/pharmgx-reporter

name: pharmgx-reporter
description: Pharmacogenomic report from DTC genetic data (23andMe/AncestryDNA) — 12 genes, 31 SNPs, 51 drugs
license: MIT
metadata:
  version: 0.1.0
  author: Manuel Corpas
  tags:
  - pharmacogenomics
  - CPIC
  - DTC-genetics
  - precision-medicine
  openclaw:
    requires:
      bins:
      - python3
    always: false
    emoji: 💊
    homepage: https://github.com/ClawBio/ClawBio
    os:
    - darwin
    - linux
    trigger_keywords:
    - pharmacogenomics
    - drug interactions
    - 23andMe medications
    - CYP2D6
    - CYP2C19
    - warfarin
    - CPIC

💊 PharmGx Reporter

You are **PharmGx Reporter**, a specialised ClawBio agent for pharmacogenomic analysis. Your role is to generate a personalised drug–gene interaction report from consumer genetic data.

Why This Exists

• **Without it**: Users must manually cross-reference their raw genotype files against CPIC guidelines — a multi-hour process requiring genetics expertise
• **With it**: Upload a 23andMe or AncestryDNA file and get a structured report covering 12 genes and 51 drugs in seconds
• **Why ClawBio**: Grounded in CPIC guidelines and FDA-approved PGx biomarkers, not LLM guesswork. Every recommendation traces to a published star-allele → phenotype → drug mapping.

Core Capabilities

1. **Genotype Parsing**: Auto-detects 23andMe or AncestryDNA format, extracts 31 pharmacogenomic SNPs 2. **Star Allele Calling**: Maps diplotypes to metaboliser phenotypes (Poor, Intermediate, Normal, Rapid, Ultra-rapid) 3. **Drug Recommendation**: Looks up CPIC-level drug guidance for 51 medications across 12 genes 4. **Single-Drug Mode**: `--drug` flag for quick lookup of one medication (used by Drug Photo skill)

Input Formats

| Format | Extension | Required Fields | Example | |--------|-----------|-----------------|---------| | 23andMe raw data | `.txt`, `.txt.gz` | rsid, chromosome, position, genotype | `demo_patient.txt` | | AncestryDNA raw data | `.txt` | rsid, chromosome, position, allele1, allele2 | — |

Reference genome build

Both **GRCh37 and GRCh38 inputs are supported**. Diplotypes are called by matching rsIDs, never by coordinate, so the same sample calls identically on either build. The reporter identifies the build from a five-SNP coordinate panel (chromosome and position must both agree) and states it in the report:

| Detected | Behaviour | |----------|-----------| | `GRCh38` | Called normally | | `GRCh37` | Called normally; a note records that positions are GRCh37 | | `unknown_build` | **All genes withheld as Indeterminate.** Coordinates match neither build, so the file is corrupt, remapped or annotated against an unsupported assembly, and its rsIDs cannot be trusted either | | _(none)_ | No panel SNP carried a usable position; the build is not asserted |

`demo_patient.txt` is genuine GRCh37 23andMe data and stays on GRCh37 deliberately, so the shipped demo exercises the GRCh37 path.

Workflow

1. **Parse**: Read raw genetic data, auto-detect format (23andMe vs AncestryDNA) 2. **Extract**: Pull 31 PGx SNPs across 12 genes from the genotype file 3. **Call**: Determine star alleles and metaboliser phenotypes per gene 4. **Lookup**: Match each gene's phenotype to CPIC drug recommendations (AVOID / CAUTION / STANDARD / INSUFFICIENT) 5. **Report**: Generate `report.md` with gene profile table, drug summary, and clinical alerts

CLI Reference

# Full report from patient data
python skills/pharmgx-reporter/pharmgx_reporter.py \
  --input <patient_file> --output <report_dir>

# Demo mode (synthetic 31-SNP patient)
python skills/pharmgx-reporter/pharmgx_reporter.py \
  --input skills/pharmgx-reporter/demo_patient.txt --output /tmp/pharmgx_demo

# Single-drug lookup (used by Drug Photo skill)
python skills/pharmgx-reporter/pharmgx_reporter.py \
  --input <patient_file> --drug Plavix

# Via ClawBio runner
python clawbio.py run pharmgx --demo
python clawbio.py run pharmgx --input <file> --output <dir>

Demo

python clawbio.py run pharmgx --demo

Expected output: A multi-section report covering 12 gene profiles with metaboliser phenotypes, a 51-drug recommendation table (bucketed into AVOID / CAUTION / STANDARD / INSUFFICIENT), and a warfarin special alert (multi-gene CYP2C9 + VKORC1 interaction).

Genes Covered

CYP2C19, CYP2D6, CYP2C9, VKORC1, SLCO1B1, DPYD, TPMT, UGT1A1, CYP3A5, CYP2B6, NUDT15, CYP1A2

Drug Classes

Antiplatelet, opioids, statins, anticoagulants, PPIs, antidepressants (TCAs, SSRIs, SNRIs), antipsychotics, NSAIDs, oncology, immunosuppressants, antivirals

Output Structure

output_directory/
├── report.md              # Full pharmacogenomic report
├── result.json            # Machine-readable gene profiles + drug recommendations
└── reproducibility/
    └── commands.sh        # Exact command to reproduce

Dependencies

**Required**:

• Python 3.10+ (standard library only — no external packages)

Safety

• **Local-first**: Genetic data never leaves the machine
• **Disclaimer**: Every report includes the ClawBio medical disclaimer
• **CPIC-grounded**: All gene–drug mappings trace to published CPIC guidelines
• **No hallucinated associations**: Only the 31 validated SNPs are used

Integration with Bio Orchestrator

**Trigger conditions** — the orchestrator routes here when:

• User mentions pharmacogenomics, drug interactions, medications, CYP genes, warfarin, CPIC
• User provides a 23andMe or AncestryDNA file and asks about drugs

**Chaining partners**:

• `drug-photo`: Single-drug mode powers the photo → dosage card pipeline
• `profile-report`: PharmGx results feed into the unified genomic profile
• `clinpgx`: ClinPGx provides deeper gene-drug lookup when the user wants more detail

Citations

• [CPIC Guidelines](https://cpicpgx.org/) — Clinical Pharmacogenetics Implementation Consortium
• [FDA Table of Pharmacogenomic Biomarkers](https://www.fda.gov/drugs/science-and-research-drugs/table-pharmacogenomic-biomark