bio-clinical-databases-pharmacogenomics

Version Compatibility

Reference examples tested with: pandas 2.2+

Before using code patterns, verify installed versions match. If versions differ:

• Python: pip show <package> then help(module.function) to check signatures

If code throws ImportError, AttributeError, or TypeError, introspect the installed package and adapt the example to match the actual API rather than retrying.

Pharmacogenomics

PharmGKB REST API

Goal: Retrieve drug-gene clinical annotations and dosing guidelines from PharmGKB.

Approach: Query PharmGKB REST endpoints by gene symbol or drug name and parse JSON annotation records.

"Find pharmacogenomic annotations for this gene" → Query PharmGKB for clinical annotations linking genes to drug response.

• Python: requests.get() against PharmGKB API (requests)

Query Drug-Gene Relationships

import requests

def get_pharmgkb_annotations(gene_symbol):
    '''Get PharmGKB clinical annotations for a gene'''
    url = f'https://api.pharmgkb.org/v1/data/clinicalAnnotation'
    params = {'view': 'base', 'location.genes.symbol': gene_symbol}
    response = requests.get(url, params=params)
    return response.json()['data']

annotations = get_pharmgkb_annotations('CYP2D6')
for ann in annotations[:5]:
    print(f"{ann['location']['genes'][0]['symbol']}: {ann['chemicals'][0]['name']}")

Query by Drug

def get_drug_annotations(drug_name):
    '''Get pharmacogenomic annotations for a drug'''
    url = 'https://api.pharmgkb.org/v1/data/clinicalAnnotation'
    params = {'view': 'base', 'chemicals.name': drug_name}
    response = requests.get(url, params=params)
    return response.json()['data']

warfarin_annotations = get_drug_annotations('warfarin')

Get Dosing Guidelines

def get_cpic_guidelines(gene_symbol):
    '''Get CPIC dosing guidelines for a gene'''
    url = 'https://api.pharmgkb.org/v1/data/guideline'
    params = {'view': 'base', 'relatedGenes.symbol': gene_symbol, 'source': 'CPIC'}
    response = requests.get(url, params=params)
    return response.json()['data']

guidelines = get_cpic_guidelines('CYP2C19')
for g in guidelines:
    print(f"{g['name']}: {g['chemicals'][0]['name']}")