Effect of fluvoxamine on the pharmacokinetics of quinidine

Assessment of Quinidine-Induced Torsades de Pointes Risks Using a Whole-Body Physiologically Based Pharmacokinetic Model Linked to Cardiac Ionic Current Inhibition

The lethality of torsades de pointes (TdP) by drugs is one of main reasons that some drugs were withdrawn from the market. In order to assess drug-induced TdP risks, a model of cardiac ionic current suppression in human ventricular myocytes (ToR-ORd model), combined with the maximum effective free therapeutic plasma concentration or the maximum effective free therapeutic myocyte concentration was often used, with the latter proved to be more relevant and more accurate. We aimed to develop a whole-body physiologically-based pharmacokinetic (PBPK) model, incorporated with a human cardiomyocyte pharmacodynamic (PD) model, to provide a comprehensive assessment of drug-induced TdP risks in normal and specific scenarios. Quinidine served as an example to validate the PBPK-PD model via predicting plasma quinidine concentrations and quinidine-induced changes in QT interval (ΔQTc). The predicted plasma quinidine concentrations and ΔQTc values following oral administration or intravenous administration of quinidine were comparable to clinic observations. Visual predictive checks showed that most of the observed plasma concentrations and ΔQTc values fell within the 5th and 95th percentiles of simulations. The validated PBPK-PD model was further applied to assess the TdP risks using frequencies of early afterdepolarization and long-QT syndrome occurrence in 4 scenarios, such as therapeutic dose, supra-therapeutic dose, alkalosis, and hyperkalemia in 200 human subjects. In conclusion, the developed PBPK-PD model may be applied to predict the quinidine pharmacokinetics and quinidine-induced TdP risks in healthy subjects, but also simulate quinidine-induced TdP risks under disease conditions, such as hypokalemia and alkalosis.

Physiologically-based pharmacokinetic modeling of quinidine to establish a CYP3A4, P-gp, and CYP2D6 drug-drug-gene interaction network

The antiarrhythmic agent quinidine is a potent inhibitor of cytochrome P450 (CYP) 2D6 and P-glycoprotein (P-gp) and is therefore recommended for use in clinical drug-drug interaction (DDI) studies. However, as quinidine is also a substrate of CYP3A4 and P-gp, it is susceptible to DDIs involving these proteins. Physiologically-based pharmacokinetic (PBPK) modeling can help to mechanistically assess the absorption, distribution, metabolism, and excretion processes of a drug and has proven its usefulness in predicting even complex interaction scenarios. The objectives of the presented work were to develop a PBPK model of quinidine and to integrate the model into a comprehensive drug-drug(-gene) interaction (DD(G)I) network with a diverse set of CYP3A4 and P-gp perpetrators as well as CYP2D6 and P-gp victims. The quinidine parent-metabolite model including 3-hydroxyquinidine was developed using pharmacokinetic profiles from clinical studies after intravenous and oral administration covering a broad dosing range (0.1-600 mg). The model covers efflux transport via P-gp and metabolic transformation to either 3-hydroxyquinidine or unspecified metabolites via CYP3A4. The 3-hydroxyquinidine model includes further metabolism by CYP3A4 as well as an unspecific hepatic clearance. Model performance was assessed graphically and quantitatively with greater than 90% of predicted pharmacokinetic parameters within two-fold of corresponding observed values. The model was successfully used to simulate various DD(G)I scenarios with greater than 90% of predicted DD(G)I pharmacokinetic parameter ratios within two-fold prediction success limits. The presented network will be provided to the research community and can be extended to include further perpetrators, victims, and targets, to support investigations of DD(G)Is.

Physiologically-Based Pharmacokinetic Modeling Approach to Predict Rifampin-Mediated Intestinal P-Glycoprotein Induction

Physiologically‐based pharmacokinetic (PBPK) modeling is a powerful tool to quantitatively describe drug disposition profiles in vivo, thereby providing an alternative to predict drug–drug interactions (DDIs) that have not been tested clinically. This study aimed to predict effects of rifampin‐mediated intestinal P‐glycoprotein (Pgp) induction on pharmacokinetics of Pgp substrates via PBPK modeling. First, we selected four Pgp substrates (digoxin, talinolol, quinidine, and dabigatran etexilate) to derive in vitro to in vivo scaling factors for intestinal Pgp kinetics. Assuming unbound Michaelis‐Menten constant (K_m) to be intrinsic, we focused on the scaling factors for maximal efflux rate (J_max) to adequately recover clinically observed results. Next, we predicted rifampin‐mediated fold increases in intestinal Pgp abundances to reasonably recover clinically observed DDI results. The modeling results suggested that threefold to fourfold increases in intestinal Pgp abundances could sufficiently reproduce the DDI results of these Pgp substrates with rifampin. Hence, the obtained fold increases can potentially be applicable to DDI prediction with other Pgp substrates.

