tooluniverse-clinical-trial-design

What the source does

• FilesystemNone observedNo reads or writes in the source
• NetworkNone observedNo outbound calls in the source
• ShellNone observedNo commands run in the source
• DependenciesPinnedNothing floats
• SecretsNone foundNo keys in source

Five audit layers

Gates applied: no behavioural pass.

.env.template

Audit 0.4.1 · source sha 43be0fac747b · 31 Oct 2026Report an issue or request a re-scan

• Publishermims-harvard GitHub organizationOwner of the repository this skill is read from
• Source foldermims-harvard/tooluniverse/skills/tooluniverse-clinical-trial-designThe exact folder we audited
• LicenceApache-2.0As the repository states it
• Commit pinned for this verdict43be0fac747bA new audit runs when the source changes
• Repository statusNot archivedPushed today
• Sandboxed runNot runSkills are read, not executed; layer L4 is skipped

Its description: Strategic clinical trial design feasibility assessment. Analyzes 6 dimensions (endpoint, population, comparator, effect size, duration, regulatory pathway) using precedent trials and FDA guidance. Produces enrollment…

---
name: tooluniverse-clinical-trial-design
description: Strategic clinical trial design feasibility assessment. Analyzes 6 dimensions (endpoint, population, comparator, effect size, duration, regulatory pathway) using precedent trials and FDA guidance. Produces enrollment projections, endpoint recommendations, and approval-pathway analysis. Use for trial-protocol design, power/sample-size estimation, comparator selection, and FDA submission strategy. Driven by precedent-based reasoning rather than first-principles math.
disable-model-invocation: true
---

# Clinical Trial Design Feasibility Assessment

Systematically assess clinical trial feasibility by analyzing 6 research dimensions. Produces comprehensive feasibility reports with quantitative enrollment projections, endpoint recommendations, and regulatory pathway analysis.

**IMPORTANT**: Always use English terms in tool calls (drug names, disease names, biomarker names), even if the user writes in another language. Only try original-language terms as a fallback if English returns no results. Respond in the user's language.

## Reasoning Before Searching

Trial design starts with the question, not the methods. Answer these four questions before running any tools — they determine everything else:

1. **What is the primary endpoint?** Is it overall survival (gold standard but slow), PFS (faster but surrogate), ORR (single-arm friendly but not always accepted), or a biomarker (needs validation as surrogate first)? The endpoint determines FDA pathway, statistical design, and duration.
2. **Who is the population?** Broad unselected vs. biomarker-enriched. Enriched populations have higher response rates, allowing smaller trials — but require a validated companion diagnostic and reduce the eligible patient pool.
3. **What is the comparator?** Placebo (only if no standard of care exists), active control (requires non-inferiority or superiority framing), or single-arm with historical control (acceptable for rare diseases or breakthrough designations, but FDA scrutiny is high).
4. **Is the effect size realistic given the mechanism?** A 20% improvement in ORR over SOC requires ~100 patients per arm. A 50% improvement requires ~30. If the mechanism only justifies a 10% improvement, the trial may be underpowered regardless of design. Check precedent effect sizes in similar trials before committing to an endpoint.

These four answers determine sample size, duration, and trial design. Look them up from precedent trials and FDA guidance — do not derive them from first principles.

**LOOK UP DON'T GUESS**: Never assume what the standard of care is for an indication — look it up with DrugBank and FDA tools. Never assume an endpoint is FDA-accepted — verify with `search_clinical_trials` precedents and `OpenFDA_get_approval_history`. Never estimate prevalence from memory — use OpenTargets, gnomAD, or COSMIC.

## Core Principles

### 1. Report-First Approach (MANDATORY)
**DO NOT** show tool outputs to user. Instead:
1. Create `[INDICATION]_trial_feasibility_report.md` FIRST
2. Initialize with all section headers
3. Progressively update as data arrives
4. Present only the final report

### 2. Evidence Grading System

| Grade | Symbol | Criteria | Examples |
|-------|--------|----------|----------|
| **A** | 3-star | Regulatory acceptance, multiple precedents | FDA-approved endpoint in same indication |
| **B** | 2-star | Clinical validation, single precedent | Phase 3 trial in related indication |
| **C** | 1-star | Preclinical or exploratory | Phase 1 use, biomarker validation ongoing |
| **D** | 0-star | Proposed, no validation | Novel endpoint, no precedent |

### 3. Feasibility Score (0-100)
Weighted composite score:
- **Patient Availability** (30%): Population size x biomarker prevalence x geography
- **Endpoint Precedent** (25%): Historical use, regulatory acceptance
- **Regulatory Clarity** (20%): Pathway defined, precedents exist
- **Comparator Feasibility** (15%): Standard of care availability
- **Safety Monitoring** (10%): Known risks, monitoring established

**Interpretation**: >=75 HIGH (proceed), 50-74 MODERATE (additional validation), <50 LOW (de-risking required)

---

## When to Use This Skill

Apply when users:
- Plan early-phase trials (Phase 1/2 emphasis)
- Need enrollment feasibility assessment
- Design biomarker-selected trials
- Evaluate endpoint strategies
- Assess regulatory pathways
- Compare trial design options
- Need safety monitoring plans

**Trigger phrases**: "clinical trial design", "trial feasibility", "enrollment projections", "endpoint selection", "trial planning", "Phase 1/2 design", "basket trial", "biomarker trial"

---

## Core Strategy: 6 Research Paths

Execute 6 parallel research dimensions. See `STUDY_DESIGN_PROCEDURES.md` for detailed steps per path.

```
Trial Design Query
|
+-- PATH 1: Patient Population Sizing
|   Disease prevalence, biomarker prevalence, geographic distribution,
|   eligibility criteria impact, enrollment projections
|
+-- PATH 2: Biomarker Prevalence & Testing
|   Mutation frequency, testing availability, turnaround time,
|   cost/reimbursement, alternative biomarkers
|
+-- PATH 3: Comparator Selection
|   Standard of care, approved comparators, historical controls,
|   placebo appropriateness, combination therapy
|
+-- PATH 4: Endpoint Selection
|   Primary endpoint precedents, FDA acceptance history,
|   measurement feasibility, surrogate vs clinical endpoints
|
+-- PATH 5: Safety Endpoints & Monitoring
|   Mechanism-based toxicity, class effects, organ-specific monitoring,
|   DLT history, safety monitoring plan
|
+-- PATH 6: Regulatory Pathway
    Regulatory precedents (505(b)(1), 505(b)(2)), breakthrough therapy,
    orphan drug, fast track, FDA guidance
```

---

## Report Structure (14 Sections)

Create `[INDICATION]_trial_feasibility_report.md` with all 14 sections. See `REPORT_TEMPLATE.md` for full templates with fillable fields.

1. **Executive Summary** - Feasibility score, key

Excerpt, first 6,000 characters of SKILL.md, verbatim from the audited commit. It is text from someone else’s repository, quoted so you can judge it before your agent reads it.

1. 2026-10-31
   ✓SAFE B 89 / 100

   first audit · source 43be0fac747b

Questions about tooluniverse-clinical-trial-design

• github.com/mims-harvard/tooluniverse/tree/main/skills/tooluniver — the audited source at commit 43be0fac747b and every finding aboveObserved · 31 Oct 2026

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