Clinical drug-drug interactions: focus on venlafaxine.

Drug Metab Pers Therap 2015; 30(1): 3–17

Review Paulo Magalhães, Gilberto Alves*, Adrián LLerena and Amílcar Falcão

Clinical drug-drug interactions: focus on venlafaxine Abstract: Venlafaxine (VEN) is an antidepressant agent widely used nowadays as an alternative to selective serotonin reuptake inhibitors (SSRIs), particularly for the treatment of SSRI-resistant depression. As the co-administration of antidepressant drugs with other medications is very common in clinical practice, the potential risk for pharmacokinetic and/or pharmacodynamic drug interactions that may be clinically meaningful increases. Bearing in mind that VEN has exhibited large variability in antidepressant response, besides the individual genetic background, several other factors may contribute to those variable clinical outcomes, such as the occurrence of significant drug-drug interactions. Indeed, the presence of drug interactions is possibly one of the major reasons for interindividual variability, and their anticipation should be considered in conjugation with other specific patients’ characteristics to optimize the antidepressant therapy. Hence, a comprehensive overview of the pharmacokinetic- and pharmacodynamic-based drug interactions involving VEN is herein provided, particularly addressing their clinical relevance. *Corresponding author: Gilberto Alves, PharmD, PhD, Faculty of Health Sciences, University of Beira Interior, CICS-UBI, Health Sciences Research Centre, University of Beira Interior, Av. Infante D. Henrique, 6200-506 Covilhã, Portugal, Phone: +351 275 329002, Fax: +351 275 329099, E-mail: [email protected] Paulo Magalhães: Faculty of Pharmacy, Laboratory of Pharmacology, University of Coimbra, Pólo das Ciências da Saúde, Azinhaga de Santa Comba, Coimbra, Portugal; Centre for Neuroscience and Cell Biology (CNC), University of Coimbra, Coimbra, Portugal; Health Sciences Research Centre, University of Beira Interior (CICS-UBI), Covilhã, Portugal; and Clinical Research Centre (CICAB), Extremadura University Hospital and Medical School, Badajoz, Spain Gilberto Alves: Centre for Neuroscience and Cell Biology (CNC), University of Coimbra, Coimbra, Portugal; and Health Sciences Research Centre, University of Beira Interior (CICS-UBI), Covilhã, Portugal Adrián LLerena: Clinical Research Centre (CICAB), Extremadura University Hospital and Medical School, Badajoz, Spain Amílcar Falcão: Faculty of Pharmacy, Laboratory of Pharmacology, University of Coimbra, Pólo das Ciências da Saúde, Azinhaga de Santa Comba, Coimbra, Portugal; and Centre for Neuroscience and Cell Biology (CNC), University of Coimbra, Coimbra, Portugal

Keywords: drug-drug interactions; pharmacodynamics; pharmacokinetics; venlafaxine. DOI 10.1515/dmdi-2014-0011 Received February 24, 2014; accepted May 1, 2014; previously published online June 18, 2014

Introduction Antidepressants are a class of drugs of major importance within the current pharmacotherapeutic armamentarium. The growing prevalence of depressive disorders in modern societies has led to a dramatic increase in the prescription of antidepressant agents over the last years [1]. Moreover, some newer antidepressants have demonstrated clinical utility in the treatment of psychiatric disorders other than depression (e.g., generalized anxiety disorder, panic disorder, obsessive-compulsive disorder, posttraumatic stress disorder, and eating disorders) [2, 3], as well as in non-psychiatric conditions (e.g., neuropathic pain, fibromyalgia, migraine, overactive bladder syndrome, and irritable bowel syndrome) [4]. Hence, antidepressant drugs are frequently used in co-therapy with other medications required for the management of psychiatric co-morbidities and/or somatic health conditions. Furthermore, depression normally requires extended periods of treatment and, thereby, the likelihood of co-administration of antidepressants with other drugs is high. Also, the concomitant use of specific drugs such as lithium, atypical antipsychotics, and thyroid hormones has been sometimes recommended to enhance the therapeutic response in cases of pharmacoresistant depression. Thus, bearing in mind such aforementioned aspects, antidepressant drugs are likely to be involved in clinically important drug-drug interactions. In addition to all this, it must also be considered that the increased prevalence of depression in the elderly leads to antidepressant drugs being often added to complex polytherapy regimens. As polypharmacy significantly enhances the risk for drug interactions, there is a great potential for the occurrence of clinically relevant

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4 Magalhães et al.: Clinical drug interactions: venlafaxine drug-drug interactions in elderly persons also involving antidepressant agents [5–7]. Thereby, one way to improve antidepressant therapy is to understand in detail the drug interaction profiles and the underlying interaction mechanisms, discriminating between those drug interactions that are clinically meaningful (even in specific subpopulations) from those that are not. Obviously, not all drug interactions have a negative impact on the therapeutic results, and some of them may even be intentionally triggered as a strategy for therapeutic optimization [8]. Nevertheless, several factors may increase the potential for drug interactions and even determine its clinical relevance. Besides co-medication and polytherapy, other factors such as particular physiological conditions (e.g., pregnancy or aging), genetic background (e.g., poor metabolizers or extensive metabolizers), and disease states (e.g., hepatic and renal impairment) can play a substantial role in the clinical outcome of a particular drug-drug interaction [5–7]. In fact, a dramatic growth of antidepressants use, mainly due to the increased prescribing of selective serotonin reuptake inhibitors (SSRIs) and serotonin-noradrenaline reuptake inhibitors (SNRIs), has been verified [9]. Effectively, venlafaxine (VEN) has emerged as a successful SNRI antidepressant in the post-SSRI period [10]. However, recent studies have shown that 50% of depressive patients do not respond to the first pharmacotherapeutic option and approximately one-third do not reach clinical remission of symptoms after being tested with multiple antidepressants [11]. Although this is not always easily demonstrated, the unsuccessful outcomes achieved in many of those patients may be related to drug-drug interactions [5, 12]. Considering that VEN has been related with a high fatal toxicity index (deaths in proportion to drug consumption) and, in turn, the fatal episodes of VEN poisonings have been associated with a high prevalence of drug-drug interactions [13], the present review was prepared aiming at gathering the documented clinical data on pharmacokinetic- and pharmacodynamic-based drug interactions involving VEN. The clinical significance of such drug-drug interactions was also herein critically discussed, underlining the need to consider in an integrated manner the available data about genotype/phenotype relations and drug-drug interactions toward the achievement of better therapeutic outcomes through a personalized medicine approach. The literature search was conducted in MEDLINE database (via PubMed), and it was focused on the available clinical data from clinical trials, case reports, and review articles published in English until September 2013,

