Abstract
BACKGROUND AND OBJECTIVE: Tramadol is a widely used opioid, and pharmacogenetics is partially responsible for the variability in its response. The objective was to develop a tramadol population pharmacokinetic (popPK) model including pharmacogenetic information. METHODS: A single oral dose of 37.5 mg tramadol + 400 mg ibuprofen arginine was administered to 24 European healthy volunteers, and 18 blood samples were obtained from 0.25 h to 24 h after drug intake. Subjects were genotyped for the main pharmacogenes and a popPK model was built using NONMEM(®) (version 7.3). The role of CYP2D6, CYP2B6, and CYP3A4 phenotypes was analyzed. The final parameter estimates were compared with results obtained by noncompartmental analysis (NCA) in the same cohort. Simulations depending on CYP2D6 phenotype were performed in single dose and steady state conditions. RESULTS: A two-compartment model, with transit absorption into the depot compartment and first-order elimination, was the best fit to the data. In total, 8 volunteers were CYP2D6 intermediate metabolizers (IMs) and 14 were normal metabolizers (NMs), merged for the analysis with the two ultrarapid metabolizers (UMs), whereas no poor metabolizers (PMs) were present (European frequencies: 38.3%, 49.2%, 2.3%, and 6.5%, respectively). CYP2D6 phenotype affected clearance, which was 20% reduced in IMs compared with NMs + UMs. CYP2B6 (NMs = 11, IMs = 11, and PMs = 2) and CYP3A4 (NMs = 20, IMs = 3) phenotypes did not affect clearance. PopPK and NCA estimates were in close agreement. Simulations indicated a 20% and even 40% higher area under the curve after single dose and steady state conditions, respectively, in CYP2D6 IMs compared with NMs and UMs. CONCLUSIONS: A popPK model including CYP2D6 phenotype well described the data. Further research with increased sample size is needed to analyze the clinical impact and effect of CYP2B6 and CYP3A4 phenotype on tramadol pharmacokinetics.