Paroxetine does not affect the cardiac safety and pharmacokinetics of terfenadine in healthy adult men

A Phase I, Open-Label, Fixed Sequence Study to Investigate the Effect of Cytochrome P450 2D6 Inhibition on the Pharmacokinetics of Ulotaront in Healthy Subjects

BACKGROUND

Ulotaront is a novel psychotropic agent with agonist activity at trace amine-associated receptor 1 (TAAR1) and 5-hydroxytryptamine type 1A (5-HT1A) receptors in phase III clinical development for the treatment of schizophrenia.

OBJECTIVE

This study aimed to investigate the effect of paroxetine, a strong cytochrome P450 (CYP) 2D6 inhibitor, on ulotaront pharmacokinetics (PK) in healthy volunteers.

METHODS

Subjects received a single oral dose of 25 mg ulotaront on Day 1 and an oral dose of 20 mg paroxetine once daily from Days 5 to 10 to achieve steady-state plasma paroxetine levels. On Day 11, subjects received another single oral dose of 25 mg ulotaront, with continued daily oral dosing of 20 mg paroxetine from Days 11 to 14. All 24 subjects were CYP2D6 normal metabolizers.

RESULTS

Coadministration of paroxetine increased ulotaront maximum observed plasma concentration (Cmax) and area under the plasma concentration-time curve from time zero to infinity (AUC∞) by 31% and 72%, respectively, and decreased ulotaront apparent clearance (CL/F) by approximately 42%. While coadministration of paroxetine increased AUC∞ of active but minor metabolite SEP-363854 by 32%, it had no effect on SEP-363854 Cmax, or on SEP-363854 to the ulotaront AUC from time zero to the last quantifiable concentration (AUClast) ratio. Based on the acceptable adverse event profile of ulotaront across previous phase II studies, the increase in ulotaront exposure is unlikely to be clinically meaningful.

CONCLUSIONS

Weak drug-drug interactions were observed between ulotaront and the strong CYP2D6 inhibitor paroxetine; however, dose adjustment as a precondition when ulotaront is coadministered with strong CYP2D6 inhibitors or administered to CYP2D6 poor metabolizers should not be necessary.

Cytochrome P450 3A Time-Dependent Inhibition Assays Are Too Sensitive for Identification of Drugs Causing Clinically Significant Drug-Drug Interactions: A Comparison of Human Liver Microsomes and Hepatocytes and Definition of Boundaries for Inactivation Rate Constants

Time-dependent inhibition (TDI) of CYP3A is an important mechanism underlying numerous drug-drug interactions (DDIs), and assays to measure this are done to support early drug research efforts. However, measuring TDI of CYP3A in human liver microsomes (HLMs) frequently yields overestimations of clinical DDIs and thus can lead to the erroneous elimination of many viable drug candidates from further development. In this investigation, 50 drugs were evaluated for TDI in HLMs and suspended human hepatocytes (HHEPs) to define appropriate boundary lines for the TDI parameter rate constant for inhibition (k_obs) at a concentration of 30 µM. In HLMs, a k_obs value of 0.002 minute^-1 was statistically distinguishable from control; however, many drugs show k_obs greater than this but do not cause DDI. A boundary line defined by the drug with the lowest k_obs that causes a DDI (diltiazem) was established at 0.01 minute^-1 Even with this boundary, of the 33 drugs above this value, only 61% cause a DDI (true positive rate). A corresponding analysis was done using HHEPs; k_obs of 0.0015 minute^-1 was statistically distinguishable from control, and the boundary was established at 0.006 minute^-1 Values of k_obs in HHEPs were almost always lower than those in HLMs. These findings offer a practical guide to the use of TDI data for CYP3A in early drug-discovery research. SIGNIFICANCE STATEMENT: Time-dependent inhibition of CYP3A is responsible for many drug interactions. In vitro assays are employed in early drug research to identify and remove CYP3A time-dependent inhibitors from further consideration. This analysis demonstrates suitable boundaries for inactivation rates to better delineate drug candidates for their potential to cause clinically significant drug interactions.

