Extensión de tiempo QT
Efectos adversos de las drogas
Variantes ✨Para la evaluación computacionalmente intensiva de las variantes, elija la suscripción estándar paga.
Áreas de aplicación
Explicaciones para pacientes
No tenemos advertencias adicionales para la combinación de ciclosporina, alogliptin y ketoconazol. Consulte también la información especializada pertinente.
Los cambios en la exposición mencionados se refieren a cambios en la curva de concentración plasmática-tiempo [AUC]. La exposición a ciclosporina aumenta al 215%, cuando se combina con alogliptin (100%) y ketoconazol (215%). Esto puede provocar un aumento de los efectos secundarios. La exposición a ketoconazol aumenta al 137%, cuando se combina con ciclosporina (137%) y alogliptin (100%). La exposición a alogliptin aumenta al 107%, cuando se combina con ciclosporina (104%) y ketoconazol (107%).
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 ciclosporina tiene una baja biodisponibilidad oral [ F ] del 27%, por lo que el nivel plasmático máximo [Cmax] tiende a cambiar fuertemente con una interacción. La vida media terminal [ t12 ] es de 13.35 horas y se alcanzan niveles plasmáticos constantes [ Css ] después de aproximadamente 53.4 horas. La unión a proteínas [ Pb ] es 95.4% fuerte y el volumen de distribución [ Vd ] es muy grande a 92 litros, Dado que la sustancia tiene una tasa de extracción hepática baja de 0,9, el desplazamiento de la unión a proteínas [Pb] en el contexto de una interacción puede aumentar la exposición. El metabolismo tiene lugar principalmente a través de CYP3A4. y el transporte activo tiene lugar en particular a través de PGP.
La alogliptin tiene una alta biodisponibilidad oral [ F ] del 95%, por lo que los niveles plasmáticos máximos [Cmax] tienden a cambiar poco durante 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 débil al 20% y el volumen de distribución [ Vd ] es muy grande a 417 litros. Dado que la sustancia tiene una tasa de extracción hepática baja de 0,9, el desplazamiento de la unión a proteínas [Pb] en el contexto de una interacción puede aumentar la exposición. Aproximadamente el 65.5% de la dosis administrada se excreta inalterada a través de los riñones y esta proporción rara vez se modifica por las interacciones. El metabolismo tiene lugar a través de CYP2D6 y CYP3A4, entre otros..
La ketoconazol tiene una biodisponibilidad oral media [ F ] del 67%, por lo que los niveles plasmáticos máximos [Cmax] tienden a cambiar con una interacción. La vida media terminal [ t12 ] es bastante corta a las 5 horas y se alcanzan rápidamente niveles plasmáticos constantes [ Css ]. La unión a proteínas [ Pb ] es moderadamente fuerte al 91.5% y el volumen de distribución [ Vd ] es muy grande a 84 litros, Dado que la sustancia tiene una tasa de extracción hepática baja de 0,9, el desplazamiento de la unión a proteínas [Pb] en el contexto de una interacción puede aumentar la exposición. El metabolismo tiene lugar principalmente a través de CYP3A4. y el transporte activo tiene lugar en particular a través de PGP.
|Efectos serotoninérgicos a||0||Ø||Ø||Ø|
Clasificación: Según nuestro conocimiento, ni la ciclosporina, alogliptin ni la ketoconazol aumentan la actividad serotoninérgica.
|Kiesel & Durán b||0||Ø||Ø||Ø|
Clasificación: Según nuestros hallazgos, ni la alogliptin ni la ketoconazol aumentan la actividad anticolinérgica. El efecto anticolinérgico de ciclosporina no es relevante.
Extensión de tiempo QT
Recomendación: Asegúrese de minimizar los factores de riesgo influibles. Las alteraciones electrolíticas, como los bajos niveles de calcio, potasio y magnesio, deben compensarse. Se debe usar la dosis efectiva más baja de ketoconazol.
Clasificación: La ketoconazol puede prolongar potencialmente el tiempo QT y, si hay factores de riesgo, se pueden favorecer las arritmias del tipo torsades de pointes. No conocemos ningún potencial de prolongación del intervalo QT para ciclosporina y alogliptin.
