Extension de temps QT
Effets indésirables des médicaments
Variantes ✨Pour l'évaluation intensive en calcul des variantes, veuillez choisir l'abonnement standard payant.
Explications pour les patients
L'administration de phénytoïne et de voriconazole doit être évitée.
Diminution du voriconazole et augmentation des concentrations de phénytoïneMécanisme: Le voriconazole est un substrat du CYP2C19 et du CYP3A4 et un inhibiteur du CYP3A4, la phénytoïne est un inducteur du CYP2C19 et du CYP3A4. Cela peut conduire à des influences pharmacocinétiques mutuelles.
Effet: il faut s'attendre à ce que les concentrations de voriconazole soient considérablement réduites, et un échec thérapeutique peut même survenir. En association, les concentrations de phénytoïne peuvent également être augmentées avec un risque accru de symptômes toxiques tels que diplopie, nystagmus, nausées, vomissements, tremblements et étourdissements. La phénytoïne (300 mg une fois par jour) a diminué la Cmax et l'ASC du voriconazole de 49% et 69%, respectivement, dans les études du fabricant. Le voriconazole a augmenté la Cmax et l'ASC de la phénytoïne de 67% et 81%, respectivement.
Mesures: La combinaison doit être évitée si possible. Si l'association est cependant nécessaire, selon le fabricant (Vfend), la dose d'entretien intraveineuse de voriconazole en association avec la phénytoïne doit être de 5 mg / kg de poids corporel deux fois par jour, la dose d'entretien orale doit être de 400 mg deux fois par jour (ou 200 mg deux fois par jour chez les patients de poids corporel <40 kg). Les concentrations plasmatiques de phénytoïne doivent être étroitement surveillées.
|Voriconazole||0.31 [0.28,0.38] 1||1.55||0.28|
|Phénytoïne||1.52 [1.52,2.42] 2||1.42||1.1|
Les changements d'exposition mentionnés sont liés aux changements de la courbe concentration plasmatique en fonction du temps [ASC]. L'exposition à la voriconazole est réduite à 31%, lorsqu'il est associé à la cimétidine (155%) et à la phénytoïne (28%). L'ASC est comprise entre 28% et 38% selon le
Les paramètres pharmacocinétiques de la population moyenne sont utilisés comme point de départ pour calculer les changements individuels d'exposition dus aux interactions.
La voriconazole a une biodisponibilité orale élevée [ F ] de 88%, raison pour laquelle les concentrations plasmatiques maximales [Cmax] ont tendance à peu changer pendant une interaction. La demi-vie terminale [ t12 ] est assez courte à 6 heures et des taux plasmatiques constants [ Css ] sont atteints rapidement. La liaison aux protéines [ Pb ] est plutôt faible à 58% et le volume de distribution [ Vd ] est très important à 90 litres, Étant donné que la substance a un faible taux d'extraction hépatique de 0,9, le déplacement de la liaison aux protéines [Pb] dans le contexte d'une interaction peut augmenter l'exposition. Le métabolisme a lieu via le CYP2C19, CYP2C9 et le CYP3A4, entre autres.
La cimétidine a une biodisponibilité orale moyenne [ F ] de 65%, raison pour laquelle les concentrations plasmatiques maximales [Cmax] ont tendance à changer avec une interaction. La demi-vie terminale [ t12 ] est assez courte à 1.6333333 heures et des taux plasmatiques constants [ Css ] sont atteints rapidement. La liaison aux protéines [ Pb ] est très faible à 19% et le volume de distribution [ Vd ] est très important à 91 litres. Le métabolisme ne se fait pas via les cytochromes communs et le transport actif s'effectue en partie via BCRP et PGP.
La phénytoïne a une biodisponibilité orale élevée [ F ] de 85%, raison pour laquelle les concentrations plasmatiques maximales [Cmax] ont tendance à peu changer pendant une interaction. La demi-vie terminale [ t12 ] est de 13 heures et les taux plasmatiques constants [ Css ] sont atteints après environ 9 999 heures. La liaison aux protéines [ Pb ] est modérément forte à 90% et le volume de distribution [ Vd ] est de 47 litres dans la fourchette moyenne, Étant donné que la substance a un faible taux d'extraction hépatique de 0,9, le déplacement de la liaison aux protéines [Pb] dans le contexte d'une interaction peut augmenter l'exposition. Le métabolisme a lieu via le CYP2C19, CYP2C9 et le CYP2E1, entre autres et le transport actif se fait notamment via PGP.
|Les scores||∑ Points||vor||cim||phé|
|Effets sérotoninergiques a||0||Ø||Ø||Ø|
Évaluation: Selon nos connaissances, ni la voriconazole, cimétidine ni la phénytoïne n'augmentent l'activité sérotoninergique.
|Les scores||∑ Points||vor||cim||phé|
|Kiesel & Durán b||1||Ø||+||Ø|
Recommandation: Par mesure de précaution, une attention particulière doit être portée aux symptômes anticholinergiques, en particulier après augmentation de la dose et à des doses dans l'intervalle thérapeutique supérieur.