Quantitative Assessment of the Physiological Parameters Influencing QT Interval Response to Medication: Application of Computational Intelligence Tools

Human heart electrophysiology is complex biological phenomenon, which is indirectly assessed by the measured ECG signal. ECG trace is further analyzed to derive interpretable surrogates including QT interval, QRS complex, PR interval, and T wave morphology. QT interval and its modification are the most commonly used surrogates of the drug triggered arrhythmia, but it is known that the QT interval itself is determined by other nondrug related parameters, physiological and pathological. In the current study, we used the computational intelligence algorithms to analyze correlations between various simulated physiological parameters and QT interval. Terfenadine given concomitantly with 8 enzymatic inhibitors was used as an example. The equation developed with the use of genetic programming technique leads to general reasoning about the changes in the prolonged QT. For small changes of the QT interval, the drug-related IKr and ICa currents inhibition potentials have major impact. The physiological parameters such as body surface area, potassium, sodium, and calcium ions concentrations are negligible. The influence of the physiological variables increases gradually with the more pronounced changes in QT. As the significant QT prolongation is associated with the drugs triggered arrhythmia risk, analysis of the role of physiological parameters influencing ECG seems to be advisable.

The Role of Interaction Model in Simulation of Drug Interactions and QT Prolongation

Computational modelling is a cornerstone of Comprehensive In Vitro Proarrhythmia Assay and is re-increasingly being used in drug development. Electrophysiological effects of drug-drug interactions can be predicted in silico, e.g. with the use of in vitro cardiac ion channel data, PK profiles and human ventricular cardiomyocyte models. There are, however, several approaches with different assumptions used to assess the combined effect of multiple drugs, and there is no agreed standard interaction model. The aim of this study was to assess whether the choice of the drug-drug interaction (DDI) model (Bliss independence, Loewe additivity, or simple sum) influences the results of QT interval simulation trial. The Simcyp Simulator version 12.1 (Simcyp Ltd. [part of Certara], Sheffield, UK) and Cardiac Safety Simulator 2.0 (Simcyp Ltd. [part of Certara], Sheffield, UK) were used to simulate results of 8 virtual trials mimicking clinical studies and generate individual QTc data. The combined effect of inhibitory actions of drugs which were given simultaneously was calculated with use of three different interaction models. The PD effect of DDI was assessed and the differences between mean observed and mean predicted ΔQTcB values for terfenadine interactions were not statistically significant in all but one cases. Differences between the three DDI models are not statistically significant, implying that the choice of the DDI model, in the case of lack of synergy or antagonism, is irrelevant to the average predicted effect at the clinical level. However, in some cases, it can influence the verdict on combinatorial therapy safety for individual patients.

Virtual Clinical Trial Toward Polytherapy Safety Assessment: Combination of Physiologically Based Pharmacokinetic/Pharmacodynamic-Based Modeling and Simulation Approach With Drug-Drug Interactions Involving Terfenadine as an Example

A Quantitative Systems Pharmacology approach was utilized to predict the cardiac consequences of drug-drug interaction (DDI) at the population level. The Simcyp in vitro-in vivo correlation and physiologically based pharmacokinetic platform was used to predict the pharmacokinetic profile of terfenadine following co-administration of the drug. Electrophysiological effects were simulated using the Cardiac Safety Simulator. The modulation of ion channel activity was dependent on the inhibitory potential of drugs on the main cardiac ion channels and a simulated free heart tissue concentration. ten Tusscher's human ventricular cardiomyocyte model was used to simulate the pseudo-ECG traces and further predict the pharmacodynamic consequences of DDI. Consistent with clinical observations, predicted plasma concentration profiles of terfenadine show considerable intra-subject variability with recorded C_max values below 5 ng/mL for most virtual subjects. The pharmacokinetic and pharmacodynamic effects of inhibitors were predicted with reasonable accuracy. In all cases, a combination of the physiologically based pharmacokinetic and physiology-based pharmacodynamic models was able to differentiate between the terfenadine alone and terfenadine + inhibitor scenario. The range of QT prolongation was comparable in the clinical and virtual studies. The results indicate that mechanistic in vitro-in vivo correlation can be applied to predict the clinical effects of DDI even without comprehensive knowledge on all mechanisms contributing to the interaction.

