Alpha 1-acid glycoprotein (AAG) and serum protein binding of methadone in heroin addicts with abstinence syndrome

Monitoring Prenatal Exposure to Buprenorphine and Methadone

PURPOSE

Buprenorphine and methadone are international gold standards for managing opioid use disorders. Although they are efficacious in treating opioid dependence, buprenorphine and methadone present risks, especially during pregnancy, causing neonatal abstinence syndrome and adverse obstetrical outcomes. Buprenorphine and methadone are also abused during pregnancy, and identifying their use is important to limit unprescribed prenatal exposure. Previous studies have suggested that concentrations of buprenorphine, but not methadone markers in unconventional matrices may predict child outcomes, although currently only limited data exist. We reviewed the literature on concentrations of buprenorphine, methadone, and their metabolites in unconventional matrices to improve data interpretation.

METHODS

A literature search was conducted using scientific databases (PubMed, Scopus, Web of Science, and reports from international institutions) to review published articles on buprenorphine and methadone monitoring during pregnancy.

RESULTS

Buprenorphine and methadone and their metabolites were quantified in the meconium, umbilical cord, placenta, and maternal and neonatal hair. Methadone concentrations in the meconium and hair were typically higher than those in other matrices, although the concentrations in the placenta and umbilical cord were more suitable for predicting neonatal outcomes. Buprenorphine concentrations were lower and required sensitive instrumentation, as measuring buprenorphine glucuronidated metabolites is critical to predict neonatal outcomes.

CONCLUSIONS

Unconventional matrices are good alternatives to conventional ones for monitoring drug exposure during pregnancy. However, data are currently scarce on buprenorphine and methadone during pregnancy to accurately interpret their concentrations. Clinical studies should be conducted with larger cohorts, considering confounding factors such as illicit drug co-exposure.

Methadone for Cancer Pain in Pediatric End-of-Life Care

BACKGROUND

The goal of adequate pain control becomes increasingly salient for children with cancer and their families as the patients approach the end of life. Methadone is one option that is particularly desirable in end-of-life care given its long duration of action and NMDA antagonism that may help in controlling pain refractory to conventional opioids. The purpose of this study was to describe a single institution's experience with methadone for the treatment of cancer pain in pediatric end-of-life care.

METHODS

This retrospective, observational, single-center study included all patients during a 9-year period who died in the inpatient setting and were receiving methadone in their last 30 days of life.

RESULTS

Twenty patients were identified, 18 (90%) of whom received methadone for nociceptive pain. The median duration of methadone use was 32 days (range 2-323 days). Methadone doses ranged from 0.09 to 7.76 mg/kg per day. There were no instances of discontinuing methadone due to an increased QTc interval. No episodes of torsades de pointes were observed.

CONCLUSION

In patients with pediatric cancer who are nearing the end of life, methadone is a valuable adjunctive therapy to treat nociceptive and neuropathic pain and to prevent opioid-induced hyperalgesia and opioid tolerance. An individualized approach to dosage and route should be considered based on specific clinical circumstances.

Serum proteomic profiling of patients with amphetamine use disorder

BACKGROUND

Amphetamine use disorder has been recently classified as an epidemic condition. Amphetamine use/abuse has been associated with several neurological and inflammatory effects. However, the exact mechanism involved in these effects warrants further investigation. The aim of this study was to determine any alterations in the serum proteome of individuals classified as patients with amphetamine use disorder compared to that of control subjects.

METHODS

An untargeted proteomic approach employing two-dimensional difference in gel electrophoresis coupled with mass spectrometry was used to identify the patterns of differentially expressed proteins. Serum samples were collected from 20 individuals (males) including 10 subjects with amphetamine use disorder and 10 healthy controls for the present study.

RESULTS

The analysis revealed 78 proteins with a significant difference in protein abundance between the amphetamine-addicted subjects and controls. Among them, 71 proteins were upregulated while 7 proteins remained downregulated in the amphetamine-addicted group. These proteins were further analyzed by ingenuity pathway analysis (IPA) to investigate their correlation with other biomarkers. IPA revealed the correlation of altered proteins with mitogen-activated protein kinase (MAP2K1/K2), p38MAPK, protein kinase-B (PKB; Akt), extracellular signal-regulated kinase (ERK1/2), and nuclear factor-κB signaling pathways. Importantly, these pathways are highly involved in neurological diseases, inflammatory responses, and cellular compromise.

