Increased (R)-methadone plasma concentrations by quetiapine in cytochrome P450s and ABCB1 genotyped patients

Combined in vivo metabolic effects of quetiapine and methadone in brain and blood of rats

Changes in pharmacokinetics and endogenous metabolites may underlie additive biological effects of concomitant use of antipsychotics and opioids. In this study, we employed untargeted metabolomics analysis and targeted analysis to examine the changes in drug metabolites and endogenous metabolites in the prefrontal cortex (PFC), midbrain, and blood of rats following acute co-administration of quetiapine and methadone. Rats were divided into four groups and received cumulative increasing doses of quetiapine (QTP), methadone (MTD), quetiapine + methadone (QTP + MTD), or vehicle (control). All samples were analyzed using liquid chromatography-mass spectrometry (LC-MS). Our findings revealed increased levels of the quetiapine metabolites: Norquetiapine, O-dealkylquetiapine, 7-hydroxyquetiapine, and quetiapine sulfoxide, in the blood and brain when methadone was present. Our study also demonstrated a decrease in methadone and its metabolite 2-ethylidene-1,5-dimethyl-3,3-diphenylpyrrolidine (EDDP) in the rat brain when quetiapine was present. Despite these findings, there were only small differences in the levels of 225-296 measured endogenous metabolites due to co-administration compared to single administrations. For example, N-methylglutamic acid, glutaric acid, p-hydroxyphenyllactic acid, and corticosterone levels were significantly decreased in the brain of rats treated with both compounds. Accumulation of serotonin in the midbrain was additionally observed in the MTD group, but not in the QTP + MTD group. In conclusion, this study in rats suggests a few but important additive metabolic effects when quetiapine and methadone are co-administered.

Combined effects of methadone and quetiapine on respiratory rate, haemodynamic variables, and temperature in conscious rats

Fatal poisonings where both methadone and quetiapine are detected post-mortem occurs frequently in legal autopsy cases. It is unclear whether quetiapine increases the risk of fatal methadone poisoning or if it is merely detected due to widespread use. We hypothesized that methadone and quetiapine would have additive toxic effects on respiratory rate, blood pressure, and the QTc-interval. To investigate this hypothesis, we used telemetry implants for measurements of respiratory rate, haemodynamic variables, the velocity of blood pressure changes, temperature, and movement in conscious, freely moving male Wistar rats aged 12-13 weeks. The combined effects of three accumulative i.p. doses of methadone (2.5, 10, 15 mg/kg) and quetiapine (3, 10, 30 mg/kg) were compared to rats treated with the same doses of each drug alone, and a vehicle-treated group in a randomized investigator blinded study. No additive effects of quetiapine and methadone on respiratory rate, haemodynamic variables, or movement were observed. However, body temperature was significantly lower by approximately 1.5°C on average in the group treated with both methadone and quetiapine (15 + 30 mg/kg) compared to the other groups. This indicates a synergistic effect of quetiapine and methadone on thermoregulation, which may increase the risk of fatal poisoning. We suggest studying this finding further in human settings.

Combined effects of quetiapine and opioids: A study of autopsy cases, drug users and sedation in rats

Fatal opioid poisonings often involve methadone or morphine. This study aimed to elucidate if quetiapine, a widely used sedative antipsychotic medication, may increase the risk of fatal opioid poisoning by additive inhibitory effects on the central nervous system. We used data from 323 cases of fatal methadone or/and morphine poisonings autopsied from 2013 to 2020, a survey of 34 drug users, and performed blinded placebo‐controlled studies in 75 Flinders Resistant Line rats receiving three cumulative intraperitoneal doses of vehicle, methadone (2.5, 10 and 15 mg/kg), morphine (3.75, 15 and 22.5 mg/kg), quetiapine (3, 10 and 30 mg/kg) or quetiapine combined with methadone or morphine. Quetiapine was detected in 20.4% of fatal opioid poisonings with a significantly increased frequency over time, primarily in low or therapeutic concentrations, and was not associated with methadone or morphine concentrations. Use of quetiapine, most commonly in low‐to‐moderate doses to obtain a sleep‐inducing or tranquillizing effect, was reported by 67.6% of survey respondents. In the animal studies, a significant impairment of sedation score, performance on the rotarod and open field mobility was observed in all treatment groups compared with vehicle. However, the effect of quetiapine plus the opioid was not significantly different from that of the opioid alone. Thus, no additive sedative effects were observed in rats. Our results suggest that quetiapine is more often an innocent bystander than a contributor to fatal opioid poisoning. However, the combined effects on other parameters, including blood pressure, cardiac rhythm and respiratory rate, need investigation.

Variants in COMT, CYP3A5, CYP2B6, and ABCG2 Alter Quetiapine Pharmacokinetics

Quetiapine is an atypical antipsychotic widely used for the treatment of schizophrenia and the depressive episodes of bipolar disorder. The aim of this work was to investigate the effect of variants in relevant pharmacogenes in the pharmacokinetics of quetiapine and to exploratorily evaluate adverse drug reaction (ADR) incidence based on genetic polymorphism. Specifically, 49 healthy volunteers enrolled in two bioequivalence clinical trials were included in this study. In addition, 80 variants in 19 relevant pharmacogenes were genotyped, including cytochrome P450 (CYP) genes, catechol-O-methyl transferase (COMT), other enzymes (e.g., UGT1A1 or UGT1A4), and transporters (e.g., SLCO1B1, ABCB1, or ABCG2). The COMT rs13306278 T allele was significantly related to quetiapine-increased exposure. We demonstrated the existence of quetiapine derivatives with a catechol-like structure (7,8-dihydroxi-quetiapine and 7,8-dihydroxi-N-desalkyl-quetiapine), which would be COMT metabolites and would explain quetiapine accumulation through CYP2D6 and CYP3A4 negative feedback. Moreover, CYP3A5 and CYP2B6 phenotypes were related to quetiapine exposure variability, which confirms (for CYP3A5) and suggests (for CYP2B6) that these enzymes play an important role in quetiapine’s metabolism. Finally, the ABCG2 rs2231142 T allele was related to quetiapine accumulation. Further studies are required to confirm the clinical relevance of our findings.