Drug-drug interactions and QT prolongation as a commonly assessed cardiac effect - comprehensive overview of clinical trials

Background

Proarrhythmia assessment is one of the major concerns for regulatory bodies and pharmaceutical industry. ICH guidelines recommending preclinical tests have been established in attempt to eliminate the risk of drug-induced arrhythmias. However, in the clinic, arrhythmia occurrence is determined not only by the inherent property of a drug to block ion currents and disturb electrophysiological activity of cardiac myocytes, but also by many other factors modifying individual risk of QT prolongation and subsequent proarrhythmia propensity. One of those is drug-drug interactions. Since polypharmacy is a common practice in clinical settings, it can be anticipated that there is a relatively high risk that the patient will receive at least two drugs mutually modifying their proarrhythmic potential and resulting either in triggering the occurrence or mitigating the clinical symptoms. The mechanism can be observed either directly at the pharmacodynamic level by competing for the molecular targets, or indirectly by modifying the physiological parameters, or at the pharmacokinetic level by alteration of the active concentration of the victim drug.

Methods

This publication provides an overview of published clinical studies on pharmacokinetic and/or pharmacodynamic drug-drug interactions in humans and their electrophysiological consequences (QT interval modification). Databases of PubMed and Scopus were searched and combinations of the following keywords were used for Title, Abstract and Keywords fields: interaction, coadministration, combination, DDI and electrocardiographic, QTc interval, ECG. Only human studies were included. Over 4500 publications were retrieved and underwent preliminary assessment to identify papers accordant with the topic of this review. 76 papers reporting results for 96 drug combinations were found and analyzed.

Results

The results show the tremendous variability of drug-drug interaction effects, which makes one aware of complexity of the problem, and suggests the need for assessment of an additional risk factors and careful ECG monitoring before administration of drugs with anticipated QT prolongation.

Conclusions

DDIs can play significant roles in drugs’ cardiac safety, as evidenced by the provided examples. Assessment of the pharmacodynamic effects of the drug interactions is more challenging as compared to the pharmacokinetic due to the significant diversity in the endpoints which should be analyzed specifically for various clinical effects. Nevertheless, PD components of DDIs should be accounted for as PK changes alone do not allow to fully explain the electrophysiological effects in clinic situations.

Electronic supplementary material

The online version of this article (doi:10.1186/s40360-016-0053-1) contains supplementary material, which is available to authorized users.

QTc interval prolongation and torsade de pointes associated with second-generation antipsychotics and antidepressants: a comprehensive review

We comprehensively reviewed published literature to determine whether it supported the link between corrected QT (QTc) interval prolongation and torsade de pointes (TdP) for the 11 second-generation antipsychotics and seven second-generation antidepressants commonly implicated in these complications. Using PubMed and EMBASE, we identified four thorough QT studies (one each for iloperidone, ziprasidone, citalopram, and escitalopram), 40 studies specifically designed to assess QTc interval prolongation or TdP, 58 publications based on data from efficacy and safety trials, 18 toxicology studies, and 102 case reports. Thorough QT studies, QTc prolongation-specific studies, and studies based on efficacy and safety trials did not link drug-associated QTc interval prolongation with TdP. They only showed that the drugs reviewed caused varying degrees of QTc interval prolongation, and even that information was not clear and consistent enough to stratify individual drugs for this risk. The few toxicology studies provided valuable information but their findings are pertinent only to situations of drug overdose. Case reports were most informative about the drug-QTc interval prolongation-TdP link. At least one additional well established risk factor for QTc prolongation was present in 92.2 % of case reports. Of the 28 cases of TdP, six (21.4 %) experienced it with QTc interval <500 ms; 75 % of TdP cases occurred at therapeutic doses. There is little evidence that drug-associated QTc interval prolongation by itself is sufficient to predict TdP. Future research needs to improve its precision and broaden its scope to better understand the factors that facilitate or attenuate progression of drug-associated QTc interval prolongation to TdP.

