tooluniverse-precision-medicine-stratification

Precision Medicine Patient Stratification

Transform patient genomic and clinical profiles into actionable risk stratification, treatment recommendations, and personalized therapeutic strategies. Integrates germline genetics, somatic alterations, pharmacogenomics, pathway biology, and clinical evidence to produce a quantitative risk score with tiered management recommendations.

KEY PRINCIPLES:

1. Report-first approach - Create report file FIRST, then populate progressively
2. Disease-specific logic - Cancer vs metabolic vs rare disease pipelines diverge at Phase 2
3. Multi-level integration - Germline + somatic + expression + clinical data layers
4. Evidence-graded - Every finding has an evidence tier (T1-T4)
5. Quantitative output - Precision Medicine Risk Score (0-100) with transparent components
6. Pharmacogenomic guidance - Drug selection AND dosing recommendations
7. Guideline-concordant - Reference NCCN, ACC/AHA, ADA, and other guidelines
8. Source-referenced - Every statement cites the tool/database source
9. Completeness checklist - Mandatory section showing data availability and 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:

• "Stratify this breast cancer patient: ER+/HER2-, BRCA1 mutation, stage II"
• "What is the risk profile for this diabetes patient with HbA1c 8.5 and CYP2C19 poor metabolizer?"
• "NSCLC patient with EGFR L858R, stage IV, TMB 25 - treatment strategy?"
• "Predict prognosis and recommend treatment for this cardiovascular patient"
• "Patient has Marfan syndrome with FBN1 mutation - risk stratification"
• "Alzheimer's risk assessment: APOE e4/e4, family history positive"
• "Personalized treatment plan for type 2 diabetes with genetic risk factors"
• "Which therapy is best for this patient's molecular profile?"

NOT for (use other skills instead):

• Single variant interpretation -> Use tooluniverse-variant-interpretation or tooluniverse-cancer-variant-interpretation
• Immunotherapy-specific prediction -> Use tooluniverse-immunotherapy-response-prediction
• Drug safety profiling only -> Use tooluniverse-adverse-event-detection
• Target validation -> Use tooluniverse-drug-target-validation
• Clinical trial search only -> Use tooluniverse-clinical-trial-matching
• Drug-drug interaction analysis only -> Use tooluniverse-drug-drug-interaction
• PRS calculation only -> Use tooluniverse-polygenic-risk-score

Input Parsing

Required Input

• Disease/condition: Free-text disease name (e.g., "breast cancer", "type 2 diabetes", "Marfan syndrome")
• At least one of: Germline variants, somatic mutations, gene list, or clinical biomarkers

Strongly Recommended

• Genomic data: Specific variants (e.g., "BRCA1 c.68_69delAG", "EGFR L858R"), gene names, or expression changes
• Clinical parameters: Age, sex, disease stage, biomarkers (HbA1c, PSA, LDL-C)

Optional (improves stratification)

• Comorbidities: Other conditions (e.g., "hypertension", "diabetes")
• Prior treatments: Previous therapies and responses
• Family history: Affected relatives, inheritance pattern
• Ethnicity: For population-specific risk calibration
• Current medications: For DDI and pharmacogenomic analysis
• Stratification goal: Risk assessment, treatment selection, prognosis, prevention

Input Format Examples

Disease Type Classification

Classify the disease into one of these categories (determines Phase 2 routing):

Gene Symbol Normalization

Phase 0: Tool Parameter Reference (CRITICAL)

BEFORE calling ANY tool, verify parameters using this reference table.

Verified Tool Parameters

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