Transform medication safety and efficacy by tailoring drug selection and dosing to each patient's genetic profile. Reduce adverse drug reactions, optimize therapeutic outcomes, and deliver actionable PGx reports to clinicians.
of all medications metabolized by CYP2D6 alone
Distinct alleles identified for CYP2D6
of patients with abnormal CYP2D6 copy numbers
Until recently, drug dosages have been determined by averaging responses across populations—an approach that is suboptimal and sometimes dangerous. A dosage that is effective for one patient may be ineffective for another, or even toxic. Pharmacogenomics changes this by using genetic information to guide prescribing decisions.
Genetic variability in drug-metabolizing enzymes is a leading cause of adverse reactions. Identifying poor and ultra-rapid metabolizers before prescribing prevents dangerous outcomes.
Matching drug selection and dosage to a patient's metabolizer phenotype ensures maximum efficacy while minimizing side effects and treatment failures.
CPIC and FDA pharmacogenomic guidelines provide evidence-based recommendations linking specific genotypes to drug therapy adjustments across hundreds of medications.
Pharmacogenomic testing directly informs prescribing for some of the most commonly used medications in medicine. Understanding key gene-drug interactions prevents life-threatening events and improves patient outcomes across specialties.
Poor metabolizers get no therapeutic benefit; ultra-rapid metabolizers risk respiratory depression from excess morphine conversion.
Reduced CYP2C19 activity compromises antiplatelet activation, increasing risk of stroke and heart attack in affected patients.
SLCO1B1 variants reduce hepatic transporter function, leading to elevated statin levels and increased risk of myopathy.
VKORC1 and CYP2C9 variants determine warfarin sensitivity; standard doses can cause life-threatening bleeding in susceptible patients.
An effective PGx program requires more than variant detection. The clinical workflow must translate raw genetic data into standardized allele calls, metabolizer phenotypes, and guideline-backed prescribing recommendations.
Automated mapping of SNVs, indels, and structural variants to standardized star allele nomenclature. Handles complex loci like CYP2D6 with copy number variations and hybrid alleles.
VSPGx ModuleIntegrate CPIC Tier A and Tier B gene-drug pairs directly into the interpretation workflow. Automatically link diplotypes to metabolizer phenotypes and evidence-based prescribing recommendations.
Clinical InterpretationGenerate clinician-ready reports with current medications, gene-drug interactions by severity, specific prescribing recommendations, and tested allele summaries. Fully customizable for your laboratory.
Workflow AutomationImplementing clinical pharmacogenomics requires consistent interpretation, standardized reporting, and efficient workflows. Golden Helix provides the infrastructure to adopt PGx testing at scale across any assay type.
End-to-end pharmacogenomics: star allele calling, diplotype assignment, phenotype classification, and CPIC-driven clinical reporting.
Analyze NGS-based pharmacogenomic panels with streamlined workflows purpose-built for high-throughput clinical testing.
Extract pharmacogenomic insights from WES and WGS data alongside primary clinical analysis for rare disease or oncology cases.
Explore our featured articles and expert-led webcasts on clinical pharmacogenomics and precision prescribing.
Join leading clinical laboratories using Golden Helix to deliver actionable pharmacogenomic insights and CPIC-guided prescribing recommendations.