Simulations of Cytochrome P450 3A4-Mediated Drug-Drug Interactions by Simple Two-Compartment Model-Assisted Static Method

In order to predict cytochrome P450 3A4 (CYP3A4)-mediated drug-drug interactions (DDIs), a simple 2-compartment model-assisted, overall inhibition activity (A_i,overall) method was derived based on 2 concepts. One concept was that the increase in blood victim level and fold increase in the area under the blood victim level curve produced by DDI are determined entirely by A_i,overall, the hepatic availability of the victim and fraction of urinary excreted unchanged victim, where A_i,overall is determined by the perpetrator-specific CYP isoform inhibition activities (A_i,CYPs, DDI predictor-1) and victim-specific fractional CYP isoform contributions (f_m,CYPs, predictor-2). The other concept was that a DDI can be bridged to other DDIs, so that any possible DDI produced by a given victim or a given perpetrator can be predicted by using these predictors. The A_i,CYP3A4s of 12 common CYP3A4 inhibitors were able to be determined and shown to be useful for the prediction of CYP3A4-mediated DDIs wherein victims were metabolized by multiple CYP isoforms. Additionally, it was demonstrated that f_m,CYP values with high confidence can be estimated by bridging DDIs produced by the same victim and different perpetrators. This bridging approach will accelerate prediction of DDIs produced by new chemical entities from the existing DDI database.

The relationship between clinical pharmacokinetics of aripiprazole and CYP2D6 genetic polymorphism: effects of CYP enzyme inhibition by coadministration of paroxetine or fluvoxamine

Purpose

To investigate the effects of coadministration of paroxetine or fluvoxamine on the pharmacokinetics of aripiprazole in healthy adult Japanese with different CYP2D6 genotypes.

Methods

Fourteen CYP2D6 extensive metabolizer (EM) and 14 CYP2D6 intermediate metabolizer (IM) subjects were coadministered a single oral dose of aripiprazole 3 mg after steady-state plasma concentrations of the SSRIs paroxetine (20 mg/day) or fluvoxamine (100 mg/day) were reached by repeated oral doses for 6–7 days. The pharmacokinetics of aripiprazole with and without coadministration of SSRIs were compared according to CYP2D6 genotypes.

Results

Coadministration of paroxetine, a potent CYP2D6 inhibitor, decreased systemic clearance (CL/F) of aripiprazole by 58 and 23% in CYP2D6 EMs and IMs, respectively, demonstrating that the percentage inhibition of CYP2D6 activity by coadministration of paroxetine was apparently greater in CYP2D6 EMs than in IMs. Coadministration of fluvoxamine, a less potent CYP3A4 inhibitor, decreased the CL/F of aripiprazole by 39% in CYP2D6 EMs and 40% in IMs, indicating the same inhibitory effect on CYP enzymes, regardless of the CYP2D6 genotype. Percent contribution of CYP2D6 to total CL/F (CYP2D6 plus CYP3A4) of aripiprazole estimated as a reduced percentage of CL/F by CYP enzyme inhibition was 62% for CYP2D6 EMs and 24% for IMs in paroxetine coadministration, and 40% for CYP2D6 EMs and 18% for IMs in fluvoxamine coadministration.

Conclusions

There were marked differences in the degree of influence of paroxetine coadministration on the pharmacokinetics of aripiprazole between CYP2D6 EMs and IMs, but no apparent differences were found between two CYP2D6 genotypes in fluvoxamine coadministration. Aripiprazole can be used safely in combination with SSRIs that have a CYP enzyme-inhibitory action.