Efectos secundarios generales
|Efectos secundarios||∑ frecuencia||cic||alo||ket|
|Dolor de cabeza||13.9 %||10.0↑||4.3||n.a.|
|Infeccion de las vias respiratorias altas||4.5 %||n.a.||4.5||n.a.|
Hiperpotasemia: ciclosporina, ketoconazol
Hipertrofia gingival: ciclosporina
Reacción de hipersensibilidad: alogliptin, ketoconazol
Leucoencefalopatía multifocal progresiva: ciclosporina
Sensación de ardor en el ojo: ciclosporina
Dolor en el ojo: ciclosporina
Sensacion de quemarse: ketoconazol
Síndrome de Stevens-Johnson: alogliptin
Insuficiencia suprarrenal: ketoconazol
Insuficiencia cardiaca: alogliptin
Arritmia ventricular: ketoconazol
Insuficiencia hepática: alogliptin
Síndrome urémico hemolítico: ciclosporina
Con base en sus
Referencias de literatura
Abstract: The pharmacokinetics of cyclosporine was studied in six healthy volunteers after administration of the drug orally (10 mg/kg) and intravenously (3 mg/kg) with and without concomitant rifampin administration. Both blood and plasma (separated at 37 degrees C) samples were analyzed for cyclosporine concentration. For blood and plasma, respectively, clearances of cyclosporine were calculated to be 0.30 and 0.55 L/hr/kg, values for volume of distribution at steady state were 1.31 and 1.68 L/kg, and bioavailabilities were 27% and 33% during the pre-rifampin phase. Post-rifampin phase clearances of cyclosporine were 0.42 and 0.79 L/hr/kg, values for volume of distribution at steady state were 1.36 and 1.35 L/kg, and bioavailabilities were 10% and 9% for blood and plasma, respectively. Rifampin not only induces the hepatic metabolism of cyclosporine but also decreases its bioavailability to a greater extent than would be predicted by the increased metabolism. The decreased bioavailability most probably can be explained by an induction of intestinal cytochrome P450 enzymes, which appears to be markedly greater than the induction of hepatic metabolism.
Abstract: 1. The pharmacokinetics of cyclosporine (CsA) and the time course of CsA metabolites were studied in five bone marrow transplant patients after intravenous (i.v.) administration on two separate occasions and once after oral CsA administration. 2. Cyclosporine and cyclosporine metabolites were measured in whole blood by h.p.l.c. 3. Cyclosporine clearance after i.v. administration decreased from 3.9 +/- 1.7 ml min-1 kg-1 to 2.0 +/- 0.6 ml min-1 kg-1 after 14 days of treatment. The mean +/- s.d. absolute oral bioavailability of cyclosporine was 17 +/- 11%. 4. Hydroxylated CsA (M-17) was the major metabolite in blood. There were no significant differences in the mean metabolite/CsA AUC ratios between the first and second i.v. studies. 5. After oral administration, the metabolite to CsA AUC ratios were higher for most metabolites compared to those observed in the second i.v. study, suggesting a contribution of intestinal metabolism to the clearance of CsA.
Abstract: Extensive pharmacokinetic (PK) profiles after oral dosing of 300 mg cyclosporin A (CsA) were determined in whole blood by radioimmunoassay (RIA) in 14 healthy male volunteers, using two-compartment models with either first order (M1) or zero order (M0) absorption. According to zero order absorption the mean of the following PK parameters was determined: terminal half-life = 12.1 +/- 5.0 h, apparent volume of distribution at steady-state = 5.6 +/- 2.11 X kg-1, apparent clearance = 0.51 +/- 0.11 l X h-1 X kg-1. The time lag between drug ingestion and first blood level was short, 0.38 +/- 0.11 h. Drug absorption lasted for 2.8 +/- 1.6 h. The end of absorption was indicated in each individual by a sharp drop in blood levels. The observations support the assumption that CsA is absorbed in the upper part of the small intestine with a clear-cut termination (absorption window). This assumption may explain the high degree of variability in the bioavailability of CsA.
