Abstract
Although methadone is widely used to treat opiate dependence, guidelines for its dosage are poorly defined. There is increasing evidence to suggest that a strategy based on plasma drug monitoring may be useful to detect non-compliance. Therefore, we have developed a population-based pharmacokinetic (POP-PK) model that characterises adaptive changes in methadone kinetics. Sparse plasma rac-methadone concentrations measured in 35 opiate-users were assessed using the P-Pharm software. The final structural model comprised a biexponential function with first-order input and allowance for time-dependent change in both clearance (CL) and initial volume of distribution (V ). Values of these parameters were allowed to increase or decrease exponentially to an asymptotic value. Increase in individual values of CL and increase or decrease in individual values of V with time was observed in applying the model to the experimental data. A time-dependent increase in the clearance of methadone is consistent with auto-induction of CYP3A4, the enzyme responsible for much of the metabolism of the drug. The changes in V with time might reflect both up- and down-regulation of alpha1-acid glycoprotein, the major plasma binding site for methadone. By accounting for adaptive kinetic changes, the POP-PK model provides an improved basis for forecasting plasma methadone concentrations to predict and adjust dosage of the drug and to monitor compliance in opiate-users on maintenance treatment.
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