precision-oncology-agent

$npx mdskill add swaruplab/operon/precision-oncology-agent

Fuse genomic and clinical data to rank evidence-linked therapies for tumor board.

  • Solves the challenge of integrating complex genomic and pathology data for treatment decisions.
  • Depends on OncoKB, NCCN guidelines, and internal knowledge bases for variant annotation.
  • Ranks therapies by evidence strength, patient fit, and contraindications from clinical context.
  • Delivers a ranked therapy list, variant table, and biomarker gap checklist as structured output.

SKILL.md

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---
name: precision-oncology-agent
description: Fuse genomic variants, pathology findings, and clinical context to draft evidence-linked therapy options for tumor board review.
allowed-tools:
  - read_file
  - run_shell_command
---

## At-a-Glance
- **description (10-20 chars):** Tumor board copilot
- **keywords:** oncology, genomics, OncoKB, therapy-ranking, evidence
- **measurable_outcome:** Deliver a ranked therapy list with OncoKB/NCCN citations plus data-gap checklist for every case within 10 minutes of receiving inputs.

## Inputs
- `vcf_path` (hg38 preferred) plus optional CNV/fusion summaries.
- `pathology_report` text for histology/grade/biomarkers.
- `clinical_context` dict capturing tumor type, stage, prior lines, ECOG.

## Outputs
1. Ranked treatment options (approved, off-label, clinical trials) with evidence strength + contraindications.
2. Variant interpretation table (pathogenicity, tier, therapy linkage).
3. Biomarker summary (TMB, MSI, PD-L1 if provided) and missing-test checklist.

## Workflow
1. **Ingest & normalize:** Harmonize gene symbols, genome build, and variant effects.
2. **Annotate:** Query OncoKB/NCCN + internal knowledge for actionability tiers.
3. **Contextualize:** Blend pathology + prior therapy info to filter contraindicated options.
4. **Recommend:** Present therapies ordered by evidence + patient fit; cite sources.
5. **Gaps:** Highlight assays or confirmations still required before treatment.

## Guardrails
- No autonomous treatment decisions—flag outputs as advisory.
- Cite evidence rigorously (guideline version, publication).
- Highlight resistance mechanisms and prior exposure conflicts.

## References
- See `README.md` for detailed workflow plus cited Nature Cancer study.

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