CONCLUSIONS

Our data suggest that the changes in the levels of serum proteins between amphetamine and control groups might affect cellular compromise, inflammatory response, and neurological diseases.

What the lab can and cannot do: clinical interpretation of drug testing results

Urine drug testing is one of the objective tools available to assess adherence. To monitor adherence, quantitative urinary results can assist in differentiating "new" drug use from "previous" (historical) drug use. "Spikes" in urinary concentration can assist in identifying patterns of drug use. Coupled chromatographic-mass spectrometric methods are capable of identifying very small amounts of analyte and can make clinical interpretation rather challenging, specifically for drugs that have a longer half-life. Polypharmacy is common in treatment and rehabilitation programs because of co-morbidities. Medications prescribed for comorbidities can cause drug-drug interaction and phenoconversion of genotypic extensive metabolizers into phenotypic poor metabolizers of the treatment drug. This can have significant impact on both pharmacokinetic (PK) and pharmacodynamic properties of the treatment drug. Therapeutic drug monitoring (TDM) coupled with PKs can assist in interpreting the effects of phenoconversion. TDM-PKs reflects the cumulative effects of pathophysiological changes in the patient as well as drug-drug interactions and should be considered for treatment medications/drugs used to manage pain and treat substance abuse. Since only a few enzyme immunoassays for TDM are available, this is a unique opportunity for clinical laboratory scientists to develop TDM-PK protocols that can have a significant impact on patient care and personalized medicine. Interpretation of drug screening results should be done with caution while considering pharmacological properties and the presence or absence of the parent drug and its metabolites. The objective of this manuscript is to review and address the variables that influence interpretation of different drugs analyzed from a rehabilitation and treatment programs perspective.

Integrating in vitro data and physiologically based kinetic modeling-facilitated reverse dosimetry to predict human cardiotoxicity of methadone

Development of novel testing strategies to detect adverse human health effects is of interest to replace in vivo-based drug and chemical safety testing. The aim of the present study was to investigate whether physiologically based kinetic (PBK) modeling-facilitated conversion of in vitro toxicity data is an adequate approach to predict in vivo cardiotoxicity in humans. To enable evaluation of predictions made, methadone was selected as the model compound, being a compound for which data on both kinetics and cardiotoxicity in humans are available. A PBK model for methadone in humans was developed and evaluated against available kinetic data presenting an adequate match. Use of the developed PBK model to convert concentration–response curves for the effect of methadone on human-induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CM) in the so-called multi electrode array (MEA) assay resulted in predictions for in vivo dose–response curves for methadone-induced cardiotoxicity that matched the available in vivo data. The results also revealed differences in protein plasma binding of methadone to be a potential factor underlying variation between individuals with respect to sensitivity towards the cardiotoxic effects of methadone. The present study provides a proof-of-principle of using PBK modeling-based reverse dosimetry of in vitro data for the prediction of cardiotoxicity in humans, providing a novel testing strategy in cardiac safety studies.

Dose, Plasma Level, and Treatment Outcome Among Methadone Patients in Shanghai, China

The purpose of this study was to investigate the blood levels of methadone in participants receiving methadone for the treatment of opioid dependence. After stabilization on methadone for four weeks, blood samples from 95 participants were collected between treatment weeks 4 and 12, before and after receiving doses of methadone, and its blood levels were measured. A multiple linear regression model was used to examine the association between methadone blood levels and the outcomes of methadone maintenance treatment (MMT). Outcome differences between participants who had high (≥2) or low (<2) peak-to-trough ratios were also compared using an independent sample t-test. The blood level of methadone was not correlated with the clinical outcome of MMT with the moderate range of doses given. However, the retention of patients who had a free peak-to-trough ratio >2 was significantly poorer than those whose ratio was <2. Thus, monitoring plasma methadone levels is unlikely to be effective for guiding dosing decisions in situations where compliance with MMT is already very high or when the methadone dose is no longer the dominant factor in determining the clinical outcome. However, monitoring plasma methadone levels is still helpful for guiding the dosage for patients with a rapid metabolism.