Novel associations between CYP2B6 polymorphisms, perioperative methadone metabolism and clinical outcomes in children

Aim: Methadone exhibits significant variability in clinical response. This study explores the genetic influence of variable methadone pharmacokinetics. Methods: This is a prospective study of methadone in children undergoing major surgery. CYP2B6 genotyping, plasma methadone and metabolite levels were obtained. Clinical outcomes include pain scores and postoperative nausea and vomiting (PONV). Results: CYP2B6 poor metabolizers (*6/*6) had >twofold lower methadone metabolism compared with normal/rapid metabolizers. The incidence of PONV was 4.7× greater with CYP2B6 rs1038376 variant. AG/GG variants of rs2279343 SNP had 2.86-fold higher incidence of PONV compared with the wild variant (AA). Nominal associations between rs10500282, rs11882424, rs4803419 and pain scores were observed. Conclusion: We have described novel associations between CYP2B6 genetic variants and perioperative methadone metabolism, and associations with pain scores and PONV.

Relapse-like behavior in a mouse model of the OPRM1 (mu-opioid receptor) A118G polymorphism: Examination with intravenous oxycodone self-administration

The widely abused prescription opioid oxycodone is a mu-opioid receptor (MOP-r) agonist and addiction to such opioids is a relapsing disorder. The human MOP-r gene (OPRM1) has an important functional single nucleotide polymorphism (SNP), A118G, which affects risk of severe opioid use disorders. A112G (G/G) knock-in mice are models of human A118G carriers. We examined oxycodone self-administration (SA) in male and female G/G versus wild type (A/A) mice in SA sessions and in relapse-like behavior. Adult male and female G/G and A/A mice self-administered oxycodone (0.25 mg/kg/infusion, FR1) for 10 consecutive days. Following 10-day home cage drug free withdrawal, the mice were re-exposed to oxycodone SA for a further 10 days. MOP-r receptor mRNA in various brain regions were examined immediately after the last re-exposure session. We found that G/G mice had greater oxycodone SA than A/A mice in the initial and in re-exposure sessions. Mice of both genotypes had greater oxycodone intake during the re-exposure period than during the initial exposure. We also detected differences in MOP-r gene expression due to genotype, sex and oxycodone SA history in the dorsal striatum, hippocampus, and prefrontal cortex. These studies may improve our understanding of MOP-r-agonist self-exposure and relapse in human carriers of the A118G SNP.

Quetiapine and other antipsychotics combined with opioids in legal autopsy cases: A random finding or cause of fatal outcome?

Opioid poisoning is a frequent cause of death in drug addicts and occurs with opioid treatment. Quetiapine is often found in forensic autopsies and may increase the risk of fatal opioid poisoning by enhancing sedation, respiratory depression, hypotension and QT prolongation. We systematically searched for studies of acute toxicity of quetiapine or other antipsychotics combined with morphine or methadone. Case reports describing toxicity of quetiapine combined with morphine or methadone were also included. We retrieved one human study that observed pharmacokinetic interaction between quetiapine and methadone, and 16 other human studies. Fourteen investigated the combination of droperidol and morphine in treatment doses, and some indicated an additive sedative effect. Five animal studies with acepromazine in combination with morphine or methadone were located and indicated an additive effect on sedation and hypotension. Six forensic case reports in which death could have been caused solely by quetiapine, the opioid, or other drugs were found. Thus, acute toxicity of quetiapine combined with morphine or methadone has not been studied. Because of quetiapine's effects on alpha-adrenoceptors, muscarinic and histamine receptors, human ether-a-go-go-channels and methadone kinetics, we suggest further research to clarify if the indicated additive effects of opioids and droperidol or acepromazine are also true for quetiapine.

Pharmacogenomics of methadone: a narrative review of the literature

Background: Methadone, a synthetic opioid with longer duration of action and lower abuse potential compared with morphine, is used to prevent opioid withdrawal, as well as to manage chronic and acute surgical pain. The variability in response to methadone has been widely recognized. The purpose of this article is to review the literature on the pharmacogenetic factors underlying this variability. Materials & methods: This is a narrative overview of the literature on the genetic variants affecting pharmacodynamics and pharmacokinetics of methadone, retrieved from searches of databases such as PubMed and google scholar. Discussion: Clinical responses to methadone may be affected by genetic variants in the opioidergic, dopaminergic and neurotrophic pathways. Polymorphisms in genes related to disposition and elimination of methadone alter the pharmacokinetics, and possibly pharmacodynamics of methadone. Cytochrome P450 enzymes and P-glycoprotein variants contribute to the interindividual variability in methadone pharmacokinetics. Evidence for single gene variants affecting methadone response remains weak. Multiple genetic variants must be considered in conjunction to improve predictive ability. Conclusion: Evidence remains scarce at this time, to recommend pharmacogenetic testing before methadone administration. Well-powered clinical studies are needed with population pharmacokinetic-pharmacodynamic modeling and multigenetic signature-based predictions to enable tailored use of methadone in clinical practice.