Clinically relevant drug interactions between anticancer drugs and psychotropic agents

Drug interactions are commonly seen in the treatment of cancer patients. Psychotropics are often indicated for these patients since they may also suffer from pre-existing psychological disorders or experience insomnia and anxiety associated with cancer therapy. Thus, the risk of anticancer drug (ACD)-psychotropic drug-drug interactions (DDIs) is high. Drug interactions were compiled from the British National Formulary (53rd edn), Lexi-Comp's Drug Information Handbook (15th edn), Micromedex (v5.1), Hansten & Horn's Drug Interactions (2000) and Drug Interaction Facts (2008 edn). Product information of the individual drugs, as well as documented literature on ACD-psychotropic interactions from PubMed and other databases was also incorporated. This paper identifies clinically important ACD-psychotropic DDIs that are frequently observed. Pharmacokinetic DDIs were observed for tyrosine kinase inhibitors, corticosteroids and antimicrotubule agents due to their inhibitory or inductive effects on cytochrome P450 isoenzymes. Pharmacodynamic DDIs were identified for thalidomide with central nervous system depressants, procarbazine with antidepressants, myelosuppressive ACDs with clozapine and anthracyclines with QT-prolonging psychotropics. Clinicians should be vigilant when psychotropics are prescribed concurrently with ACDs. Close monitoring of plasma drug levels should be carried out to avoid toxicity in the patient, as well as to ensure adequate chemotherapeutic and psychotropic coverage.

Potential role of intestinal first-pass metabolism in the prediction of drug-drug interactions

BACKGROUND

The contribution of intestine to the magnitude of drug-drug interactions (DDI) may be significant, considering high levels of inhibitors in the gut lumen achieved during absorption and the abundance of metabolic enzymes in the mature enterocytes. Intestinal inhibition is incorporated in the DDI prediction models as the ratio of the intestinal wall availability in the presence and absence of the inhibitor (F(G)(') and F(G), respectively).

OBJECTIVE

This review will focus on the ability of the current approaches to estimate the extent of intestinal DDI accurately, addressing predominantly the most abundant intestinal P450 enzyme, CYP3A4.

METHODS

Considering the sensitivity of the DDI prediction models to the accuracy of the F(G) estimates, the current study focuses on 3 different in vitro and in vivo approaches to assess this parameter.

RESULTS/CONCLUSION

The advantages and limitations of each of F(G) methods are outlined. Accurate assessment of this parameter is essential for the prediction of human drug clearance and drug-drug interaction potential.

Intestinal and Hepatic Metabolic Activity of Five Cytochrome P450 Enzymes: Impact on Prediction of First-Pass Metabolism

The contribution of the gut is not routinely incorporated into in vitro-in vivo predictions of either clearance or drug-drug interactions, and this omission may partially explain the general underprediction trend often observed. In the current study, the metabolic ability of hepatic and intestinal pooled microsomes was compared for eight CYP3A substrates (midazolam, triazolam, diazepam, alprazolam, flunitrazepam, nifedipine, testosterone, and quinidine) and paclitaxel, tolbutamide, S-mephenytoin, and bufuralol as CYP2C8, CYP2C9, CYP2C19, and CYP2D6 probes, respectively. A general agreement in the type of kinetics was observed between the two systems for the substrates investigated. Of the 16 pathways investigated, 75% of K(m) (S(50)) values obtained in intestinal microsomes (5.9-769 microM) were within 2-fold of hepatic estimates. Irrespective of the cytochrome P450 (P450) investigated and normalization of V(max) values for the P450 abundance, clearance was 4.5- to 50-fold lower in intestinal microsomes (0.0005-0.51 microl/min/P450) compared with the hepatic estimates (0.002-5.8 microl/min/P450), whereas the rank order was consistent between the systems. Assessment of two enterocyte isolation methods (mucosal scraping or enterocyte elution) was performed at the substrate concentrations corresponding to the determined V(max) conditions for 11 pathways. The activity difference between the methods (3-29-fold) was P450-related in the following rank order: CYP2C19 > CYP3A4 > CYP2C9 approximately CYP2D6. After correction for the loss of activity between the methods, the intrinsic activities of hepatic and intestinal CYP3A4, CYP2C9, CYP2C19, and CYP2D6 were comparable for the 16 pathways. The implications of these findings on the prediction of intestinal first-pass metabolism are discussed.

