The most clinically impactful pharmacogenomic variants — covering the metabolic pathways responsible for the majority of drug metabolism and the most common sources of adverse drug reactions.
CYP2D6, CYP2C19, CYP2C9, CYP3A4, and CYP1A2 — the enzymes responsible for metabolizing the majority of clinically used drugs. Poor, intermediate, extensive, and ultrarapid metabolizer phenotypes, with drug-specific implications.
SLCO1B1, ABCB1, and ABCG2 — transporter variants affecting bioavailability and tissue distribution of statins, antiretrovirals, and other transporter-sensitive compounds. Adverse reaction risk stratified by variant.
VKORC1 and CYP2C9 — the primary determinants of warfarin sensitivity and dosing. Extended to include NOACs and antiplatelet pharmacogenomics where evidence supports actionable guidance.
OPRM1 opioid receptor variation, ADRB1/ADRB2 beta-adrenergic receptor polymorphisms, and dopamine receptor variants — affecting drug efficacy and dose-response relationships in the target population.
NAT2 acetylation status, TPMT thiopurine metabolism, UGT1A1 glucuronidation — relevant to oncology, immunosuppression, and psychiatric pharmacogenomics.
HLA-B*57:01 (abacavir), HLA-B*15:02 (carbamazepine), and other HLA alleles associated with severe cutaneous adverse reactions — the most actionable pharmacogenomic findings in clinical practice.
Genomic segmentation for clinical trial design and post-market analysis. Identify the patient populations most likely to respond, those at elevated adverse reaction risk, and the dosing windows that genomics predicts.
Structured pharmacogenomic data that supports companion diagnostic development — surfacing the variant profiles that correlate with efficacy or safety outcomes in your specific compound's mechanism of action.
An API layer that surfaces relevant pharmacogenomic findings at the point of prescribing — integrated into clinical workflows to flag metabolizer status, contraindications, and dosing considerations.
A structured, citation-traceable pharmacogenomics layer that supports label language development, prescribing information updates, and regulatory submission packages requiring genomic evidence.
We'll walk through the coverage relevant to your compound, the integration architecture, and the evidence standard our data is built to.