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Skillstooluniverse-clinical-trial-design

tooluniverse-clinical-trial-design

Design & creation

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Updated 10-15 18:45

About this skill

Source: https://github.com/aipoch/medical-research-skills

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.

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 ★★★ Regulatory acceptance, multiple precedents FDA-approved endpoint in same indication
B ★★☆ Clinical validation, single precedent Phase 3 trial in related indication
C ★☆☆ Preclinical or exploratory Phase 1 use, biomarker validation ongoing
D ☆☆☆ Proposed, no validation Novel endpoint, no precedent

3. Feasibility Score (0-100)

Weighted composite score:

  • Patient Availability (30%): Population size × biomarker prevalence × 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 (validate) | <50 = LOW (de-risk)

→ Detailed scoring rules: references/scoring_and_endpoints.md

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"

NOT for:

  • Patient-to-trial matching → use tooluniverse-clinical-trial-matching
  • Phase 3/4 confirmatory trial design → needs specialized biostatistics consultation
  • Post-market surveillance or pharmacovigilance → use tooluniverse-adverse-event-detection
  • Regulatory submission document preparation → use specialized regulatory affairs tools

Quick Start

from tooluniverse import ToolUniverse

tu = ToolUniverse(use_cache=True)
tu.load_tools()

# Example: EGFR+ NSCLC trial feasibility
indication = "EGFR-mutant non-small cell lung cancer"
biomarker = "EGFR L858R"

# Step 1: Get disease prevalence
disease_info = tu.tools.OpenTargets_get_disease_id_description_by_name(
    diseaseName="non-small cell lung cancer"
)

# Step 2: Estimate biomarker prevalence
variants = tu.tools.ClinVar_search_variants(gene="EGFR", significance="pathogenic")

# Step 3: Find precedent trials
trials = tu.tools.search_clinical_trials(
    condition="EGFR positive non-small cell lung cancer",
    status="completed", phase="2"
)

# Step 4: Identify standard of care comparator
soc_drugs = tu.tools.FDA_OrangeBook_search_drugs(ingredient="osimertinib")

# Compile into feasibility report...

Core Strategy: 6 Research Paths

Execute 6 parallel research dimensions:

Trial Design Query (e.g., "EGFR+ NSCLC trial, Phase 2, ORR endpoint")
│
├─ PATH 1: Patient Population Sizing
│   Disease prevalence → Biomarker prevalence → Eligibility funnel → Enrollment projection
│
├─ PATH 2: Biomarker Prevalence & Testing
│   Mutation frequency → CDx availability → Turnaround time → Alternative biomarkers
│
├─ PATH 3: Comparator Selection
│   Standard of care → Approved comparators → Historical controls → Placebo appropriateness
│
├─ PATH 4: Endpoint Selection
│   Primary endpoint precedents → FDA acceptance → Measurement feasibility → Surrogate vs clinical
│
├─ PATH 5: Safety Endpoints & Monitoring
│   Mechanism-based toxicity → Class effects → Organ monitoring → SMC plan
│
└─ PATH 6: Regulatory Pathway
    Regulatory precedents → Breakthrough potential → Orphan designation → FDA guidance

→ Detailed execution instructions & tool calls: references/research_paths_detail.md

Report Structure (14 Sections)

Create [INDICATION]_trial_feasibility_report.md with:

1. Executive Summary

# Clinical Trial Feasibility Report: [INDICATION]
**Date**: [YYYY-MM-DD] | **Trial Type**: [Phase 1/2] | **Primary Endpoint**: [ORR]
**Feasibility Score**: [0-100] - [LOW/MODERATE/HIGH]

## Key Findings
- **Patient Availability**: [Est. enrollable patients/year]
- **Enrollment Timeline**: [Months to target N]
- **Endpoint Precedent**: [Grade A/B/C/D]
- **Regulatory Pathway**: [505(b)(1), breakthrough, orphan]
- **Critical Risks**: [Top 3]

