each step and result and propose, if necessary, next steps—all without revealing trial data. A descriptive log is generated on the fly, combining code, QC results, and LLM explanations in one auditor-friendly document. When real data arrive, the same script reruns unchanged, delivering submission-ready tables in minutes while boosting clarity and compliance.