CYP2D6 metabolizes approximately 25% of all clinically used drugs — including codeine, tramadol, many antidepressants, and beta-blockers. Poor metabolizers accumulate toxic drug levels; ultrarapid metabolizers may receive subtherapeutic doses. One of the most actionable pharmacogenomic findings in practice.
CYP2C19 governs metabolism of clopidogrel (antiplatelet), common SSRIs, and proton pump inhibitors. Poor metabolizers on clopidogrel have significantly elevated cardiovascular event risk — the FDA has added pharmacogenomics warnings to the drug label based on this evidence.
The VKORC1 and CYP2C9 combination explains the majority of warfarin dose variability in clinical populations. Together with CYP4F2, these variants form the basis for pharmacogenomics-guided warfarin dosing algorithms recommended by the FDA and CPIC.
SLCO1B1 encodes a hepatic transporter that determines statin uptake into the liver. The c.521T>C variant significantly increases simvastatin exposure — leading to elevated myopathy risk at standard doses. A straightforward genetic test that could prevent one of the most common adverse drug reactions.
HLA-B*57:01 is required testing before abacavir (HIV treatment) prescription — carriers have near-100% risk of a severe hypersensitivity reaction. HLA-B*15:02 predicts carbamazepine-induced Stevens-Johnson syndrome in Southeast Asian populations. The highest-stakes pharmacogenomics findings in clinical use.
TPMT and NUDT15 variants determine thiopurine metabolism — affecting the safe dose of azathioprine and mercaptopurine in autoimmune and oncology settings. CPIC recommends dose reductions of 30–90% in intermediate and poor metabolizers — a directly life-affecting pharmacogenomics finding.
Structured metabolizer phenotype for each major CYP450 enzyme — poor, intermediate, normal, or ultrarapid — with drug-specific implications surfaced for the most clinically relevant compounds in each pathway.
HLA-associated hypersensitivity risks, statin myopathy risk, thiopurine toxicity risk, and other high-stakes adverse reaction markers — clearly graded and linked to primary clinical evidence and guideline recommendations.
Structured, actionable prescribing considerations for affected drug classes — tied to the specific variant, the specific drug, and the specific clinical implication. Designed for integration into clinical workflows without requiring pharmacogenomics specialists to interpret.
CPIC, PharmGKB, and FDA label updates are tracked and incorporated. As new pharmacogenomics evidence reaches clinical consensus, it enters the GeneOps knowledge base — ensuring the data your product delivers stays current with the science.
Discuss how medication safety genomics integrates into your clinical workflow, wellness platform, or consumer health product. We'll walk through coverage and clinical context.