Effect of venlafaxine versus fluoxetine on metabolism of dextromethorphan, a CYP2D6 probe

Critical Assessment of Phenotyping Cocktails for Clinical Use in an African Context

Interethnic and interindividual variability in in vivo cytochrome P450 (CYP450)-dependent metabolism and altered drug absorption via expressed transport channels such as P-glycoprotein (P-gp) contribute to the adverse drug reactions, drug-drug interaction and therapeutic failure seen in clinical practice. A cost-effective phenotyping approach could be advantageous in providing real-time information on in vivo phenotypes to assist clinicians with individualized drug therapy, especially in resource-constrained countries such as South Africa. A number of phenotyping cocktails have been developed and the aim of this study was to critically assess the feasibility of their use in a South African context. A literature search on library databases (including AccessMedicine, BMJ, ClinicalKey, MEDLINE (Ovid), PubMed, Scopus and TOXLINE) was limited to in vivo cocktails used in the human population to phenotype phase I metabolism and/or P-gp transport. The study found that the implementation of phenotyping in clinical practice is currently limited by multiple administration routes, the varying availability of probe drugs, therapeutic doses eliciting side effects, the interaction between probe drugs and extensive sampling procedures. Analytical challenges include complicated sample workup or extraction assays and impractical analytical procedures with low detection limits, analyte sensitivity and specificity. It was concluded that a single time point, non-invasive capillary sampling, combined with a low-dose probe drug cocktail, to simultaneously quantify in vivo drug and metabolite concentrations, would enhance the feasibility and cost-effectiveness of routine phenotyping in clinical practice; however, future research is needed to establish whether the quantitative bioanalysis of drugs in a capillary whole-blood matrix correlates with that of the standard plasma/serum matrixes used as a reference in the current clinical environment.

Pharmacogenomics in psychiatry - the challenge of cytochrome P450 enzyme phenoconversion and solutions to assist precision dosing

Pharmacogenomic (PGx) testing of cytochrome P450 (CYP) enzymes may improve the efficacy and/or safety of some medications. This is facilitated by increased availability and affordability of genotyping, the development of clinical practice PGx guidelines and regulatory support. However, the common occurrence of CYP phenoconversion, a mismatch between genotype-predicted CYP phenotype and the actual CYP phenotype, currently limits the application of PGx testing for precision dosing in psychiatry. This review proposes a stepwise approach to assist precision dosing in psychiatry via the introduction of PGx stewardship programs and innovative PGx education strategies. A future perspective on delivering precision dosing for psychiatrists is discussed that involves innovative clinical decision support systems powered by model-informed precision dosing.

Assessing the Mechanism of Fluoxetine-Mediated CYP2D6 Inhibition

Fluoxetine is still one of the most widely used antidepressants in the world. The drug is extensively metabolized by several cytochrome P450 (CYP450) enzymes and subjected to a myriad of CYP450-mediated drug interactions. In a multidrug regimen, preemptive mitigation of drug-drug interactions requires knowledge of fluoxetine actions on these CYP450 enzymes. The major metabolic pathway of fluoxetine leading to the formation of its active metabolite, norfluoxetine, is mediated by CYP2D6. Fluoxetine and norfluoxetine are strong affinity substrates of CYP2D6 and can inhibit, potentially through various mechanisms, the metabolism of other sensitive CYP2D6 substrates. Remarkably, fluoxetine-mediated CYP2D6 inhibition subsides long after fluoxetine first passes through the liver and even remains long after the discontinuation of the drug. Herein, we review pharmacokinetic and pharmacogenetic information to help us understand the mechanisms underlying the prolonged inhibition of CYP2D6 following fluoxetine administration. We propose that long-term inhibition of CYP2D6 is likely a result of competitive inhibition. This is due to strong affinity binding of fluoxetine and norfluoxetine to the enzyme and unbound fluoxetine and norfluoxetine levels circulating in the blood for a long period of time because of their long elimination half-life. Additionally, we describe that fluoxetine is a CYP2C9 substrate and a mechanism-based inhibitor of CYP2C19.

Discontinuation and dose adjustment of metoprolol after metoprolol-paroxetine/fluoxetine co-prescription in Dutch elderly

Purpose

Co‐prescription of paroxetine/fluoxetine (a strong CYP2D6 inhibitor) in metoprolol (a CYP2D6 substrate) users is common, but data on the clinical consequences of this drug‐drug interaction are limited and inconclusive. Therefore, we assessed the effect of paroxetine/fluoxetine initiation on the existing treatment with metoprolol on the discontinuation and dose adjustment of metoprolol among elderly.

