Resumen
79%
Farmacocinética
|
-3% | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|
Amiodarona | |||||||||||
Itraconazol |
Puntuaciones | -8% | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|
Extensión de tiempo QT
| |||||||||||
Efectos anticolinérgicos
| |||||||||||
Efectos serotoninérgicos
|
Efectos adversos de las drogas
|
-10% | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|
Náusea | |||||||||||
Vómitos | |||||||||||
Hipotiroidismo |
Variantes ✨
Para la evaluación computacionalmente intensiva de las variantes, elija la suscripción estándar paga.
Farmacocinética
-3%
∑ Exposicióna | ami | itr | |
---|---|---|---|
Amiodarona | n.a. | n.a. | |
Itraconazol | 2.08 | 2.08 |
Leyenda (n.a.): Información no disponible
Los cambios en la exposición mencionados se refieren a cambios en la curva de concentración plasmática-tiempo [AUC]. No detectamos ningún cambio en la exposición a amiodarona. Actualmente no podemos estimar la influencia de la itraconazol. La exposición a itraconazol aumenta al 208%, cuando se combina con amiodarona (208%). Esto puede provocar un aumento de los efectos secundarios.
Clasificación:
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 amiodarona tiene una biodisponibilidad oral media [ F ] del 55%, por lo que los niveles plasmáticos máximos [Cmax] tienden a cambiar con una interacción. La vida media terminal [ t12 ] es bastante larga a las 1884 horas y los niveles plasmáticos constantes [ Css ] solo se alcanzan después de más de 7536 horas. La unión a proteínas [ Pb ] es 96% fuerte. El metabolismo tiene lugar a través de CYP2C8 y CYP3A4, entre otros. y el transporte activo tiene lugar en particular a través de PGP.
La itraconazol tiene una biodisponibilidad oral media [ F ] del 55%, por lo que los niveles plasmáticos máximos [Cmax] tienden a cambiar con una interacción. La vida media terminal [ t12 ] es de 21 horas y se alcanzan niveles plasmáticos constantes [ Css ] después de aproximadamente 84 horas. La unión a proteínas [ Pb ] es muy fuerte al 99.8% y el volumen de distribución [ Vd ] es muy grande a 796 litros, por eso, con una tasa de extracción hepática media de 0,9, tanto el flujo sanguíneo hepático [Q] como un cambio en la unión a proteínas [Pb] son relevantes. El metabolismo tiene lugar principalmente a través de CYP3A4. y el transporte activo tiene lugar en particular a través de PGP.
Efectos serotoninérgicos
-0%
Puntuaciones | ∑ Puntos | ami | itr |
---|---|---|---|
Efectos serotoninérgicos a | 0 | Ø | Ø |
Clasificación: Según nuestro conocimiento, ni la amiodarona ni la itraconazol aumentan la actividad serotoninérgica.
Efectos anticolinérgicos
-0%
Puntuaciones | ∑ Puntos | ami | itr |
---|---|---|---|
Kiesel b | 0 | Ø | Ø |
Clasificación: Según nuestros hallazgos, ni la amiodarona ni la itraconazol aumentan la actividad anticolinérgica.
Extensión de tiempo QT
-9%
Puntuaciones | ∑ Puntos | ami | itr |
---|---|---|---|
RISK-PATH c | 3.25 | +++ | + |
Recomendación:
Para poder evaluar el riesgo individual de arritmias, le recomendamos que responda las siguientes
Clasificación: En combinación, la amiodarona y la itraconazol pueden desencadenar potencialmente arritmias ventriculares del tipo torsades de pointes.
