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":"[Truncated]"},"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

[!note] Vault audit 2026-07-24 — USE-16 Use this to generate an offline direct-to-consumer PGx report from a genotype/VCF (local script, CPIC gene-drug guidance); for live gene-drug lookups against the ClinPGx API use clinpgx, and for the image-triggered dosage card use drug-photo. Offline report generation vs live API vs image-triggered card is the distinguishing axis.

[!note] Running these commands in this vault The CLI examples below are written for the upstream ClawBio repo layout, where skills live under skills/ and a clawbio.py orchestrator exists. This flat skills vault has no clawbio.py: run a skill's script directly and drop the skills/ prefix — e.g. python pharmgx-reporter/pharmgx_reporter.py .... The clawbio.py run <cmd> multi-skill pipelines require the upstream ClawBio repo.

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	—

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 — Clinical Pharmacogenetics Implementation Consortium
• FDA Table of Pharmacogenomic Biomarkers — FDA-approved PGx drug labels