Population-based pharmacokinetic approach for methadone monitoring of opiate addicts: potential clinical utility.
OBJECTIVE
There is evidence that plasma methadone measurements may be of benefit in dosage adjustment during methadone maintenance treatment for opiate dependence. However, to date the kinetics of oral rac-methadone have been poorly characterized. We describe plasma methadone concentration-time data collected from 35 opiate addicts.


METHODS
Oral doses of rac-methadone were given to 24 male and 11 female addicts attending a community-based drug treatment centre.


METHODS
Plasma methadone concentrations were measured by liquid chromatography (HPLC).


METHODS
Plasma concentration-time data were collected from patients prescribed oral rac-methadone in order to describe the complex kinetics of the drug incorporating its long elimination half-life.


RESULTS
Auto-induction of methadone metabolism was demonstrated and it was observed that clearance of methadone was significantly lower (p < 0.05) in opiate addicts at the start of treatment (median elimination half-life, 128-hours) than in those who had reached steady-state (median elimination half-life, 48 hours). Our data has provided the basis for a population-based pharmacokinetic (POP-PK) model which is intended for use as a clinical tool in association with plasma measurements in methadone maintenance patients.


CONCLUSIONS
Using plasma monitoring in combination with the application of Bayesian forecasting it should be possible to predict trough levels of methadone during daily dosing. The model is able to utilize sparse sampling, and two blood samples are expected to be sufficient to define patient compliance. Random samples during treatment could be used to assess methadone dosing by comparing predicted with observed measurements for each individual. The clinical tool could therefore help to detect incomplete (failure to consume the whole daily dose as prescribed) and poor (due to ingestion of extra illicit methadone) compliance as well as therapeutic failure due to drug-drug interactions. Targeting resources in this way could be a cost-effective tool for supervision of methadone dosing.
Wolff
K
K
National Addiction Centre, Institute of Psychiatry, 4 Windsor Walk, Denmark Hill, London SE5 8AF.
Rostami-Hodjegan
A
A
Hay
A W
AW
Raistrick
D
D
Tucker
G
G
D000284:Administration, Oral; D000293:Adolescent; D000328:Adult; D001499:Bayes Theorem; D002851:Chromatography, High Pressure Liquid; D016903:Drug Monitoring / Q000379:methods*; D005260:Female; D006207:Half-Life; D006556:Heroin Dependence / Q000097:blood / Q000534:rehabilitation*; D006801:Humans; D008297:Male; D008691:Methadone / Q000008:administration & dosage / Q000493:pharmacokinetics*; D009294:Narcotics / Q000008:administration & dosage / Q000493:pharmacokinetics*; D010349:Patient Compliance; D011237:Predictive Value of Tests
D009294:Narcotics; D008691:Methadone