PREDICTION OF TIME-DEPENDENT CYP3A4 DRUG-DRUG INTERACTIONS: IMPACT OF ENZYME DEGRADATION, PARALLEL ELIMINATION PATHWAYS, AND INTESTINAL INHIBITION

Time-dependent inhibition of CYP3A4 often results in clinically significant drug-drug interactions. In the current study, 37 in vivo cases of irreversible inhibition were collated, focusing on macrolides (erythromycin, clarithromycin, and azithromycin) and diltiazem as inhibitors. The interactions included 17 different CYP3A substrates showing up to a 7-fold increase in AUC (13.5% of studies were in the range of potent inhibition). A systematic analysis of the impact of CYP3A4 degradation half-life (mean t1/2deg = 3 days, ranging from 1 to 6 days) on the prediction of the extent of interaction for compounds with a differential contribution from CYP3A4 to the overall elimination (defined by fmCYP3A4) was performed. Although the prediction accuracy was very sensitive to the CYP3A4 degradation rate for substrates mainly eliminated by this enzyme fm(CYP3A4 >or= 0.9), minimal effects are observed when CYP3A4 contributes less than 50% to the overall elimination in cases when the parallel elimination pathway is not subject to inhibition. Use of the mean CYP3A4 t1/2deg (3 days), average unbound systemic plasma concentration of the inhibitor, and the corresponding fm(CYP3A4) resulted in 89% of studies predicted within 2-fold of the in vivo value. The impact of the interaction in the gut wall was assessed by assuming maximal intestinal inhibition of CYP3A4. Although a reduced number of false-negative predictions was observed, there was an increased number of overpredictions, and generally, a loss of prediction accuracy was observed. The impact of the possible interplay between CYP3A4 and efflux transporters on the intestinal interaction requires further evaluation.

Some Aspects of Genetic Polymorphism in the Biotransformation of Antidepressants

Tricyclic antidepressants are all hydroxylated by cytochrome P450 (CYP) 2D6, but the tertiary amines, amitriptyline, clomipramine and imipramine, are also N-demethylated to the active metabolites, nortriptyline, N-desmethylclomipramine and desipramine, by several CYPs, including the polymorphic CYP2C19, CYP1A2 and CYP3A4. The five selective serotonin reuptake inhibitors, citalopram, fluoxetine, fluvoxamine, paroxetine and sertraline are also oxidised by the CYP enzyme system. Thus, fluoxetine, fluvoxamine and paroxetine are partially metabolised by CYP2D6, citalopram by CYP2C19 and sertraline by at least five different CYPs. Paroxetine and fluoxetine are very potent inhibitors of CYP2D6 while citalopram, fluvoxamine and sertraline are moderate inhibitors of this enzyme. Fluvoxamine is a potent inhibitor of CYP1A2 and CYP2C19 and a moderate inhibitor of CYP2C9. Since the termination of the human genome project, there is no longer a technical hindrance to the identification of all of the genes involved in the clinical response to antidepressants. Research in the future will involve modern technologies and new scientific disciplines, including DNA-micro-array technology and bioinformatics. The research ultimately aims at developing better and safer antidepressants and/or better and safer use of currently available antidepressants.

Toxicological interactions involving psychiatric drugs and alcohol: an update

This review focuses on the toxicological interactions between alcohol (ethanol) and psychiatric drugs (antidepressants and antipsychotics), including those leading to fatal poisoning. Acute or chronic ingestion of alcohol when combined with psychiatric drugs may lead to several clinically significant toxicological interactions. The metabolism of these drugs is generally but not always delayed by acute alcohol ingestion. Drugs undergoing metabolism may also show increased metabolic clearance with chronic alcohol ingestion. Therefore, the net effect may be influenced by internal (e.g. disease, age, gender), external (e.g. environment, diet) and pharmacokinetic (e.g. dose, timing of ingestion, gastrointestinal absorption, distribution and elimination) factors. Cases of fatal poisoning involving coadministration of psychiatric drugs, alcohol and other drugs prompted this review.

The Intestinal First-pass Metabolism of Substrates of CYP3A4 and P-glycoprotei—Quantitative Analysis Based on Information from the Literature

