Prolongación del tiempo QT
Eventos adversos de medicamentos
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 abarelix y efavirenz. Consulte también la información especializada pertinente.
|Efavirenz||1 [1,1.73] 1||1|
Los cambios informados en la exposición corresponden a los cambios en la curva de concentración plasmática-tiempo [ AUC ]. No esperamos ningún cambio en la exposición a abarelix, cuando se combina con efavirenz (100%). No esperamos ningún cambio en la exposición a efavirenz, cuando se combina con abarelix (100%). El AUC se encuentra entre 0 % y 100 % dependiendo del
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.
Se desconoce la biodisponibilidad de la abarelix. La vida media terminal [ t12 ] es relativamente extensa a las 316.8 horas y los niveles plasmáticos constantes [ Css ] sólo se alcanzan después de más de 1267.2 horas. La unión a proteínas [ Pb ] es 100 % fuerte. Actualmente, se sigue trabajando en el metabolismo por citocromos.
La efavirenz tiene una biodisponibilidad oral media [ F ] del 100 %, por lo que los niveles plasmáticos máximos [Cmax] tienden a cambiar con una interacción. La vida media terminal [ t12 ] es relativamente extensa a las 47.5 horas y los niveles plasmáticos constantes [ Css ] sólo se alcanzan después de más de 190 horas. La unión a proteínas [ Pb ] es muy fuerte al 100 % y el volumen de distribución [ Vd ] es muy grande a 184 litros, El metabolismo tiene lugar a través de CYP1A2, CYP2B6 y CYP3A4, entre otros y el transporte activo tiene lugar en parte a través de BCRP y UGT2B7.
|Efectos serotoninérgicos a||0||Ø||Ø|
Clasificación: Según nuestro conocimiento, ni la abarelix ni la efavirenz aumentan la actividad serotoninérgica.
|Kiesel & Durán b||0||Ø||Ø|
Clasificación: Según nuestro conocimiento, ni la abarelix ni la efavirenz aumentan la actividad anticolinérgica.
Prolongación del tiempo QT
Clasificación: En combinación, la abarelix y la efavirenz pueden desencadenar potencialmente arritmias ventriculares del tipo torsades de pointes.
Efectos adversos generales
|Efectos secundarios||∑ frecuencia||aba||efa|
|Dolor de cabeza||5.7 %||n.a.||5.7|
ALT elevado: efavirenz
AST elevado: efavirenz
Elevado GGT: efavirenz
Insuficiencia hepática: efavirenz
Trastorno del sueño: efavirenz
Eritema multiforme: efavirenz
Síndrome de Stevens-Johnson: efavirenz
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: Efavirenz is a non-nucleoside reverse transcriptase inhibitor (NNRTI) which shows good inhibitory activity against HIV-1. Reduced susceptibility to efavirenz has been reported with HIV-1 variants containing single and multiple mutations to the reverse transcriptase enzyme. In vitro and in vivo data suggest that the resistance profile of efavirenz overlaps with that of the NNRTIs nevirapine and delavirdine. Clinically significant drug interactions have been reported with efavirenz and indinavir and saquinavir. An increase in dosage of indinavir from 800 to 1000 mg 3 times daily is recommended during coadministration with efavirenz. Use of efavirenz in combination with saquinavir as the sole protease inhibitor is not recommended. Once-daily efavirenz in combination with zidovudine plus lamivudine or indinavir or nelfinavir increased CD4+ cell counts and reduced HIV RNA plasma levels to below quantifiable levels (< 400 copies/ml) in HIV-infected patients. A sustained reduction in viral load was maintained for at least 72 weeks in 1 study. Nervous system symptoms (including headache, dizziness, insomnia and fatigue) and dermatological effects (including maculopapular rash) appear to be the most common adverse events reported with efavirenz-containing antiretroviral regimens.
Abstract: OBJECTIVE: To report a case of acquired long QT syndrome that, after exclusion of all other possible causes, was probably related to therapy with efavirenz, a novel nonnucleoside reverse transcriptase inhibitor. CASE SUMMARY: This patient presented with recurrent syncope and polymorphic ventricular tachycardia, which was treated with overdrive ventricular pacing and was eliminated by discontinuation of the offending drug. DISCUSSION: This is the first reported case of QT prolongation and severe ventricular arrhythmia associated with the use of efavirenz. The temporal relationship between the initiation of treatment and the onset of electrocardiographic abnormalities, the absence of other apparent precipitating factors, as well as the normalization of QT interval and the resolution of the arrhythmia after discontinuation of the drug, strongly suggest a causal relationship between efavirenz and this adverse clinical event. CONCLUSIONS: Our case shows that any new pharmaceutical compound introduced in clinical practice may potentially result in QT prolongation and life-threatening arrhythmia.