Drug-drug-gene interactions and adverse drug reactions

The economic and health burden caused by adverse drug reactions has increased dramatically in the last few years. This is likely to be mediated by increasing polypharmacy, which increases the likelihood for drug–drug interactions. Tools utilized by healthcare practitioners to flag potential adverse drug reactions secondary to drug–drug interactions ignore individual genetic variation, which has the potential to markedly alter the severity of these interactions. To date there have been limited published studies on impact of genetic variation on drug–drug interactions. In this review, we establish a detailed classification for pharmacokinetic drug–drug–gene interactions, and give examples from the literature that support this approach. The increasing availability of real-world drug outcome data linked to genetic bioresources is likely to enable the discovery of previously unrecognized, clinically important drug–drug–gene interactions.

Prevalence of Antipsychotic-Treated Patients in a Cohort of Adult Addicted Patients

PURPOSE

The objective of this cross-sectional study was to describe and estimate the prevalence of antipsychotics (AP) in a cohort of addicted patients, and to compare the profiles of addictive patients receiving AP or not.

METHODS

We included all adult patients seen at the addiction care center of Montpellier University Hospital, between January 1, 2015, and March 31, 2015. Demographic, clinical, and therapeutic data were collected from the patients' medical records.

RESULTS

During the study period, 415 patients were included, with a mean age of 38 ± 10 years. They were mostly men (73.3%), French (54.9%), and unemployed (61.8%). Among the study population, 93 patients (patients treated with AP [trAP], 22.4%) were treated by 111 different AP, mainly cyamemazine (29.0% of treated patients), aripiprazole (20.4%), olanzapine (17.2%), and quetiapine (16.1%), mostly in monotherapy (80.6%) and by oral route (93.2% of AP). Psychiatric history was more frequent in trAP than in those without AP (untrAP) (55.9% vs 35.4% respectively; P < 0.001). Professional activity tended to be less frequent in patients with AP (25.3% vs 38.9%, P = 0.08).When compared with untrAP, trAP consumed more amphetamine (10.8% vs 4.4%; P = 0.02) and tended to consume less opiates (7.5% vs 14.9%; P = 0.06); the consumptions of cannabis (43.0% vs 35.7%; P = 0.20) and cocaine (22.6% vs 16.8%; P = 0.20) were not statistically different.Opiate maintenance therapy was reported in 63.7% of trAP and 68.4% of untrAP (P = 0.41): it consisted of methadone (trAP, 60.3% vs untrAP, 56.5%) and buprenorphine (trAP, 39.7% vs untrAP, 43.5%).

CONCLUSIONS

The concomitant management of psychiatric and substance use disorders in the same center may explain the high prevalence of trAP in this study. Cannabis and psychostimulants may have been used in these patients as self-medication for mental disease-related symptoms or adverse effects of APs.

Polydrug abuse among opioid maintenance treatment patients is related to inadequate dose of maintenance treatment medicine

BACKGROUND

Polydrug abuse is a known problem among opioid-dependent patients receiving opioid maintenance treatment (OMT). However, improved laboratory diagnostics is required to reveal polydrug abuse in its current scope. Furthermore, there are few studies focusing on the relationship between polydrug abuse and adequacy of the dose of OMT medicine. This study aimed to evaluate the polydrug abuse among opioid-dependent patients receiving OMT with inadequate (Group IA) and adequate (Group A) doses of OMT medicine as experienced by the patients. Craving for opioids and withdrawal symptoms were evaluated as indicators of the adequacy rating.

METHODS

This is a retrospective register-based study of 60 OMT patients on either methadone or sublingual buprenorphine/naloxone medication, whose polydrug abuse was studied from urine samples by means of a comprehensive high-resolution mass spectrometry method.

RESULTS

Inadequate doses of the OMT medicines were associated with higher subjective withdrawal scores and craving for opioids. Six groups of abused substances (benzodiazepines, amphetamines, opioids, cannabis, new psychoactive substances, and non-prescribed psychotropic medicines) were found among OMT patients. Group IA patients showed significantly more abuse of benzodiazepines and amphetamines than the Group A patients. All the new psychoactive substances and most of the non-prescribed psychotropic medicines were detected from the Group IA patients. There was no difference in the doses of the OMT medicine between Groups IA and A patients.

CONCLUSIONS

Polydrug abuse, detected by definitive laboratory methods, was widespread and more common among Group IA than Group A patients, emphasizing the requirement for individual OMT medicine dose adjustment.

Coupling Data Mining and Laboratory Experiments to Discover Drug Interactions Causing QT Prolongation

BACKGROUND

QT interval-prolonging drug-drug interactions (QT-DDIs) may increase the risk of life-threatening arrhythmia. Despite guidelines for testing from regulatory agencies, these interactions are usually discovered after drugs are marketed and may go undiscovered for years.

OBJECTIVES

Using a combination of adverse event reports, electronic health records (EHR), and laboratory experiments, the goal of this study was to develop a data-driven pipeline for discovering QT-DDIs.

METHODS

1.8 million adverse event reports were mined for signals indicating a QT-DDI. Using 1.6 million electrocardiogram results from 380,000 patients in our institutional EHR, these putative interactions were either refuted or corroborated. In the laboratory, we used patch-clamp electrophysiology to measure the human ether-à-go-go-related gene (hERG) channel block (the primary mechanism by which drugs prolong the QT interval) to evaluate our top candidate.