A comparison of the risk of QT prolongation among SSRIs

OBJECTIVE

To report QT prolongation potential in selective serotonin reuptake inhibitors (SSRIs) in order to advise clinicians on safe use of SSRIs other than citalopram in light of citalopram warnings.

DATA SOURCES

Primary literature and case reports were identified through a systematic search. Data from drug manufacturers, package inserts, and the ArizonaCERT database were also utilized.

STUDY SELECTION AND DATA EXTRACTION

English-language studies and case reports were included.

DATA SYNTHESIS

Studies demonstrate possible dose-related clinically significant QT prolongation with escitalopram. Fluoxetine, fluvoxamine, and sertraline at traditional doses demonstrate a lack of clinically significant increases in QTc in the majority of studies. Further, paroxetine monotherapy shows a lack of clinically significant QTc prolongation in all studies. However, case reports or reporting tools still link these SSRIs with QTc prolongation. Fluoxetine, escitalopram, and sertraline used in post-acute coronary syndrome patients did not demonstrate risk of QTc prolongation.

CONCLUSION

For clinicians who choose not to use citalopram due to recent Food and Drug Administration (FDA) recommendations, other antidepressants within this class may be considered. When citalopram is not utilized based on risk factors for TdP, use of escitalopram is not likely the safest alternative. Based on current literature, fluoxetine, fluvoxamine, and sertraline appear to have similar, low risk for QT prolongation, and paroxetine appears to have the lowest risk. However, there are significant limitations in interpreting the studies, including varying definitions of significant QT prolongation. Therefore, choice of an alternative SSRI should be based on individual risk factors for arrhythmias and other patient-specific factors.

Importance of multi-p450 inhibition in drug-drug interactions: evaluation of incidence, inhibition magnitude, and prediction from in vitro data

Drugs that are mainly cleared by a single enzyme are considered more sensitive to drug-drug interactions (DDIs) than drugs cleared by multiple pathways. However, whether this is true when a drug cleared by multiple pathways is coadministered with an inhibitor of multiple P450 enzymes (multi-P450 inhibition) is not known. Mathematically, simultaneous equipotent inhibition of two elimination pathways that each contribute half of the drug clearance is equal to equipotent inhibition of a single pathway that clears the drug. However, simultaneous strong or moderate inhibition of two pathways by a single inhibitor is perceived as an unlikely scenario. The aim of this study was (i) to identify P450 inhibitors currently in clinical use that can inhibit more than one clearance pathway of an object drug in vivo and (ii) to evaluate the magnitude and predictability of DDIs caused by these multi-P450 inhibitors. Multi-P450 inhibitors were identified using the Metabolism and Transport Drug Interaction Database. A total of 38 multi-P450 inhibitors, defined as inhibitors that increased the AUC or decreased the clearance of probes of two or more P450s, were identified. Seventeen (45%) multi-P450 inhibitors were strong inhibitors of at least one P450, and an additional 12 (32%) were moderate inhibitors of one or more P450s. Only one inhibitor (fluvoxamine) was a strong inhibitor of more than one enzyme. Fifteen of the multi-P450 inhibitors also inhibit drug transporters in vivo, but such data are lacking on many of the inhibitors. Inhibition of multiple P450 enzymes by a single inhibitor resulted in significant (>2-fold) clinical DDIs with drugs that are cleared by multiple pathways such as imipramine and diazepam, while strong P450 inhibitors resulted in only weak DDIs with these object drugs. The magnitude of the DDIs between multi-P450 inhibitors and diazepam, imipramine, and omeprazole could be predicted using in vitro data with similar accuracy as probe substrate studies with the same inhibitors. The results of this study suggest that inhibition of multiple clearance pathways in vivo is clinically relevant, and the risk of DDIs with object drugs may be best evaluated in studies using multi-P450 inhibitors.

Antidepressants and the risk of sudden cardiac death and ventricular arrhythmia

PURPOSE

To examine the association between exposure to antidepressants and emergency department or inpatient admission for sudden cardiac death and ventricular arrhythmia (SD/VA), and to examine the impact of dose and cytochrome P-450 inhibition.