Efectos secundarios generales
-10%
Efectos secundarios | ∑ frecuencia | ami | itr |
---|---|---|---|
Náusea | 27.0 % | 21.5 | 7.0↑ |
Vómitos | 25.4 % | 21.5 | 5.0↑ |
Hipotiroidismo | 10.0 % | 10.0 | n.a. |
Nasofaringitis | 9.0 % | n.a. | 9.0↑ |
Mareo | 8.9 % | 6.5 | 2.6↑ |
Infeccion de las vias respiratorias altas | 8.0 % | n.a. | 8.0↑ |
Fotosensibilidad | 6.5 % | 6.5 | n.a. |
Estreñimiento | 6.5 % | 6.5 | n.a. |
Pérdida de apetito | 6.5 % | 6.5 | n.a. |
Ataxia | 6.5 % | 6.5 | n.a. |
Signo (+): efecto adverso descrito, pero frecuencia no conocida
Signo (↑/↓): frecuencia bastante más alta / más baja debido a la exposición
Neurológico
Problema de coordinación (6.5%): amiodarona
Parestesia (6.5%): amiodarona
Dolor de cabeza (6.1%): itraconazol
Neuropatía periférica: amiodarona
Pseudotumor cerebri: amiodarona
Oftalmológico
Visión borrosa (6.5%): amiodarona
Neuritis óptica: amiodarona
Pérdida visual: amiodarona
Dermatológico
Erupción (6%): itraconazol
Prurito (4%): itraconazol
Síndrome de Stevens-Johnson: amiodarona
Necrolisis epidérmica toxica: amiodarona
Respiratorio
Sinusitis (4.5%): itraconazol
Síndrome de distrés respiratorio agudo (2%): amiodarona
Fibrosis pulmonar: amiodarona
Edema pulmonar: itraconazol
Cardíaco
Edema periférico (4%): itraconazol
Hipertensión (3%): itraconazol
Hipotension: amiodarona
Bradicardia: amiodarona
Insuficiencia cardiaca: amiodarona, itraconazol
Arritmia ventricular: amiodarona
Gastrointestinal
Dolor abdominal (2.9%): itraconazol
Diarrea (2.9%): itraconazol
Pancreatitis: itraconazol
Sistémico
Fiebre (2.5%): itraconazol
Fatiga (2.3%): itraconazol
Endocrino
Hipertiroidismo (2%): amiodarona
Electrolitos
Hipopotasemia: itraconazol
Hiperpotasemia: itraconazol
Hematológico
Trombocitopenia: amiodarona
Hepático
Hepatotoxicidad: amiodarona, itraconazol
Inmunológico
Reacción de hipersensibilidad: amiodarona, itraconazol
Renal
Insuficiencia renal: amiodarona
Vascular
Vasculitis: amiodarona
Auricular
Pérdida de la audición: itraconazol
Limitaciones
Con base en sus
Referencias de literatura
Abstract: Amiodarone is considered to be safe in patients with prior QT prolongation and torsades de pointes taking class I antiarrhythmic agents who require continued antiarrhythmic drug therapy. However, the safety of amiodarone in advanced heart failure patients with a history of drug-induced torsades de pointes, who may be more susceptible to proarrhythmia, is unknown. Therefore, the objective of this study was to assess amiodarone safety and efficacy in heart failure patients with prior antiarrhythmic drug-induced torsades de pointes. We determined the history of torsades de pointes in 205 patients with heart failure treated with amiodarone, and compared the risk of sudden death in patients with and without such a history. To evaluate the possibility that all patients with a history of torsades de pointes would be at high risk for sudden death regardless of amiodarone treatment, we compared this risk in patients with a history of torsades de pointes who were and were not subsequently treated with amiodarone. Of 205 patients with advanced heart failure, 8 (4%) treated with amiodarone had prior drug-induced torsades de pointes. Despite similar severity of heart failure, the 1-year actuarial sudden death risk was markedly increased in amiodarone patients with than without prior torsades de pointes (55% vs 15%, p = 0.0001). Similarly, the incidence of 1-year sudden death was markedly increased in patients with prior torsades de pointes taking amiodarone compared with such patients who were not subsequently treated with amiodarone (55% vs 0%, p = 0.09).(ABSTRACT TRUNCATED AT 250 WORDS)
Abstract: No Abstract available
Abstract: Itraconazole (ITZ) is a potent inhibitor of CYP3A in vivo. However, unbound plasma concentrations of ITZ are much lower than its reported in vitro Ki, and no clinically significant interactions would be expected based on a reversible mechanism of inhibition. The purpose of this study was to evaluate the reasons for the in vitro-in vivo discrepancy. The metabolism of ITZ by CYP3A4 was studied. Three metabolites were detected: hydroxy-itraconazole (OH-ITZ), a known in vivo metabolite of ITZ, and two new metabolites: keto-itraconazole (keto-ITZ) and N-desalkyl-itraconazole (ND-ITZ). OHITZ and keto-ITZ were also substrates of CYP3A4. Using a substrate depletion kinetic approach for parameter determination, ITZ exhibited an unbound K(m) of 3.9 nM and an intrinsic clearance (CLint) of 69.3 ml.min(-1).nmol CYP3A4(-1). The respective unbound Km values for OH-ITZ and keto-ITZ were 27 nM and 1.4 nM and the CLint values were 19.8 and 62.5 ml.min(-1).nmol CYP3A4(-1). Inhibition of CYP3A4 by ITZ, OH-ITZ, keto-ITZ, and ND-ITZ was evaluated using hydroxylation of midazolam as a probe reaction. Both ITZ and OH-ITZ were competitive inhibitors of CYP3A4, with unbound Ki (1.3 nM for ITZ and 14.4 nM for OH-ITZ) close to their respective Km. ITZ, OH-ITZ, keto-ITZ and ND-ITZ exhibited unbound IC50 values of 6.1 nM, 4.6 nM, 7.0 nM, and 0.4 nM, respectively, when coincubated with human liver microsomes and midazolam (substrate concentration < Km). These findings demonstrate that ITZ metabolites are as potent as or more potent CYP3A4 inhibitors than ITZ itself, and thus may contribute to the inhibition of CYP3A4 observed in vivo after ITZ dosing.