In silico ordinary differential equation/partial differential equation hemodialysis model estimates methadone removal during dialysis

Background

There is a need to have a model to study methadone’s losses during hemodialysis to provide informed methadone dose recommendations for the practitioner.

Aim

To build a one-dimensional (1-D), hollow-fiber geometry, ordinary differential equation (ODE) and partial differential equation (PDE) countercurrent hemodialyzer model (ODE/PDE model).

Methodology

We conducted a cross-sectional study in silico that evaluated eleven hemodialysis patients. Patients received a ceiling dose of methadone hydrochloride 30 mg/day. Outcome measures included: the total amount of methadone removed during dialysis; methadone’s overall intradialytic mass transfer rate coefficient, k_m; and, methadone’s removal rate, j_ME. Each metric was measured at dialysate flow rates of 250 mL/min and 800 mL/min.

Results

The ODE/PDE model revealed a significant increase in the change of methadone’s mass transfer with increased dialysate flow rate, %Δk_m=18.56, P=0.02, N=11. The total amount of methadone mass transferred across the dialyzer membrane with high dialysate flow rate significantly increased (0.042±0.016 versus 0.052±0.019 mg/kg, P=0.02, N=11). This was accompanied by a small significant increase in methadone’s mass transfer rate (0.113±0.002 versus 0.014±0.002 mg/kg/h, P=0.02, N=11). The ODE/PDE model accurately predicted methadone’s removal during dialysis. The absolute value of the prediction errors for methadone’s extraction and throughput were less than 2%.

Conclusion

ODE/PDE modeling of methadone’s hemodialysis is a new approach to study methadone’s removal, in particular, and opioid removal, in general, in patients with end-stage renal disease on hemodialysis. ODE/PDE modeling accurately quantified the fundamental phenomena of methadone’s mass transfer during hemodialysis. This methodology may lead to development of optimally designed intradialytic opioid treatment protocols, and allow dynamic monitoring of outflow plasma opioid concentrations for model predictive control during dialysis in humans.

The pharmacokinetics of methadone in adolescents undergoing posterior spinal fusion

BACKGROUND

The optimal methadone dosing regimen for children undergoing spinal surgery is uncertain because of sparse pediatric pharmacokinetic data and a paucity of analgesic effect data. The minimum effective analgesic concentration of methadone in opioid naïve adults is 58 mcg · L(-1).

METHODS

Adolescents aged 12-19 years undergoing idiopathic scoliosis correction were administered 0.25 mg · kg(-1) racemic methadone IV prior to surgical incision. Arterial blood samples for methadone assay were obtained at 0 min, 5 min, 10 min, 15 min, 20 min, 40 min, 1 h, 2 h, 4 h, 5 h, 6 h, 8 h, 10 h, 12 h, 24 h, and 48 h. Compartment analysis was undertaken using nonlinear mixed effects models. Parameter estimates were standardized to a 70-kg person using allometric models.

RESULTS

A three-compartment linear disposition model best described observed time-concentration profiles. Population parameter estimates (between-subjects variability) were central volume (V1) 19.1 (126%) L 70 kg(-1), peripheral volumes of distribution V2 65.5 (60%) L 70 kg(-1), V3 485 (23%) L 70 kg(-1), clearance (CL) 9.3 (11%) L · h(-1) · 70 kg(-1), and inter-compartment clearances Q2 282 (95%) L · h(-1) 70 kg(-1), Q3 139 (42%) L · h(-1) 70 kg(-1). The terminal elimination half-life was 44.4 h. The mean observed methadone concentration was <58 mcg · L(-1) by the first hour after administration.

CONCLUSIONS

Current pharmacokinetic parameter estimates in adolescents are similar to those reported in adults. Methadone undergoes rapid redistribution after bolus administration. This may result in plasma concentrations that provide inadequate analgesia postoperatively. We would suggest following the bolus (0.25 mg.kg(-1)) with an infusion (0.1-0.15 mg · kg(-1) · h(-1) for 4 h) during spinal surgery to ensure adequate plasma concentrations for 24 h.