Abstract: Cyclosporine and tacrolimus share the same pharmacodynamic property of activated T-cell suppression via inhibition of calcineurin. The introduction of these drugs to the immunosuppressive repertoire of transplant management has greatly improved the outcomes in organ transplantation and constitutes arguably one of the major breakthroughs in modern medicine. To this date, calcineurin inhibitors are the mainstay of prevention of allograft rejection. The experience gained from the laboratory and clinical use of cyclosporine and tacrolimus has greatly advanced our knowledge about the nature of many aspects of immune response. However, the clinical practice still struggles with the shortcomings of these drugs: the significant inter- and intraindividual variability of their pharmacokinetics, the unpredictability of their pharmacodynamic effects, as well as complexity of interactions with other agents in transplant recipients. This article briefly reviews the pharmacological aspects of calcineurin antagonists as they relate to the mode of action and pharmacokinetics as well as drug interactions and monitoring.
Abstract: Ketoconazole is not known to be proarrhythmic without concomitant use of QT interval-prolonging drugs. We report a woman with coronary artery disease who developed a markedly prolonged QT interval and torsades de pointes (TdP) after taking ketoconazole for treatment of fungal infection. Her QT interval returned to normal upon withdrawal of ketoconazole. Genetic study did not find any mutation in her genes that encode cardiac IKr channel proteins. We postulate that by virtue of its direct blocking action on IKr, ketoconazole alone may prolong QT interval and induce TdP. This calls for attention when ketoconazole is administered to patients with risk factors for acquired long QT syndrome.
Abstract: OBJECTIVE: To investigate the effect of efavirenz on the ketoconazole pharmacokinetics in HIV-infected patients. METHODS: Twelve HIV-infected patients were assigned into a one-sequence, two-period pharmacokinetic interaction study. In phase one, the patients received 400 mg of ketoconazole as a single oral dose on day 1; in phase two, they received 600 mg of efavirenz once daily in combination with 150 mg of lamivudine and 30 or 40 mg of stavudine twice daily on days 2 to 16. On day 16, 400 mg of ketoconazole was added to the regimen as a single oral dose. Ketoconazole pharmacokinetics were studied on days 1 and 16. RESULTS: Pretreatment with efavirenz significantly increased the clearance of ketoconazole by 201%. C(max) and AUC(0-24) were significantly decreased by 44 and 72%, respectively. The T ((1/2)) was significantly shorter by 58%. CONCLUSION: Efavirenz has a strong inducing effect on the metabolism of ketoconazole.
Abstract: AIMS: To investigate the interaction between ketoconazole and darunavir (alone and in combination with low-dose ritonavir), in HIV-healthy volunteers. METHODS: Volunteers received darunavir 400 mg bid and darunavir 400 mg bid plus ketoconazole 200 mg bid, in two sessions (Panel 1), or darunavir/ritonavir 400/100 mg bid, ketoconazole 200 mg bid and darunavir/ritonavir 400/100 mg bid plus ketoconazole 200 mg bid, over three sessions (Panel 2). Treatments were administered with food for 6 days. Steady-state pharmacokinetics following the morning dose on day 7 were compared between treatments. Short-term safety and tolerability were assessed. RESULTS: Based on least square means ratios (90% confidence intervals), during darunavir and ketoconazole co-administration, darunavir area under the curve (AUC(12h)), maximum plasma concentration (C(max)) and minimum plasma concentration (C(min)) increased by 155% (80, 261), 78% (28, 147) and 179% (58, 393), respectively, compared with treatment with darunavir alone. Darunavir AUC(12h), C(max) and C(min) increased by 42% (23, 65), 21% (4, 40) and 73% (39, 114), respectively, during darunavir/ritonavir and ketoconazole co-administration, relative to darunavir/ritonavir treatment. Ketoconazole pharmacokinetics was unchanged by co-administration with darunavir alone. Ketoconazole AUC(12h), C(max) and C(min) increased by 212% (165, 268), 111% (81, 144) and 868% (544, 1355), respectively, during co-administration with darunavir/ritonavir compared with ketoconazole alone. CONCLUSIONS: The increase in darunavir exposure by ketoconazole was lower than that observed previously with ritonavir. A maximum ketoconazole dose of 200 mg day(-1) is recommended if used concomitantly with darunavir/ritonavir, with no dose adjustments for darunavir/ritonavir.
