Chantal Csajka1,2, Séverine Crettol3, Monia Guidi4,5, Chin B Eap4,3. 1. School of Pharmaceutical Sciences, University of Geneva, University of Lausanne, Geneva, Switzerland. chantal.csajka@chuv.ch. 2. Division of Clinical Pharmacology and Toxicology, Service of Biomedicine, University Hospital Center and University of Lausanne, Lausanne, Switzerland. chantal.csajka@chuv.ch. 3. Unit of Pharmacogenetics and Clinical Psychopharmacology, Centre for Psychiatric Neuroscience, Department of Psychiatry, Lausanne University Hospital, Lausanne, Switzerland. 4. School of Pharmaceutical Sciences, University of Geneva, University of Lausanne, Geneva, Switzerland. 5. Division of Clinical Pharmacology and Toxicology, Service of Biomedicine, University Hospital Center and University of Lausanne, Lausanne, Switzerland.
Abstract
BACKGROUND AND OBJECTIVES: Methadone is a μ-opioid agonist widely used for the treatment of pain, and for detoxification or maintenance treatment in opioid addiction. It has been shown to exhibit large pharmacokinetic variability and concentration-QTc relationships. In this study we investigated the relative influence of genetic polymorphism and other variables on the dose concentration-QTc relationship. PATIENTS AND METHODS: A population model for methadone enantiomers in 251 opioid-dependent patients was developed using non-linear mixed effect modeling (NONMEM®). Various models were tested to characterize the pharmacokinetics of (R)- and (S)-methadone and the pharmacokinetic-pharmacodynamic relationship, while including demographics, physiological conditions, co-medications, and genetic variants as covariates. Model-based simulations were performed to assess the relative increase in QTc with dose upon stratification according to genetic polymorphisms involved in methadone disposition. RESULTS: A two-compartment model with first-order absorption and lag time provided the best model fit for (R)- and (S)-methadone pharmacokinetics. (S)-methadone clearance was influenced by cytochrome P450 (CYP) 2B6 activity, ABCB1 3435C>T, and α-1 acid glycoprotein level, while (R)-methadone clearance was influenced by CYP2B6 activity, POR*28, and CYP3A4*22. A linear model described the methadone concentration-QTc relationship, with a mean QTc increase of 9.9 ms and 19.2 ms per 1000 ng/ml of (R)- and (S)-methadone, respectively. Simulations with different methadone doses up to 240 mg/day showed that <8 % of patients presented with a QTc interval above 450 ms; however, this might reach 12 to 18 % for (R)- and (S)-methadone, respectively, in patients with a genetic status associated with a decreased methadone elimination at doses exceeding 240 mg/day. CONCLUSION: Risk factor assessment, electrocardiogram monitoring, and therapeutic drug monitoring are beneficial to optimize treatment in methadone patients, especially for those who have low levels despite high methadone doses, or who are at risk of overdosing.
BACKGROUND AND OBJECTIVES:Methadone is a μ-opioid agonist widely used for the treatment of pain, and for detoxification or maintenance treatment in opioid addiction. It has been shown to exhibit large pharmacokinetic variability and concentration-QTc relationships. In this study we investigated the relative influence of genetic polymorphism and other variables on the dose concentration-QTc relationship. PATIENTS AND METHODS: A population model for methadone enantiomers in 251 opioid-dependent patients was developed using non-linear mixed effect modeling (NONMEM®). Various models were tested to characterize the pharmacokinetics of (R)- and (S)-methadone and the pharmacokinetic-pharmacodynamic relationship, while including demographics, physiological conditions, co-medications, and genetic variants as covariates. Model-based simulations were performed to assess the relative increase in QTc with dose upon stratification according to genetic polymorphisms involved in methadone disposition. RESULTS: A two-compartment model with first-order absorption and lag time provided the best model fit for (R)- and (S)-methadone pharmacokinetics. (S)-methadone clearance was influenced by cytochrome P450 (CYP) 2B6 activity, ABCB1 3435C>T, and α-1 acid glycoprotein level, while (R)-methadone clearance was influenced by CYP2B6 activity, POR*28, and CYP3A4*22. A linear model described the methadone concentration-QTc relationship, with a mean QTc increase of 9.9 ms and 19.2 ms per 1000 ng/ml of (R)- and (S)-methadone, respectively. Simulations with different methadone doses up to 240 mg/day showed that <8 % of patients presented with a QTc interval above 450 ms; however, this might reach 12 to 18 % for (R)- and (S)-methadone, respectively, in patients with a genetic status associated with a decreased methadone elimination at doses exceeding 240 mg/day. CONCLUSION: Risk factor assessment, electrocardiogram monitoring, and therapeutic drug monitoring are beneficial to optimize treatment in methadonepatients, especially for those who have low levels despite high methadone doses, or who are at risk of overdosing.
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