QT time prolongation
Adverse drug events
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Explanations of the substances for patients
We have no additional warnings for the combination of asenapine and voriconazole. Please also consult the relevant specialist information.
|Voriconazole||1 [0.74,2.64] 1||1|
The reported changes in exposure correspond to the changes in the plasma concentration-time curve [ AUC ]. We do not expect any change in exposure for asenapine, when combined with voriconazole (100%). We do not expect any change in exposure for voriconazole, when combined with asenapine (100%). The AUC is between 74% and 264% depending on the CYP2C19
The pharmacokinetic parameters of the average population are used as the starting point for calculating the individual changes in exposure due to the interactions.
Asenapine has a low oral bioavailability [ F ] of 2%, which is why the maximum plasma level [Cmax] tends to change strongly with an interaction. The terminal half-life [ t12 ] is 24 hours and constant plasma levels [ Css ] are reached after approximately 96 hours. The protein binding [ Pb ] is moderately strong at 95% and the volume of distribution [ Vd ] is very large at 1700 liters. The metabolism mainly takes place via CYP1A2 and the active transport takes place in particular via UGT1A4.
Voriconazole has a high oral bioavailability [ F ] of 88%, which is why the maximum plasma level [Cmax] tends to change little during an interaction. The terminal half-life [ t12 ] is rather short at 6 hours and constant plasma levels [ Css ] are reached quickly. The protein binding [ Pb ] is rather weak at 58% and the volume of distribution [ Vd ] is very large at 90 liters, Since the substance has a low hepatic extraction rate of 0.11, displacement from protein binding [Pb] in the context of an interaction can lead to increased exposure. The metabolism takes place via CYP2C19, CYP2C9 and CYP3A4, among others.
|Serotonergic Effects a||0||Ø||Ø|
Rating: According to our knowledge, neither asenapine nor voriconazole increase serotonergic activity.
|Kiesel & Durán b||1||+||Ø|
Recommendation: As a precaution, attention should be paid to anticholinergic symptoms, especially after increasing the dose and at doses in the upper therapeutic range.
Rating: Asenapine only has a mild effect on the anticholinergic system. The risk of anticholinergic syndrome with this medication is rather low if the dosage is in the usual range. According to our knowledge, voriconazole does not increase anticholinergic activity.
QT time prolongation
Rating: In combination, asenapine and voriconazole can potentially trigger ventricular arrhythmias of the torsades de pointes type.
General adverse effects
|Side effects||∑ frequency||ase||vor|
|Blurred vision||26.0 %||n.a.||26.0|
|Abdominal pain||12.0 %||n.a.||12.0|
|Weight gain||11.5 %||11.5||n.a.|
Rash (7%): voriconazole
Erythema multiforme (1.9%): voriconazole
Malignant melanoma (1.9%): voriconazole
Squamous cell carcinoma (1.9%): voriconazole
Stevens johnson syndrome (1.9%): voriconazole
Toxic epidermal necrolysis (1.9%): voriconazole
Photophobia (6%): voriconazole
Optic neuritis: voriconazole
Fever (5.7%): voriconazole
Dizziness (5.5%): asenapine
Headache (3%): voriconazole
Neuroleptic malignant syndrome: asenapine
Nausea (5.4%): voriconazole
Vomiting (4.4%): voriconazole
Diarrhea (1.9%): voriconazole
Cholestatic hepatitis (4.9%): voriconazole
Hepatotoxicity (1.9%): voriconazole
Jaundice (1.9%): voriconazole
Liver failure (1.9%): voriconazole
Suicidal (2.5%): asenapine
Peripheral edema (1.9%): voriconazole
Orthostatic hypotension (1.5%): asenapine
Renal failure: voriconazole
Hypersensitivity reaction: asenapine
Based on your answers and scientific information, we assess the individual risk of undesirable side effects. These recommendations are intended to advise professionals and are not a substitute for consultation with a doctor. In the restricted test version (alpha), the risk of all substances has not yet been conclusively assessed.
