clinpgx-database

# ClinPGx Database

## Overview

ClinPGx (Clinical Pharmacogenomics Database) is a comprehensive resource for clinical pharmacogenomics information, successor to PharmGKB. It consolidates data from PharmGKB, CPIC, and PharmCAT, providing curated information on how genetic variation affects medication response. Access gene-drug pairs, clinical guidelines, allele functions, and drug labels for precision medicine applications.

## When to Use This Skill

This skill should be used when:

- **Gene-drug interactions**: Querying how genetic variants affect drug metabolism, efficacy, or toxicity
- **CPIC guidelines**: Accessing evidence-based clinical practice guidelines for pharmacogenetics
- **Allele information**: Retrieving allele function, frequency, and phenotype data
- **Drug labels**: Exploring FDA and other regulatory pharmacogenomic drug labeling
- **Pharmacogenomic annotations**: Accessing curated literature on gene-drug-disease relationships
- **Clinical decision support**: Using PharmDOG tool for phenoconversion and custom genotype interpretation
- **Precision medicine**: Implementing pharmacogenomic testing in clinical practice
- **Drug metabolism**: Understanding CYP450 and other pharmacogene functions
- **Personalized dosing**: Finding genotype-guided dosing recommendations
- **Adverse drug reactions**: Identifying genetic risk factors for drug toxicity

## Installation and Setup

### Python API Access

The ClinPGx REST API provides programmatic access to all database resources. Basic setup:

```bash
uv pip install requests
```

### API Endpoint

```python
BASE_URL = "https://api.clinpgx.org/v1/"
```

**Rate Limits**:
- 2 requests per second maximum
- Excessive requests will result in HTTP 429 (Too Many Requests) response

**Authentication**: Not required for basic access

**Data License**: Creative Commons Attribution-ShareAlike 4.0 International License

For substantial API use, notify the ClinPGx team at api@clinpgx.org

## Core Capabilities

### 1. Gene Queries

**Retrieve gene information** including function, clinical annotations, and pharmacogenomic significance:

```python
import requests

# Get gene details
response = requests.get("https://api.clinpgx.org/v1/gene/CYP2D6")
gene_data = response.json()

# Search for genes by name
response = requests.get("https://api.clinpgx.org/v1/gene",
                       params={"q": "CYP"})
genes = response.json()
```

**Key pharmacogenes**:
- **CYP450 enzymes**: CYP2D6, CYP2C19, CYP2C9, CYP3A4, CYP3A5
- **Transporters**: SLCO1B1, ABCB1, ABCG2
- **Other metabolizers**: TPMT, DPYD, NUDT15, UGT1A1
- **Receptors**: OPRM1, HTR2A, ADRB1
- **HLA genes**: HLA-B, HLA-A

### 2. Drug and Chemical Queries

**Retrieve drug information** including pharmacogenomic annotations and mechanisms:

```python
# Get drug details
response = requests.get("https://api.clinpgx.org/v1/chemical/PA448515")  # Warfarin
drug_data = response.json()

# Search drugs by name
response = requests.get("https://api.clinpgx.org/v1/chemical",
                       params={"name": "warfarin"})
drugs = response.json()
```

**Drug categories with pharmacogenomic significance**:
- Anticoagulants (warfarin, clopidogrel)
- Antidepressants (SSRIs, TCAs)
- Immunosuppressants (tacrolimus, azathioprine)
- Oncology drugs (5-fluorouracil, irinotecan, tamoxifen)
- Cardiovascular drugs (statins, beta-blockers)
- Pain medications (codeine, tramadol)
- Antivirals (abacavir)

### 3. Gene-Drug Pair Queries

**Access curated gene-drug relationships** with clinical annotations:

```python
# Get gene-drug pair information
response = requests.get("https://api.clinpgx.org/v1/geneDrugPair",
                       params={"gene": "CYP2D6", "drug": "codeine"})
pair_data = response.json()

# Get all pairs for a gene
response = requests.get("https://api.clinpgx.org/v1/geneDrugPair",
                       params={"gene": "CYP2C19"})
all_pairs = response.json()
```

**Clinical annotation sources**:
- CPIC (Clinical Pharmacogenetics Implementation Consortium)
- DPWG (Dutch Pharmacogenetics Working Group)
- FDA (Food and Drug Administration) labels
- Peer-reviewed literature summary annotations

### 4. CPIC Guidelines

**Access evidence-based clinical practice guidelines**:

```python
# Get CPIC guideline
response = requests.get("https://api.clinpgx.org/v1/guideline/PA166104939")
guideline = response.json()

# List all CPIC guidelines
response = requests.get("https://api.clinpgx.org/v1/guideline",
                       params={"source": "CPIC"})
guidelines = response.json()
```

**CPIC guideline components**:
- Gene-drug pairs covered
- Clinical recommendations by phenotype
- Evidence levels and strength ratings
- Supporting literature
- Downloadable PDFs and supplementary materials
- Implementation considerations

**Example guidelines**:
- CYP2D6-codeine (avoid in ultra-rapid metabolizers)
- CYP2C19-clopidogrel (alternative therapy for poor metabolizers)
- TPMT-azathioprine (dose reduction for intermediate/poor metabolizers)
- DPYD-fluoropyrimidines (dose adjustment based on activity)
- HLA-B*57:01-abacavir (avoid if positive)

### 5. Allele and Variant Information

**Query allele function and frequency data**:

```python
# Get allele information
response = requests.get("https://api.clinpgx.org/v1/allele/CYP2D6*4")
allele_data = response.json()

# Get all alleles for a gene
response = requests.get("https://api.clinpgx.org/v1/allele",
                       params={"gene": "CYP2D6"})
alleles = response.json()
```

**Allele information includes**:
- Functional status (normal, decreased, no function, increased, uncertain)
- Population frequencies across ethnic groups
- Defining variants (SNPs, indels, CNVs)
- Phenotype assignment
- References to PharmVar and other nomenclature systems

**Phenotype categories**:
- **Ultra-rapid metabolizer** (UM): Increased enzyme activity
- **Normal metabolizer** (NM): Normal enzyme activity
- **Intermediate metabolizer** (IM): Reduced enzyme activity
- **Poor metaboliz