METHODS

A cohort study was conducted using 1999-2003 Medicaid claims data from beneficiaries of five large states, supplemented with Medicare claims for dually eligible individuals. Exposures were prescription claims for antidepressants of interest or a reference antidepressant. Outcomes were incident first-listed emergency department or principal inpatient diagnoses indicative of SD/VA originating in the outpatient setting, an outcome previously found to have a positive predictive value of 85%.

RESULTS

In 1.3 million person-years of antidepressant exposure, we identified 4222 SD/VA outcomes for a rate of 3.3/1000 person-years (95%CI, 3.2-3.4). Compared with paroxetine (a referent with a putatively favorable cardiovascular risk profile), adjusted hazard ratios (HRs) were 0.80 (0.67-0.95) for bupropion, 1.24 (0.93-1.65) for doxepin, 0.79 (0.55-1.15) for lithium, and 1.26 (1.11-1.42) for mirtazapine. HRs for amitriptyline, citalopram, fluoxetine, nefazodone, nortriptyline, sertraline, trazodone, and venlafaxine were near unity. For antidepressants having nonnull risks (bupropion and mirtazapine), we observed no relationship with antidepressant dose and some relationships with concomitant cytochrome P-450 inhibition.

CONCLUSIONS

Of antidepressants studied, only mirtazapine had a statistically significantly greater SD/VA risk versus paroxetine. However, baseline differences between these users suggest that this finding may be attributable to residual confounding. Eleven other antidepressants had SD/VA risks no greater than that of paroxetine, thereby providing reassurance regarding the comparative cardiovascular safety of antidepressants.

Therapeutic management of allergic diseases

Allergic diseases are characterized by the activation of inflammatory cells and by a massive release of mediators. The aim of this chapter was to describe succinctly the modes of action, indications, and side effects of the major antiallergic and antiasthmatic drugs. When considering the ideal pharmacokinetic characteristics of a drug, a poorly metabolized drug may confer a lower variability in plasma concentrations and metabolism-based drug interactions, although poorly metabolized drugs may be prone to transporter-based disposition and interactions. The ideal pharmacological properties of a drug include high binding affinity, high selectivity, and appropriate association and dissociation rates. Finally, from a patient perspective, the frequency and route of administration are important considerations for ease of use.

Interaction study of the combined use of paroxetine and fosamprenavir-ritonavir in healthy subjects

Human immunodeficiency virus-infected patients have an increased risk for depression. Despite the high potential for drug-drug interactions, limited data on the combined use of antidepressants and antiretrovirals are available. Theoretically, ritonavir-boosted protease inhibitors may inhibit CYP2D6-mediated metabolism of paroxetine. We wanted to determine the effect of fosamprenavir-ritonavir on paroxetine pharmacokinetics and vice versa and to evaluate the safety of the combination. Group A started with 20 mg paroxetine every day for 10 days; after a wash-out period of 16 days, subjects received paroxetine (20 mg every day) plus fosamprenavir-ritonavir (700/100 mg twice a day) from days 28 to 37. Group B received the regimens in reverse order. On days 10 and 37, pharmacokinetic curves were recorded. Twenty-six healthy subjects (18 females, 8 males) were included. Median (range) age and weight were 44.4 (18.2 to 64.3) years and 68.8 (51.0 to 89.4) kg. Three subjects were excluded (two because of adverse events; one for nonadherence). Addition of fosamprenavir-ritonavir to paroxetine resulted in a significant decrease in paroxetine exposure: the geometric mean ratios (90% confidence intervals) of paroxetine plus fosamprenavir-ritonavir to paroxetine alone were 0.45 (0.41 to 0.49) for the area under the concentration-time curve from 0 to 24 h (AUC(0-24)), 0.49 (0.45 to 0.53) for the maximum concentration of the drug in plasma (C(max)), and 0.75 (0.71 to 0.80) for the apparent elimination half-life (t(1/2)). The free fraction of paroxetine showed a median (interquartile range) increase of 30% (18 to 42%) after the addition of fosamprenavir-ritonavir. The AUC(0-12), C(max), C(min), and t(1/2) of amprenavir and ritonavir were similar to those of historical controls. No serious adverse events occurred. Fosamprenavir-ritonavir reduced total paroxetine exposure by 55%. This is partly explained by protein displacement of paroxetine. We think that this interaction is clinically relevant and that titration to a higher dose of paroxetine may be necessary to accomplish the needed antidepressant effect.