using the search terms “venlafaxine”, “SNRIs”, “drug interactions”, “pharmacokinetics”, “cytochrome P450”, “P-glycoprotein”, “induction”, “inhibition”, “pharmacodynamics”, and “clinical relevance”; in this context, it should be noted that only articles published in peerreviewed journals were included. Additional data were also obtained from the PubChem database, the cytochrome P450 drug interaction database of the Indiana University, and the summary of product characteristics of the drug (VEN).

VEN: a pharmacological overview VEN was the first SNRI antidepressant introduced in the market for the treatment of depression and anxiety disorders, being one of the antidepressant agents most commonly prescribed nowadays [10]. From the pharmacodynamic point of view, VEN essentially acts as a serotonin reuptake inhibitor under low daily doses (75 mg/day), and becomes a dual-acting antidepressant under a daily dose of > 150 mg/day. Indeed, VEN is more potent as a serotonin reuptake inhibitor than as a noradrenaline reuptake inhibitor [5, 14–16]. Additionally, VEN is also a weak inhibitor of dopamine reuptake; however, it does not inhibit monoamine oxidase and has no significant affinity for α1-adrenergic, muscarinic cholinergic, H1 histaminergic, benzodiazepine, or opioid receptors [5, 17]. As a result, VEN has a low potential to cause anticholinergic and orthostatic hypotensive adverse effects, as well as sedation or weight gain. However, this drug may suppress the rapid eye movement sleep and increase the wake time; however, particularly important, VEN may elevate blood pressure [10, 17]. In terms of pharmacokinetics, VEN is extensively absorbed after oral administration (at least 92% of a single dose) and significantly distributed through the body (6–7 L/kg) [6, 18]. The plasma protein binding of VEN and its main metabolite O-desmethylvenlafaxine (ODV), also referred as desvenlafaxine (Figure 1), is low (27% and 30%, respectively). Hence, the occurrence of VEN drug interactions at the level of plasma protein binding is unlikely [18, 23]. However, VEN and ODV are P-glycoprotein (P-gp) substrates and, contrary to ODV, VEN is also a P-gp inducer [12, 24–27]. As P-gp is expressed in the intestinal epithelium and brain vascular endothelium, differences in the P-gp-mediated drug efflux transport can influence the oral bioavailability and the distribution into the brain (biophase) of VEN and ODV, and consequently, the therapeutic outcomes (efficacy vs. adverse effects) [12, 24, 26].


Magalhães et al.: Clinical drug interactions: venlafaxine 5

Pharmacokinetic-based drug interactions

Figure 1 Main metabolic pathways of venlafaxine (VEN) in humans. The chemical structures of VEN and its metabolites are shown [6, 19–22]. The bold arrow indicates the major metabolic pathway of VEN. The main metabolizing enzyme(s) of each pathway is/are indicated above the arrows, at superior size. CYP, cytochrome P450.

Once absorbed from the gastrointestinal tract, VEN undergoes wide presystemic cytochrome P450 (CYP)mediated metabolism to its major and equiactive metabolite, ODV. Therefore, the concentrations of ODV found in plasma are usually 2- to 3-fold higher than those found for VEN. Furthermore, other minor metabolites such as N-desmethylvenlafaxine (NDV) and N,O-didesmethylvenlafaxine (DDV) are also formed by secondary metabolic pathways (Figure 1), which have been described as VEN derivatives devoid of pharmacological activity. In this context, taking into account that VEN is hepatically metabolized by CYP isoenzymes, there is today a consensus that the O-demethylation reactions are catalyzed by CYP2C9, CYP2C19, and predominantly by CYP2D6, whereas the N-demethylation reactions are mediated by CYP2C9, CYP2C19, and CYP3A4 [5, 6, 14, 19, 28–30]. A schematic representation of the main metabolic pathways of VEN is shown in Figure 1. Lastly, most of the administered dose of VEN is eliminated by renal excretion (≈92%), with terminal elimination half-life (t1/2β) values of approximately 5 h for VEN and 11 h for ODV [6, 17]. Taking into consideration the scope of this review, after having performed a general overview about the pharmacokinetics, pharmacodynamics, and clinical properties of VEN, it is now time to focus the attention in depth on specific pharmacokinetic and pharmacodynamic interactions involving this antidepressant agent.

The pharmacokinetic interaction profile of VEN is determined by the potential that this antidepressant has to act as an object drug or as a precipitant drug in relation to other co-administered medications. At this level, the available data on pharmacokinetic-based drug interactions entailing VEN are mainly related to the fact that this drug is a well-known substrate of CYP isoenzymes and P-gp efflux transporter, as well as to its capacity for inhibition and induction of each of these systems, respectively [5, 6, 12, 14, 17, 24–29]. A summary of this kind of drug interactions is shown in Table 1 [7, 8, 16, 31–49]. Although most of the pharmacokinetic-based drug interactions mentioned in Table 1 have been reported from numerous clinical trials, it is clearly evidenced that the clinical consequences of such drug interactions have not been widely evaluated. Indeed, the clinical impact of the drug interactions involving VEN has been reported in the context of case reports [16, 33, 40] and also in a quinidine study [41]. In reality, most of the pharmacokinetic-based clinical trials only predicted how the changes in pharmacokinetics can be translated into clinical practice, considering the magnitude of change in the pharmacokinetic parameters, the pharmacodynamic properties of the affected drug, and even the individual characteristics of the target patients. Thus, the possible conclusions to be drawn from these data cannot be at all definitive. In the following sections, an exhaustive discussion on the pharmacokinetic-based drug interactions involving VEN will be provided, focusing in particular the potential clinical and therapeutic implications.

