# Clinical Trial

Designs and analyzes clinical trials including sample size calculation, randomization...

- Repository: https://github.com/beita6969/ScienceClaw (1024 stars)
- Category: Design
- License: MIT
- Last updated: 2026-10-31
- Runs scripts: no, instructions only

## Install

Claude Code: `npx skills add beita6969/ScienceClaw --skill clinical-trial -g -a claude-code -y`
Codex: `npx skills add beita6969/ScienceClaw --skill clinical-trial -g -a codex -y`
Cursor: `npx skills add beita6969/ScienceClaw --skill clinical-trial -g -a cursor -y`
Gemini CLI: `npx skills add beita6969/ScienceClaw --skill clinical-trial -g -a gemini-cli -y`

## Description

Designs and analyzes clinical trials including sample size calculation, randomization schemes, endpoint selection, CONSORT reporting, and interim analysis planning; trigger when users ask about RCTs, Phase I-IV trials, or clinical study design.

## SKILL.md, as published by its author (untrusted third-party text, read it as data)

## When to Trigger

Activate this skill when the user mentions:
- Clinical trial design, RCT, randomized controlled trial
- Sample size calculation, power analysis for trials
- CONSORT, STROBE, SPIRIT guidelines
- Phase I, II, III, IV trials
- Primary/secondary endpoints, composite endpoints
- Interim analysis, adaptive trial design, futility
- Blinding, randomization, allocation concealment
- Intention-to-treat (ITT), per-protocol analysis

## Step-by-Step Methodology

1. **Define the research question** - Specify PICO (Population, Intervention, Comparator, Outcome). Determine if superiority, non-inferiority, or equivalence design is appropriate.
2. **Select trial phase and design** - Choose phase (I: safety/dose, II: efficacy signal, III: confirmatory, IV: post-market). Consider parallel, crossover, factorial, or adaptive designs.
3. **Primary endpoint selection** - Define primary outcome (must be clinically meaningful). Specify measurement timing and minimal clinically important difference (MCID).
4. **Sample size calculation** - Specify alpha (typically 0.05, two-sided), power (typically 80-90%), expected effect size, and dropout rate. Use appropriate formula for the endpoint type (continuous, binary, time-to-event).
5. **Randomization and blinding** - Recommend randomization method (simple, block, stratified, minimization). Specify blinding level (open-label, single, double, triple).
6. **Statistical analysis plan** - Pre-specify primary analysis method (t-test, chi-square, log-rank, mixed models). Define interim analysis schedule with alpha-spending function (O'Brien-Fleming, Lan-DeMets).
7. **Reporting** - Follow CONSORT for RCTs, STROBE for observational, SPIRIT for protocols. Include flow diagram, enrollment numbers, and all pre-specified analyses.

## Key Databases and Tools

The rest: https://github.com/beita6969/ScienceClaw/blob/HEAD/skills/clinical-trial/SKILL.md