Clinical Pharmacokinetics of Atomoxetine

Atomoxetine (Strattera, a potent and selective inhibitor of the presynaptic norepinephrine transporter, is used clinically for the treatment of attention-deficit hyperactivity disorder (ADHD) in children, adolescents and adults. Atomoxetine has high aqueous solubility and biological membrane permeability that facilitates its rapid and complete absorption after oral administration. Absolute oral bioavailability ranges from 63 to 94%, which is governed by the extent of its first-pass metabolism. Three oxidative metabolic pathways are involved in the systemic clearance of atomoxetine: aromatic ring-hydroxylation, benzylic hydroxylation and N-demethylation. Aromatic ring-hydroxylation results in the formation of the primary oxidative metabolite of atomoxetine, 4-hydroxyatomoxetine, which is subsequently glucuronidated and excreted in urine. The formation of 4-hydroxyatomoxetine is primarily mediated by the polymorphically expressed enzyme cytochrome P450 (CYP) 2D6. This results in two distinct populations of individuals: those exhibiting active metabolic capabilities (CYP2D6 extensive metabolisers) and those exhibiting poor metabolic capabilities (CYP2D6 poor metabolisers) for atomoxetine. The oral bioavailability and clearance of atomoxetine are influenced by the activity of CYP2D6; nonetheless, plasma pharmacokinetic parameters are predictable in extensive and poor metaboliser patients. After single oral dose, atomoxetine reaches maximum plasma concentration within about 1-2 hours of administration. In extensive metabolisers, atomoxetine has a plasma half-life of 5.2 hours, while in poor metabolisers, atomoxetine has a plasma half-life of 21.6 hours. The systemic plasma clearance of atomoxetine is 0.35 and 0.03 L/h/kg in extensive and poor metabolisers, respectively. Correspondingly, the average steady-state plasma concentrations are approximately 10-fold higher in poor metabolisers compared with extensive metabolisers. Upon multiple dosing there is plasma accumulation of atomoxetine in poor metabolisers, but very little accumulation in extensive metabolisers. The volume of distribution is 0.85 L/kg, indicating that atomoxetine is distributed in total body water in both extensive and poor metabolisers. Atomoxetine is highly bound to plasma albumin (approximately 99% bound in plasma). Although steady-state concentrations of atomoxetine in poor metabolisers are higher than those in extensive metabolisers following administration of the same mg/kg/day dosage, the frequency and severity of adverse events are similar regardless of CYP2D6 phenotype.Atomoxetine administration does not inhibit or induce the clearance of other drugs metabolised by CYP enzymes. In extensive metabolisers, potent and selective CYP2D6 inhibitors reduce atomoxetine clearance; however, administration of CYP inhibitors to poor metabolisers has no effect on the steady-state plasma concentrations of atomoxetine.

Metabolic drug interactions with new psychotropic agents

New psychotropic drugs introduced in clinical practice in recent years include new antidepressants, such as selective serotonin reuptake inhibitors (SSRI) and 'third generation' antidepressants, and atypical antipsychotics, i.e. clozapine, risperidone, olanzapine, quetiapine, ziprasidone and amisulpride. These agents are extensively metabolized in the liver by cytochrome P450 (CYP) enzymes and are therefore susceptible to metabolically based drug interactions with other psychotropic medications or with compounds used for the treatment of concomitant somatic illnesses. New antidepressants differ in their potential for metabolic drug interactions. Fluoxetine and paroxetine are potent inhibitors of CYP2D6, fluvoxamine markedly inhibits CYP1A2 and CYP2C19, while nefazodone is a potent inhibitor of CYP3A4. These antidepressants may be involved in clinically significant interactions when coadministered with substrates of these isoforms, especially those with a narrow therapeutic index. Other new antidepressants including sertraline, citalopram, venlafaxine, mirtazapine and reboxetine are weak in vitro inhibitors of the different CYP isoforms and appear to have less propensity for important metabolic interactions. The new atypical antipsychotics do not affect significantly the activity of CYP isoenzymes and are not expected to impair the elimination of other medications. Conversely, coadministration of inhibitors or inducers of the CYP isoenzymes involved in metabolism of the various antipsychotic compounds may alter their plasma concentrations, possibly leading to clinically significant effects. The potential for metabolically based drug interactions of any new psychotropic agent may be anticipated on the basis of knowledge about the CYP enzymes responsible for its metabolism and about its effect on the activity of these enzymes. This information is essential for rational prescribing and may guide selection of an appropriate compound which is less likely to interact with already taken medication(s).