RESULTS

Both direct and indirect signals in the adverse event reports provided evidence that the combination of ceftriaxone (a cephalosporin antibiotic) and lansoprazole (a proton-pump inhibitor) will prolong the QT interval. In the EHR, we found that patients taking both ceftriaxone and lansoprazole had significantly longer QTc intervals (up to 12 ms in white men) and were 1.4 times more likely to have a QTc interval above 500 ms. In the laboratory, we found that, in combination and at clinically relevant concentrations, these drugs blocked the hERG channel. As a negative control, we evaluated the combination of lansoprazole and cefuroxime (another cephalosporin), which lacked evidence of an interaction in the adverse event reports. We found no significant effect of this pair in either the EHR or in the electrophysiology experiments. Class effect analyses suggested this interaction was specific to lansoprazole combined with ceftriaxone but not with other cephalosporins.

CONCLUSIONS

Coupling data mining and laboratory experiments is an efficient method for identifying QT-DDIs. Combination therapy of ceftriaxone and lansoprazole is associated with increased risk of acquired long QT syndrome.

Pharmacogenetics of drug-drug interaction and drug-drug-gene interaction: a systematic review on CYP2C9, CYP2C19 and CYP2D6

Currently, most guidelines on drug-drug interaction (DDI) neither consider the potential effect of genetic polymorphism in the strength of the interaction nor do they account for the complex interaction caused by the combination of DDI and drug-gene interaction (DGI) where there are multiple biotransformation pathways, which is referred to as drug-drug-gene interaction (DDGI). In this systematic review, we report the impact of pharmacogenetics on DDI and DDGI in which three major drug-metabolizing enzymes - CYP2C9, CYP2C19 and CYP2D6 - are central. We observed that several DDI and DDGI are highly gene-dependent, leading to a different magnitude of interaction. Precision drug therapy should take pharmacogenetics into account when drug interactions in clinical practice are expected.

An Integrative Data Science Pipeline to Identify Novel Drug Interactions that Prolong the QT Interval

Introduction

Drug-induced prolongation of the QT interval on the electrocardiogram (long QT syndrome, LQTS) can lead to a potentially fatal ventricular arrhythmia known as torsades de pointes (TdP). Over 40 drugs with both cardiac and non-cardiac indications are associated with increased risk of TdP, but drug–drug interactions contributing to LQTS (QT-DDIs) remain poorly characterized. Traditional methods for mining observational healthcare data are poorly equipped to detect QT-DDI signals due to low reporting numbers and lack of direct evidence for LQTS.

Objective

We hypothesized that LQTS could be identified latently using an adverse event (AE) fingerprint of more commonly reported AEs. We aimed to generate an integrated data science pipeline that addresses current limitations by identifying latent signals for QT-DDIs in the US FDA’s Adverse Event Reporting System (FAERS) and retrospectively validating these predictions using electrocardiogram data in electronic health records (EHRs).

Methods

We trained a model to identify an AE fingerprint for risk of TdP for single drugs and applied this model to drug pair data to predict novel DDIs. In the EHR at Columbia University Medical Center, we compared the QTc intervals of patients prescribed the flagged drug pairs with patients prescribed either drug individually.

Results

We created an AE fingerprint consisting of 13 latently detected side effects. This model significantly outperformed a direct evidence control model in the detection of established interactions (p = 1.62E−3) and significantly enriched for validated QT-DDIs in the EHR (p = 0.01). Of 889 pairs flagged in FAERS, eight novel QT-DDIs were significantly associated with prolonged QTc intervals in the EHR and were not due to co-prescribed medications.

Conclusions

Latent signal detection in FAERS validated using the EHR presents an automated and data-driven approach for systematically identifying novel QT-DDIs. The high-confidence hypotheses flagged using this method warrant further investigation.

Electronic supplementary material

The online version of this article (doi:10.1007/s40264-016-0393-1) contains supplementary material, which is available to authorized users.

Relationship between ABCB1 polymorphisms and serum methadone concentration in patients undergoing methadone maintenance therapy (MMT)

BACKGROUND

Methadone is a substrate of the permeability glycoprotein (P-gp) efflux transporter, which is encoded by the ABCB1 (MDR1) gene. Large interindividual variability in serum methadone levels for therapeutic response has been reported. Genetic variations in ABCB1 gene may be responsible for the variability in observed methadone concentrations.

OBJECTIVE

This study investigated the associations of ABCB1 polymorphisms and serum methadone concentration over the 24-hour dosing interval in opioid-dependent patients on methadone maintenance therapy (MMT).

METHODS

One hundred and forty-eight male opioid-dependent patients receiving MMT were recruited. Genomic deoxyribonucleic acid (DNA) was extracted from whole blood and genotyped for ABCB1 polymorphisms [i.e. 1236C>T (dbSNP rs1128503), 2677G>T/A (dbSNP rs2032582), and 3435C>T (dbSNP rs1045642)] using the allelic discrimination real-time polymerase chain reaction (PCR). Blood samples were collected at 0, 0.5, 1, 2, 4, 8, 12, and 24 hours after the dose. Serum methadone concentrations were measured using the Methadone ELISA Kit.

RESULTS

Our results revealed an association of CGC/TTT diplotype (1236C>T, 2677G>T/A, and 3435C>T) with dose-adjusted serum methadone concentration over the 24-hour dosing interval. Patients with CGC/TTT diplotype had 32.9% higher dose-adjusted serum methadone concentration over the 24-hour dosing interval when compared with those without the diplotype [mean (SD) = 8.12 (0.84) and 6.11 (0.41) ng ml^-1 mg^-1, respectively; p = 0.033].

CONCLUSION

There was an association between the CGC/TTT diplotype of ABCB1 polymorphisms and serum methadone concentration over the 24-hour dosing interval among patients on MMT. Genotyping of ABCB1 among opioid-dependent patients on MMT may help individualize and optimize methadone substitution treatment.