VEN as an object drug As previously reported, VEN is primarily metabolized through CYP2D6 (Figure 1). Thus, as this CYP isoenzyme also mediates the metabolism of about 25% of the currently available therapeutic drugs, there is an increased likelihood for the occurrence of metabolic-based drug interactions with other CYP2D6 substrates and/or inhibitors (CYP2D6 inducers are not known until now) [37, 50]. Because VEN is mainly metabolized by CYP2D6 isoenzyme to its major active metabolite ODV, the co-administration of CYP2D6 inhibitors increases the extent of systemic exposure to VEN and decreases the exposure to ODV [as assessed by the area under the plasma concentration-time curve (AUC)]. Nevertheless, it has been


Diphenhydramine

Imipramine

Ketoconazole


Propafenone

Quinidine

Lithium

CYP2D6 EMs: VEN (↓ oral CL, from 100 ± 62 L/h to 17 ± 5 L/h) CYP2D6 PMs: VEN (oral CL, ↔)

NE

VEN [↓ renal CL (from 0.053 to 0.027 L/h/kg); total CL, ↔]

CYP2D6 PMs: VEN [↑ AUC (70%); Cmax (48%)]; ODV [↑ AUC (33%); Cmax (29%)]; VEN+ODV (↑ AUC; ∼53%) CYP2D6 EMs: VEN [↑ AUC (21%); Cmax (26%)]; ODV [↑ AUC (23%); Cmax (14%)]; VEN+ODV (↑ AUC, ∼23%)

VEN (↑ Cp); ODV(↓ Cp); VEN+ODV (Cp, ↔)

CYP2D6 EMs: VEN [↓ oral CL (59%); ↑ AUC (2-fold)] CYP2D6 PMs: ↔

VEN+ODV (↑ Cp, ∼30%)

VEN [↓CL (43%); ↑ AUC (∼60%); ↑ Cmax (∼60%)]

Cotrimoxazole

VEN [↓ oral CL; ↑ SS Cp (74%)]; VEN+ODV (↑ Cp, 13%)

Cimetidine

VEN (exposure may be decreased)

Carbamazepine

VEN (↑ Cp); ODV (↓ Cp)

ODV (↑ Cp)

VEN as an object drug Bupropion

Pharmacokinetic effects

Calcineurin inhibitors (cyclosporine, tacrolimus)

Drugs

Table 1 Pharmacokinetic-based drug interactions involving venlafaxine.

CYP2D6 inhibition

CYP2D6 and P-gp inhibition

Unknown

CYP2C, CYP3A4, and P-gp inhibition

CYP2D6 inhibition

CYP2D6 inhibition

Cardiovascular toxicity

Visual hallucinations and psychomotor agitation

Unlikely (once the hepatic clearance is the major elimination pathway)

Unknown

Unknown

Unknown

Severe tremor due to serotonergic stimulation

↓ N-demethylation of VEN (reduced expression of CYP2C19 genetically determined; CYP2C9 inhibition)

Unknown

Unknown

Serotonin syndrome

Possibly dose-dependent serotonergic and noradrenergic adverse effects (e.g., anxiety, restlessness, and increased blood pressure)

Clinical impact

CYP inhibition

CYP3A4 induction

P-gp inhibition and CYP3A4 saturation

CYP2D6 inhibition

Proposed mechanisms

Pharmacokinetic-based clinical trial

Case report





Case report


Review

Two case reports

Pharmacokinetic-based clinical trials

Scientific evidence

[41]

[40]

[39]

[37, 38]

[37]

[7, 36]

[16]

[8]

[35]

[34]

[33]

[31, 32]

References

6 Magalhães et al.: Clinical drug interactions: venlafaxine

Terbinafine

Voriconazole

VEN as a precipitant drug Alprazolam

Desipramine

Diazepam

Haloperidol

Imipramine

Indinavir

Metoprolol

Risperidone

Risperidone [↓ oral CL (38%); ↑ Vd (17%) ↑ AUC (32%)]; 9-hydroxyrisperidone [↓ renal CL (20%); AUC, ↔]; total active moiety [AUC, ↔ (7%)]

Metoprolol (↑ Cp, 30%–40%); α-hydroxymetoprolol (Cp, ↔)

With VEN immediate release: ↓ AUC (28%); ↓ Cmax (36%)

Imipramine [↓ CL (28%); ↑ Cmax; ↑ AUC (28%)]; desipramine [↓ oral CL (20%); ↓ Vd (25%); ↑ Cmax (41%); ↑ AUC (40%)]

↓ Oral CL (42%); ↑ AUC (70%); ↑ Cmax (88%)

↑ Oral CL (from 24 ± 8 to 26 ± 6 mL/h/kg); ↑ Vd (from 0.85 ± 0.28 to 0.99 ± 0.34 L/kg); ↓ AUC (from 5973 ± 2304 to 5008 ± 1354 ng h/mL)

Desipramine (↑ AUC, ↑ Cmax, ↑ Cmin, ∼35%); 2-hydroxy-desipramine (↑ AUC, 2.5- to 4.5-fold)

↑ Oral CL (36%); ↓ t1/2 (21%); ↑ Vd (9%); ↓ AUC (29%)

