clinical-trial-design

A Claude Code plugin and MCP server for end-to-end clinical trial design.

clinical-trial-design helps biostatisticians and clinical trialists design Phase 2 and Phase 3 confirmatory studies through a conversational interface, backed by validated R packages (gsDesign, gsDesign2, graphicalMCP).

v0.0.13 — pre-beta. Nine MCP tools across single-primary endpoint design (binary, continuous, time-to-event under PH and four NPH frameworks), multi-hypothesis design (co-primary, multi-population, graphical multiplicity / Maurer-Bretz), Monte-Carlo verification, and Word/PDF reporting. Reasoning-chain schema with sponsor-confidential redaction. Operational kernel solves accrual ↔ duration ↔ N, plus optional max_n / max_duration feasibility warnings. 288/288 R tests, 18/18 MCP smoke. Published to npm (clinical-trial-design) and the official MCP registry (io.github.wei-ai-lab/clinical-trial-design). Full change history in CHANGELOG.md; API contract in API_STABILITY.md.

What it is

clinical-trial-design has four layers:

Plus an eval harness under eval/ (11 reproducible scenarios × six scoring dimensions × multi-vendor Claude family) and an examples gallery under examples/ (5 published trials reproduced end-to-end).

What clinical-trial-design actually computes

Status

Tool surface

Nine MCP tools — three single-primary design tools, three multi-hypothesis design tools, three meta tools. Same unified result schema across families.

Single-primary design tools (3)

All three accept comparison ∈ {"superiority", "non-inferiority", "equivalence"} (equivalence on fixed-sample binary / continuous only), alpha, power, sided, allocation_ratio, GS parameters (k, timing, sfu, sfl, test.type), an optional operational block, and an optional reasoning_chain array (citation trail with source_type tags).

design_survival adds events_calc ∈ {"schoenfeld" (default), "lachin-foulkes", "freedman"} for PH GS designs and accepts control_hazard_rate (events per patient-year) as an alternative to control_median.

Multi-hypothesis design tools (3)

Meta tools (3)

Operational kernel

Every endpoint design tool accepts an operational block that solves the simple relations accrual_rate × accrual_duration = sample_size_total and total_trial_duration = accrual_duration + follow_up_duration (plus target_events = sample_size_total × cumulative_event_rate(...) for survival, via uniroot over the closed-form pooled exponential-PH event probability — same kernel gsDesign::nSurv uses internally).

Supply any 0–4 of {accrual_rate, accrual_duration, follow_up_duration, total_trial_duration} plus optional caps {max_n, max_duration}. The solver fills in the missing values with an audit trail (given, derived); cap violations surface as structured feasibility_warnings rather than silent over-cap designs.

Quick start

Prerequisites: R ≥ 4.2, Node ≥ 18. No npm install step (the MCP server ships pre-bundled in mcp-server/dist/index.js) and no remotes::install_local step (the launcher sources r-package/ClinicalTrialDesign/R/*.R directly out of the plugin cache).

1. Install CRAN dependencies (one-time)

R -e 'install.packages(c("gsDesign","gsDesign2","graphicalMCP","jsonlite","officer","rmarkdown"))'

The first four are runtime imports; officer and rmarkdown are Suggests: and only needed for design_report(format="docx") / format="pdf".

Tested dependency versions

clinical-trial-design v0.0.13 was developed and tested against the versions below. CRAN's latest is usually fine; pin to these floors only if you hit a version-skew issue.

2. Install the plugin

Method A — slash commands (recommended, inside Claude Code)

/plugin marketplace add wei-ai-lab/clinical-trial-design
/plugin install clinical-trial-design@wei-ai-lab

After install, restart Claude Code so it loads the bundled MCP server. Confirm with /plugin (clinical-trial-design should be listed and enabled at version 0.0.13).

Method B — host shell (equivalent, scriptable)