Prolongación del tiempo QT
Eventos adversos de medicamentos
|Aumento de peso|
Variantes ✨Para la evaluación computacionalmente intensiva de las variantes, elija la suscripción estándar paga.
Explicaciones de las sustancias para pacientes.
No existen advertencias adicionales para la combinación de asenapina y propafenona. Consulte también la información especializada pertinente.
Los cambios informados en la exposición corresponden a los cambios en la curva de concentración plasmática-tiempo [ AUC ]. La exposición a asenapina aumenta al 110%, cuando se combina con propafenona (110%). No detectamos ningún cambio en la exposición a la propafenona. Actualmente no podemos estimar la influencia de la asenapina.
Los parámetros farmacocinéticos de la población media se utilizan como punto de partida para calcular los cambios individuales en la exposición debidos a las interacciones.
La asenapina tiene una baja biodisponibilidad oral [ F ] del 2%, por lo que el nivel plasmático máximo [Cmax] tiende a cambiar fuertemente con una interacción. La vida media terminal [ t12 ] es de 24 horas y se alcanzan niveles plasmáticos constantes [ Css ] después de aproximadamente 96 horas. La unión a proteínas [ Pb ] es moderadamente fuerte al 95% y el volumen de distribución [ Vd ] es muy grande a 1700 litros. El metabolismo tiene lugar principalmente a través de CYP1A2 y el transporte activo tiene lugar especialmente a través de UGT1A4.
La propafenona tiene una baja biodisponibilidad oral [ F ] del 30%, por lo que el nivel plasmático máximo [Cmax] tiende a cambiar fuertemente con una interacción. La vida media terminal [ t12 ] es relativamente corta a las 3.7 horas y los niveles plasmáticos constantes [ Css ] se alcanzan rápidamente. La unión a proteínas [ Pb ] es moderadamente fuerte al 94.3% y el volumen de distribución [ Vd ] es muy grande a 175 litros. por eso, con una tasa de extracción hepática media de 0.65, tanto el flujo sanguíneo hepático [Q] como un cambio en la unión a proteínas [Pb] son relevantes. El metabolismo tiene lugar a través de CYP1A2, CYP2D6 y CYP3A4, entre otros.
|Efectos serotoninérgicos a||0||Ø||Ø|
Clasificación: Según nuestro conocimiento, ni la asenapina ni la propafenona aumentan la actividad serotoninérgica.
|Kiesel & Durán b||1||+||Ø|
Recomendación: Como precaución, se debe prestar atención a los síntomas anticolinérgicos, especialmente después de aumentar la dosis y en dosis en el rango terapéutico superior.
Clasificación: La asenapina solo tiene un efecto leve sobre el sistema anticolinérgico. El riesgo de síndrome anticolinérgico con este medicamento es relativamente bajo si la dosis se encuentra en el rango habitual. Según nuestro conocimiento, la propafenona no aumenta la actividad anticolinérgica.
Prolongación del tiempo QT
Clasificación: En combinación, la asenapina y la propafenona pueden desencadenar potencialmente arritmias ventriculares del tipo torsades de pointes.
Efectos adversos generales
|Efectos secundarios||∑ frecuencia||ase||pro|
|Aumento de peso||11.5 %||11.5||n.a.|
|Dolor en el pecho||5.0 %||n.a.||5.0|
|Trastorno del gusto||5.0 %||n.a.||5.0|
Ansiedad (5%): propafenona
Suicida (2.5%): asenapina
Disnea (5%): propafenona
Estreñimiento (4%): propafenona
Vómitos (2%): propafenona
Dolor abdominal: propafenona
Bloqueo auriculoventricular (2%): propafenona
Hipotensión ortostática (1.5%): asenapina
Taquicardia ventricular: propafenona
Dolor de cabeza: propafenona
Incautación: propafenona, asenapina
Síndrome neuroléptico maligno: asenapina
Visión borrosa: propafenona
Hepatitis colestásica: propafenona
Reacciones alérgicas de la piel: propafenona
Lupus eritematoso: propafenona
Reacción de hipersensibilidad: asenapina
Con base en sus respuestas e información científica, evaluamos el riesgo individual de efectos secundarios adversos. Estas recomendaciones están destinadas a asesorar a los profesionales y no sustituyen la consulta con un médico. En la versión de prueba restringida (alfa), el riesgo de todas las sustancias aún no se ha evaluado de manera concluyente.
Abstract: Propafenone is a class 1C antiarrhythmic agent which is administered as a racemate of S(+)- and R(-)-enantiomers. It is well absorbed and is predominantly bound to alpha 1-acid glycoprotein in the plasma. The enantiomers display stereoselective disposition characteristics, the R-enantiomer being cleared more quickly. The hepatic metabolism of propafenone is polymorphic and genetically determined: about 10% of Caucasians have a reduced capacity to hydroxylate the drug. This polymorphic metabolism accounts for the marked interindividual variability in the relationships between dose and concentration, and between concentration and pharmacodynamic effects. During long term administration, the metabolism is saturable in patients with the 'extensive metaboliser' phenotype, leading to accumulation of the parent compound. Propafenone blocks fast inward sodium channels in a frequency-dependent manner, and also has moderate beta-blocking effects. Both the enantiomers and the 5-OH metabolite have a potency to block sodium channels comparable with that of the parent compound. The S-enantiomer is a more potent beta-antagonist than the R-enantiomer. Propafenone typically slows conduction markedly but only modestly prolongs refractoriness. These cardiac effects are determined by the extent of its myocardial accumulation. The drug should be used with caution in patients with serious structural heart disease, as it may cause or aggravate life-threatening arrhythmias. Significant interactions occur when propafenone is coadministered with other drugs. It increases the plasma concentrations of digoxin, warfarin, metoprolol and propranolol as well as enhancing their respective pharmacodynamic effects. Doses of these drugs should therefore be decreased if they are coadministered with propafenone.
