Population pharmacokinetics of methadone in opiate users: characterization of time-dependent changes

Abstract

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.

Figure 1

Predictions of plasma methadone concentrations during continuous drug administration from single dose (thicker line) or late dose (thinner line) data. Experimental data are normalised for a dose of 10 mg methadone HCl and indicated by ▪.

Figure 2

Model fits (lines) to plasma methadone concentrations (data points) in a representative individual according to the time bin (TB) used (▪ TB I = 0–120 h; □ TB II = 120–300 h; • TB III≥300 h). Experimental data are normalised for a daily dose of 10 mg methadone HCl.

Figure 4

Model fits to the same individual data set: (a) simple two compartment model, (b) as (a) but with time-dependent clearance, and (c) as (a) but with time-dependent clearance and volume of distribution (experimental data are normalised for a daily dose of 10 mg methadone HCl).

Figure 3

Fit (line) of model incorporating time-dependent clearance to plasma methadone concentrations (▪) in a representative subject. Experimental data are from the same subject as shown in Figure 2.

Figure 5

Individual estimates of (a) oral clearance, (b) terminal elimination half-life, and (c) volume of distribution obtained using a simple two compartment model (no time dependency in any PK parameter) and on incorporating time-dependence in clearance and distribution ((0) signifies first dose value; (ss) signifies values at steady state).

Figure 6

Plasma α₁-acid glycoprotein concentrations in subjects taking part in protocol G3. Solid line indicates the best regression fit (r² = 0.054; P=0.17).