Individual skill
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...
scientific-skills/Evidence Insight/tooluniverse-clinical-trial-matching/SKILL.md
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- bioinformatics Repository topic
- computational-biology Repository topic
- data-analysis Repository topic
- ai Repository topic
- biology Repository topic
- cancer-genomics Repository topic
- data-visualization Repository topic
- differential-expression Repository topic
- genomics Repository topic
- medical Repository topic
- engineering Derived category
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EXAMPLES.mddoc · 5,568 bytesPOLISH_CHANGELOG.mddoc · 635 bytesQUICK_START.mddoc · 4,926 bytesSKILL.mdcore · 10,281 bytesSKILL.mdcore · 10,281 bytesSKILL.mdcore · 10,281 bytesTOOLS_REFERENCE.mddoc · 7,582 byteseval_report_tooluniverse-clinical-trial-matching_result.jsonasset · 11,121 bytesreferences/parsing_and_validation.mddoc · 14,077 bytesreferences/phases_detail.mddoc · 36,174 bytesreferences/scoring_and_matching.mddoc · 13,570 bytes
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> **Source**: [https://github.com/aipoch/medical-research-skills](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