Abstract: Although therapeutic drug monitoring (TDM) of immunosuppressive drugs has been an integral part of routine clinical practice in solid organ transplantation for many years, ongoing research in the field of immunosuppressive drug metabolism, pharmacokinetics, pharmacogenetics, pharmacodynamics, and clinical TDM keeps yielding new insights that might have future clinical implications. In this review, the authors will highlight some of these new insights for the calcineurin inhibitors (CNIs) cyclosporine and tacrolimus and the antimetabolite mycophenolic acid (MPA) and will discuss the possible consequences. For CNIs, important relevant lessons for TDM can be learned from the results of 2 recently published large CNI minimization trials. Furthermore, because acute rejection and drug-related adverse events do occur despite routine application of CNI TDM, alternative approaches to better predict the dose-concentration-response relationship in the individual patient are being explored. Monitoring of CNI concentrations in lymphocytes and other tissues, determination of CNI metabolites, and CNI pharmacogenetics and pharmacodynamics are in their infancy but have the potential to become useful additions to conventional CNI TDM. Although MPA is usually administered at a fixed dose, there is a rationale for MPA TDM, and this is substantiated by the increasing knowledge of the many nongenetic and genetic factors contributing to the interindividual and intraindividual variability in MPA pharmacokinetics. However, recent, large, randomized clinical trials investigating the clinical utility of MPA TDM have reported conflicting data. Therefore, alternative pharmacokinetic (ie, MPA free fraction and metabolites) and pharmacodynamic approaches to better predict drug efficacy and toxicity are being explored. Finally, for MPA and tacrolimus, novel formulations have become available. For MPA, the differences in pharmacokinetic behavior between the old and the novel formulation will have implications for TDM, whereas for tacrolimus, this probably will not to be the case.
Abstract: Organic anion transporting polypeptide (OATP) family transporters accept a number of drugs and are increasingly being recognized as important factors in governing drug and metabolite pharmacokinetics. OATP1B1 and OATP1B3 play an important role in hepatic drug uptake while OATP2B1 and OATP1A2 might be key players in intestinal absorption and transport across blood-brain barrier of drugs, respectively. To understand the importance of OATPs in the hepatic clearance of drugs, the rate-determining process for elimination should be considered; for some drugs, hepatic uptake clearance rather than metabolic intrinsic clearance is the more important determinant of hepatic clearances. The importance of the unbound concentration ratio (liver/blood), K(p,uu) , of drugs, which is partly governed by OATPs, is exemplified in interpreting the difference in the IC(50) of statins between the hepatocyte and microsome systems for the inhibition of HMG-CoA reductase activity. The intrinsic activity and/or expression level of OATPs are affected by genetic polymorphisms and drug-drug interactions. Their effects on the elimination rate or intestinal absorption rate of drugs may sometimes depend on the substrate drug. This is partly because of the different contribution of OATP isoforms to clearance or intestinal absorption. When the contribution of the OATP-mediated pathway is substantial, the pharmacokinetics of substrate drugs should be greatly affected. This review describes the estimation of the contribution of OATP1B1 to the total hepatic uptake of drugs from the data of fold-increases in the plasma concentration of substrate drugs by the genetic polymorphism of this transporter. To understand the importance of the OATP family transporters, modeling and simulation with a physiologically based pharmacokinetic model are helpful.