Methods

We performed a cohort study using the University of Groningen IADB.nl prescription database (www.IADB.nl). We selected all elderly (≥60 years) who had ever been prescribed metoprolol and had a first co‐prescription of paroxetine/fluoxetine, citalopram (weak CYP2D6 inhibitor), or mirtazapine (negative control) from 1994 to 2015. The exposure group was metoprolol and paroxetine/fluoxetine co‐prescription, and the other groups acted as controls. The outcomes were early discontinuation and dose adjustment of metoprolol. Logistic regression was applied to estimate adjusted odds ratios (OR) and 95% confidence intervals (CI).

Results

Combinations of metoprolol‐paroxetine/fluoxetine, metoprolol‐citalopram, and metoprolol‐mirtazapine were started in 528, 673, and 625 patients, respectively. Compared with metoprolol‐citalopram, metoprolol‐paroxetine/fluoxetine was not significantly associated with the early discontinuation and dose adjustment of metoprolol (OR = 1.07, 95% CI:0.77‐1.48; OR = 0.87, 95% CI:0.57‐1.33, respectively). In comparison with metoprolol‐mirtazapine, metoprolol‐paroxetine/fluoxetine was associated with a significant 43% relative increase in early discontinuation of metoprolol (OR = 1.43, 95% CI:1.01‐2.02) but no difference in the risk of dose adjustment. Stratified analysis by gender showed that women have a significantly high risk of metoprolol early discontinuation (OR = 1.62, 95% CI:1.03‐2.53).

Conclusion

Paroxetine/fluoxetine initiation in metoprolol prescriptions, especially for female older patients, is associated with the risk of early discontinuation of metoprolol.

The influence of a single and chronic administration of venlafaxine on tramadol pharmacokinetics in a rabbit model

BACKGROUND

The combined use of tramadol with selective serotonin and norepinephrine reuptake inhibitors e.g. venlafaxine may be associated with serotonin syndrome. No previous studies exist examining the influence of a weak CYP2D6 inhibitor venlafaxine on the pharmacokinetics of tramadol. Therefore, the aim of this study was to determine the effect of a single and chronic administration of venlafaxine on the pharmacokinetics of tramadol using a rabbit model.

METHODS

Adult New Zealand white rabbits of both sexes (n = 21) were used. Animals received 100 mg of tramadol per os (one slow release tablet) and 75 mg of venlafaxine (one prolonged release capsule), and were divided into four groups: control group - a single dose of tramadol alone, 1 day group - a single dose of tramadol and venlafaxine, 7 and 14 days groups - seven and fourteen days administration of venlafaxine once daily plus a single dose of tramadol on the last day of the study.

RESULTS

Venlafaxine administration over a period of 7 and 14 days resulted in faster elimination of tramadol compared to the control group: significantly higher values of k_el, and lower values of t_1/2kel and MRT for the 7 and 14 days group were observed. Although no differences in bioavailability of tramadol were obtained.

CONCLUSION

Using a rabbit model, there is no evidence that the combined administration of tramadol and venlafaxine may increase the plasma exposure of tramadol and therefore increase the risk of serotonin syndrome.

Simultaneous administration of fluoxetine and simvastatin ameliorates lipid profile, improves brain level of neurotransmitters, and increases bioavailability of simvastatin

Simvastatin (STT), a 3-hydroxy-3-methylglutaryl coenzyme A reductase inhibitor, is widely prescribed for dyslipidemia, whereas fluoxetine (FLX) is the first-choice drug for the treatment of depression and anxiety. A recent report suggests that selective serotonin reuptake inhibitors can interact with the cytochrome P450 3A4 substrate, and another one suggests that STT enhances the antidepressant activity of FLX. However, the data are inconclusive. The present study was designed to explore the pharmacokinetic and pharmacodynamic consequences of coadministration of STT and FLX in experimental animals. For this, Wistar rats weighing 250±10 g were divided into four groups, including control, STT (40 mg/kg/day), FLX (20 mg/kg/day), and STT+FLX group, respectively. After the dosing period of 4 weeks, the animals were sacrificed, and the blood and brain samples were collected for the analysis of STT, simvastatin acid (STA), FLX, total cholesterol, triglyceride, high-density lipoprotein (HDL), 5-hydroxytryptamine, dopamine, and hydroxy indole acetic acid. It was found that the coadministration resulted in a significant increase in the bioavailability of STT in the plasma (41.8%) and brain (68.7%) compared to administration of STT alone (p<0.05). The maximum drug concentration (C_max) of STT was also found to be increased significantly in the plasma and brain compared to that achieved after monotherapy (p<0.05). However, STT failed to improve the pharmacokinetics of FLX up to a significant level. The results of this study showed that the combined regimen significantly reduced the level of cholesterol and triglyceride and increased the level of HDL when compared to STT monotherapy. Furthermore, the coadministration of STT with FLX led to an elevated level of neurotransmitters in the brain (p<0.05). FLX increased the concentration of STT in the plasma and brain. The coadministration of these drugs also led to an improved lipid profile. However, in the long-term, this interaction may have a vital clinical importance because the increase in STT level may lead to life-threatening side effects associated with statins.