Abstract: OBJECTIVE: The reverse transcriptase inhibitor efavirenz is currently used at a fixed dose of 600 mg/d. However, dosage individualization based on plasma concentration monitoring might be indicated. This study aimed to assess the efavirenz pharmacokinetic profile and interpatient versus intrapatient variability in patients who are positive for human immunodeficiency virus, to explore the relationship between drug exposure, efficacy, and central nervous system toxicity and to build up a Bayesian approach for dosage adaptation. METHODS: The population pharmacokinetic analysis was performed by use of NONMEM based on plasma samples from a cohort of unselected patients receiving efavirenz. With the use of a 1-compartment model with first-order absorption, the influence of demographic and clinical characteristics on oral clearance and oral volume of distribution was examined. The average drug exposure during 1 dosing interval was estimated for each patient and correlated with markers of efficacy and toxicity. The population kinetic parameters and the variabilities were integrated into a Bayesian equation for dosage adaptation based on a single plasma sample. RESULTS: Data from 235 patients with a total of 719 efavirenz concentrations were collected. Oral clearance was 9.4 L/h, oral volume of distribution was 252 L, and the absorption rate constant was 0.3 h(-1). Neither the demographic covariates evaluated nor the comedications showed a clinically significant influence on efavirenz pharmacokinetics. A large interpatient variability was found to affect efavirenz relative bioavailability (coefficient of variation, 54.6%), whereas the intrapatient variability was small (coefficient of variation, 26%). An inverse correlation between average drug exposure and viral load and a trend with central nervous system toxicity were detected. This enabled the derivation of a dosing adaptation strategy suitable to bring the average concentration into a therapeutic target from 1000 to 4000 microg/L to optimize viral load suppression and to minimize central nervous system toxicity. CONCLUSIONS: The high interpatient and low intrapatient variability values, as well as the potential relationship with markers of efficacy and toxicity, support the therapeutic drug monitoring of efavirenz. However, further evaluation is needed before individualization of an efavirenz dosage regimen based on routine drug level monitoring should be recommended for optimal patient management.
Abstract: There are few data on the use of highly active antiretroviral therapy in HIV-positive patients with end-stage renal disease. We describe the tolerability, safety and efficacy of an efavirenz-containing regimen in one such patient on continuous ambulatory peritoneal dialysis.
Abstract: Drug-drug interactions involving efavirenz are of major concern in clinical practice. We evaluated the effects of multiple doses of efavirenz on omeprazole 5-hydroxylation (CYP2C19) and sulfoxidation (CYP3A). Healthy volunteers (n = 57) were administered a single 20 mg oral dose of racemic omeprazole either with a single 600 mg oral dose of efavirenz or after 17 days of administration of 600 mg/day of efavirenz. The concentrations of racemic omeprazole, 5-hydroxyomeoprazole (and their enantiomers), and omeprazole sulfone in plasma were measured using a chiral liquid chromatography-tandem mass spectrometry method. Relative to single-dose treatment, multiple doses of efavirenz significantly decreased (P < 0.0001) the area under the plasma concentration-time curve from 0 to infinity (AUC(0-∞)) of racemic-, R- and S-omeprazole (2.01- to 2.15-fold) and the corresponding AUC(0-∞) metabolic ratio (MR) for 5-hydroxyomeprazole (1.36- to 1.44-fold) as well as the MR for omeprazole sulfone (∼2.0) (P < 0.0001). The significant reduction in the AUC of 5-hydroxyomeprazole after repeated efavirenz dosing suggests induction of sequential metabolism and mixed inductive/inhibitory effects of efavirenz on CYP2C19. In conclusion, efavirenz enhances omeprazole metabolism in a nonstereoselective manner through induction of CYP3A and CYP2C19 activity.
Abstract: In this study, we present efavirenz physiologically based pharmacokinetic (PBPK) model development as an example of our best practice approach that uses a stepwise approach to verify the different components of the model. First, a PBPK model for efavirenz incorporating in vitro and clinical pharmacokinetic (PK) data was developed to predict exposure following multiple dosing (600 mg q.d.). Alfentanil i.v. and p.o. drug-drug interaction (DDI) studies were utilized to evaluate and refine the CYP3A4 induction component in the liver and gut. Next, independent DDI studies with substrates of CYP3A4 (maraviroc, atazanavir, and clarithromycin) and CYP2B6 (bupropion) verified the induction components of the model (area under the curve [AUC] ratios within 1.0-1.7-fold of observed). Finally, the model was refined to incorporate the fractional contribution of enzymes, including CYP2B6, propagating autoinduction into the model (Racc 1.7 vs. 1.7 observed). This validated mechanistic model can now be applied in clinical pharmacology studies to prospectively assess both the victim and perpetrator DDI potential of efavirenz.
Abstract: BACKGROUND: Antiretroviral drugs are among the therapeutic agents with the highest potential for drug-drug interactions (DDIs). In the absence of clinical data, DDIs are mainly predicted based on preclinical data and knowledge of the disposition of individual drugs. Predictions can be challenging, especially when antiretroviral drugs induce and inhibit multiple cytochrome P450 (CYP) isoenzymes simultaneously. METHODS: This study predicted the magnitude of the DDI between efavirenz, an inducer of CYP3A4 and inhibitor of CYP2C8, and dual CYP3A4/CYP2C8 substrates (repaglinide, montelukast, pioglitazone, paclitaxel) using a physiologically based pharmacokinetic (PBPK) modeling approach integrating concurrent effects on CYPs. In vitro data describing the physicochemical properties, absorption, distribution, metabolism, and elimination of efavirenz and CYP3A4/CYP2C8 substrates as well as the CYP-inducing and -inhibitory potential of efavirenz were obtained from published literature. The data were integrated in a PBPK model developed using mathematical descriptions of molecular, physiological, and anatomical processes defining pharmacokinetics. Plasma drug-concentration profiles were simulated at steady state in virtual individuals for each drug given alone or in combination with efavirenz. The simulated pharmacokinetic parameters of drugs given alone were compared against existing clinical data. The effect of efavirenz on CYP was compared with published DDI data. RESULTS: The predictions indicate that the overall effect of efavirenz on dual CYP3A4/CYP2C8 substrates is induction of metabolism. The magnitude of induction tends to be less pronounced for dual CYP3A4/CYP2C8 substrates with predominant CYP2C8 metabolism. CONCLUSION: PBPK modeling constitutes a useful mechanistic approach for the quantitative prediction of DDI involving simultaneous inducing or inhibitory effects on multiple CYPs as often encountered with antiretroviral drugs.
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.