A collection of agent skills for pharmaceutical R&D.
| Skill | Description |
|---|---|
| group-sequential-design | Design group sequential clinical trials for survival endpoints (OS, PFS, DFS) with interim analyses, spending functions, multiplicity, and event/enrollment prediction |
| clinical-trial-simulation | Design and simulate clinical trials using the TrialSimulator R package and produce a QC-ready build-order-spine report. Design-agnostic: composes from independent building blocks (endpoints, arms, milestones, regimens) rather than following a fixed catalog of design templates. |
| admiral/admiral-adsl | Derive ADaM Subject-Level Analysis Datasets (ADSL) from SDTM domains using the {admiral} R package. Encodes the workflow, function selection logic, and CDISC conventions for QC-ready, submission-traceable R code. |
| admiral/admiral-bds | Derive ADaM BDS findings datasets (ADVS, ADLB) from SDTM VS/LB domains. Covers parameter assignment, baseline flagging, change from baseline, visit windowing, and ADLB normal range derivations. |
| clinical-trial-ipd-sim | Generate synthetic IPD, source CRFs, SDTM, ADaM, and exports for registered clinical trials using an R/pharmaverse g-formula causal-DAG workflow calibrated to posted protocol and results. |
| statistical-reviewer | Simulate an independent statistical reviewer auditing a clinical trial submission package (SDTM, ADaM, TLF, SAP, CSR) — reproducing endpoints, tracing results across data layers, flagging population inconsistencies, and assessing data realism. |
Option 1: Conversational / CLI Ask your agent to directly enable a skill from this repo:
enable "group-sequential-design" skill from https://github.com/RConsortium/pharma_skills
Option 2: Local IDE (Cursor, Windsurf, Copilot, etc.)
- Clone this repository locally or as a git submodule.
- Symlink the skill you want into your project, or manually reference it in your configuration files (like
.cursorrulesorllms.txt):Please refer to /path/to/pharma_skills/group-sequential-design/SKILL.md for the trial design workflow.
Contributions of new skills are welcome. Each skill should:
- Live in its own folder at the repo root
- Include a
SKILL.mdwith frontmatter (name,description) and instructions - Include a
README.mddescribing what the skill does, requirements, and usage - Include an MIT
LICENSE - Follow the Agent Skill Development Lifecycle
You can add new benchmark data by creating new github issues following the benchmark templates.
If you're interested in contributing to the skill evaluation using your Claude Code account, following this video to set it up.
All skills in this repository are required to be licensed under the MIT License to ensure maximum permissiveness and rapid adoption within pharmaceutical research.
This effort is the part of R consortium Submissions Working Group Pilot 7. It is a joint effort between the R consortium and the BBSW AI committee.
Pilot 7 was initiated to help the community navigate the rapidly growing number of AI capabilities, tools, and R packages available for clinical trial workflows. One major challenge is the lack of high-quality, diverse benchmark resources, including patient-level datasets and structured test cases such as trial design scenarios. Pilot 7 addresses this gap by crowdsourcing both AI skills and benchmark resources, then using community evaluation to continuously improve them.
Pilot 7 holds weekly standups three times a month on Fridays from 8–9 AM PST. We also host monthly Submissions Working Group meetings with FDA staff, bringing together participants across different pilot subgroups.
Everyone is welcome to join. To access our calendar and join the Slack workspace, please see here
To learn more about the R consortium Submissions Working Group, visit here