Effect of selective serotonin reuptake inhibitors use on endocrine therapy adherence and breast cancer mortality: a population-based study

The purpose of the study was to investigate whether the concomitant use of selective serotonin reuptake inhibitors (SSRI) with tamoxifen influences the risk of death due to breast cancer, and we also investigated the association between SSRI use and adherence to oral endocrine therapy (ET). We analyzed data from BCBaSe Sweden, which is a database created by the data linkage of Registries from three different regions of Sweden. To investigate the association between ET adherence and SSRI use, we included all women who were diagnosed with non-distant metastatic ER-positive invasive breast cancer from July 2007 to July 2011 and had at least one dispensed prescription of oral tamoxifen or aromatase inhibitor. To investigate the role of concurrent administration of SSRI and tamoxifen on breast cancer prognosis, we performed a nested case–control study. In the adherence cohort, 9104 women were included in the analyses. Women who received SSRI, either before or after breast cancer diagnosis, were at higher risk for low adherence to ET. However, when the overlapping period between SSRI use and ET was >50 %, no excess risk for low adherence was observed. Non-adherence (<80 %) to ET was significantly associated with worse breast cancer survival (OR 4.07; 95 % CI 3.27–5.06). In the case–control study, 445 cases and 11125 controls were included. The concomitant administration of SSRI and tamoxifen did not influence breast cancer survival, neither in short-term (OR 1.41; 95 % CI 0.74–2.68) nor in long-term SSRI users (OR 0.85; 95 % CI 0.35–2.08). Concomitant SSRI and tamoxifen use does not seem to increase risk for death due to breast cancer. Given the positive association between continuing antidepressive pharmacotherapy for a longer period of time and adherence to ET, it is essential to capture and treat depression in breast cancer patients to secure adherence to ET.

Addressing phenoconversion: the Achilles' heel of personalized medicine

Phenoconversion is a phenomenon that converts genotypic extensive metabolizers (EMs) into phenotypic poor metabolizers (PMs) of drugs, thereby modifying their clinical response to that of genotypic PMs. Phenoconversion, usually resulting from nongenetic extrinsic factors, has a significant impact on the analysis and interpretation of genotype-focused clinical outcome association studies and personalizing therapy in routine clinical practice. The high phenotypic variability or genotype-phenotype mismatch, frequently observed due to phenoconversion within the genotypic EM population, means that the real number of phenotypic PM subjects may be greater than predicted from their genotype alone, because many genotypic EMs would be phenotypically PMs. If the phenoconverted population with genotype-phenotype mismatch, most extensively studied for CYP2D6, is as large as the evidence suggests, there is a real risk that genotype-focused association studies, typically correlating only the genotype with clinical outcomes, may miss clinically strong pharmacogenetic associations, thus compromising any potential for advancing the prospects of personalized medicine. This review focuses primarily on co-medication-induced phenoconversion and discusses potential approaches to rectify some of the current shortcomings. It advocates routine phenotyping of subjects in genotype-focused association studies and proposes a new nomenclature to categorize study populations. Even with strong and reliable data associating patients' genotypes with clinical outcome(s), there are problems clinically in applying this knowledge into routine pharmacotherapy because of potential genotype-phenotype mismatch. Drug-induced phenoconversion during routine clinical practice remains a major public health issue. Therefore, the principal challenges facing personalized medicine, which need to be addressed, include identification of the following factors: (i) drugs that are susceptible to phenoconversion; (ii) co-medications that can cause phenoconversion; and (iii) dosage amendments that need to be applied during and following phenoconversion.

Pharmacokinetic and Pharmacodynamic Interactions of Oral Midazolam with Ketoconazole, Fluoxetine, Fluvoxamine, and Nefazodone

The objective of this study was to investigate pharmacokinetic and pharmacodynamic interactions between midazolam and fluoxetine, fluvoxamine, nefazodone, and ketoconazole. Forty healthy subjects were randomized to receive one of the four study drugs for 12 days in a parallel study design: fluoxetine 60 mg per day for 5 days, followed by 20 mg per day for 7 days; fluvoxamine titrated to a daily dose of 200 mg; nefazodone titrated to a daily dose of 400 mg; or ketoconazole 200 mg per day. All 40 subjects received oral midazolam solution before and after the 12-day study drug regimen. Blood samples for determination of midazolam concentrations were drawn for 24 hours after each midazolam dose and used for the calculation of pharmacokinetic parameters. The effects of the study drugs on midazolam pharmacodynamics were assessed using the symbol digit modalities test (SDMT). The mean area under the curve (AUC) for midazolam was increased 771.9% by ketoconazole and 444.0% by nefazodone administration. However, there was no significant change in midazolam AUC as a result of fluoxetine (13.4% decrease) and a statistical trend for fluvoxamine (66.1% increase) administration. Pharmacodynamic data are consistent with pharmacokinetic data indicating that nefazodone and ketoconazole resulted in significant increases in midazolam-related cognition impairment. The significant impairment in subjects' cognitive function reflects the changes in midazolam clearance after treatment with ketoconazole and nefazodone. These results suggest that caution with the use of midazolam is warranted with potent CYP3A4 inhibitors.