Abstract: No Abstract available
Abstract: This review presents the published clinical pharmacokinetic data for the antifungal agent voriconazole. Aspects regarding absorption, tissue distribution, elimination and kinetic interactions are also discussed.
Abstract: Voriconazole is the first available second-generation triazole with potent activity against a broad spectrum of clinically significant fungal pathogens, including Aspergillus,Candida, Cryptococcus neoformans, and some less common moulds. Voriconazole is rapidly absorbed within 2 hours after oral administration and the oral bioavailability is over 90%, thus allowing switching between oral and intravenous formulations when clinically appropriate. Voriconazole shows nonlinear pharmacokinetics due to its capacity-limited elimination, and its pharmacokinetics are therefore dependent upon the administered dose. With increasing dose, voriconazole shows a superproportional increase in area under the plasma concentration-time curve (AUC). In doses used in children (age < 12 years) voriconazole pharmacokinetics appear to be linear. Steady-state plasma concentrations are reached approximately 5 days after both intravenous and oral administration; however, steady state is reached within 24 hours with voriconazole administered as an intravenous loading dose. The volume of distribution of voriconazole is 2-4.6 L/kg, suggesting extensive distribution into extracellular and intracellular compartments. Voriconazole was measured in tissue samples of brain, liver, kidney, heart, lung as well as cerebrospinal fluid. The plasma protein binding is about 60% and independent of dose or plasma concentrations. Clearance is hepatic via N-oxidation by the hepatic cytochrome P450 (CYP) isoenzymes, CYP2C19, CYP2C9 and CYP3A4. The elimination half-life of voriconazole is approximately 6 hours, and approximately 80% of the total dose is recovered in the urine, almost completely as metabolites. As with other azole drugs, the potential for drug interactions is considerable. Voriconazole shows time-dependent fungistatic activity against Candida species and time-dependent slow fungicidal activity against Aspergillus species. A short post-antifungal effect of voriconazole is evident only for Aspergillus species. The predictive pharmacokinetic/pharmacodynamic parameter for voriconazole treatment efficacy in Candida infections is the free drug AUC from 0 to 24 hour : minimum inhibitory concentration ratio.
Abstract: We describe 2 patients who developed prolonged QTc interval on electrocardiogram while being treated with voriconazole. The first patient had undergone induction chemotherapy for acute myelogenous leukemia, and her course had been complicated by invasive aspergillosis and an acute cardiomyopathy. She developed torsades de pointes 3 weeks after starting voriconazole therapy. She was re-challenged with voriconazole without recurrent QTc prolongation or cardiac dysfunction. The second patient had a significantly prolonged QTc interval while on voriconazole therapy. We recommend careful monitoring for QTc prolongation and arrhythmia in patients who are receiving voriconazole, particularly those who have significant electrolyte disturbances, are on concomitant QT prolonging medications, have heart failure such as from a dilated cardiomyopathy, or have recently received anthracycline-based chemotherapy. The potential for synergistic cardiotoxicity must be carefully considered.