VEN+ODV (↑ AUC, 31%)

VEN (↑ AUC, 490%); ODV (↓ AUC, 57%)

Pharmacokinetic effects

CYP2D6 inhibition

CYP2D6 inhibition

P-gp induction

CYP2D6 inhibition

Possibly CYP2D6 inhibition

Unknown

CYP2D6 inhibition

Unknown

CYP3A4, CYP2C9, and CYP2C19 inhibition

CYP2D6 inhibition

Proposed mechanisms

Unknown

Unknown

Unknown

Unknown

Unknown

Unknown

Unknown

Unknown

Unknown

Unknown

Clinical impact











Scientific evidence

[49]

[37]

[48]

[47]

[46]

[45]

[37, 44]

[43]

[42]

[42]

References

AUC, area under the plasma concentration-time curve; CL, clearance; Cmax, maximum plasma concentration; Cmin, minimum plasma concentration; Cp, plasma concentration; CYP, cytochrome P450; EMs, extensive metabolizers; NE, not evaluated; ODV, O-desmethylvenlafaxine; P-gp, P-glycoprotein; PMs, poor metabolizers; SS, steady state; Vd, volume of distribution; VEN, venlafaxine; ↓, decreased; ↑, increased; ↔, no significant changes.

Drugs

(Table 1 Continued)



8 Magalhães et al.: Clinical drug interactions: venlafaxine suggested by some authors that the inhibition of CYP2D6 isoenzyme does not present substantial implications on the therapeutic outcomes of VEN [35, 37]. This hypothesis is based on the pharmacological equipotency of VEN and ODV as antidepressant agents [17]. Although the inhibition of CYP2D6 isoenzyme determines an increase in the plasma concentrations of VEN, this is offset by a reduction in the plasma concentrations of ODV, determining minimum changes in the concentrations of the total active moiety (VEN plus ODV). Attending to this reason, dosage adjustments have not been usually recommended when VEN is co-administered with CYP2D6 inhibitors, even in the summary of product characteristics of Effexor (a trade name for VEN) [37]. These assumptions were taken from findings observed with the co-administration of VEN and recognized CYP2D6 inhibitors (cimetidine and imipramine) [51, 52] (Table 1). Notwithstanding, the results of these studies do not seem to be enough to support this conclusion, as the clinical impact of these drug-drug interactions was not assessed. At this level, the cardiotoxicity observed with the co-administration of VEN and quinidine (a potent CYP2D6 inhibitor) reinforces the previous consideration [41]. Indeed, taking into account that cimetidine and imipramine are partial CYP2D6 inhibitors [37, 53], the co-administration of drugs with a higher capacity for CYP2D6 inhibition may have meaningful clinical implications. Moreover, cimetidine also inhibits other VEN-metabolizing CYP isoenzymes such as CYP2C9, CYP2C19, and CYP3A4 [37, 53–57]; thus, based on the findings obtained from cimetidine, it is inconsistent to make predictions about the need for dose adjustments in cases where VEN is co-administrated with other CYP2D6 inhibitors. In addition, the impact of these pharmacokinetic-based drug interactions in highrisk subpopulations (e.g., elderly or those with hepatic impairment) is unknown [35, 37]. Furthermore, several studies have associated the CYP2D6 poor metabolizer phenotype with the development of adverse effects ascribed to VEN [40, 41, 50, 58–63] and even to a less favorable clinical response [14, 64, 65]. All these facts call into question the generalization made for CYP2D6 inhibitors. For the remaining studies about CYP2D6 inhibition [7, 31, 32, 36, 40–42], the influence on the concentrations of the total active moiety of VEN is not mentioned, further hindering the analysis of its value. Although the real clinical effects of each drug interaction is unknown, it is unlikely that the isolated administration of CYP2D6 inhibitors can manifest undesirable results for VEN; however, it may induce variability in the drug pharmacokinetics that may be additive to other factors (e.g., physiological, pathophysiological, genetic,

and/or environmental factors) determining, therefore, variability in the overall clinical response. In particular, the effects of terbinafine and propafenone deserve a special discussion. In the case of terbinafine (a potent CYP2D6 inhibitor), the extensive increase in the AUC of VEN (490%) predisposes the occurrence of toxic effects; hence, the co-administration of terbinafine and VEN should be avoided or a dosage adjustment needs to be considered [42]. Besides the inhibition of CYP2D6 claimed by some authors, other mechanisms of interaction may occur as terbinafine is mostly metabolized by CYP2C9, CYP2C19, CYP1A2, CYP3A4, and CYP2C8 [66], sharing the CYP isoenzymes implicated in the metabolic pathways of VEN. Thus, in the presence of terbinafine, a possible competitive metabolic inhibition may occur, decreasing the hepatic clearance of VEN. Concerning propafenone, more than the CYP2D6 inhibition, this drug is also a P-gp inhibitor, which can increase the absorption of VEN and its brain exposure, thus explaining the excessive serotonergic stimulation [40]. The same reasoning can be taken into account for calcineurin inhibitors and ketoconazole with respect to P-gp [33]. At this level, there are no research works evaluating the individual contribution of P-gp inhibition/induction on the pharmacokinetics and pharmacodynamics variability of VEN; however, this potential exists and it should be considered in prescribing. The inhibition of minor metabolic pathways of VEN mediated by CYP3A4, CYP2C9, and CYP2C19 (Figure 1) has not been extensively studied. The investigations found on this issue involved the antifungals ketoconazole [38] and voriconazole [42] and, more recently, cotrimoxazole [16] as precipitant drugs (Table 1). The concomitant use of these inhibitors seems to have a more evident effect on the increase of the total concentrations of active moiety (VEN plus ODV) against the use of CYP2D6 inhibitors; in fact, CYP3A4, CYP2C9, and CYP2C19 isoenzymes are responsible for converting the active moiety (VEN and ODV) to non-active metabolites. As a result, a reduction of the drug clearance by these minor metabolic pathways can still potentiate the appearance of toxicity. However, when the metabolic capacities of the different isoenzymes implicated in the same metabolic pathway are simultaneously diminished, and/or when different pathways are concurrently affected, synergistic toxicity may occur. This can be the result of multiple concurrent mechanisms; for instance, a specific CYP isoenzyme can be inhibited owing to the co-administration of inhibitor agents, whereas other CYP isoenzyme can present a lower metabolic capacity due to genetic polymorphisms. Therefore, genetic and/or phenotypic information should be taken into