Adjunctive sleep medications and depression outcome in the treatment of serotonin-selective reuptake inhibitor resistant depression in adolescents study

OBJECTIVE

In the Treatment of Resistant Depression in Adolescents, study participants who received medication for sleep had a lower response rate. This report sought to clarify this finding.

METHOD

Depressed adolescents who had not responded to a previous adequate serotonin-selective reuptake inhibitor (SSRI) trial were randomly assigned to another SSRI, venlafaxine, another SSRI+cognitive behavior therapy (CBT), or venlafaxine+CBT. Augmentation with sleep medication was permitted as clinically indicated.

RESULTS

Youth who received trazodone were six times less likely to respond than those with no sleep medication (adjusted odds ratio [OR]=0.16, 95% confidence interval [CI]: 0.05-0.50, p=0.001) and were three times more likely to experience self-harm (OR=3.0, 95% CI: 1.1-7.9, p=0.03), even after adjusting for baseline differences associated with trazodone use. None (0/13) of those cotreated with trazodone and either paroxetine or fluoxetine responded. In contrast, those treated with other sleep medications had similar rates of response (60.0% vs. 50.4%, χ(2)=0.85, p=0.36) and of self-harm events (OR=0.5, 95% CI: 0.1-2.6, p=0.53) as those who received no sleep medication.

CONCLUSIONS

These findings should be interpreted cautiously because these sleep agents were not assigned randomly, but at clinician discretion. Nevertheless, they suggest that the use of trazodone for the management of sleep difficulties in adolescent depression should be re-evaluated and that future research on the management of sleep disturbance in adolescent depression is needed. The very low response rate of participants cotreated with trazodone and either fluoxetine or paroxetine could be due to inhibition of CYP 2D6 by these antidepressants.

[Interactions between metoprolol and antidepressants]

BACKGROUND

Metoprolol, the most commonly used beta-receptor antagonist in Norway, is eliminated mainly via the enzyme cytochrome P450 (CYP) 2D6. This enzyme is inhibited to a varying extent by antidepressants. The aim of this article is to provide an overview of the interactions between metoprolol and antidepressants with an emphasis on CYP2D6 inhibition.

MATERIAL AND METHODS

Relevant literature was identified by a PubMed search using the word "metoprolol" combined with generic names of antidepressant drugs.

RESULTS

The potent CYP2D6 inhibitor paroxetine has been shown to increase the biologically available dose of metoprolol about 4- to 6-fold. The same degree of increase is expected for the two other potent CYP2D6 inhibitors in the class, fluoxetine and bupropion. Severe bradycardia and atroventricular block has been reported in patients who have taken metoprolol in combination with these three drugs. Escitalopram, citalopram and duloxetine are less potent CYP2D6 inhibitors, and have been shown to cause 2- to 3-fold increases in biologically available dose of metoprolol. Other antidepressants, such as sertraline, venlafaxine, mianserin and mirtazapine, inhibit CYP2D6 to little or no extent, and are not expected to cause clinically relevant interactions with metoprolol.

CONCLUSION

Metoprolol should not be used concomitantly with paroxetine, fluoxetine or bupropion due to extensive interactions and the risk of serious adverse effects. Dose reductions of metoprolol should be considered for combined treatment with citalopram, escitalopram or duloxetine, while concurrent use with sertraline, venlafaxine, mianserin and mirtazapine should be safe.

Coprescription of tamoxifen and medications that inhibit CYP2D6

Evidence has emerged that the clinical benefit of tamoxifen is related to the functional status of the hepatic metabolizing enzyme cytochrome P450 2D6 (CYP2D6). CYP2D6 is the key enzyme responsible for the generation of the potent tamoxifen metabolite, endoxifen. Multiple studies have examined the relationship of CYP2D6 status to breast cancer outcomes in tamoxifen-treated women; the majority of studies demonstrated that women with impaired CYP2D6 metabolism have lower endoxifen concentrations and a greater risk of breast cancer recurrence. As a result, practitioners must be aware that some of the most commonly prescribed medications coadministered with tamoxifen interfere with CYP2D6 function, thereby reducing endoxifen concentrations and potentially increasing the risk of breast cancer recurrence. After reviewing the published data regarding tamoxifen metabolism and the evidence relating CYP2D6 status to breast cancer outcomes in tamoxifen-treated patients, we are providing a guide for the use of medications that inhibit CYP2D6 in patients administered tamoxifen.