Abstract: Itraconazole (ITZ) is metabolized in vitro to three inhibitory metabolites: hydroxy-itraconazole (OH-ITZ), keto-itraconazole (keto-ITZ), and N-desalkyl-itraconazole (ND-ITZ). The goal of this study was to determine the contribution of these metabolites to drug-drug interactions caused by ITZ. Six healthy volunteers received 100 mg ITZ orally for 7 days, and pharmacokinetic analysis was conducted at days 1 and 7 of the study. The extent of CYP3A4 inhibition by ITZ and its metabolites was predicted using this data. ITZ, OH-ITZ, keto-ITZ, and ND-ITZ were detected in plasma samples of all volunteers. A 3.9-fold decrease in the hepatic intrinsic clearance of a CYP3A4 substrate was predicted using the average unbound steady-state concentrations (C(ss,ave,u)) and liver microsomal inhibition constants for ITZ, OH-ITZ, keto-ITZ, and ND-ITZ. Accounting for circulating metabolites of ITZ significantly improved the in vitro to in vivo extrapolation of CYP3A4 inhibition compared to a consideration of ITZ exposure alone.
Abstract: PURPOSE: The objective is to confirm if the prediction of the drug-drug interaction using a physiologically based pharmacokinetic (PBPK) model is more accurate. In vivo Ki values were estimated using PBPK model to confirm whether in vitro Ki values are suitable. METHOD: The plasma concentration-time profiles for the substrate with coadministration of an inhibitor were collected from the literature and were fitted to the PBPK model to estimate the in vivo Ki values. The AUC ratios predicted by the PBPK model using in vivo Ki values were compared with those by the conventional method assuming constant inhibitor concentration. RESULTS: The in vivo Ki values of 11 inhibitors were estimated. When the in vivo Ki values became relatively lower, the in vitro Ki values were overestimated. This discrepancy between in vitro and in vivo Ki values became larger with an increase in lipophilicity. The prediction from the PBPK model involving the time profile of the inhibitor concentration was more accurate than the prediction by the conventional methods. CONCLUSION: A discrepancy between the in vivo and in vitro Ki values was observed. The prediction using in vivo Ki values and the PBPK model was more accurate than the conventional methods.
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: BACKGROUND: The most common acquired cause of Long QT syndrome (LQTS) is drug induced QT interval prolongation. It is an electrophysiological entity, which is characterized by an extended duration of the ventricular repolarization. Reflected as a prolonged QT interval in a surface ECG, this syndrome increases the risk for polymorphic ventricular tachycardia (Torsade de Pointes) and sudden death. METHOD: Bibliographic databases as MEDLINE and EMBASE, reports and drug alerts from several regulatory agencies (FDA, EMEA, ANMAT) and drug safety guides (ICH S7B, ICH E14) were consulted to prepare this article. The keywords used were: polymorphic ventricular tachycardia, adverse drug events, prolonged QT, arrhythmias, intensive care unit and Torsade de Pointes. Such research involved materials produced up to December 2017. RESULTS: Because of their mechanism of action, antiarrhythmic drugs such as amiodarone, sotalol, quinidine, procainamide, verapamil and diltiazem are associated to the prolongation of the QTc interval. For this reason, they require constant monitoring when administered. Other noncardiovascular drugs that are widely used in the Intensive Care Unit (ICU), such as ondansetron, macrolide and fluoroquinolone antibiotics, typical and atypical antipsychotics agents such as haloperidol, thioridazine, and sertindole are also frequently associated with the prolongation of the QTc interval. As a consequence, critical patients should be closely followed and evaluated. CONCLUSION: ICU patients are particularly prone to experience a QTc interval prolongation mainly for two reasons. In the first place, they are exposed to certain drugs that can prolong the repolarization phase, either by their mechanism of action or through the interaction with other drugs. In the second place, the risk factors for TdP are prevalent clinical conditions among critically ill patients. As a consequence, the attending physician is expected to perform preventive monitoring and ECG checks to control the QTc interval.
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: Amiodarone is one of the most commonly used antiarrhythmic drugs. Despite its well-known side effects, amiodarone is considered to be a relatively safe drug, especially in short-term usage to prevent life-threatening ventricular arrhythmias. Our case demonstrates an instance where short-term usage can yield drug side effect.