consideration in assessing the susceptibility for clinically relevant drug interactions. Such aspects were considered in some studies summarized in Table 1, particularly those where ketoconazole [37, 38], voriconazole [42], and cotrimoxazole [16] were co-administrated with VEN. Specifically, after the concomitant use of VEN and ketoconazole (a CYP2C and CYP3A4 inhibitor) in healthy volunteers phenotypically characterized as CYP2D6 extensive metabolizers or CYP2D6 poor metabolizers, higher plasma levels of VEN were found for the majority of the subjects independently of CYP2D6 phenotype. However, on average, the CYP2D6 poor metabolizers had a superior increase of the AUC of total active moiety (VEN plus ODV) compared with extensive metabolizers, indicating that CYP2D6 poor metabolizers may potentially present a higher risk of adverse effects upon co-administration with CYP2C- and CYP3A4-inhibiting agents [37, 38]. Nevertheless, the effect of ketoconazole on the disposition of VEN was inconsistent in CYP2D6 poor metabolizers, with some subjects showing a marked increase in AUC and Cmax of VEN, whereas other subjects display small or no changes [38]. The P-gp inhibitory effects of ketoconazole are also well known (Table 2), and this aspect might also have contributed to increase the plasma concentrations of VEN [38]. Therefore, caution is advisable about the combination of ketoconazole and/or voriconazole with VEN. This does not mean that these drug interactions are clinically translated, but their mechanisms may potentiate the process. However, in relation to cotrimoxazole, it is unlikely that the combination of this antibiotic alone with VEN has any clinical impact, as the inhibition of CYP2C9 isoenzyme appears to have a minor contribution in the overall metabolism of VEN. However, in persons who are CYP2C9 intermediate metabolizers, an increase of the active moiety occurred and, especially, the coadministration with lithium potentiate the onset of serotonergic symptoms (serotonin additive effects). Thus, the co-administration of VEN with cotrimoxazole should be avoided when other serotonergic agents are included in the patient’s pharmacotherapeutic profile [16]. In turn, although metabolic inducer agents can possibly contribute to cases of treatment-resistant depression, this issue has not been studied. Indeed, only one research work was found for carbamazepine [34]. On the basis of the metabolic profile of VEN, in our opinion, the induction of VEN’s active moiety metabolizing isoenzymes (CYP3A4, CYP2C9, and CYP2C19) may interfere to a great extent in the therapeutic results comparatively to the induction of CYP2D6 because ODV is pharmacologically active and equipotent to VEN. It is still important to note that the pharmacokinetics of VEN is not meaningfully modified by

ethanol [67], diazepam [45], metoprolol [68], and indinavir [48]. Thus, as VEN is metabolized through different metabolic pathways mediated by several CYP isoenzymes (Figure 1), and taking into account that the main metabolic pathway produces a pharmacologically active metabolite (ODV) equipotent to the parent drug, the occurrence of clinically significant drug interactions induced by metabolic inhibition is less probable. However, with the information available so far, the co-administration of these drugs with VEN must be carefully considered and the need for dose adjustments should be monitored. This is especially relevant in patients with a high risk of drug accumulation (e.g., elderly, with polytherapy, or with renal and/or hepatic dysfunction) and whenever multiple mechanisms can have a synergic and/or additive contribution for increasing the drug concentrations (co-inhibition of different metabolizing isoenzymes and/or efflux transporters involved in the biodisposition of VEN). Hence, in those health conditions where the concomitant use of VEN and known interacting drugs is required, the monitoring of VEN serum concentrations may be useful. In addition to the drugs already evaluated, the knowledge of other agents able to inhibit the VEN-metabolizing isoenzymes and P-gp will allow to anticipate the development of possible toxicity events (Table 2). As the data on metabolic inducers and P-gp inducers are limited, the knowledge of such drugs (Table 2) may also help explain some cases of therapeutic failure.

VEN as a precipitant drug VEN has a low propensity to precipitate pharmacokineticbased interactions with co-administered medications, mainly due to its weak interference on the metabolic activity of CYP isoenzymes [7]. In vitro and in vivo studies have indicated that VEN weakly inhibits CYP2D6, CYP3A4, and CYP1A2, and this does not seem to occur at usual therapeutic doses [5, 14, 17, 28]. VEN has been characterized like one of the antidepressant agents with a lower potency for inhibiting CYP isoenzymes [69], which makes it a good choice for patients under treatment with narrow therapeutic index drugs, such as ritonavir [70], tamoxifen [71], and other anticancer drugs [72]. The most pronounced inhibitory effects triggered by VEN are those involving the CYP2D6 isoenzyme (Table 1). Indeed, under co-medication with VEN, drug substrates of the CYP2D6 isoenzyme, such as metoprolol, imipramine, desipramine, risperidone, and haloperidol, have shown higher plasma concentrations, suggesting


10 Magalhães et al.: Clinical drug interactions: venlafaxine Table 2 Known inhibitors and inducers of the cytochrome P450 (CYP)-metabolizing isoenzymes and P-glycoprotein (P-gp) efflux transporter involved in the biodisposition of venlafaxine [37, 42, 54–57]. CYP isoenzyme/ P-gp efflux transporter