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.

Methadone adverse reaction presenting with large increase in plasma methadone binding: a case series

Introduction

The use of methadone as an analgesic is on the increase, but it is widely recognized that the goal of predictable and reproducible dosing is confounded by considerable variability in methadone pharmacokinetics, and unpredictable side effects that include sedation, respiratory depression and cardiac arrhythmias. The mechanisms underlying these unpredictable effects are frequently unclear. Here, to the best of our knowledge we present the first report of an association between accidental methadone overexposure and increased plasma protein binding, a new potential mechanism for drug interactions with methadone.

Case presentation

We describe here the cases of two patients who experienced markedly different responses to the same dose of methadone during co-administration of letrozole. Both patients were post-menopausal Caucasian women who were among healthy volunteers participating in a clinical trial. Under the trial protocol both patients received 6 mg of intravenous methadone before and then after taking letrozole for seven days. One woman (aged 59) experienced symptoms consistent with opiate overexposure after the second dose of methadone that were reversed by naloxone, while the other (aged 49) did not. To understand the etiology of this event, we measured methadone pharmacokinetics in both patients. In our affected patient only, a fourfold to eightfold increase in methadone plasma concentrations after letrozole treatment was observed. Detailed pharmacokinetic analysis indicated no change in metabolism or renal elimination in our patient, but the percentage of unbound methadone in the plasma decreased 3.7-fold. As a result, the volume of distribution of methadone decreased approximately fourfold. The increased plasma binding in our affected patient was consistent with observed increases in plasma protein concentrations.

Conclusions

The marked increase in the total plasma methadone concentration observed in our patient, and the enhanced pharmacodynamic effect, appear primarily due to a reduced volume of distribution. The extent of plasma methadone binding may help to explain the unpredictability of its pharmacokinetics. Changes in volume of distribution due to plasma binding may represent important causes of clinically meaningful drug interactions.

Actual and potential drug interactions associated with methadone

OBJECTIVE

To identify and characterize methadone-related drug interactions, as well as factors accounting for the variability in manifesting these interactions clinically.

DESIGN

Systematic review of the primary literature.

METHODS

Over 200 articles, reports of clinical trials, and case reports were reviewed. Studies and case reports were included if they revealed either quantitative or qualitative methods to identify, evaluate severity of, or compare methadone-related drug interactions.

RESULTS OF DATA SYNTHESIS

The evidence base associated with methadone drug interactions is underdeveloped in general, as the majority of references found were case reports or case series. Most of the studies and reports focused on inpatients receiving methadone maintenance treatment (MMT) that were between 20 and 60 years of age, taking 200 mg/day of methadone or less. Evidence supporting the involvement of lesser known cytochrome P450 enzymes such as 2B6 is emerging, which may partially explain the inconsistencies previously found in studies looking specifically at 3A4 in vitro and in vivo. Genetic variability may play a role in the pharmacokinetics and pharmacodynamics of many medications, including methadone.

CONCLUSIONS

Drug interactions associated with methadone and their clinical significance are still poorly understood in general. Many tertiary drug information references and review articles report interactions associated with methadone in a general sense, much of which is theoretical and not verified by case reports, much less well-designed clinical trials. The majority of drug interaction reports that do exist were performed in the MMT population, which may differ significantly from chronic pain or cancer pain populations.

Free and bound enantiomers of methadone and its metabolite, EDDP in methadone maintenance treatment: relationship to dosage?

OBJECTIVES

To determine the effects of metabolism and protein binding on the relationship between administered dose, blood levels of R methadone and biological response by measuring the free and protein-bound forms of the R and S enantiomers of methadone and EDDP, its metabolite.

DESIGN AND METHODS

To measure free and total drug, trough levels were collected from 45 methadone clients. To measure free methadone, samples were filtered using ultrafiltration with a MW weight cut-off of 10,000 and extracted using liquid-liquid extraction. The solvent was evaporated and samples reconstituted in mobile phase for analysis by LC/MS/MS. Total analyte was determined by extracting unfiltered samples. Enantiomeric separation of methadone and EDDP was by chiral chromatography.