Selective serotonin reuptake inhibitors and breast cancer mortality in women receiving tamoxifen: a population based cohort study

OBJECTIVE

To characterise whether some selective serotonin reuptake inhibitor (SSRI) antidepressants reduce tamoxifen's effectiveness by inhibiting its bioactivation by cytochrome P450 2D6 (CYP2D6).

DESIGN

Population based cohort study.

PARTICIPANTS

Women living in Ontario aged 66 years or older treated with tamoxifen for breast cancer between 1993 and 2005 who had overlapping treatment with a single SSRI.

MAIN OUTCOME MEASURES

Risk of death from breast cancer after completion of tamoxifen treatment, as a function of the proportion of time on tamoxifen during which each SSRI had been co-prescribed.

RESULTS

Of 2430 women treated with tamoxifen and a single SSRI, 374 (15.4%) died of breast cancer during follow-up (mean follow-up 2.38 years, SD 2.59). After adjustment for age, duration of tamoxifen treatment, and other potential confounders, absolute increases of 25%, 50%, and 75% in the proportion of time on tamoxifen with overlapping use of paroxetine (an irreversible inhibitor of CYP2D6) were associated with 24%, 54%, and 91% increases in the risk of death from breast cancer, respectively (P<0.05 for each comparison). By contrast, no such risk was seen with other antidepressants. We estimate that use of paroxetine for 41% of tamoxifen treatment (the median overlap in our sample) would result in one additional breast cancer death within five years of cessation of tamoxifen for every 19.7 (95% confidence interval 12.5 to 46.3) patients so treated; the risk with more extensive overlap would be greater.

CONCLUSION

Paroxetine use during tamoxifen treatment is associated with an increased risk of death from breast cancer, supporting the hypothesis that paroxetine can reduce or abolish the benefit of tamoxifen in women with breast cancer.

Correction of venlafaxine- and duloxetine-induced transaminase elevations with desvenlafaxine in a patient with Gilbert's syndrome

Recent reviews have questioned whether the serotonin-norepinephrine reuptake inhibitor (SNRI) desvenlafaxine succinate offers any practical clinical advantages over existing SNRIs. The following case is one instance where it appears that this SNRI offers unique safety and benefit. Presented is a case report of a patient with Gilbert's syndrome, longstanding social phobia, and more recent depressive disorder not otherwise specified, who was found to have elevated liver transaminases when prescribed both duloxetine and venlafaxine. The patient subsequently responded to desvenlafaxine but without liver abnormalities. In this patient with Gilbert's Syndrome, desvenlafaxine's lack of metabolism through the cytochrome P450 (CYP) 2D6 pathway may explain the avoidance of these abnormalities and thus suggests a possible therapeutic role for this SNRI in similarly susceptible patients.

Pharmacokinetic/pharmacodynamic modelling of venlafaxine: pupillary light reflex as a test system for noradrenergic effects

BACKGROUND AND OBJECTIVE

Venlafaxine and its major active metabolite O-desmethylvenlafaxine selectively inhibit serotonin and norepinephrine reuptake from the synaptic gap. The inhibition of norepinephrine uptake is assumed to enhance antidepressant efficacy when venlafaxine is given at higher therapeutic doses. Thus investigation of the concentration-response relationship of noradrenergic effects is of clinical interest. We used pupillography as a test system for the pharmacodynamic response to venlafaxine, since it had been shown to be useful for assessment of noradrenergic effects on the autonomous nervous system. The aim of the study was to develop a pharmacokinetic/pharmacodynamic model by means of nonlinear mixed-effects modelling in order to describe the time course of the noradrenergic response to venlafaxine.

SUBJECTS AND METHODS

Twelve healthy male subjects received venlafaxine 37.5 mg or placebo orally twice daily for 7 days and subsequently 75 mg or placebo twice daily for another 7 days. After a 14-day washout phase, the two groups were crossed over. After the last dose of venlafaxine or placebo on day 14, blood samples were drawn to determine venlafaxine and O-desmethylvenlafaxine concentrations and the amplitude and recovery time of the pupillary light reflex were measured. A pharmacokinetic/pharmacodynamic model was developed to describe the data using nonlinear mixed-effects modelling.

RESULTS

The pharmacokinetic part of the model could be simultaneously fitted to both venlafaxine and O-desmethylvenlafaxine data, yielding precise parameter estimates that were similar to published data. The model detected high variability of the intrinsic clearance of venlafaxine (94.8%), most likely due to cytochrome P450 2D6 polymorphism. Rapid development of tolerance of the pupillary light reflex parameters was seen and could be successfully accounted for in the pharmacodynamic part of the model. The half-life of development and regression of tolerance was estimated to be 30 minutes for the amplitude and 40 minutes for the recovery time.