Inhibitors

Inducers

CYP1A2

Amiodarone, cimetidine, ciprofloxacin, citalopram, diltiazem, enoxacin, erythromycin, fluvoxamine, furafylline, interferon, methoxsalen, mexiletine, mibefradil, ofloxacin, tacrine, ticlopidine

β-Naphthoflavone, broccoli, Brussels sprouts, char-grilled meat, carbamazepine, insulin, methylcholanthrene, modafinil, nafcillin, omeprazole, tobacco

CYP2D6

Amiodarone, bupropion, celecoxib chlorpheniramine, chlorpromazine, cimetidine, cinacalcet, citalopram, clemastine, clomipramine, cocaine, diphenhydramine, doxepin, doxorubicin, duloxetine, escitalopram, fluoxetine, haloperidol, hydroxyzine, indinavir, methadone, metoclopramide, mibefradil, midodrine, moclobemide, paroxetine, perphenazine, propafenone, quinidine, ranitidine, ritonavir, sertraline, terbinafine, thioridazine, ticlopidine, tripelennamine, venlafaxine

Unknown

CYP2C9

Amiodarone, cimetidine fenofibrate, fluconazole, fluoxetine, fluvastatin, fluvoxamine, isoniazid, lovastatin, metronidazole, paroxetine, phenylbutazone, probenicid, sertraline, sulfamethoxazole/trimethoprim, sulfaphenazole, teniposide, ticlopidine, voriconazole, zafirlukast

Phenobarbital, rifampin, secobarbital

CYP2C19

Chloramphenicol, cimetidine, felbamate, fluoxetine, fluvoxamine, indomethacin, ketoconazole, lansoprazole, modafinil, omeprazole, oxcarbazepine, pantoprazole paroxetine, probenicid, rabeprazole, ticlopidine, topiramate, voriconazol

Carbamazepine, norethindrone, prednisone, rifampicin

CYP3A(4/5/7)

Amiodarone, boceprevir, cimetidine, ciprofloxacin, chloramphenicol, clarithromycin, cyclosporine, danazol, delaviridine, diltiazem, diethyl-dithiocarbamate, erythromycin, fluconazole, fluvoxamine, gestodene, grapefruit juice, imatinib, indinavir, itraconazole, ketoconazole, mibefradil, miconazole, mifepristone, nelfinavir, nefazadone, norfloxacin, norfluoxetine omeprazole, quinidine, ritonavir, saquinavir, startfruit, telaprevir, telithromycin, verapamil, voriconazole

Carbamazepine, efavirenz, glucocorticoids, modafinil, nevirapine, oxcarbazepine, phenobarbital, phenytoin, pioglitazone, rifabutin, rifampicin, ritonavir, St. John’s wort, troglitazone

P-gp

Amiodarone, astemizole, atorvastatin, bepridil, biricodar, bromocriptine, carvedilol, chlorpromazine, clarithromycin, cortisol, cyclosporine, diltiazem, dipyridamole, disulfiram, erythromycin, felodipine, fluoxetine, itraconazole, ketoconazole, midazolam, nicardipine, nitrendipine, paroxetine, progesterone, propafenone, quinidine, quinine, reserpine, ritonavir, sertraline, tacrolimus, tamoxifen, terfenadine, tetrabenzine, valinomycin, verapamil, vinblastine

Amiodarone, amprenavir, bromocriptine, chlorambucil, cisplatin, clotrimazole, colchicine, cyclosporine, daunorubicin, dexamethasone, diltiazem, doxorubicin, erythromycin, etoposide, fluorouracil, hydroxyurea, insulin, indinavir, methotrexate, midazolam, mitoxantrone, morphine, nelfinavir, nicardipine, nifedipine, phenobarbital, phenothiazine, phenytoin, probenecid, reserpine, retinoid acid, rifampicin, ritonavir, St John’s wort, tacrolimus, tamoxifen, verapamil, vinblastine, vincristine, yohimbine

the ability of VEN to inhibit CYP2D6 [37, 44, 46, 47, 49]. Among these drug interactions, the clinical impact of the co-administration of risperidone and VEN is unlikely because the changes observed in the pharmacokinetics of risperidone were only a slight increase in the AUC of the total active moiety [49]. Concerning the interaction with

metoprolol, a recent review concluded that VEN is one of the antidepressant agents for which clinically important interactions with this drug are not expected [68]. Nevertheless, VEN impaired the blood-pressure-lowering effect of metoprolol [37]. Therefore, it is recommended that patients receiving VEN have a regular monitoring



of blood pressure [37]. With respect to imipramine, the results are additive. Seeing the potential for serotonergic syndrome with tricyclic antidepressants (TCAs), the increased exposure to imipramine and its major metabolite (desipramine) may induce a high risk for adverse effects [44, 47]. Thus, the combination of VEN and these two drugs (imipramine and desipramine) is inadvisable. Concerning the drug interaction between VEN and haloperidol, the great impact induced by VEN on the pharmacokinetics of haloperidol should be clearly underlined; in fact, the administration of VEN promoted a marked increase not only in the AUC but also in the Cmax (88%) of haloperidol, which is directly related to the likelihood of developing adverse effects [46]. Haloperidol appears to be a substrate of CYP2D6 and CYP3A4 isoenzymes [73, 74], which are also CYP isoforms entailed in the metabolism of VEN. Thus, the underlying mechanism to this drug interaction certainly involved the competitive enzymatic inhibition of CYP2D6 and also CYP3A4. The fact of haloperidol to be metabolized by two isoenzymes inhibited by VEN possibly determines the observed findings. At usual therapeutic doses, VEN does not appear to inhibit the CYP1A2 and CYP3A4 isoenzymes in vivo. Indeed, after the treatment of healthy volunteers with VEN, no significant changes were observed in the concentrations of specific CYP1A2 ((caffeine) [7]) and CYP3A4 (alprazolam [43], diazepam [45], terfenadine [37], and carbamazepine [69]) probe drugs administered in single-dose regimens. Furthermore, VEN did not change the pharmacokinetic disposition of ethanol [67], tolbutamide (CYP2C9 substrate) [37], and lithium [39] in healthy volunteers. When VEN was co-administered with diazepam and alprazolam, a decrease in the AUC for both drugs was evidenced [43, 45], but the mechanism and clinical consequences of these findings are unclear. However, these research works did not consider the individual metabolizer genotypes for the isoenzymes involved in the metabolism of these drugs. Thereby, further research on VEN-benzodiazepine interactions is warranted. Additionally, from a clinical trial conducted to investigate the potential for drug interactions between VEN and indinavir, the obtained findings showed that indinavir had no significant effect on the plasma concentrations of VEN, but otherwise the co-administration of VEN resulted in a considerable decrease in the AUC and Cmax of indinavir. Although the clinical impact of this drug interaction is unknown, the co-administration of indinavir and VEN raises some concerns because the plasma concentrations of protease inhibitors are critical in terms of the efficacy and potential for viral resistance. The interference of VEN in the biodisposition of indinavir will be certainly related