Variability of response to methadone: genome-wide DNA methylation analysis in two independent cohorts

Aim: Methadone maintenance treatment is characterized by large interindividual dose variability. The aim of this study was to evaluate whether DNA methylations are associated with daily dose of methadone. Materials & methods: Subjects stabilized at high (n = 12) or low (n = 12) methadone doses were selected from two independent cohorts (French and Swiss). DNA methylation patterns were analyzed using HumanMethylation450 BeadChips. Results: In total, 584 differentially methylated sites were identified in the French cohort corresponding to 352 genes. Of these, 26 were replicated in the Swiss cohort. The methylation status of 13 genes varied similarly in both cohorts and calcium signaling pathway was significantly enriched. Conclusion: Our results indicate that differentially methylated sites are associated with methadone daily dose and give insights into the molecular pathways underlying this interindividual dose variability.

[Abuse Liability of Quetiapine (Xeroquel®)]

OBJECTIVE

In recent years, there have been several reports in the literature concerning the misuse and abuse of quetiapine. The aim of this study was to review the data reported to the French Network of the Addictovigilance Centers as well as the published data.

METHODS

Epidemiological data from the studies of French network addictovigilance centers (spontaneous notifications, suspicious presciptions suggesting possible abuse [ ordonnances suspectes indicateur d'abus possibles, OSIAP], observatory of illegal psychotropic substances or delivered substances diverted from their medicinal use survey [observation des produits psychotropes illicites ou détournées de leur utilisation médicamenteuse, OPPIDUM], deaths related to medication and substance abuse survey [décès en relation avec l'abus de médicaments et de substances, DRAMES]) were analyzed between 2011 and 2014. All cases of abuse and dependence with quetiapine in PubMed were reviewed using the MeSH terms "quetiapine," "substances abuse," and "dependence", until October 2014.

RESULTS

The analysis of the literature has identified 21 cases of abuse related to quetiapine, mainly in men (85.7%), with a history of substance abuse (76%). The main route of administration was oral but other routes were also reported (intravenous, intranasal). The main reason for abuse was sedation and anxiolytic. Other characteristics of quetiapine abuse include amplification or even simulation of psychotic symptoms to obtain quetiapine, an increased dose and the existence of street names. The French addictovigilance network reported few cases of abuse with quetiapine.

DISCUSSION-CONCLUSION

The pharmacological mechanism of abuse of quetiapine is not fully understood. However, several arguments are in favor of the abuse liability of quetiapine. Despite the recent availability of quetiapine in France, there have been some isolated signals of abuse. Therefore, it seems important to inform prescribers on the risk of misuse of quetiapine and also of some other antipsychotics.

Transporter-Mediated Disposition of Opioids: Implications for Clinical Drug Interactions

Opioid-related deaths, abuse, and drug interactions are growing epidemic problems that have medical, social, and economic implications. Drug transporters play a major role in the disposition of many drugs, including opioids; hence they can modulate their pharmacokinetics, pharmacodynamics and their associated drug-drug interactions (DDIs). Our understanding of the interaction of transporters with many therapeutic agents is improving; however, investigating such interactions with opioids is progressing relatively slowly despite the alarming number of opioids-mediated DDIs that may be related to transporters. This review presents a comprehensive report of the current literature relating to opioids and their drug transporter interactions. Additionally, it highlights the emergence of transporters that are yet to be fully identified but may play prominent roles in the disposition of opioids, the growing interest in transporter genomics for opioids, and the potential implications of opioid-drug transporter interactions for cancer treatments. A better understanding of drug transporters interactions with opioids will provide greater insight into potential clinical DDIs and could help improve opioids safety and efficacy.

Pharmacogenomics of methadone maintenance treatment

Methadone is the major opioid substitution therapy for opioid dependence. Dosage is highly variable and is often controlled by the patient and prescriber according to local and national policy and guidelines. Nevertheless many genetic factors have been investigated including those affecting its metabolism (CYP2B6-consistent results), efflux transport (P-gp-inconsistent results), target μ-opioid receptor (μ-opioid receptor-inconsistent results) and a host of other receptors (DRD2) and signaling elements (GIRK2 and ARRB2; not replicated). None by themselves have been able to substantially explain dosage variation (the major but not sole end point). When multiple genes have been combined such as ABCB1, CYP2B6, OPRM1 and DRD2 a greater contribution to dosage variation was found but not as yet replicated. As stabilization of dosage needs to be made rapidly, it is imperative that larger internationally based studies be instigated so that genetic contribution to dosage can be properly assessed, which may or may not tailor to different ethnic groups and each country’s policy towards an outcome that benefits all.

Impact of ABCB1 and CYP2B6 genetic polymorphisms on methadone metabolism, dose and treatment response in patients with opioid addiction: a systematic review and meta-analysis

BACKGROUND

Genetic variability may influence methadone metabolism, dose requirements, and risk of relapse.

OBJECTIVES

To determine whether the CYP2B6*6 or ABCB1 (rs1045642) polymorphisms are associated with variation in methadone response (plasma concentration, dose, or response to treatment).

METHODS

Two independent reviewers searched Medline, EMBASE, CINAHL, PsycINFO, and Web of Science databases. We included studies that reported methadone plasma concentration, methadone response, or methadone dose in relation to the CYP2B6*6 or ABCB1 polymorphisms.