Effect of potent CYP2D6 inhibition by paroxetine on atomoxetine pharmacokinetics

The purpose of this study was to characterize the effect of potent CYP2D6 inhibition byparoxetine on atomoxetine disposition in extensive metabolizers. This was a single-blind, two-period, sequential studyin 22 healthy individuals. In period 1, 20 mg atomoxetine bid was administered to steady state. In period 2, 20 mg paroxetine was administered qd for 17 days. On days 12 through 17, 20 mg atomoxetine bid were coadministered. Plasma pharmacokinetics of atomoxetine, 4-hydroxyatomoxetine, and N-desmethylatomoxetine was determined at steady state in each treatment period. Plasma pharmacokinetics of paroxetine were determined after the 11th and 17th doses. Paroxetine increased C(ss,max), AUC0-12, and t1/2 of atomoxetine by approximately 3.5-, 6.5-, and 2.5-fold, respectively. After coadministration with paroxetine, increases in N-desmethylatomoxetine and decreases in 4-hydroxyatomoxetine concentrations were observed. No changes in paroxetine pharmacokinetics were observed after coadministration with atomoxetine. It was concluded that inhibition of CYP2D6 by paroxetine markedly affected atomoxetine disposition, resulting in pharmacokinetics similar to poor metabolizers of CYP2D6 substrates.

Evaluation of drug-induced QT interval prolongation: implications for drug approval and labelling

Assessment of proarrhythmic toxicity of newly developed drugs attracts significant attention from drug developers and regulatory agencies. Although no guidelines exist for such assessment, the present experience allows several key suggestions to be made and an appropriate technology to be proposed. Several different in vitro and in vitro preclinical models exist that, in many instances, correctly predict the clinical outcome. However, the correspondence between different preclinical models is not absolute. None of the available models has been demonstrated to be more predictive and/or superior to others. Generally, compounds that do not generate any adverse preclinical signal are less likely to lead to cardiac toxicity in humans. Nevertheless, differences in likelihood offer no guarantee compared with entities with a preclinical signal. Thus, the preclinical investigations lead to probabilistic answers with the possibility of both false positive and false negative findings. Clinical assessment of drug-induced QT interval prolongation is crucially dependent on the quality of electrocardiographic data and the appropriateness of electrocardiographic analyses. An integral part of this is a precise heart rate correction of QT interval, which has been shown to require the assessment of QT/RR relationship in each study individual. The numbers of electrocardiograms required for such an assessment are larger than usually obtained in pharmacokinetic studies. Thus, cardiac safety considerations need to be an integral part of early phase I/II studies. Once proarrhythmic safety has been established in phase I/II studies, large phase III studies and postmarketing surveillance can be limited to less strict designs. The incidence of torsade de pointes tachycardia varies from 1 to 5% with clearly proarrhythmic drugs (e.g. quinidine) to 1 in hundreds of thousands with drugs that are still considered unsafe (e.g. terfenadine, cisapride). Thus, not recording any torsade de pointes tachycardia during large phase III studies offers no guarantee, and the clinical premarketing evaluation has to rely on the assessment of QT interval changes. However, since QT interval prolongation is only an indirect surrogate of predisposition to the induction of torsade de pointes tachycardia, any conclusion that a drug is safe should be reserved until postmarketing surveillance data are reviewed. The area of drug-related cardiac proarrhythmic toxicity is fast evolving. The academic perspective includes identification of markers more focused compared with simple QT interval measurement, as well as identification of individuals with an increased risk of torsade de pointes. The regulatory perspective includes careful adaptation of new research findings.