to the induction of P-gp mediated by VEN (immediaterelease formulation) [48]. Nevertheless, a recent study also showed a lack of pharmacokinetic interactions for VEN (extended-release formulation)/indinavir and ODV (extended-release formulation)/indinavir, suggesting that this type of pharmaceutical formulation is a good choice when these two drugs have to be concomitantly administered [75]. In fact, several authors have claimed a better profile in terms of drug interactions for extended-release formulations of VEN [6, 17]. To sum up, special attention is required toward the co-administration of VEN with other drug substrates of CYP2D6, essentially if they have a narrow therapeutic window and do not present other alternative metabolic pathways. In theory, the substrates of P-gp should also be cautiously used in patients receiving VEN because many of them have a narrow therapeutic range and VEN can lead to changes in the rate and extent of their systemic exposure. All pharmacokinetic studies presented in Table 1 share some limitations. Apart from they have not evaluated the real clinical impact owing to ethical and logistical reasons, they usually employed a single, not very high, dose of the precipitant drug. The pharmacokinetic behavior of the drug can be distinct, and the underlying interaction mechanisms can be more pronounced under multiple-dosage regimens rather than after single doses. For example, the occurrence of saturable enzymatic processes is more likely to occur at steady-state conditions. Furthermore, pharmacokinetic drug interactions may often result from changes in the expression and/or functionality of metabolizing enzymes and transporter proteins. Moreover, the genetic background may also determine considerable interindividual variability in drug absorption and biodisposition; however, many of the studies did not contemplate the possible influence of genetic polymorphisms affecting drug pharmacokinetics.

Pharmacodynamic-based drug interactions The profile of pharmacodynamic interactions involving VEN is much simpler and clear than the profile of pharmacokinetic-based drug interactions. From a pharmacodynamic perspective, VEN primarily interacts with drugs that have serotonergic properties and drugs that interfere with hemostasis (Table 3). Undoubtedly, VEN stimulates the serotonergic neurotransmitter system. Hence, the co-administration of other


Lithium

Mirtazapine

St John’s wort

Tramadol

Tranylcypromine

Trazodone

Drugs interfering with hemostasis (warfarin, acenocoumarol non-steroidal anti-inflammatory drugs, and aspirin)


SSRIs, serotonin selective reuptake inhibitors; TCAs, tricyclic antidepressants.

Increased bleeding risk (specifically of the upper gastrointestinal for non-steroidal anti-inflammatory drugs and aspirin)

Serotonin syndrome

Serotonin syndrome

Serotonin syndrome

Serotonin syndrome

Serotonin syndrome

Serotonin syndrome

Serotonin syndrome

Linezolid

Clinical impact Possible occurrence of serotonin syndrome

Amphetamines, brompheniramine, buspirone, carbamazepine, chlorpheniramine, cocaine, dextromethorphan, ecstasy, fentanyl, levodopa, lysergic acid diethylamide, monoamine oxidase inhibitors, meperidine, nefazodone, pargyline, pentazocine, propoxyphene, reserpine, sibutramine, SSRIs, TCAs, triptans, and other serotoninergic agents

Drugs

Table 3 Pharmacodynamic-based drug interactions involving venlafaxine.

Depletion of platelet serotonin content (decreased platelet aggregation)

Excessive serotonergic stimulation

Monoamine oxidase inhibition (serotonergic effect)


Additive effect on serotonin reuptake



Monoamine oxidase inhibition (serotonergic effect)


Proposed mechanisms

Epidemiological studies

Case report

Multiple case reports


Case reports




Reviews

Scientific evidence

[34, 37, 88–91]

[87]

[84–86]

[81, 83]

[82]

[80, 81]

[16, 44, 78, 79]

[37, 76, 77]

[34, 44, 52]