Abstract: BACKGROUND: Anticholinergic drugs are often involved in explicit criteria for inappropriate prescribing in older adults. Several scales were developed for screening of anticholinergic drugs and estimation of the anticholinergic burden. However, variation exists in scale development, in the selection of anticholinergic drugs, and the evaluation of their anticholinergic load. This study aims to systematically review existing anticholinergic risk scales, and to develop a uniform list of anticholinergic drugs differentiating for anticholinergic potency. METHODS: We performed a systematic search in MEDLINE. Studies were included if provided (1) a finite list of anticholinergic drugs; (2) a grading score of anticholinergic potency and, (3) a validation in a clinical or experimental setting. We listed anticholinergic drugs for which there was agreement in the different scales. In case of discrepancies between scores we used a reputed reference source (Martindale: The Complete Drug Reference®) to take a final decision about the anticholinergic activity of the drug. RESULTS: We included seven risk scales, and evaluated 225 different drugs. Hundred drugs were listed as having clinically relevant anticholinergic properties (47 high potency and 53 low potency), to be included in screening software for anticholinergic burden. CONCLUSION: Considerable variation exists among anticholinergic risk scales, in terms of selection of specific drugs, as well as of grading of anticholinergic potency. Our selection of 100 drugs with clinically relevant anticholinergic properties needs to be supplemented with validated information on dosing and route of administration for a full estimation of the anticholinergic burden in poly-medicated older adults.
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: All pharmaceutical companies are required to assess pharmacokinetic drug-drug interactions (DDIs) of new chemical entities (NCEs) and mathematical prediction helps to select the best NCE candidate with regard to adverse effects resulting from a DDI before any costly clinical studies. Most current models assume that the liver is a homogeneous organ where the majority of the metabolism occurs. However, the circulatory system of the liver has a complex hierarchical geometry which distributes xenobiotics throughout the organ. Nevertheless, the lobule (liver unit), located at the end of each branch, is composed of many sinusoids where the blood flow can vary and therefore creates heterogeneity (e.g. drug concentration, enzyme level). A liver model was constructed by describing the geometry of a lobule, where the blood velocity increases toward the central vein, and by modeling the exchange mechanisms between the blood and hepatocytes. Moreover, the three major DDI mechanisms of metabolic enzymes; competitive inhibition, mechanism based inhibition and induction, were accounted for with an undefined number of drugs and/or enzymes. The liver model was incorporated into a physiological-based pharmacokinetic (PBPK) model and simulations produced, that in turn were compared to ten clinical results. The liver model generated a hierarchy of 5 sinusoidal levels and estimated a blood volume of 283 mL and a cell density of 193 × 106 cells/g in the liver. The overall PBPK model predicted the pharmacokinetics of midazolam and the magnitude of the clinical DDI with perpetrator drug(s) including spatial and temporal enzyme levels changes. The model presented herein may reduce costs and the use of laboratory animals and give the opportunity to explore different clinical scenarios, which reduce the risk of adverse events, prior to costly human clinical studies.
Abstract: Programmed cell death, which occurs through a conserved core molecular pathway, is important for fundamental developmental and homeostatic processes. The human iron-sulfur binding protein NAF-1/CISD2 binds to Bcl-2 and its disruption in cells leads to an increase in apoptosis. Other members of the CDGSH iron sulfur domain (CISD) family include mitoNEET/CISD1 and Miner2/CISD3. In humans, mutations in CISD2 result in Wolfram syndrome 2, a disease in which the patients display juvenile diabetes, neuropsychiatric disorders and defective platelet aggregation. The C. elegans genome contains three previously uncharacterized cisd genes that code for CISD-1, which has homology to mitoNEET/CISD1 and NAF-1/CISD2, and CISD-3.1 and CISD-3.2, both of which have homology to Miner2/CISD3. Disrupting the function of the cisd genes resulted in various germline abnormalities including distal tip cell migration defects and a significant increase in the number of cell corpses within the adult germline. This increased germ cell death is blocked by a gain-of-function mutation of the Bcl-2 homolog CED-9 and requires functional caspase CED-3 and the APAF-1 homolog CED-4. Furthermore, the increased germ cell death is facilitated by the pro-apoptotic, CED-9-binding protein CED-13, but not the related EGL-1 protein. This work is significant because it places the CISD family members as regulators of physiological germline programmed cell death acting through CED-13 and the core apoptotic machinery.