Drug interactions with cisapride: clinical implications

Cisapride, a prokinetic agent, has been used for the treatment of a number of gastrointestinal disorders, particularly gastro-oesophageal reflux disease in adults and children. Since 1993, 341 cases of ventricular arrhythmias, including 80 deaths, have been reported to the US Food and Drug Administration. Marketing of the drug has now been discontinued in the US; however, it is still available under a limited-access protocol. Knowledge of the risk factors for cisapride-associated arrhythmias will be essential for its continued use in those patients who meet the eligibility criteria. This review summarises the published literature on the pharmacokinetic and pharmacodynamic interactions of cisapride with concomitantly administered drugs, providing clinicians with practical recommendations for avoiding these potentially fatal events. Pharmacokinetic interactions with cisapride involve inhibition of cytochrome P450 (CYP) 3A4, the primary mode of elimination of cisapride, thereby increasing plasma concentrations of the drug. The macrolide antibacterials clarithromycin, erythromycin and troleandomycin are inhibitors of CYP3A4 and should not be used in conjunction with cisapride. Azithromycin is an alternative. Similarly, azole antifungal agents such as fluconazole, itraconazole and ketoconazole are CYP3A4 inhibitors and their concomitant use with cisapride should be avoided. Of the antidepressants nefazodone and fluvoxamine should be avoided with cisapride. Data with fluoxetine is controversial, we favour the avoidance of its use. Citalopram, paroxetine and sertraline are alternatives. The HIV protease inhibitors amprenavir, indinavir, nelfinavir, ritonavir and saquinavir inhibit CYP3A4. Clinical experience with cisapride is lacking but avoidance with all protease inhibitors is recommended, although saquinavir is thought to have clinically insignificant effects on CYP3A4. Delavirdine is also a CYP3A4 inhibitor and should be avoided with cisapride. We also recommend avoiding coadministration of cisapride with amiodarone, cimetidine (alternatives are famotidine, nizatidine, ranitidine or one of the proton pump inhibitors), diltiazem and verapamil (the dihydropyridine calcium antagonists are alternatives), grapefruit juice, isoniazid, metronidazole, quinine, quinupristin/dalfopristin and zileuton (montelukast is an alternative). Pharmacodynamic interactions with cisapride involve drugs that have the potential to have additive effects on the QT interval. We do not recommend use of cisapride with class Ia and III antiarrhythmic drugs or with adenosine, bepridil, cyclobenzaprine, droperidol, haloperidol, nifedipine (immediate release), phenothiazine antipsychotics, tricyclic and tetracyclic antidepressants or vasopressin. Vigilance is advised if anthracyclines, cotrimoxazole (trimethoprim-sulfamethoxazole), enflurane, halothane, isoflurane, pentamidine or probucol are used with cisapride. In addition, uncorrected electrolyte disturbances induced by diuretics may increase the risk of torsade de pointes. Patients receiving cisapride should be promptly treated for electrolyte disturbances.

Debate resolved: there are differential effects of serotonin selective reuptake inhibitors on cytochrome P450 enzymes

In 1993, it was first proposed that an important difference between selective serotonin reuptake inhibitors (SSRIs) was the degree of inhibition of the cytochrome P450 (CYP) enzyme 2D6 that they produced under usually dosing conditions (Preskorn, 1993). Specifically, fluoxetine and paroxetine, in contrast to sertraline, were identified as causing substantial increases in the plasma levels of coadministered drugs, which were principally dependent on CYP 2D6 for their metabolism. Over the next 5 years, this position was hotly contested (Preskorn and Nemeroff, 1997). However, an extensive body of research has now accumulated, which incontrovertibly supports the original position. This paper will reviews this research and extends the discussion to all five SSRIs and four other important CYP enzymes: 1A2, 2C9/10, 2C19, and 3A3/4.