Immunotherapy Response Prediction

Predict patient response to immune checkpoint inhibitors (ICIs) using multi-biomarker integration. Transforms a patient tumor profile (cancer type + mutations + biomarkers) into a quantitative ICI Response Score with drug-specific recommendations, resistance risk assessment, and monitoring plan.

KEY PRINCIPLES:

1. Report-first approach - Create report file FIRST, then populate progressively
2. Evidence-graded - Every finding has an evidence tier (T1-T4)
3. Quantitative output - ICI Response Score (0-100) with transparent component breakdown
4. Cancer-specific - All thresholds and predictions are cancer-type adjusted
5. Multi-biomarker - Integrate TMB + MSI + PD-L1 + neoantigen + mutations
6. Resistance-aware - Always check for known resistance mutations (STK11, PTEN, JAK1/2, B2M)
7. Drug-specific - Recommend specific ICI agents with evidence
8. Source-referenced - Every statement cites the tool/database source
9. English-first queries - Always use English terms in tool calls

When to Use