Abstract: The objective of this study was to evaluate the pharmacokinetics of voriconazole and the potential correlations between pharmacokinetic parameters and patient variables in liver transplant patients on a fixed-dose prophylactic regimen. Multiple blood samples were collected within one dosing interval from 15 patients who were initiated on a prophylactic regimen of voriconazole at 200 mg enterally (tablets) twice daily starting immediately posttransplant. Voriconazole plasma concentrations were measured using high-pressure liquid chromatography (HPLC). Noncompartmental pharmacokinetic analysis was performed to estimate pharmacokinetic parameters. The mean apparent systemic clearance over bioavailability (CL/F), apparent steady-state volume of distribution over bioavailability (Vss/F), and half-life (t1/2) were 5.8+/-5.5 liters/h, 94.5+/-54.9 liters, and 15.7+/-7.0 h, respectively. There was a good correlation between the area under the concentration-time curve from 0 h to infinity (AUC0-infinity) and trough voriconazole plasma concentrations. t1/2, maximum drug concentration in plasma (Cmax), trough level, AUC0-infinity, area under the first moment of the concentration-time curve from 0 h to infinity (AUMC0-infinity), and mean residence time from 0 h to infinity (MRT0-infinity) were significantly correlated with postoperative time. t1/2, lambda, AUC0-infinity, and CL/F were significantly correlated with indices of liver function (aspartate transaminase [AST], total bilirubin, and international normalized ratio [INR]). The Cmax, last concentration in plasma at 12 h (Clast), AUMC0-infinity, and MRT0-infinity were significantly lower in the presence of deficient CYP2C19*2 alleles. Donor characteristics had no significant correlation with any of the pharmacokinetic parameters estimated. A fixed dosing regimen of voriconazole results in a highly variable exposure of voriconazole in liver transplant patients. Given that trough voriconazole concentration is a good measure of drug exposure (AUC), the voriconazole dose can be individualized based on trough concentration measurements in liver transplant patients.
Abstract: An assessment of the effects of asenapine on QTc interval in patients with schizophrenia revealed a discrepancy between the results obtained by two different methods: an intersection-union test (IUT) (as recommended in the International Conference on Harmonisation E14 guidance) and an exposure-response (E-R) analysis. Simulations were performed in order to understand and reconcile this discrepancy. Although estimates of the time-matched, placebo-corrected mean change in QTc from baseline (ddQTc) at peak plasma concentrations from the E-R analysis ranged from 2 to 5 ms per dose level, the IUT applied to simulated data from the E-R model yielded maximum ddQTc estimates of 7-10 ms for the various doses of asenapine. These results indicate that the IUT can produce biased estimates that may induce a high false-positive rate in individual thorough QTc trials. In such cases, simulations from an E-R model can aid in reconciling the results from the two methods and may support the use of E-R results as a basis for labeling.
Abstract: The metabolism and excretion of asenapine [(3aRS,12bRS)-5-chloro-2-methyl-2,3,3a,12b-tetrahydro-1H-dibenzo[2,3:6,7]-oxepino [4,5-c]pyrrole (2Z)-2-butenedioate (1:1)] were studied after sublingual administration of [(14)C]-asenapine to healthy male volunteers. Mean total excretion on the basis of the percent recovery of the total radioactive dose was ∼90%, with ∼50% appearing in urine and ∼40% excreted in feces; asenapine itself was detected only in feces. Metabolic profiles were determined in plasma, urine, and feces using high-performance liquid chromatography with radioactivity detection. Approximately 50% of drug-related material in human plasma was identified or quantified. The remaining circulating radioactivity corresponded to at least 15 very polar, minor peaks (mostly phase II products). Overall, >70% of circulating radioactivity was associated with conjugated metabolites. Major metabolic routes were direct glucuronidation and N-demethylation. The principal circulating metabolite was asenapine N(+)-glucuronide; other circulating metabolites were N-desmethylasenapine-N-carbamoyl-glucuronide, N-desmethylasenapine, and asenapine 11-O-sulfate. In addition to the parent compound, asenapine, the principal excretory metabolite was asenapine N(+)-glucuronide. Other excretory metabolites were N-desmethylasenapine-N-carbamoylglucuronide, 11-hydroxyasenapine followed by conjugation, 10,11-dihydroxy-N-desmethylasenapine, 10,11-dihydroxyasenapine followed by conjugation (several combinations of these routes were found) and N-formylasenapine in combination with several hydroxylations, and most probably asenapine N-oxide in combination with 10,11-hydroxylations followed by conjugations. In conclusion, asenapine was extensively and rapidly metabolized, resulting in several regio-isomeric hydroxylated and conjugated metabolites.
