This skill matches patients to optimal clinical trials based on their molecular profile, disease characteristics, and eligibility criteria. It searches ClinicalTrials.gov and cross-references molecular databases to produce evidence-graded, scored trial recommendations.
Simply describe your patient profile and ask for trial matches:
Find clinical trials for a patient with non-small cell lung cancer,
EGFR L858R mutation, Stage IV, who failed first-line osimertinib.
Patient profile:
- Disease: Non-small cell lung cancer (adenocarcinoma)
- Biomarker: EGFR L858R mutation
- Stage: Stage IV, metastatic
- Prior treatment: Failed platinum-based chemotherapy
- ECOG: 0-1
Find the best clinical trial matches.
Match clinical trials for:
- Melanoma, advanced/metastatic
- TMB-high (>10 mut/Mb)
- PD-L1 positive (TPS >= 50%)
- Failed ipilimumab/nivolumab combination
- ECOG 0
Find basket/tumor-agnostic trials for a patient with:
- Solid tumor (colorectal cancer)
- NTRK1 fusion detected by NGS
- No prior TRK inhibitor therapy
Clinical trial options for:
- HR+/HER2- breast cancer
- Failed CDK4/6 inhibitor (palbociclib) + letrozole
- ESR1 Y537S mutation detected
- Bone and liver metastases
Find trials for:
- Colorectal cancer, Stage IV
- KRAS G12C mutation
- Failed FOLFOX + bevacizumab
- MSS (microsatellite stable)
Find lung cancer clinical trials:
- Non-small cell lung cancer, any molecular subtype
- Prefer trials in Boston, Massachusetts area
- Currently recruiting
- Phase II or III only
For each patient, the skill produces:
- Executive Summary - Top 3 trial recommendations with Trial Match Scores
- Patient Profile - Standardized disease/biomarker information with EFO and gene IDs
- Biomarker Actionability - FDA-approved vs investigational status
- Ranked Trial List - Up to 10+ trials with detailed scoring breakdown:
- Molecular Match (0-40 points)
- Clinical Eligibility (0-25 points)
- Evidence Strength (0-20 points)
- Trial Phase (0-10 points)
- Geographic Feasibility (0-5 points)
- Trial Details - NCT ID, phase, status, interventions, eligibility, locations
- Drug-Biomarker Alignment - Whether trial drugs target the patient's biomarkers
- Evidence Grading - T1 (FDA-approved) through T4 (computational)
- Alternative Options - Basket trials, expanded access, off-label options
- Additional Testing - Biomarker tests that would unlock more trials
- Completeness Checklist - What analyses were performed
| Score | Tier | Meaning |
|---|---|---|
| 80-100 | Optimal | Strongly recommend - patient's biomarker directly targeted |
| 60-79 | Good | Recommend - good disease and biomarker alignment |
| 40-59 | Possible | Consider - matches on some criteria, needs discussion |
| 0-39 | Exploratory | Backup - general disease trials or weak match |
- Be specific about biomarkers - Include variant-level detail (e.g., "EGFR L858R" not just "EGFR mutation")
- Include prior treatments - Post-progression trials need to know what failed
- Specify stage - Many trials require specific disease stages
- Add geographic preference - If location matters, include city/state
- Mention performance status - ECOG score helps filter eligibility
- List multiple biomarkers - Complex profiles help find the best-matched trials
| Source | What It Provides |
|---|---|
| ClinicalTrials.gov | Trial search, eligibility, locations, status |
| OpenTargets | Drug-target associations, disease ontology |
| CIViC | Clinical variant interpretations |
| ChEMBL | Drug mechanisms and targets |
| FDA | Approved indications, biomarker labels |
| DrugBank | Drug targets and pharmacology |
| PharmGKB | Pharmacogenomics data |
| PubMed | Literature evidence |
| OLS/EFO | Disease ontology standardization |
| MyGene | Gene identifier resolution |
- Trial availability changes frequently; always verify current status at ClinicalTrials.gov
- Eligibility assessment is approximate; final determination is by trial investigators
- Geographic distance calculations are approximate (state/city level, not exact)
- Report is for informational/research purposes only; discuss with healthcare team
- Some trials may have enrollment caps not reflected in public data