References

12 Magalhães et al.: Clinical drug interactions: venlafaxine


serotonergic drugs may result in a state of serotonergic overstimulation, which is a potentially life-threatening condition clinically called “serotonin syndrome.” These agents usually promote the release of serotonin or inhibit its reuptake and/or metabolism in the intersynaptic space. This syndrome manifests as altered mental status, involving agitation, confusion and coma, neuromuscular hyperactivity, and autonomic dysfunction [76]. On the basis of the underlying pharmacodynamic mechanisms, there is a vast arsenal of drugs displaying an evident potential to enhance the serotonergic effects of VEN; however, even so, for many of the drugs, there are no reports documenting clinical safety concerns caused by additivity or synergism with regard to serotonergic effects (Table 3) [44, 87]. This potential serotonergic risk may be augmented in the presence of factors that may raise drug plasma concentrations, such as the reduction in drug elimination due to pathological conditions, genetic polymorphisms, and/or pharmacokinetic-based drug interactions such as metabolic phenoconversion by the inhibition of CYP isoenzymes. These factors can hence contribute to the clinical manifestation of pharmacodynamic interactions with VEN, requiring additional care in these cases. In this context, imipramine, which interacts with VEN through pharmacokinetic- and pharmacodynamic-based mechanisms, is a good example [44, 47]. There are case reports that describe the development of serotonin syndrome as a result of an excessive serotonergic stimulation involving linezolid, lithium, mirtazapine, St John’s wort (an herbal product), tramadol, tranylcypromine, and trazodone (Table 3) [16, 37, 44, 76, 87, 77–86]. In addition, there have been rare postmarketing reports of serotonin syndrome with concomitant use of SSRIs and triptans (antimigraine serotonergic agents) [37]. Moreover, no pharmacodynamic interactions have been documented between VEN and ethanol [67] or diazepam [45]. Usually, the case reports assessed the strength of the association of the symptoms with drug interactions through appropriate algorithms (such as the Naranjo probability scale). The remission of symptoms as a result of dose adjustments, and also due to the discontinuation of combination therapy, represents relevant indicators. Therefore, if the concomitant treatment of VEN with the drugs listed in Table 3 or other serotonergic agents is clinically warranted, a careful monitoring of the patients is advised, particularly during treatment initiation and dose increases. Concerning hemostasis, it is true that the serotonin released by platelets plays an important role in mediating the hemostatic response to vascular damage, promoting vascular constriction and platelet aggregation.

As a result, the platelet serotonin content influences the homeostasis of coagulation. As platelets do not synthesize serotonin, there is a crucial storage mechanism that consists in the uptake of serotonin from the circulation to the platelets themselves. Thus, drugs that prevent the reuptake of serotonin may thereby inhibit this mechanism, leading, consequently, to the depletion of platelet serotonin content, reducing platelet aggregation [92]. Indeed, case-control and cohort design epidemiological studies have demonstrated changes in anticoagulant effects and an augmented risk of over-anticoagulation upon the concomitant use of drugs with anticoagulant properties and drugs that interfere with serotonin reuptake, such as VEN [37, 92]. At this level, an increased risk for gastrointestinal tract bleeding has been shown in patients taking VEN in combination with non-steroidal anti-inflammatory drugs or aspirin [34, 88]. Similarly, an increased risk of bleeding when VEN is co-administered with warfarin, clopidogrel, and acenocoumarol has been postulated [34, 89, 93]. However, a recent in vitro study about the effects of SNRIs on the human platelet adhesion and coagulation found that VEN did not inhibit the platelet adhesion, in contrast to the other antidepressants studied, but slightly increased the platelet adhesion to fibrinogen [94]. These findings indicate that VEN is less prone to pharmacodynamic interactions with anticoagulant drugs compared with other SNRIs. Moreover, the increased risk for bleeding complications in users of antidepressants may be explained not only by the depletion of serotonin in platelets, but there may also be other factors contributing to these effects, for instance the co-influence of pharmacokinetic interactions. This idea was proposed by Teles et al. [90] for warfarin, where VEN possibly interferes with warfarin metabolism, increasing the bleeding risk. Given that the main metabolizing isoenzymes of these drugs are CYP1A2, CYP3A4, CYP2C9, and CYP2C19 [95, 96, 51], it is possible that VEN causes some level of interference in the metabolism of warfarin by competitive enzymatic inhibition. Thus, drug interactions between VEN and these drugs may have a mixed contribution of pharmacokinetic and pharmacodynamic mechanisms.

Conclusions VEN is one of the safer antidepressants in terms of the propensity to be involved in clinically significant drugdrug interactions, being, thereby, a good alternative to SSRIs in polymedicated patients, chiefly if they are taking narrow therapeutic index drugs. Attending to the state of


14 Magalhães et al.: Clinical drug interactions: venlafaxine the art of antidepressant therapy, it is of utmost importance to improve the therapeutic outcomes in clinical practice. Therefore, selecting an antidepressant that is well characterized and that displays a low potential for drug-drug interactions, such as VEN, is highly desirable. Nonetheless, a variety of factors contribute to drug-drug interactions, and each individual case must be evaluated in an integrated context of specific environmental, therapeutic, pathophysiological, and even pharmacogenetic variables, and taking together into account pharmacokinetic- and pharmacodynamic-based considerations. This fact still becomes more important in patients who are susceptible to display a wide variability in the pharmacokinetics and pharmacodynamics determined by multiple factors. Overall, the risk of detrimental drug interactions may be preventively reduced by avoiding the unnecessary use of complex pharmacotherapeutic regimens and by selecting co-medications that are less likely to interact. Whenever the use of potentially interacting drugs cannot be avoided, clinical and therapeutic consequences may be minimized through the adjustment and individualization of dosing regimens guided by careful monitoring of the clinical response and even through the plasma drug concentrations. Undoubtedly, the detailed knowledge of the drug interaction profile and its application into clinical practice constitute an integral and fundamental part of the pharmacotherapeutic interventions inserted in the scope of therapeutic drug monitoring. The approach of these data as putative sources of inter-/intra-individual variability in the pharmacologic response, complementary to other non-genetic and genetic sources, provide the rational basis for therapeutic optimization in an attempt to better predict, explain, and guide the therapeutic outcomes. Authors’ conflict of interest disclosure: The authors stated that there are no conflicts of interest regarding the publication of this article. Research funding played no role in the study design; in the collection, analysis, and interpretation of data; in the writing of the report; or in the decision to submit the report for publication. Research funding: Paulo Magalhães was supported by Fundação para a Ciência e a Tecnologia (Portugal) through the PhD fellowship SFRH/BD/85069/2012, involving the POPH (Programa Operacional Potencial Humano), which is co-funded by FSE (Fundo Social Europeu), União Europeia. Employment or leadership: None declared. Honorarium: None declared.

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