RESULTS

The presence of unmetabolized methadone suggested that none of the patients were very fast metabolizers. R and S forms were metabolized at the same rate at all administered doses. Free R methadone levels correlated both with methadone dose and with the total amount of R methadone. The free fraction of R methadone (%free R) was higher at lower doses than at high doses, varied from 5 to 25% and was inversely proportional to the total dose of administered drug in a relationship that was logarithmic and non-linear.

CONCLUSIONS

By measuring the free, biologically active form of the drug, we were unable to account for the large variations in dose required between different patients to prevent the onset of withdrawal symptoms. The reason for the large range in dosage may be multifactorial.

Determination of total and free concentrations of the enantiomers of methadone and its metabolite (2-ethylidene-1,5-dimethyl-3,3-diphenyl-pyrrolidine) in human plasma by enantioselective liquid chromatography with mass spectrometric detection

A sensitive enantioselective liquid chromatographic assay with mass spectrometric detection (LC-MS) has been validated for the determination of total and free plasma concentrations of (R)- and (S)-methadone (Met) and (R)- and (S)-2-ethylidene-1,5-dimethyl-3,3-diphenylpyrrolidine (EDDP, the primary metabolite of Met), using their respective deuterium-labeled compounds as internal standards [(R,S)-d3-Met and (R,S)-d3-EDDP]. For total drug determinations, 1 ml human plasma was extracted, using a cation-exchange solid-phase extraction cartridge; the eluate was evaporated, reconstituted in the mobile phase, and injected into the LC-MS system. The free fractions of Met and EDDP were determined, using 500 microl of plasma, which were placed in an ultrafiltration device and centrifuged at 2000 x g until 250 microl of filtrate was collected. The filtrate was extracted as described above and analyzed. Enantioselective separations were achieved using an alpha1-acid glycoprotein chiral stationary phase, a mobile phase composed of acetonitrile-ammonium acetate buffer [10 mM, pH 7.0] (18:82, v/v), a flow rate of 0.9 ml/min at 25 degrees C. Under these conditions, enantioselective separations were observed for Met (alpha = 1.30) and EDDP (alpha = 1.17) within 15 min. Met, EDDP, [2H3]-Met and [2H3]-EDDP were detected using selected ion monitoring at m/z 310.30, 278.20, 313.30, and 281.20, respectively. Linear relationships between peak height ratio and drug-enantiomer concentrations were obtained for Met in the range 1.0-300.0 ng/ml, and for EDDP from 0.1 to 25.0 ng/ml with correlation coefficients greater than 0.999, where the lower limit of quantification (LLOQ) was 1 ng/ml for Met and 0.1 ng/ml for EDDP. The relative standard deviation (R.S.D.) expressed as R.S.D. for the intra- and inter-day precision of the method were < 5.3% and the R.S.D. for accuracy was < 5.0%. The method was used to analyze plasma samples obtained from patients enrolled in a Met-maintenance program.

Alpha‐1‐acid glycoprotein directly affects the pharmacokinetics and the analgesic effect of methadone in the rat beyond protein binding

Methadone is a basic drug highly bound to alpha1-acid glycoprotein (AGP), a plasma protein that increases in several pathological situations. Our aims were to evaluate the processes (pharmacokinetics-PK and/or pharmacodynamics-PD) associated with changes of methadone analgesia under conditions of increased AGP, and whether these changes are dependent on binding, secondary to a pathology, or directly attributable to AGP. AGP levels, in rats, were increased by two different methods: (a) experimental inflammation with turpentine oil (TP), and (b) by directly infusing the protein (exo-AGP). Both had a corresponding control group. Tail-flick analgesia and PK were evaluated after methadone dose (0.35 mg/kg i.v.). Bicompartmental PK parameters as well as interanimal and assay variabilities were estimated using NONMEM. The relationship between Cp and analgesic effect (PD) was analyzed with WINNONLIN. AGP levels in both pretreated groups (TP and exo-AGP) were significantly increased, and the unbound fraction (fu) was decreased, compared to controls. All PK parameters were lower in the pretreated groups, but in exo-AGP the difference was maintained even when corrected by fu. Paradoxically, also in exo-AGP the analgesic effect was practically nonexistent, although the unbound Cp remained high, possibly associated to a change in the PD. AGP appears responsible for alterations in both PK and PD, beyond protein binding and inflammatory processes.

