Allongement du temps QT
Événements indésirables médicamenteux
|Gain de poids|
Variantes ✨Pour une évaluation intensive des variantes par ordinateur, veuillez choisir l'abonnement standard payant.
Explications concernant les substances pour les patients
Nous n'avons pas de mise en garde supplémentaire concernant l'association de asénapine et de promazin. Veuillez également consulter les informations pertinentes des spécialistes.
Les changements d'exposition rapportés correspondent aux changements de la courbe concentration-temps plasmatique [ AUC ]. Nous ne prévoyons aucun changement dans l'exposition à la asénapine, lorsqu'il est associé à la promazin (100%). Nous ne prévoyons aucun changement dans l'exposition à la promazin, lorsqu'il est associé à la asénapine (100%).
Les paramètres pharmacocinétiques de la population moyenne sont utilisés comme point de départ pour calculer les changements individuels d'exposition dus aux interactions.
La asénapine a une faible biodisponibilité orale [ F ] de 100 %, c'est pourquoi la concentration plasmatique maximale [Cmax] a tendance à changer fortement avec une interaction. La demi-vie terminale [ t12 ] est de 24 heures et des taux plasmatiques constants [ Css ] sont atteints après environ 96 heures. La liaison aux protéines [ Pb ] est modérément forte à 95% et le volume de distribution [ Vd ] est très grand à 1700 litres. Le métabolisme se fait principalement via CYP1A2 et le transport actif s'effectue notamment via UGT1A4.
La biodisponibilité de la promazin est inconnue. La demi-vie terminale [ t12 ] est assez longue (jusqu'à 30 heures) et des taux plasmatiques constants [ Css ] ne sont atteints qu'après plus de 120 heures. La liaison aux protéines [ Pb ] est modérément forte à 94%. Le métabolisme a lieu via CYP1A2, CYP2C19, CYP2C9 et CYP3A4, entre autres et le transport actif s'effectue notamment via PGP.
|Effets sérotoninergiques a||0||Ø||Ø|
Note: À notre connaissance, ni la asénapine ni la promazin n'augmentent l'activité sérotoninergique.
|Kiesel & Durán b||2||+||+|
Recommandation: Par mesure de précaution, une attention particulière doit être portée aux symptômes anticholinergiques, en particulier après augmentation de la dose et à de celles situées dans la marge thérapeutique supérieure.
Notation: La asénapine et la promazin n'ont qu'un effet modéré sur le système anticholinergique. Le risque de syndrome anticholinergique avec ce médicament est plutôt faible si la dosage est respecté.
Allongement du temps QT
Note: En association, la asénapine et la promazin peuvent potentiellement déclencher des arythmies ventriculaires de type torsades de pointes.
Effets indésirables généraux
|Effets secondaires||∑ fréquence||asé||pro|
|Gain de poids||11.5 %||11.5||n.a.|
|Hypotension orthostatique||1.5 %||1.5||n.a.|
|Crise d'épilepsie||0.3 %||0.3||n.a.|
Réaction d'hypersensibilité: asénapine
Syndrome malin des neuroleptiques: asénapine
Sur la base de vos réponses et des informations scientifiques, nous évaluons le risque individuel d'effets secondaires indésirables. Ces recommandations sont destinées à conseiller les professionnels et ne se substituent pas à la consultation d'un médecin. Dans la version d'essai (alpha), le risque de toutes les substances n'a pas encore été évalué de manière concluante.
Abstract: 1. The aim of the present study was to identify human cytochrome p-450 isoforms (CYPs) involved in 5-sulphoxidation and N-demethylation of the simplest phenothiazine neuroleptic promazine in human liver. 2. The experiments were performed in the following in vitro models: (A). a study of promazine metabolism in liver microsomes-(a). correlations between the rate of promazine metabolism and the level and activity of CYPs; (b). the effect of specific inhibitors on the rate of promazine metabolism (inhibitors: CYP1A2-furafylline, CYP2D6-quinidine, CYP2A6+CYP2E1-diethyldithiocarbamic acid, CYP2C9-sulfaphenazole, CYP2C19-ticlopidine, CYP3A4-ketoconazole); (B). promazine biotransformation by cDNA-expressed human CYPs (Supersomes 1A1, 1A2, 2A6, 2B6, 2C9, 2C19, 2E1, 3A4); (C). promazine metabolism in a primary culture of human hepatocytes treated with specific inducers (rifampicin-CYP3A4, CYP2B6 and CYP2C inducer, 2,3,7,8-tetrachlordibenzeno-p-dioxin (TCDD)-CYP1A1/1A2 inducer). 3. In human liver microsomes, the formation of promazine 5-sulphoxide and N-desmethylpromazine was significantly correlated with the level of CYP1A2 and ethoxyresorufin O-deethylase and acetanilide 4-hydroxylase activities, as well as with the level of CYP3A4 and cyclosporin A oxidase activity. Moreover, the formation of N-desmethylpromazine was correlated well with S-mephenytoin 4'-hydroxylation. 4. Furafylline (a CYP1A2 inhibitor) and ketoconazole (a CYP3A4 inhibitor) significantly decreased the rate of promazine 5-sulphoxidation, while furafylline and ticlopidine (a CYP2C19 inhibitor) significantly decreased the rate of promazine N-demethylation in human liver microsomes. 