Abstract: BACKGROUND AND OBJECTIVE: The effects of hepatic or renal impairment on the pharmacokinetics of atypical antipsychotics are not well understood. Drug exposure may increase in patients with hepatic disease, owing to a reduction of certain metabolic enzymes. The objective of the present study was to study the effects of hepatic or renal impairment on the pharmacokinetics of asenapine and its N-desmethyl and N⁺-glucuronide metabolites. METHODS: Two clinical studies were performed to assess exposure to asenapine, desmethylasenapine and asenapine N⁺-glucuronide in subjects with hepatic or renal impairment. Pharmacokinetic parameters were determined from plasma concentration-time data, using standard noncompartmental methods. The pharmacokinetic variables that were studied included the maximum plasma concentration (C(max)) and the time to reach the maximum plasma concentration (t(max)). Eligible subjects, from inpatient and outpatient clinics, were aged ≥18 years with a body mass index of ≥18 kg/m² and ≤32 kg/m². Sublingual asenapine (Saphris®) was administered as a single 5 mg dose. RESULTS: Thirty subjects participated in the hepatic impairment study (normal hepatic function, n = 8; mild hepatic impairment [Child-Pugh class A], n = 8; moderate hepatic impairment [Child-Pugh class B], n = 8; severe hepatic impairment [Child-Pugh class C], n = 6). Thirty-three subjects were enrolled in the renal impairment study (normal renal function, n = 9; mild renal impairment, n = 8; moderate renal impairment, n = 8; severe renal impairment, n = 8). Asenapine and N-desmethylasenapine exposures were unaltered in subjects with mild or moderate hepatic impairment, compared with healthy controls. Severe hepatic impairment was associated with increased area under the plasma concentration-time curve from time zero to infinity (AUC(∞)) values for total asenapine, N-desmethylasenapine and asenapine N⁺-glucuronide (5-, 3-, and 2-fold, respectively), with slight increases in the C(max) of asenapine but 3- and 2-fold decreases in the C(max) values for N-desmethylasenapine and asenapine N⁺-glucuronide, respectively, compared with healthy controls. The mean AUC(∞) of unbound asenapine was more than 7-fold higher in subjects with severe hepatic impairment than in healthy controls. Mild renal impairment was associated with slight elevations in the AUC(∞) of asenapine compared with healthy controls; alterations observed with moderate and severe renal impairment were marginal. N-desmethylasenapine exposure was only slightly altered by renal impairment. No correlations were observed between exposure and creatinine clearance. CONCLUSION: Severe hepatic impairment (Child-Pugh class C) was associated with pronounced increases in asenapine exposure, but significant increases were not seen with mild (Child-Pugh class A) or moderate (Child-Pugh class B) hepatic impairment, or with any degree of renal impairment. Asenapine is not recommended in patients with severe hepatic impairment; no dose adjustment is needed in patients with mild or moderate hepatic impairment, or in patients with renal impairment.
Abstract: No Abstract available
Abstract: No Abstract available
Abstract: Asenapine is one of the newer atypical antipsychotics on the market. It is a sublingually administered drug that is indicated for the treatment of both schizophrenia and bipolar disorder, and is considered to be safe and well tolerated. Herein, we report a 71-year-old female with a history of bipolar disorder who had ventricular trigemini and experienced a large increase in her QTc interval after starting treatment with asenapine. These changes ceased following withdrawal of asenapine. In this case report, we discuss the importance of cardiac monitoring when switching antipsychotics, even to those that are considered to have low cardiac risk.