Interindividual variability of the clinical pharmacokinetics of methadone: implications for the treatment of opioid dependence

Methadone is widely used for the treatment of opioid dependence. Although in most countries the drug is administered as a racemic mixture of (R)- and (S)- methadone, (R)-methadone accounts for most, if not all, of the opioid effects. Methadone can be detected in the blood 15-45 minutes after oral administration, with peak plasma concentration at 2.5-4 hours. Methadone has a mean bioavailability of around 75% (range 36-100%). Methadone is highly bound to plasma proteins, in particular to alpha(1)-acid glycoprotein. Its mean free fraction is around 13%, with a 4-fold interindividual variation. Its volume of distribution is about 4 L/kg (range 2-13 L/kg). The elimination of methadone is mediated by biotransformation, followed by renal and faecal excretion. Total body clearance is about 0.095 L/min, with wide interindividual variation (range 0.02-2 L/min). Plasma concentrations of methadone decrease in a biexponential manner, with a mean value of around 22 hours (range 5-130 hours) for elimination half-life. For the active (R)-enantiomer, mean values of around 40 hours have been determined. Cytochrome P450 (CYP) 3A4 and to a lesser extent 2D6 are probably the main isoforms involved in methadone metabolism. Rifampicin (rifampin), phenobarbital, phenytoin, carbamazepine, nevirapine, and efavirenz decrease methadone blood concentrations, probably by induction of CYP3A4 activity, which can result in severe withdrawal symptoms. Inhibitors of CYP3A4, such as fluconazole, and of CYP2D6, such as paroxetine, increase methadone blood concentrations. There is an up to 17-fold interindividual variation of methadone blood concentration for a given dosage, and interindividual variability of CYP enzymes accounts for a large part of this variation. Since methadone probably also displays large interindividual variability in its pharmacodynamics, methadone treatment must be individually adapted to each patient. Because of the high morbidity and mortality associated with opioid dependence, it is of major importance that methadone is used at an effective dosage in maintenance treatment: at least 60 mg/day, but typically 80-100 mg/day. Recent studies also show that a subset of patients might benefit from methadone dosages larger than 100 mg/day, many of them because of high clearance. In clinical management, medical evaluation of objective signs and subjective symptoms is sufficient for dosage titration in most patients. However, therapeutic drug monitoring can be useful in particular situations. In the case of non-response trough plasma concentrations of 400 microg/L for (R,S)-methadone or 250 microg/L for (R)-methadone might be used as target values.

One step purification of alpha(1)-acid glycoprotein from human plasma. Fractionation of its polymorphic allele products

Alpha(1)-acid glycoprotein is a plasma protein that exhibits both microheterogeneity and polymorphism. Its purification from human plasma is usually performed using a sequence of different fractionation steps. Here we report a one-step isolation technique of this protein based upon pseudo-ligand affinity chromatography on immobilized Cibacron Blue F3GA at acidic pH. In addition, the use of two narrow pH elution buffers allows us to separate the two genetic products of this protein, which differ from each other by 21 amino acid substitutions. This technique will facilitate the study of the structural, biological and pharmacokinetic properties of each individual allele product.

Therapeutic drug monitoring in methadone maintenance: choosing a matrix

Methadone maintenance is the premier pharmacological treatment for opioid addiction, but it is rarely informed by evidence-based practice guidelines for dosage monitoring and adjustment. Such guidelines are crucial because the pharmacokinetics of methadone vary greatly among patients, and this variation may account for differences in treatment outcome. We review the pharmacokinetics of methadone and factors that may alter it (including drug interactions, disease states, and idiosyncratic differences among patients). Also reviewed are prospects for therapeutic drug monitoring (TDM) of methadone in plasma, urine, sweat, and saliva. Due to its ease of collection and its presumed representation of the bioavailable free-fraction of methadone, saliva may be a promising matrix. However, saliva methadone concentrations are influenced by salivary pH, and future studies are needed to determine how to control for that. Administrative, medical, and social implications of methadone TDM are briefly discussed.