5. The cDNA-expressed human CYPs generated different amounts of promazine metabolites, but the rates of CYP isoforms to catalyse promazine metabolism at therapeutic concentration (10 microM) was as follows: 1A1>2B6>1A2>2C9>3A4>2E1>2A6>2D6>2C19 for 5-sulphoxidation and 2C19>2B6>1A1>1A2>2D6>3A4>2C9>2E1>2A6 for N-demethylation. The highest intrinsic clearance (V(max)/K(m)) was found for CYP1A subfamily, CYP3A4 and CYP2B6 in the case of 5- sulphoxidation, and for CYP2C19, CYP1A subfamily and CYP2B6 in the case of N-demethylation. 6. In a primary culture of human hepatocytes, TCDD (a CYP1A subfamily inducer), as well as rifampicin (mainly a CYP3A4 inducer) induced the formation of promazine 5-sulphoxide and N-desmethylpromazine. 7. Regarding the relative expression of various CYPs in human liver, the obtained results indicate that CYP1A2 and CYP3A4 are the main isoforms responsible for 5-sulphoxidation, while CYP1A2 and CYP2C19 are the basic isoforms that catalyse N-demethylation of promazine in human liver. Of the other isoforms studied, CYP2C9 and CYP3A4 contribute to a lesser degree to promazine 5-sulphoxidation and N-demethylation, respectively. The role of CYP2A6, CYP2B6, CYP2D6 and CYP2E1 in the investigated metabolic pathways of promazine seems negligible.
Abstract: BACKGROUND: Cognitive decline is common in Parkinson's disease (PD). Although some of the aetiological factors are known, it is not yet known whether drugs with anticholinergic activity (AA) contribute to this cognitive decline. Such knowledge would provide opportunities to prevent acceleration of cognitive decline in PD. OBJECTIVE: To study whether the use of agents with anticholinergic properties is an independent risk factor for cognitive decline in patients with PD. METHODS: A community-based cohort of patients with PD (n=235) were included and assessed at baseline. They were reassessed 4 and 8 years later. Cognition was assessed using the Mini-Mental State Examination (MMSE). A detailed assessment of the AA of all drugs prescribed was made, and AA was classified according to a standardised scale. Relationships between cognitive decline and AA load and duration of treatment were assessed using bivariate and multivariate statistical analyses. RESULTS: More than 40% used drugs with AA at baseline. During the 8-year follow-up, the cognitive decline was higher in those who had been taking AA drugs (median decline on MMSE 6.5 points) compared with those who had not taken such drugs (median decline 1 point; p=0.025). In linear regression analyses adjusting for age, baseline cognition and depression, significant associations with decline on MMSE were found for total AA load (standardised beta=0.229, p=0.04) as well as the duration of using AA drugs (standardised beta 0.231, p=0.032). CONCLUSION: Our findings suggest that there is an association between anticholinergic drug use and cognitive decline in PD. This may provide an important opportunity for clinicians to avoid increasing progression of cognitive decline by avoiding drugs with AA. Increased awareness by clinicians is required about the classes of drugs that have anticholinergic properties.
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: Transporters in proximal renal tubules contribute to the disposition of numerous drugs. Furthermore, the molecular mechanisms of tubular secretion have been progressively elucidated during the past decades. Organic anions tend to be secreted by the transport proteins OAT1, OAT3 and OATP4C1 on the basolateral side of tubular cells, and multidrug resistance protein (MRP) 2, MRP4, OATP1A2 and breast cancer resistance protein (BCRP) on the apical side. Organic cations are secreted by organic cation transporter (OCT) 2 on the basolateral side, and multidrug and toxic compound extrusion (MATE) proteins MATE1, MATE2/2-K, P-glycoprotein, organic cation and carnitine transporter (OCTN) 1 and OCTN2 on the apical side. Significant drug-drug interactions (DDIs) may affect any of these transporters, altering the clearance and, consequently, the efficacy and/or toxicity of substrate drugs. Interactions at the level of basolateral transporters typically decrease the clearance of the victim drug, causing higher systemic exposure. Interactions at the apical level can also lower drug clearance, but may be associated with higher renal toxicity, due to intracellular accumulation. Whereas the importance of glomerular filtration in drug disposition is largely appreciated among clinicians, DDIs involving renal transporters are less well recognized. This review summarizes current knowledge on the roles, quantitative importance and clinical relevance of these transporters in drug therapy. It proposes an approach based on substrate-inhibitor associations for predicting potential tubular-based DDIs and preventing their adverse consequences. We provide a comprehensive list of known drug interactions with renally-expressed transporters. While many of these interactions have limited clinical consequences, some involving high-risk drugs (e.g. methotrexate) definitely deserve the attention of prescribers.
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: 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.