## Go/No-Go Recommendation
[RECOMMEND PROCEED / ADDITIONAL VALIDATION / DO NOT RECOMMEND]

2. Disease Background — Indication, prevalence, SOC, unmet need

3. Patient Population Analysis — Funnel model with enrollment projections

4. Biomarker Strategy — Prevalence, CDx, logistics

5. Endpoint Selection & Justification — Primary/secondary/exploratory with evidence grades

6. Comparator Analysis — SOC, design options, drug sourcing

7. Safety Endpoints & Monitoring Plan — DLT, toxicities, organ monitoring, SMC

8. Study Design Recommendations — Phase, schema, eligibility, treatment plan, schedule

9. Enrollment & Site Strategy — Site selection, projections, recruitment

10. Regulatory Pathway — FDA pathway, precedents, pre-IND, IND timeline

11. Budget & Resource Considerations — Cost drivers, FTE requirements

12. Risk Assessment — Feasibility risks, scientific risks, mitigation

13. Success Criteria & Go/No-Go Decision — Phase 1/2 criteria, scorecard

14. Recommendations & Next Steps — Final recommendation, critical path, alternatives

→ Detailed section templates: references/research_paths_detail.md

Feasibility Scorecard Template

| Dimension | Weight | Score (0-10) | Weighted | Grade |
|-----------|--------|--------------|----------|-------|
| Patient Availability | 30% | [X] | [0.30×X] | [★★☆] |
| Endpoint Precedent | 25% | [X] | [0.25×X] | [★★★] |
| Regulatory Clarity | 20% | [X] | [0.20×X] | [★★☆] |
| Comparator Feasibility | 15% | [X] | [0.15×X] | [★★★] |
| Safety Monitoring | 10% | [X] | [0.10×X] | [★★☆] |
| **TOTAL** | **100%** | - | **[XX/100]** | - |

→ Full scoring algorithm & dimension guides: references/scoring_and_endpoints.md

Output Format Requirements

Report File Naming

  • [INDICATION]_trial_feasibility_report.md
  • Example: EGFR_L858R_NSCLC_trial_feasibility_report.md

Section Completeness

All 14 sections MUST be present (listed above).

Evidence Grading Required In

Sections 1, 4, 5, 6, 7, 10, 13 — all key claims must carry evidence grades (★★★/★★☆/★☆☆/☆☆☆).

Feasibility Score Transparency

Show calculation with raw scores, weights, and evidence sources.

Tool Quick Reference

Path Primary Tools
PATH 1 OpenTargets_get_disease_id_description_by_name, OpenTargets_get_diseases_phenotypes, ClinVar_search_variants, gnomAD_search_gene_variants
PATH 2 ClinVar_get_variant_details, COSMIC_search_mutations, gnomAD_get_variant_details
PATH 3 drugbank_get_drug_basic_info_by_drug_name_or_id, FDA_OrangeBook_search_drugs, FDA_get_drug_approval_history
PATH 4 search_clinical_trials, PubMed_search_articles, FDA_get_drug_approval_history
PATH 5 drugbank_get_pharmacology_by_drug_name_or_drugbank_id, FAERS_search_reports_by_drug_and_reaction, FAERS_count_reactions_by_drug_event
PATH 6 FDA_get_drug_approval_history, PubMed_search_articles, search_clinical_trials

All tools accessed via tu.tools.<tool_name>(<params>). Use English for all query parameters.

Input Validation

This skill accepts requests that match the documented purpose of tooluniverse-clinical-trial-design and include enough context to complete the workflow safely.

Do not continue the workflow when the request is out of scope, missing a critical input, or would require unsupported assumptions. Instead respond:

tooluniverse-clinical-trial-design only handles its documented workflow. Please provide the missing required inputs or switch to a more suitable skill.

References

File Content
references/research_paths_detail.md 6 Research Path detailed execution instructions, step-by-step code, report templates, tool references
references/scoring_and_endpoints.md Feasibility Score complete algorithm, dimension scoring criteria, endpoint selection decision tree, success criteria definitions
references/examples_and_troubleshooting.md Complete EGFR L858R example, 5 use cases, common pitfalls, best practices, integration guide

Error Handling

  • If required inputs are missing, state exactly which fields are missing and request only the minimum additional information.
  • If the task goes outside the documented scope, stop instead of guessing or silently widening the assignment.
  • If execution fails, report the failure point, summarize what can still be completed safely, and provide a manual fallback.
  • Do not fabricate files, citations, data, search results, or execution outcomes.