AIM

To construct a population pharmacokinetic model for methadone enantiomers in the setting of methadone maintenance treatment for opioid dependence.

METHODS

A population pharmacokinetic model was developed using P-Pharm software for rac-, (R)- and (S)-methadone using data (8-13 plasma samples per subject) obtained from 59 methadone maintenance patients during one interdosing interval at steady state. The patients were randomly assigned to either a development (n = 38) or a validation dataset (n = 21). The model was refined by inclusion of all subjects to construct a final basic model, which was used to construct a covariate model.

RESULTS

A population-based two-compartment open model with first-order absorption and lag time was developed and validated for all analytes. The population geometric mean (coefficient of variation) of maximum a posteriori probability Bayesian estimated values for clearance, terminal half-life and volume of distribution at steady-state of the active (R)-enantiomer were 8.7 (42%) l h(-1), 51 (45%) h and 597 (45%) l, respectively. For all analytes, the volume of the central compartment was decreased with increasing plasma alpha(1)-acid glycoprotein concentration and was lower in females, while the delay in absorption was longer at higher doses. No covariates were identified for apparent oral clearance. The apparent oral clearance of (R)-methadone (geometric mean ratio; 95% confidence interval) was 105% (99, 110), that of (S)-methadone (P = 0.19), while (R)-methadone V(c)/F (154%; 151, 157), V(dss) /F (173%; 164, 183), t(1/2beta) (162%; 153, 172) and mean residence time (166%; 156, 176) were significantly greater (P < 0.0001) than for (S)-methadone. The population pharmacokinetic models were able to predict accurately oral clearance values from limited (one or two samples) blood sampling protocols.

CONCLUSIONS

The substantial stereoselectivity in methadone disposition reinforces the potential for misinterpretation of racemic methadone disposition data. The marked interindividual variability in (R)-methadone clearance, with no covariates identified, highlights the need for alternative methods to determine an individual's metabolic clearance. The ability to predict (R)-methadone clearance from one to two blood samples at steady state may prove clinically useful if a drug-drug interaction or poor adherence are suspected and guide the prescriber in deciding if a client's request for a dose increase is warranted or whether an alternative opioid would be more appropriate.