jeffreyad/rpharma-2026-workshop
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2026 R/Pharma workshop: Hands-On AI Skills for Clinical Programming & Biostatistics
Обзор
A hands-on workshop, to be delivered at , on using Claude Code skills to accelerate two common clinical-programming tasks: 1. (ADSL, ADAE, ADVS/ADLB) from SDTM with the {admiral} R package. 2. for survival endpoints — boundaries, sample size, multiplicity, and simulation-based verification. https://jeffreyad.github.io/rpharma-2026-workshop/ - What an agent skill is (a SKILL.md workflow plus supporting references and scripts) and how Claude Code picks one up. - How the admiral skills encode function-selection logic and CDISC conventions so the agent writes QC-ready, submission-traceable R — with # REVIEW: markers at every protocol-specific decision. - How to go from a trial scenario to a fully specified group sequential design and a Word report, with the design verified by lrstat simulation. - How to run these skills yourself: install once, then drive them by describing the task in natural language. You will clone this repo and run the skills live during the session.
README
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R/Pharma 2026 Workshop — AI Skills for Clinical Trial Design & ADaM Derivation
A hands-on workshop, to be delivered at R/Pharma 2026, on using Claude Code skills to accelerate two common clinical-programming tasks:
- Deriving ADaM analysis datasets (ADSL, ADAE, ADVS/ADLB) from SDTM with the {admiral} R package.
- Designing group sequential trials for survival endpoints — boundaries, sample size, multiplicity, and simulation-based verification.
Slides:
What you’ll learn
- What an agent skill is (a
SKILL.mdworkflow plus supporting references and scripts) and how Claude Code picks one up. - How the admiral skills encode function-selection logic and CDISC conventions so
the agent writes QC-ready, submission-traceable R — with
# REVIEW:markers at every protocol-specific decision. - How to go from a trial scenario to a fully specified group sequential design
and a Word report, with the design verified by
lrstatsimulation. - How to run these skills yourself: install once, then drive them by describing the task in natural language.
You will clone this repo and run the skills live during the session.
Included skills
| Skill | One-line description |
|---|---|
skills/admiral |
Parent skill — shared admiral conventions: library setup, native-pipe / exprs() style, date-imputation rules, "Y"/NA flag convention, # REVIEW: annotation and stopifnot() QC patterns. |
skills/admiral/admiral-adsl |
Derive the ADaM Subject-Level Analysis Dataset (ADSL) from SDTM DM/EX/DS — treatment dates, disposition, demographics, and population flags. |
skills/admiral/admiral-adae |
Derive the ADaM Adverse Events dataset (ADAE) from SDTM AE + ADSL — treatment-emergent flag, severity, seriousness, causality, and study-day variables. |
skills/admiral/admiral-bds |
Derive ADaM BDS findings datasets (ADVS, ADLB) — parameter assignment, baseline flagging, change from baseline, visit windowing, and ADLB normal-range derivations. |
skills/group-sequential-design |
Design group sequential trials for survival endpoints (OS, PFS, DFS): spending-function boundaries, N-first sample sizing, graphical multiplicity, NPH sensitivity, lrstat verification, and a template-driven Word report. |
Setup
1. Clone
git clone https://github.com/jeffreyad/rpharma-2026-workshop.git
cd rpharma-2026-workshop
2. Install the dependencies
Use R >= 4.2 (the skills were exercised on R 4.4.1) and, for the group-sequential-design report step, Python >= 3.8.
Rscript install_packages.R # the 12 R packages
python3 -m pip install --user python-docx # Word-report dependency
3. Verify
Rscript check_setup.R
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Установка
npx skillfish add jeffreyad/rpharma-2026-workshop