Abstract: The pharmacokinetics of oral and i.v. propafenone and its major metabolites have been investigated in 8 healthy subjects. The total body clearance of propafenone was 963 ml/min, the terminal half-life 198 min and its absolute bioavailability was 15.5%. The two active metabolites (5-hydroxypropafenone and N-depropylpropafenone) showed non-linear kinetics in that both the dose-corrected area under the serum concentration-time curve and the amount excreted in the urine were larger after oral dosing. This resulted in considerably higher serum concentrations of the metabolites despite comparable serum concentrations of the parent compound. Thus, the concentration-effect relationship in the same patient may differ after oral and intravenous doses if concentrations of the active metabolite(s) are not taken into consideration. Although the mechanism of the nonlinearity is not clear, the data indicate that it may be due to saturable biliary excretion of the metabolites.
Abstract: Twenty-nine drugs of disparate structures and physicochemical properties were used in an examination of the capability of human liver microsomal lability data ("in vitro T(1/2)" approach) to be useful in the prediction of human clearance. Additionally, the potential importance of nonspecific binding to microsomes in the in vitro incubation milieu for the accurate prediction of human clearance was investigated. The compounds examined demonstrated a wide range of microsomal metabolic labilities with scaled intrinsic clearance values ranging from less than 0.5 ml/min/kg to 189 ml/min/kg. Microsomal binding was determined at microsomal protein concentrations used in the lability incubations. For the 29 compounds studied, unbound fractions in microsomes ranged from 0.11 to 1.0. Generally, basic compounds demonstrated the greatest extent of binding and neutral and acidic compounds the least extent of binding. In the projection of human clearance values, basic and neutral compounds were well predicted when all binding considerations (blood and microsome) were disregarded, however, including both binding considerations also yielded reasonable predictions. Including only blood binding yielded very poor projections of human clearance for these two types of compounds. However, for acidic compounds, disregarding all binding considerations yielded poor predictions of human clearance. It was generally most difficult to accurately predict clearance for this class of compounds; however the accuracy was best when all binding considerations were included. Overall, inclusion of both blood and microsome binding values gave the best agreement between in vivo clearance values and clearance values projected from in vitro intrinsic clearance data.
Abstract: OBJECTIVE: A clinical study on enzyme induction in elderly subjects was performed by investigation of the effect of rifampin (INN, rifampicin) on propafenone disposition. Propafenone was chosen as a model drug because of its complex metabolism that permits the simultaneous in vivo assessment of induction of phase 1 and phase 2 pathways. METHODS: Six extensive metabolizers of CYP2D6 (age, 70.5 +/- 3.5 years) ingested 600 mg rifampin once daily for 9 consecutive days. One day before the first rifampin dose and on the day of the last rifampin dose, each elderly individual received a single intravenous infusion of 70 mg unlabeled propafenone and received a single oral dose of 300 mg deuterated propafenone 2 hours later. Pharmacokinetics and pharmacodynamics of propafenone were compared before and during induction. RESULTS: Maximum QRS prolongation after oral propafenone was decreased significantly by rifampin (18% +/- 5% versus 6% +/- 3%; P < .01). There were no substantial differences in pharmacokinetics and pharmacodynamics of intravenous propafenone during induction. However, bioavailability of propafenone dropped from 30% +/- 24% to 4% +/- 3% (P < .05). After oral propafenone was administered, clearances through N-dealkylation (6 +/- 3 mL/min versus 26 +/- 16 mL/min; P < .05) and glucuronidation (178 +/- 75 mL/min versus 739 +/- 533 mL/min; P < .05), but not 5-hydroxylation, were increased by rifampin, indicating substantial enzyme induction. CONCLUSIONS: Both phase 1 and phase 2 pathways of propafenone metabolism were induced by rifampin in elderly subjects, resulting in a clinically relevant drug interaction.
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: Predicting the pharmacokinetics of highly protein-bound drugs is difficult. Also, since historical plasma protein binding data were often collected using unbuffered plasma, the resulting inaccurate binding data could contribute to incorrect predictions. This study uses a generic physiologically based pharmacokinetic (PBPK) model to predict human plasma concentration-time profiles for 22 highly protein-bound drugs. Tissue distribution was estimated from in vitro drug lipophilicity data, plasma protein binding and the blood: plasma ratio. Clearance was predicted with a well-stirred liver model. Underestimated hepatic clearance for acidic and neutral compounds was corrected by an empirical scaling factor. Predicted values (pharmacokinetic parameters, plasma concentration-time profile) were compared with observed data to evaluate the model accuracy. Of the 22 drugs, less than a 2-fold error was obtained for the terminal elimination half-life (t1/2 , 100% of drugs), peak plasma concentration (Cmax , 100%), area under the plasma concentration-time curve (AUC0-t , 95.4%), clearance (CLh , 95.4%), mean residence time (MRT, 95.4%) and steady state volume (Vss , 90.9%). The impact of fup errors on CLh and Vss prediction was evaluated. Errors in fup resulted in proportional errors in clearance prediction for low-clearance compounds, and in Vss prediction for high-volume neutral drugs. For high-volume basic drugs, errors in fup did not propagate to errors in Vss prediction. This is due to the cancellation of errors in the calculations for tissue partitioning of basic drugs. Overall, plasma profiles were well simulated with the present PBPK model. Copyright © 2016 John Wiley & Sons, Ltd.
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.