CONCLUSION

The time course of the effect and the concentration-response relationship were successfully described by a pharmacokinetic/pharmacodynamic model that takes into account the rapid development of tolerance of pupillary light reflex parameters. This provides a basis for further investigations of the applicability of pupillography as a surrogate measurement of the effectivity of antidepressant drugs with norepinephrine reuptake-inhibiting properties.

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.

Risk and predictability of drug interactions in the elderly

The issue of drug-drug interactions is particularly relevant for geriatric patients with epilepsy because they are often treated with multiple medications for concurrent diseases such as cardiovascular disease and psychiatric disorders (e.g., dementia and depression). The antidepressants with the least potential for altering antiepileptic drug (AED) metabolism are citalopram, escitalopram, venlafaxine, duloxetine, and mirtazapine. The use of established AEDs with enzyme-inducing properties, such as carbamazepine, phenytoin, and phenobarbital, may be associated with reductions in the levels of drugs such as donepezil, galantamine, and particularly warfarin. Carbamazepine, phenytoin, and phenobarbital have been reported to decrease prothrombin time in patients taking oral anticoagulants, although with phenytoin, an increase in prothrombin time has also been reported. Drugs associated with increased risk of bleeding in patients taking oral anticoagulants include selective serotonin reuptake inhibitors (especially fluoxetine), gemfibrozil, fluvastatin, and lovastatin. Other drugs affected by enzyme inducers include cytochrome P450 3A4 substrates, such as calcium channel blockers (e.g., nimodipine, nilvadipine, nisoldipine, and felodipine) and the 3-hydroxy-3-methylglutaryl coenzyme A (HMG-CoA) reductase inhibitors atorvastatin, lovastatin, and simvastatin. Although there have been no reports of AEDs altering ticlopidine metabolism, ticlopidine coadministration can result in carbamazepine and phenytoin toxicity. Also, there is a significant risk of elevated levels of carbamazepine when diltiazem and verapamil are administered. In addition, there are case reports of phenytoin toxicity when administered with diltiazem. Drugs with a lower potential for metabolic drug interactions include (1) cholinesterase inhibitors (although the theoretical possibility of a reduction in donepezil and galantamine levels by enzyme-inducing AEDs should be considered) and the N-methyl-D-aspartate receptor antagonist memantine and (2) antihypertensives such as angiotensin-converting enzyme inhibitors, angiotensin receptor blockers, hydrophilic beta-blockers, and thiazide diuretics. There is a moderate risk that enzyme-inducing AEDs will decrease levels of lipophilic beta-blockers. Newer AEDs have a lower potential for drug interactions. In particular, levetiracetam and gabapentin have not been reported to alter enzyme activity. In summary, there is a significant potential for drug interactions between AEDs and drugs commonly prescribed in geriatric patients with epilepsy.

Pharmacogenetics, drug-metabolizing enzymes, and clinical practice

The application of pharmacogenetics holds great promise for individualized therapy. However, it has little clinical reality at present, despite many claims. The main problem is that the evidence base supporting genetic testing before therapy is weak. The pharmacology of the drugs subject to inherited variability in metabolism is often complex. Few have simple or single pathways of elimination. Some have active metabolites or enantiomers with different activities and pathways of elimination. Drug dosing is likely to be influenced only if the aggregate molar activity of all active moieties at the site of action is predictably affected by genotype or phenotype. Variation in drug concentration must be significant enough to provide "signal" over and above normal variation, and there must be a genuine concentration-effect relationship. The therapeutic index of the drug will also influence test utility. After considering all of these factors, the benefits of prospective testing need to be weighed against the costs and against other endpoints of effect. It is not surprising that few drugs satisfy these requirements. Drugs (and enzymes) for which there is a reasonable evidence base supporting genotyping or phenotyping include suxamethonium/mivacurium (butyrylcholinesterase), and azathioprine/6-mercaptopurine (thiopurine methyltransferase). Drugs for which there is a potential case for prospective testing include warfarin (CYP2C9), perhexiline (CYP2D6), and perhaps the proton pump inhibitors (CYP2C19). No other drugs have an evidence base that is sufficient to justify prospective testing at present, although some warrant further evaluation. In this review we summarize the current evidence base for pharmacogenetics in relation to drug-metabolizing enzymes.

