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tooluniverse-clinical-trial-matching

tooluniverse-clinical-trial-matching

AI-driven patient-to-trial matching for precision medicine and oncology. Given a patient profile (disease, molecular alterations, stage, prior treatments), discovers and ranks clinical trials from ClinicalTrials.gov using multi-dimensional matching across molecular eligibility...

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Documentación de la Skill

GitHub

name: tooluniverse-clinical-trial-matching description: AI-driven patient-to-trial matching for precision medicine and oncology. Given a patient profile (disease, molecular alterations, stage, prior treatments), discovers and ranks clinical trials from ClinicalTrials.gov using multi-dimensional matching across molecular eligibility... license: MIT author: AIPOCH

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

Clinical Trial Matching for Precision Medicine

Transform patient molecular profiles and clinical characteristics into prioritized clinical trial recommendations. Searches ClinicalTrials.gov and cross-references with molecular databases (CIViC, OpenTargets, ChEMBL, FDA) to produce evidence-graded, scored trial matches.

KEY PRINCIPLES:

  1. Report-first approach - Create report file FIRST, then populate progressively
  2. Patient-centric - Every recommendation considers the individual patient's profile
  3. Molecular-first matching - Prioritize trials targeting patient's specific biomarkers
  4. Evidence-graded - Every recommendation has an evidence tier (T1-T4)
  5. Quantitative scoring - Trial Match Score (0-100) for every trial
  6. Eligibility-aware - Parse and evaluate inclusion/exclusion criteria
  7. Actionable output - Clear next steps, contact info, enrollment status
  8. Source-referenced - Every statement cites the tool/database source
  9. Completeness checklist - Mandatory section showing analysis coverage
  10. English-first queries - Always use English terms in tool calls. Respond in user's language

When to Use

Apply when user asks:

  • "What clinical trials are available for my NSCLC with EGFR L858R?"
  • "Patient has BRAF V600E melanoma, failed ipilimumab - what trials?"
  • "Find basket trials for NTRK fusion"
  • "Breast cancer with HER2 amplification, post-CDK4/6 inhibitor trials"
  • "KRAS G12C colorectal cancer clinical trials"
  • "Immunotherapy trials for TMB-high solid tumors"
  • "Clinical trials near Boston for lung cancer"
  • "What are my options after failing osimertinib for EGFR+ NSCLC?"

NOT for (use other skills instead):

  • Single variant interpretation without trial focus -> Use tooluniverse-cancer-variant-interpretation
  • Drug safety profiling -> Use tooluniverse-adverse-event-detection
  • Target validation -> Use tooluniverse-drug-target-validation
  • General disease research -> Use tooluniverse-disease-research

Input Parsing

Required Input

  • Disease/cancer type: Free-text disease name (e.g., "non-small cell lung cancer", "melanoma")

Strongly Recommended

  • Molecular alterations: One or more biomarkers (e.g., "EGFR L858R", "KRAS G12C", "PD-L1 50%", "TMB-high")
  • Stage/grade: Disease stage (e.g., "Stage IV", "metastatic", "locally advanced")
  • Prior treatments: Previous therapies and outcomes (e.g., "failed platinum chemotherapy", "progressed on osimertinib")

Optional

  • Performance status: ECOG or Karnofsky score (e.g., "ECOG 0-1")
  • Geographic location: City/state for proximity filtering (e.g., "Boston, MA")
  • Trial phase preference: I, II, III, IV, or "any"
  • Intervention type: drug, biological, device, etc.
  • Recruiting status preference: recruiting, not yet recruiting, active

Biomarker Parsing Quick Reference

Input FormatParsed AsExample
Gene + amino acid changeSpecific mutationEGFR L858R
Gene + exon notationExon-level alterationEGFR exon 19 deletion
Gene + fusion partnerFusionEML4-ALK fusion
Gene + amplificationCopy number gainHER2 amplification
Gene + expression levelExpression biomarkerPD-L1 50%
Gene + statusStatus biomarkerMSI-high, TMB-high
Gene + resistanceResistance mutationEGFR T790M

Gene Symbol Normalization

Common AliasOfficial SymbolNotes
HER2ERBB2Search both in trials
PD-L1CD274Often searched as "PD-L1" in trials
ALKALKEML4-ALK is a fusion
VEGFVEGFAOften searched as "VEGF"
PD-1PDCD1Search as "PD-1" in trials
BRCABRCA1/BRCA2Specify which BRCA gene

Detailed parsing rules and regex patterns: see references/parsing_and_validation.md