RESULTS

We screened 182 articles and extracted 7 articles for inclusion in the meta-analysis. Considerable agreement was observed between the two independent raters on the title (kappa, 0.82), abstract (kappa, 0.43), and full text screening (kappa, 0.43). Trough (R) methadone plasma concentration was significantly higher in CYP2B6*6 homozygous carriers when compared to non-carriers (standardized mean difference [SMD] = 0.53, 95% confidence interval [CI], 0.05-1.00, p = 0.03) with minimal heterogeneity (I(2) = 0%). Similarly, trough (S) methadone plasma concentration was higher in homozygous carriers of the *6 haplotype when compared to non-carriers, (SMD = 1.44, 95% CI 0.27-2.61, p = 0.02) however significant heterogeneity was observed (I(2) = 69%). Carriers of the CYP2B6*6 haplotype were not found to be significantly different from non-carriers with respect to dose or response to treatment. We found no significant association between the ABCB1 polymorphism and the trough (R), (S) plasma concentrations, methadone dose, or methadone response.

CONCLUSION

Although the number of studies included and sample size were modest, this is the first meta analysis to show participants homozygous for the CYP2B6*6 genotype have higher trough (R) and (S) methadone plasma concentrations, suggesting that methadone metabolism is significantly slower in *6 homozygous carriers.

Clinically significant drug interactions with atypical antipsychotics

Atypical antipsychotics [also known as second-generation antipsychotics (SGAs)] have become a mainstay therapeutic treatment intervention for patients with schizophrenia, bipolar disorders and other psychotic conditions. These agents are commonly used with other medications--most notably, antidepressants and antiepileptic drugs. Drug interactions can take place by various pharmacokinetic, pharmacodynamic and pharmaceutical mechanisms. The pharmacokinetic profile of each SGA, especially with phase I and phase II metabolism, can allow for potentially significant drug interactions. Pharmacodynamic interactions arise when agents have comparable receptor site activity, which can lead to additive or competitive effects without alterations in measured plasma drug concentrations. Additionally, the role of drug transporters in drug interactions continues to evolve and may effect both pharmacokinetic and pharmacodynamic interactions. Pharmaceutical interactions occur when physical incompatibilities take place between agents prior to drug absorption. Approximate therapeutic plasma concentration ranges have been suggested for a number of SGAs. Drug interactions that markedly increase or decrease the concentrations of these agents beyond their ranges can lead to adverse events or diminished clinical efficacy. Most clinically significant drug interactions with SGAs occur via the cytochrome P450 (CYP) system. Many but not all drug interactions with SGAs are identified during drug discovery and pre-clinical development by employing a series of standardized in vitro and in vivo studies with known CYP inducers and inhibitors. Later therapeutic drug monitoring programmes, clinical studies and case reports offer methods to identify additional clinically significant drug interactions. Some commonly co-administered drugs with a significant potential for drug-drug interactions with selected SGAs include some SSRIs. Antiepileptic mood stabilizers such as carbamazepine and valproate, as well as other antiepileptic drugs such as phenobarbital and phenytoin, may decrease plasma SGA concentrations. Some anti-infective agents such as protease inhibitors and fluoroquinolones are of concern as well. Two additional important factors that influence drug interactions with SGAs are dose and time dependence. Smoking is very common among psychiatric patients and can induce CYP1A2 enzymes, thereby lowering expected plasma levels of certain SGAs. It is recommended that ziprasidone and lurasidone are taken with food to promote drug absorption, otherwise their bioavailability can be reduced. Clinicians must be aware of the variety of factors that can increase the likelihood of clinically significant drug interactions with SGAs, and must carefully monitor patients to maximize treatment efficacy while minimizing adverse events.

Contribution of CYP2B6 alleles in explaining extreme (S)-methadone plasma levels: a CYP2B6 gene resequencing study

BACKGROUND

(S)-Methadone, metabolized mainly by CYP2B6, shows a wide interindividual variability in its pharmacokinetics and pharmacodynamics.

METHODS

Resequencing of the CYP2B6 gene was performed in 12 and 35 selected individuals with high (S)-methadone plasma exposure and low (S)-methadone plasma exposure, respectively, from a previously described cohort of 276 patients undergoing methadone maintenance treatment. Selected genetic polymorphisms were then analyzed in the complete cohort.

RESULTS

The rs35303484 (*11; c136A>G; M46V) polymorphism was overrepresented in the high (S)-methadone level group, whereas the rs3745274 (*9; c516G>T; Q172H), rs2279344 (c822+183G>A), and rs8192719 (c1294+53C>T) polymorphisms were underrepresented in the low (S)-methadone level group, suggesting an association with decreased CYP2B6 activity. Conversely, the rs3211371 (*5; c1459C>T; R487C) polymorphism was overrepresented in the low-level group, indicating an increased CYP2B6 activity. A higher allele frequency was found in the high-level group compared with the low-level group for rs3745274 (*9; c516G>T; Q172H), rs2279343 (*4; c785A>G; K262R) (together representing CYP2B6*6), rs8192719 (c1294+53C>T), and rs2279344 (c822+183G>A), suggesting their involvement in decreased CYP2B6 activity. These results should be replicated in larger independent cohorts.

CONCLUSION

Known genetic polymorphisms in CYP2B6 contribute toward explaining extreme (S)-methadone plasma levels observed in a cohort of patients following methadone maintenance treatment.

Combined analysis of circulating β-endorphin with gene polymorphisms in OPRM1, CACNAD2 and ABCB1 reveals correlation with pain, opioid sensitivity and opioid-related side effects

Background

Opioids are associated with wide inter-individual variability in the analgesic response and a narrow therapeutic index. This may be partly explained by the presence of single nucleotide polymorphisms (SNPs) in genes encoding molecular entities involved in opioid metabolism and receptor activation. This paper describes the investigation of SNPs in three genes that have a functional impact on the opioid response: OPRM1, which codes for the μ-opioid receptor; ABCB1 for the ATP-binding cassette B1 transporter enzyme; and the calcium channel complex subunit CACNA2D2. The genotyping was combined with an analysis of plasma levels of the opioid peptide β-endorphin in 80 well-defined patients with chronic low back pain scheduled for spinal fusion surgery, and with differential sensitivity to the opioid analgesic remifentanil. This patient group was compared with 56 healthy controls.