Pharmacological and clinical aspects of antiepileptic drug use in the elderly

In this article, epidemiological and clinical aspects related to the use of antiepileptic drugs (AEDs) in the elderly are highlighted. Studies have shown that people with epilepsy receiving AED treatment show important deficits in physical and social functioning compared with age-matched people without epilepsy. To what extent these deficits can be ascribed to epilepsy per se or to the consequences of AED treatment remains to be clarified. The importance of characterizing the effects of AEDs in an elderly population is highlighted by epidemiological surveys indicating that the prevalence of AED use is increased in elderly people, particularly in those living in nursing homes. Both the pharmacokinetics and the pharmacodynamics of AEDs may be altered in old age, which may contribute to the observation that AEDs are among the drug classes most commonly implicated as causing adverse drug reactions in an aged population. Age alone is one of several contributors to alterations in AED response in the elderly; other factors include physical frailty, co-morbidities, dietary influences, and drug interactions. Individualization of dosage, avoidance of unnecessary polypharmacy, and careful observation of clinical response are essential for an effective and safe utilization of AEDs in an elderly population.

Drug–drug interactions in oncology: Why are they important and can they be minimized?

Adverse drug-drug interactions are a major cause of morbidity and mortality. Cancer patients are at particularly high risk of such interactions because they commonly receive multiple medications, including cytotoxic chemotherapy, hormonal agents and supportive care drugs. In addition, the majority of cancer patients are elderly, and so require medications for co-morbid conditions such as cardiovascular, gastrointestinal, and rheumatological diseases. Furthermore, the age-related decline in hepatic and renal function reduces their ability to metabolize and clear drugs and so increases the potential for toxicity. Not all drug-drug interactions can be predicted, and those that are predictable are not always avoidable. However, increased awareness of the potential for these interactions will allow healthcare providers to minimize the risk by choosing appropriate drugs and also by monitoring for signs of interaction. This review considers the basic principles of drug-drug interactions, and presents specific examples that are relevant to oncology.

Mechanistic basis of adverse drugreactions: the perils of inappropriate dose schedules

Adverse drug reactions (ADRs) have long been recognised as a significant cause of morbidity and mortality. They account for a substantial number of clinical consultations, hospital admissions and extended duration of in-patient stay as well as mortality. By far the most common ADRs are the concentration-dependent pharmacological reactions, the majority of which ought to be preventable. As a result of high concentrations of the parent drug and/or its metabolite(s), there is an augmentation of primary pharmacological activity and/or appearance of new and undesirable secondary pharmacological activity. Typically, these high concentrations result from administration of high doses in an attempt to maximise efficacy and/or modulation of the pharmacokinetics of a drug by either genetic or non-genetic factors. High plasma concentrations of parent drug may result from inherited impairment or drug-induced inhibition of its pharmacokinetic disposition. Conversely, inherited overcapacity or drug-induced induction of the metabolism of a drug may result in low concentrations of parent drug and frequently, rapid accumulation of its metabolites. Environmental, dietary and phytochemical factors may also influence the activity of drug metabolising enzymes. As with inherited polymorphisms of acetylation and cytochrome P450-based drug metabolising enzymes, polymorphisms of other conjugation reactions, such as glucuronidation, increasingly appear to be associated with drug toxicity. Diseases of organs involved in elimination of a drug also alter its pharmacokinetics, plasma concentration and, therefore, the profile of its concentration-dependent ADRs. Inherited mutations, concurrently administered drugs or presence of certain diseases may also alter the sensitivity of some pharmacological targets, accounting for a substantial number of ADRs and interactions. When there is enhanced pharmacodynamic sensitivity, plasma drug concentrations that are apparently within the normal 'non-toxic' range give rise to ADRs. Recent advances have also provided important insights into the wider scope of drug-drug interactions. Interactions that occur at P-glycoproteins, drug transporters and efflux pumps, at various transmembrane interfaces such as the gastrointestinal wall, renal tubules, hepatobiliary border and blood-brain barrier, are beginning to explain many non-metabolic interactions. These alter the systemic exposure to drugs and have so far, begun to explain unexpected neurotoxicity and hepatotoxicity. The function of these transporters is also genetically modulated. These advances, together with continued increased awareness and education of prescribers and pharmacists, offer great opportunities for substantially minimising concentration-related ADRs.

Antidepressant Drug-Drug Interaction Profile Update

Drug-drug interactions continue to be underappreciated and misunderstood by most clinicians. Although life-threatening drug interactions are rare, serious clinical consequences, including altered drug response, poor tolerability with reduced medication adherence, and increased costs for care tied to the increased complexity of therapy, are fairly commonplace. Drug interactions may be further complicated by genetic differences in metabolic capacity. Patients who routinely require long-term treatment for depression have an increased likelihood of experiencing a drug-drug interaction since they will take over-the-counter and prescription medications for intercurrent and/or co-morbid illness. Antidepressants can be the object of drug interactions when their metabolic pathways are affected by other substances, or they can precipitate interactions by inhibiting enzyme pathways. Clinicians can improve the short- and long-term outcomes of patients with a depressive disorder by considering the possibility of drug-drug interactions both before prescribing a specific antidepressant and while monitoring for response, adverse effects and patient compliance.