Workflow Overview

PhaseNameSummary
0Tool Parameter ReferenceVerify all tool parameters before calling. See references/phases_detail.md
1Patient Profile StandardizationResolve disease→EFO ID, genes→Ensembl/Entrez IDs, classify biomarker actionability
2Broad Trial DiscoveryDisease/biomarker/intervention searches on ClinicalTrials.gov, deduplicate results
3Trial CharacterizationBatch-fetch eligibility, interventions, locations, status, descriptions for candidate NCT IDs
4Molecular Eligibility MatchingParse eligibility text for biomarker requirements, score patient-trial molecular match (0-40)
5Drug-Biomarker AlignmentIdentify trial drug mechanisms via OpenTargets/ChEMBL, verify target overlap with patient biomarkers
6Evidence AssessmentFDA approval, PubMed literature, CIViC evidence, evidence tier classification (T1-T4)
7Geographic & FeasibilityTrial site locations, enrollment status, proximity to patient location
8Alternative OptionsBasket/tumor-agnostic trials, expanded access, compassionate use programs
9Scoring & RankingCalculate Trial Match Score (0-100), assign tier, rank trials
10Report SynthesisGenerate markdown report with executive summary, ranked trials, evidence grading, checklist

Detailed phase execution code and tool call examples: see references/phases_detail.md


Trial Match Score (0-100)

Score Components

ComponentMax PointsKey Criteria
Molecular Match40Exact variant match=40, Gene-level=30, Pathway=20, No criteria=10, Excluded=0
Clinical Eligibility25All criteria met=25, Most=18, Some=10, Ineligible=0
Evidence Strength20FDA-approved (T1)=20, Phase III (T2)=15, Phase II (T3)=10, Phase I (T4)=5
Trial Phase10Phase III=10, Phase II=8, Phase I/II=6, Phase I=4
Geographic Feasibility5Patient's city=5, Same country=3, International=1, Unknown=0

Recommendation Tiers

ScoreTierLabelAction
80-100Tier 1Optimal MatchStrongly recommend - contact site immediately
60-79Tier 2Good MatchRecommend - discuss with care team
40-59Tier 3Possible MatchConsider - needs further eligibility review
0-39Tier 4ExploratoryBackup option - consider if Tier 1-3 unavailable

Detailed scoring rules, evidence tier definitions, and matching algorithms: see references/scoring_and_matching.md


Output Format

Report file: clinical_trial_matching_[DISEASE]_[BIOMARKER]_[DATE].md

Required Sections

  1. Executive Summary - Top 3 trial recommendations with scores
  2. Patient Profile Summary - Standardized disease/biomarker/stage table
  3. Ranked Trial Matches - Per-trial score breakdown, eligibility, evidence, locations
  4. Trials by Category - Targeted/Immuno/Combination/Basket groupings
  5. Additional Testing Recommendations - Biomarkers that unlock more trials
  6. Alternative Options - Expanded access, off-label options
  7. Evidence Grading Summary - T1-T4 counts
  8. Completeness Checklist - Analysis step status tracking
  9. Disclaimer - Research-only notice
  10. Sources - Data source list

Full report template with markdown structure: see references/phases_detail.md#phase-10-report-synthesis


Edge Cases & Common Pitfalls

  1. ClinicalTrials.gov query complexity - Overly specific queries often return zero results. Start simple, then combine.
  2. CIViC search limitations - civic_search_variants/civic_search_evidence_items do NOT filter by query. Use civic_get_variants_by_gene with gene ID instead.
  3. No matching trials - Broaden to gene-level → pathway-level → basket trials → suggest biomarker testing.
  4. Rare biomarkers - Search gene-level trials, check CIViC, note rarity, suggest molecular tumor board.
  5. Multiple biomarkers - Search independently + in combination, score by most actionable.
  6. Conflicting eligibility - Score partial match transparently, highlight met/unmet criteria.

Full edge case handling and use patterns: see references/parsing_and_validation.md


Known CIViC Gene IDs

GeneCIViC IDGeneCIViC ID
ALK1MET52
ABL14PIK3CA37
BRAF5ROS1118
EGFR19RET122
ERBB220NTRK1197
KRAS30NTRK2560
TP5345NTRK3561

Input Validation

This skill accepts requests that match the documented purpose of tooluniverse-clinical-trial-matching 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-matching only handles its documented workflow. Please provide the missing required inputs or switch to a more suitable skill.

References

FileContent
references/phases_detail.mdPhase 0-10 detailed execution code, tool call examples, parameter tables, report template
references/scoring_and_matching.mdScoring algorithm details, drug-biomarker alignment rules, evidence tier classification, matching logic
references/parsing_and_validation.mdBiomarker parsing regex, eligibility text parsing, gene resolution code, edge case handling, common use patterns
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