Results

The plasma β-endorphin levels were significantly higher in controls than in pain patients.

A higher incidence of opioid-related side effects and sex differences was found in patients with the minor allele of the ABCB1 gene. Further, a correlation between increased opioid sensitivity and the major CACNA2D2 allele was confirmed. A tendency of a relationship between opioid sensitivity and the minor allele of OPRM1 was also found.

Conclusions

Although the sample cohort in this study was limited to 80 patients it appears that it was possible to observe significant correlations between polymorphism in relevant genes and various items related to pain sensitivity and opioid response. Of particular interest is the new finding of a correlation between increased opioid sensitivity and the major CACNA2D2 allele. These observations may open for improved strategies in the clinical treatment of chronic pain with opioids.

ABCB1 haplotype and OPRM1 118A > G genotype interaction in methadone maintenance treatment pharmacogenetics

BACKGROUND

Genetic variability in ABCB1, encoding the P-glycoprotein efflux transporter, has been linked to altered methadone maintenance treatment dose requirements. However, subsequent studies have indicated that additional environmental or genetic factors may confound ABCB1 pharmacogenetics in different methadone maintenance treatment settings. There is evidence that genetic variability in OPRM1, encoding the mu opioid receptor, and ABCB1 may interact to affect morphine response in opposite ways. This study aimed to examine whether a similar gene-gene interaction occurs for methadone in methadone maintenance treatment.

METHODS

Opioid-dependent subjects (n = 119) maintained on methadone (15-300 mg/day) were genotyped for five single nucleotide polymorphisms of ABCB1 (61A > G; 1199G > A; 1236C > T; 2677G > T; 3435C > T), as well as for the OPRM1 118A > G single nucleotide polymorphism. Subjects' methadone doses and trough plasma (R)-methadone concentrations (C(trough)) were compared between ABCB1 haplotypes (with and without controlling for OPRM1 genotype), and between OPRM1 genotypes (with and without controlling for ABCB1 haplotype).

RESULTS

Among wild-type OPRM1 subjects, an ABCB1 variant haplotype group (subjects with a wild-type and 61A:1199G:1236C:2677T:3435T haplotype combination, or homozygous for the 61A:1199G:1236C:2677T:3435T haplotype) had significantly lower doses (median ± standard deviation 35 ± 5 versus 180 ± 65 mg/day, P < 0.01) and C(trough) (78 ± 22 versus 177 ± 97 ng/mL, P < 0.05) than ABCB1 wild-type subjects. Among subjects with the most common ABCB1 haplotype combination (wild-type with 61A:1199G:1236T:2677T:3435T), the OPRM1 118 A/G genotype was associated with a significantly higher C(trough) than 118 A/A (250 ± 126 versus 108 ± 36 ng/mL, P = 0.016). No ABCB1 haplotype group or OPRM1 genotype was associated with dose or C(trough) without taking into account confounding genetic variability at the other locus. Therefore, two interacting pharmacogenetic determinants of methadone maintenance treatment response were identified, ie, ABCB1, where variants are associated with lower methadone requirements, and OPRM1, where the variant is associated with higher methadone requirements.

CONCLUSION

These opposing pharmacogenetic effects therefore need to be considered in combination when assessing methadone maintenance treatment pharmacogenetics.

Methadone: a review of drug-drug and pathophysiological interactions

Numerous established and potential drug interactions with methadone are clinically important in people treated with methadone either for addiction or for chronic pain. Methadone users often have comorbidities and are prescribed drugs that may interact with methadone. Methadone is extensively metabolized by cytochrome P450 (CYP) 3A4 and to a lesser extent by CYP 1A2, 2D6, 2D8, 2C9/2C8, 2C19, and 2B6. Eighty-six percent of methadone is protein bound, predominately to α1-acid glycoprotein (AGP). Polymorphisms in or interactions with CYPs that metabolize methadone, changes in protein binding, and other pathophysiological conditions affect the pharmacokinetic properties of methadone. It is critical for health care providers who treat patients on methadone to have adequate information on the interactions of methadone with other drugs of abuse and other medications. We set out to describe drug-drug interactions as well as physiological and pathophysiological factors that may impact the pharmacokinetics of methadone. Using MEDLINE, we conducted a systematic search for papers and related abstracts published between 1966 and June 2010. Keywords that included methadone, drug-drug interactions, CYP P450 and AGP identified a total of 7709 papers. Other databases, including the Cochrane Database of Systematic Reviews and Scopus, were also searched; an additional 929 papers were found. Final selection of 286 publications was based on the relevance of each paper to the topic. Over 50 such interactions were found. Interactions of methadone with other drugs can lead to increased or decreased methadone drug levels in patients and result in potential overdose or withdrawal, respectively. The former can contribute to methadone's fatality. Prescribers of methadone and pharmacists should enquire about any new medications (including natural products and over-the-counter medications) periodically, and especially when an otherwise stable patient suddenly experiences drug craving, withdrawal or intoxication.

