AIMS: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.
AIMS: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.
Authors: M Hassan; U S Svensson; P Ljungman; B Björkstrand; H Olsson; M Bielenstein; M Abdel-Rehim; C Nilsson; M Johansson; M O Karlsson Journal: Br J Clin Pharmacol Date: 1999-11 Impact factor: 4.335
Authors: Monica Rodriguez; M Angeles Carlos; Ignacio Ortega; Elena Suarez; Rosario Calvo; John C Lukas Journal: Pharm Res Date: 2002-06 Impact factor: 4.200