Lack of a Fluoxetine Effect on Prednisolone Disposition and Cortisol Suppression

STUDY OBJECTIVE

To evaluate the potential effect of fluoxetine, a cytochrome P450 isoenzyme inhibitor, on prednisolone disposition and cortisol suppression.

DESIGN

Sequential, two-phase, crossover, open-label pharmacokinetic study.

SETTING

General clinical research center.

SUBJECTS

Fourteen healthy volunteers.

INTERVENTION

A single intravenous dose of prednisolone 40 mg before and after 14 days of treatment with fluoxetine 20 mg/day for 5 days followed by 60 mg/day for 9 days to achieve steady-state concentrations.

MEASUREMENTS AND MAIN RESULTS

Pharmacokinetic parameters of the prednisolone and resulting pharmacodynamic effects on the time course of plasma cortisol suppression before and after fluoxetine administration were evaluated. No significant differences were observed for the mean +/- SD area under the prednisolone concentration-time curve (3739 +/- 992 vs 3498 +/- 797 microg x hr/L, respectively), clearance (8.58 +/- 2.62 vs 8.92 +/- 2.05 L/hr, respectively), volume of distribution (39.5 +/- 12.4 vs 38.2 +/- 9.9 L, respectively), elimination half-life (3.32 +/- 0.83 vs 3.05 +/- 0.80 hrs, respectively), or duration of plasma cortisol suppression (23.5 +/- 3.1 vs 22.0 +/- 4.2 hrs, respectively).

CONCLUSION

Fluoxetine administration did not significantly affect prednisolone disposition or prolong cortisol suppression. This finding suggests that coadministration of these agents is unlikely to result in clinically important pharmacokinetic or pharmacodynamic drug interactions. Prednisolone may be a useful alternative for patients who require both glucocorticoid and fluoxetine therapy.

Determination of fluoxetine and norfluoxetine in human plasma by high-performance liquid chromatography with ultraviolet detection in psychiatric patients

A rapid high-performance liquid chromatographic method is described for the simultaneous determination of the widely used antidepressant drug, fluoxetine and its principal metabolite norfluoxetine in plasma. After liquid-liquid extraction the compounds were separated in a reversed-phase column and assayed by ultraviolet absorption at 226 nm. The analytical interference from psychoactive drugs and their metabolites was also studied. The extraction recoveries were 93 and 87% for norfluoxetine and fluoxetine, respectively. The limit of quantitation under the described conditions was 14 nmol/l for both compounds. The method was found to be reproducible with coefficients of variation less than 10%. A great variability in plasma concentrations of fluoxetine and norfluoxetine as well as in fluoxetine/norfluoxetine ratios was found among the 29 patients studied. This result suggests the implication of genetically polymorphic enzymes, presumably CYP2D6, CYP2C9 and CYP2C19 in the metabolism of fluoxetine to norfluoxetine. Therapeutic drug monitoring should thus be useful in patients treated with regular doses.

CYP2D6 inhibition by selective serotonin reuptake inhibitors: analysis of achievable steady-state plasma concentrations and the effect of ultrarapid metabolism at CYP2D6

STUDY OBJECTIVE

To assess the correlation between plasma concentrations of four commonly administered selective serotonin reuptake inhibitors (SSRIs) and the magnitude of cytochrome P450 (CYP) 2D6 inhibition.

DESIGN

Prospective analysis.

SETTING

University-affiliated research laboratory.

PATIENTS

Thirty-two healthy, drug-free volunteers.

INTERVENTION

Subjects were randomized to four groups and received daily administration of either fluoxetine 60 mg (as a loading dose), fluvoxamine 100 mg, paroxetine 20 mg, or sertraline 100 mg for 8 days.

MEASUREMENTS AND MAIN RESULTS

The urinary concentration ratio of dextromethorphan:dextrorphan (interpreted as an in vivo index of CYP2D6 activity) was determined for each subject before and after the 8 days of receiving SSRIs. Plasma SSRI trough concentrations were measured on days 6-9. The CYP2D6 genotype was determined in a subject with an undetectable paroxetine concentration. Inhibition of CYP2D6 correlated significantly with plasma concentrations of paroxetine and fluoxetine. In contrast, no significant correlations emerged between CYP2D6 inhibition and plasma concentrations of sertraline or fluvoxamine. The subject with an undetectable paroxetine concentration was found to carry at least three functional CYP2D6 genes.

CONCLUSIONS

For paroxetine and fluoxetine, plasma concentrations and dosage strongly influence the magnitude of enzyme inhibition. The potential of paroxetine (a CYP2D6 substrate) as an inhibitor may be affected by the genotypes and metabolic capacities of individual subjects.