Relationship between P-glycoprotein and second-generation antipsychotics

The membrane transport protein P-glycoprotein (P-gp) is an interesting candidate for individual differences in response to antipsychotics. To present an overview of the current knowledge of P-gp and its interaction with second-generation antipsychotics (SGAs), an internet search for all relevant English original research articles concerning P-gp and SGAs was conducted. Several SGAs are substrates for P-gp in therapeutic concentrations. These include amisulpride, aripiprazole, olanzapine, perospirone, risperidone and paliperidone. Clozapine and quetiapine are not likely to be substrates of P-gp. However, most antipsychotics act as inhibitors of P-gp, and can therefore influence plasma and brain concentrations of other substrates. No information was available for sertindole, ziprasidone or zotepine. Research in animal models demonstrated significant differences in antipsychotic brain concentration and behavior owing to both P-gp knockout and inhibition. Results in patients are less clear, as several external factors have to be accounted for. Patients with polymorphisms which decrease P-gp functionality tend to perform better in clinical settings. There is some variability in the findings concerning adverse effects, and no definitive conclusions can be drawn at this point.

Pharmacokinetic drug interactions and adverse consequences between psychotropic medications and pharmacotherapy for the treatment of opioid dependence

BACKGROUND

Psychiatric comorbidities among opioid-dependent patients are common. Many medications used to treat both conditions are metabolized through complimentary cytochrome P450 isoenzymes. When medication-assisted treatment for opioid dependence is concurrently used with psychotropic medications, problematic pharmacokinetic drug interactions may occur.

METHODS

We reviewed relevant English language articles identified through the MedLine, Scopus, and Embase databases from 1950 to December 2009 using the specific generic names of medications and keywords such as pharmacokinetics and drug interactions with buprenorphine, methadone, and naltrexone. Selected references from these articles were reviewed. Additionally, a review was conducted of abstracts and conference proceedings from national and international meetings from 1990 to 2009. A total of 60 studies were identified and reviewed.

RESULTS

Clinical case series and carefully controlled pharmacokinetic interaction studies have been conducted between methadone, buprenorphine, or naltrexone and some psychoactive medications. Important pharmacokinetic drug interactions have been demonstrated within each class of medications affecting either methadone and buprenorphine or psychoactive drugs. Few studies, however, have been conducted with naltrexone.

CONCLUSIONS

Several interactions between methadone, buprenorphine, or naltrexone and psychoactive medications are described and may have important clinical consequences. To optimize care, clinicians must be alerted to these interactions.

Indicators of buprenorphine and methadone use and abuse: what do we know?

Abuse of prescription opioids is a growing problem. The number of methadone pain pills distributed now exceeds liquid methadone used in opioid treatment, and the increases in buprenorphine indicators provide evidence of the need to monitor and intervene to decrease the abuse of this drug. The need for additional and improved data to track trends is discussed, along with findings as to the characteristics of the users and combinations of drugs. Data on toxicities related to methadone or buprenorphine, particularly in combination with other prescribed drugs, are presented and clinical implications and considerations are offered. These findings underscore the need for physicians to be aware of potential toxicities and to educate their patients regarding these issues.

Methadone for Cancer Pain

Pain is one of the most common and incapacitating symptoms experienced by patients with advanced cancer. Methadone is a potent opioid with strong affinity for the µ opioid receptor. In addition to being a potent µ opioid receptor ligand, methadone blocks the N-methyl-D-aspartic acid receptor and modulates neurotransmitters involved in descending pain modulation. These 3 properties enhance analgesic activity. Methadone's lack of active metabolites makes it an attractive option when opioid responsiveness declines and renal insufficiency complicates opioid therapy. A lipophilic opioid, methadone can be given by multiple routes. Clinical trial data show equivalence with morphine as an analgesic in moderate to severe cancer pain. Further investigations are needed to define the role of methadone in the management of breakthrough pain and neuropathic pain and to determine whether it is truly superior to morphine, the gold standard of cancer analgesia.

Drug interactions of clinical importance among the opioids, methadone and buprenorphine, and other frequently prescribed medications: a review

Drug interactions are a leading cause of morbidity and mortality. Methadone and buprenorphine are frequently prescribed for the treatment of opioid addiction. Patients needing treatment with these medications often have co-occurring medical and mental illnesses that require medication treatment. The abuse of illicit substances is also common in opioid-addicted individuals. These clinical realities place patients being treated with methadone and buprenorphine at risk for potentially toxic drug interactions. A substantial literature has accumulated on drug interactions between either methadone or buprenorphine with other medications when ingested concomitantly by humans. This review summarizes current literature in this area.

Pharmacogenetics of analgesics: toward the individualization of prescription

The use of analgesics is based on the empiric administration of a given drug with clinical monitoring for efficacy and toxicity. However, individual responses to drugs are influenced by a combination of pharmacokinetic and pharmacodynamic factors that can sometimes be regulated by genetic factors. Whereas polymorphic drug-metabolizing enzymes and drug transporters may affect the pharmacokinetics of drugs, polymorphic drug targets and disease-related pathways may influence the pharmacodynamic action of drugs. After a usual dose, variations in drug toxicity and inefficacy can be observed depending on the polymorphism, the analgesic considered and the presence or absence of active metabolites. For opioids, the most studied being morphine, mutations in the ABCB1 gene, coding for P-glycoprotein (P-gp), and in the µ-opioid receptor reduce morphine potency. Cytochrome P450 (CYP) 2D6 mutations influence the analgesic effect of codeine and tramadol, and polymorphism of CYP2C9 is potentially linked to an increase in nonsteroidal anti-inflammatory drug-induced adverse events. Furthermore, drug interactions can mimic genetic deficiency and contribute to the variability in response to analgesics. This review summarizes the available data on the pharmacokinetic and pharmacodynamic consequences of known polymorphisms of drug-metabolizing enzymes, drug transporters, drug targets and other nonopioid biological systems on central and peripheral analgesics.