It is suggested that the bioavailability of CYP3A4 substrates might be low due to first-pass metabolism in the small intestine, and it is possible that P-glycoprotein (P-gp) may influence first-pass metabolism in a co-operative manner. We have collected information of the pharmacokinetics of CYP3A4 substrates to evaluate the fraction absorbed (Fa), intestinal availability (Fg) and hepatic availability (Fh) and have investigated the intestinal first-pass metabolism and the effect of P-gp on this. The pharmacokinetic data involved ten compounds metabolized by CYP3A4 in humans, with and without an inhibitor or inducer. FaFg, which is the product of Fa and Fg, and Fh were calculated using three liver blood flow rates (17.1, 21.4, 25.5 mL/min/kg) in consideration of variations in the liver flow rate. Co-administration with an inhibitor of CYP3A4 and treatment of an inducer of CYP3A4 caused an increase and decrease in the FaFg of CYP3A4 substrates, regardless of the liver blood flow, indicating that CYP3A4 substrates exhibit a first-pass effect in their metabolism. This holds true regardless of whether the compounds are P-gp substrates or not. No relationship was observed between FaFg and Fh, regardless of the hepatic blood flow rate and the P-gp substrates. The FaFg of both P-gp and non P-gp substrates decreased as the hepatic intrinsic clearance increased. FaFg was markedly reduced when the hepatic intrinsic clearance was more than 100 mL/min/kg. This in vivo intrinsic clearance corresponds to an in vitro intrinsic clearance of 78 muL/min/mg human hepatic microsomal protein, equivalent to a half-life of 8.9 min for the substrate in a commonly used metabolic stability test with human microsomes (1 mgMs protein/mL). This phenomenon was not observed in substrates of CYP isoforms other than CYP3A4. In conclusion, it is suggested that CYP3A4 substrates which have a hepatic intrinsic clearance of 100 mL/min/kg exhibit a low bioavailability due to intestinal first-pass metabolism, regardless of whether they are substrates of P-gp or not.

Cardiovascular drug-drug interactions

The drug-drug interactions discussed in this article have either documented or suspected clinical relevance for patients with cardiovascular disease and the clinician involved in the care of these patients. Oftentimes, drug-drug interactions are difficult, if not impossible, to predict because of the high degree of interpatient variability in drug disposition. Certain drug-drug interactions, however, may be avoided through knowledge and sound clinical judgment. Every clinician should maintain a working knowledge of reported drug-drug interactions and an understanding of basic pharmacokinetic and pharmacodynamic principles to help predict and minimize the incidence and severity of drug-drug interactions.

Effect of diclofenac, disulfiram, itraconazole, grapefruit juice and erythromycin on the pharmacokinetics of quinidine

AIMS

In vitro studies suggest that the oxidation of quinidine to 3-hydroxyquinidine is a specific marker reaction for CYP3A4 activity. To assess the possible use of this reaction as an in vivo marker of CYP3A4 activity, we studied the involvement of cytochromes CYP2C9, CYP2E1 and CYP3A4 in the in vivo oxidative metabolism of quinidine.

METHODS

An open study of 30 healthy young male volunteers was performed. The pharmacokinetics of a 200 mg single oral dose of quinidine was studied before and during daily administration of 100 mg diclofenac, a CYP2C9 substrate (n=6); 200 mg disulfiram, an inhibitor of CYP2E1 (n=6); 100 mg itraconazole, an inhibitor of CYP3A4 (n=6); 250 ml single strength grapefruit juice twice daily, an inhibitor of CYP3A4 (n=6); 250 mg of erythromycin 4 times daily, an inhibitor of CYP3A4 (n=6). Probes of other enzyme activities, caffeine (CYP1A2), sparteine (CYP2D6), mephenytoin (CYP2C19), tolbutamide (CYP2C9) and cortisol (CYP3A4) were also studied.

RESULTS

Concomitant administration of diclofenac reduced the partial clearance of quinidine by N-oxidation by 27%, while no effect was found for other pharmacokinetic parameters of quinidine. Concomitant administration of disulfiram did not alter any of the pharmacokinetic parameters of quinidine. Concomitant administration of itraconazole reduced quinidine total clearance, partial clearance by 3-hydroxylation and partial clearance by N-oxidation by 61, 84 and 73%, respectively. The renal clearance was reduced by 60% and the elimination half-life increased by 35%. Concomitant administration of grapefruit juice reduced the total clearance of quinidine and its partial clearance by 3-hydroxylation and N-oxidation by 15, 19 and 27%, respectively. The elimination half-life of quinidine was increased by 19%. The caffeine metabolic index was reduced by 25%. Concomitant administration of erythromycin reduced the total clearance of quinidine and its partial clearance by 3-hydroxylation and N-oxidation by 34, 50 and 33%, respectively. Cmax was increased by 39%.

CONCLUSIONS

The results confirm an important role for CYP3A4 in the oxidation of quinidine in vivo, and this applies particularly to the formation of 3-hydroxyquinidine. While a minor contribution of CYP2C9 to the N-oxidation of quinidine is possible, a major involvement of the CYP2C9 or CYP2E1 enzymes in the oxidation of quinidine in vivo is unlikely.