Abstract: The accurate estimation of "in vivo" inhibition constants () of inhibitors and fraction metabolized () of substrates is highly important for drug-drug interaction (DDI) prediction based on physiologically based pharmacokinetic (PBPK) models. We hypothesized that analysis of the pharmacokinetic alterations of substrate metabolites in addition to the parent drug would enable accurate estimation of in vivoandTwenty-four pharmacokinetic DDIs caused by P450 inhibition were analyzed with PBPK models using an emerging parameter estimation method, the cluster Newton method, which enables efficient estimation of a large number of parameters to describe the pharmacokinetics of parent and metabolized drugs. For each DDI, two analyses were conducted (with or without substrate metabolite data), and the parameter estimates were compared with each other. In 17 out of 24 cases, inclusion of substrate metabolite information in PBPK analysis improved the reliability of bothandImportantly, the estimatedfor the same inhibitor from different DDI studies was generally consistent, suggesting that the estimatedfrom one study can be reliably used for the prediction of untested DDI cases with different victim drugs. Furthermore, a large discrepancy was observed between the reported in vitroand the in vitro estimates for some inhibitors, and the current in vivoestimates might be used as reference values when optimizing in vitro-in vivo extrapolation strategies. These results demonstrated that better use of substrate metabolite information in PBPK analysis of clinical DDI data can improve reliability of top-down parameter estimation and prediction of untested DDIs.
Abstract: BACKGROUND: Anticholinergic drugs put elderly patients at a higher risk for falls, cognitive decline, and delirium as well as peripheral adverse reactions like dry mouth or constipation. Prescribers are often unaware of the drug-based anticholinergic burden (ACB) of their patients. This study aimed to develop an anticholinergic burden score for drugs licensed in Germany to be used by clinicians at prescribing level. METHODS: A systematic literature search in pubmed assessed previously published ACB tools. Quantitative grading scores were extracted, reduced to drugs available in Germany, and reevaluated by expert discussion. Drugs were scored as having no, weak, moderate, or strong anticholinergic effects. Further drugs were identified in clinical routine and included as well. RESULTS: The literature search identified 692 different drugs, with 548 drugs available in Germany. After exclusion of drugs due to no systemic effect or scoring of drug combinations (n = 67) and evaluation of 26 additional identified drugs in clinical routine, 504 drugs were scored. Of those, 356 drugs were categorised as having no, 104 drugs were scored as weak, 18 as moderate and 29 as having strong anticholinergic effects. CONCLUSIONS: The newly created ACB score for drugs authorized in Germany can be used in daily clinical practice to reduce potentially inappropriate medications for elderly patients. Further clinical studies investigating its effect on reducing anticholinergic side effects are necessary for validation.
Abstract: A highly selective and sensitive liquid chromatography-tandem mass spectrometry (LC-MS/MS) assay has been described for the determination of asenapine (ASE) in presence of its inactive metabolites-desmethyl asenapine (DMA) and asenapine--glucuronide (ASG). ASE, and ASE 13C-d3, used as internal standard (IS), were extracted from 300 µL human plasma by a simple and precise liquid-liquid extraction procedure using methyl-butyl ether. Baseline separation of ASE from its inactive metabolites was achieved on Chromolith Performance RP(100 mm × 4.6 mm) column using acetonitrile-5.0 mM ammonium acetate-10% formic acid (90:10:0.1, v/v/v) within 4.5 min. Quantitation of ASE was done on a triple quadrupole mass spectrometer equipped with electrospray ionization in the positive mode. The protonated precursor to product ion transitions monitored for ASE and ASE 13C-d3 were286.1 → 166.0 and290.0 → 166.1, respectively. The limit of detection (LOD) and limit of quantitation (LOQ) of the method were 0.0025 ng/mL and 0.050 ng/mL respectively in a linear concentration range of 0.050-20.0 ng/mL for ASE. The intra-batch and inter-batch precision (% CV) and mean relative recovery across quality control levels were ≤ 5.8% and 87.3%, respectively. Matrix effect, evaluated as IS-normalized matrix factor, ranged from 1.03 to 1.05. The stability of ASE under different storage conditions was ascertained in presence of the metabolites. The developed method is much simpler, matrix free, rapid and economical compared to the existing methods. The method was successfully used for a bioequivalence study of asenapine in healthy Indian subjects for the first time.