Évaluation: La cimétidine n'a qu'un effet léger sur le système anticholinergique. Le risque de syndrome anticholinergique avec ce médicament est plutôt faible si la posologie se situe dans la plage habituelle. Selon nos résultats, la voriconazole n'augmente pas l'activité anticholinergique. L'effet anticholinergique de la phénytoïne est insignifiant.
Extension de temps QT
|Les scores||∑ Points||vor||cim||phé|
Évaluation: En association, la voriconazole et la cimétidine peuvent potentiellement déclencher des arythmies ventriculaires de type torsades de pointes. Nous ne connaissons aucun potentiel d'allongement de l'intervalle QT pour la phénytoïne.
Effets secondaires généraux
|Effets secondaires||∑ la fréquence||vor||cim||phé|
|Vision floue||26.0 %||26.0↓||n.a.||n.a.|
|Douleur abdominale||12.0 %||12.0↓||n.a.||n.a.|
|Démangeaison de la peau||7.0 %||7.0↓||n.a.||n.a.|
|La nausée||6.3 %||5.4↓||n.a.||+|
Vomissements (5.4%): voriconazole, phénytoïne
La diarrhée (1.9%): voriconazole
Pancréatite: cimétidine, voriconazole
Hypertrophie gingivale: phénytoïne
Hépatite cholestatique (4.9%): voriconazole
Hépatotoxicité (1.9%): voriconazole
Jaunisse (1.9%): voriconazole
Insuffisance hépatique (1.9%): voriconazole
Gynécomastie (4%): cimétidine
Mal de crâne (3%): voriconazole
Déficience de mémoire: phénytoïne
Œdème périphérique (1.9%): voriconazole
Érythème polymorphe (1.9%): voriconazole
Mélanome malin (1.9%): voriconazole
Carcinome squameux (1.9%): voriconazole
Syndrome de Stevens-Johnson (1.9%): voriconazole, phénytoïne
Nécrolyse épidermique toxique (1.9%): voriconazole, phénytoïne
Dermatose bulleuse: phénytoïne
Névrite optique: voriconazole
Insuffisance rénale: voriconazole
Syndrome de DRESS: phénytoïne
Sur la base de vos
Abstract: Phenytoin is a relatively insoluble weak acid, usually administered as the sodium salt. Bioavailability is dependent upon particle size and problems of generic inequivalence have therefore arisen, particularly in Scandinavia. The drug has a moderately large volume of distribution and is approximately 90% bound to plasma proteins. Clinically important displacement can be caused by bilirubin and several drugs, particularly sodium valproate, which is often combined with phenytoin. Displacement will lower the total serum concentration but will little affect the free drug concentration. The metabolism of phenytoin to the major metabolite, 5-(p-hydroxyphenyl)-5-(phenylhydantoin, is saturable, giving rise to a non linear dose-serum concentration relationship. Therefore, the dose range compatible with a therapeutic serum concentration is narrow within subjects, and monitoring serum concentrations is of particular value in dosage tailoring. In renal failure, the binding of phenytoin to plasma proteins is reduced and therefore a lower range of serum drug concentrations is compatible with therapeutic control. In liver disease, binding may also be impaired but delayed metabolism may occur in addition. During pregnancy the serum concentration may fall progressively as pregnancy advances, probably due to an increased rate of metabolism. Phenytoin readily crosses the placenta, and is metabolised rapidly by the neonate exposed in utero.
Abstract: 1. In a double-blind crossover study 10 healthy males received either placebo or omeprazole (40 mg day-1) for 9 days, a single dose of phenytoin (300 mg) being taken on the seventh day. 2. Omeprazole significantly increased the area under the curve (0 to 72 h) of phenytoin (mean +/- s.e. mean) from 121.6 +/- 14.0 to 151.4 +/- 13.6 micrograms ml-1 h) (P less than 0.01). 3. The peak concentration, and apparent elimination half-life of phenytoin also tended to be increased though not significantly. 4. The omeprazole-phenytoin interaction observed may be clinically important because of the low therapeutic index associated with phenytoin.
Abstract: Clearance of phenytoin after i.v. injection of 100 mg was studied in six patients before and after 2 weeks daily treatment with 450 mg rifampicin, and in 14 patients with tuberculosis receiving standard treatment with 450 mg rifampicin, 300 mg isoniazid, and 1200 mg ethambutol daily. Acetylator status was measured by urinary acetylated sulphadimidine. Clearance of phenytoin in patients receiving only rifampicin increased from 46.7 ml min-1 +/- 20.6 ml min-1 to 97.8 ml min-1 +/- 33.4 ml min-1 (P less than 0.01), while clearance in patients on three drugs increased from 47.1 +/- 23.4 ml min-1 to 81.3 ml min-1 +/- 41.6 ml min-1 (P less than 0.01). No significant differences were observed between the six fast acetylators and the eight slow acetylators. Phenytoin kinetics were unchanged after further 3 months of combined treatment. Rifampicin is a strong inducer of the elimination of phenytoin. Combined treatment with isoniazid has no counter-acting effect in either fast or slow acetylators.
Abstract: No Abstract available
Abstract: Recently, the use of astemizole and terfenadine, both non-sedating H1-antihistamines, caused considerable concern. Several case reports suggested an association of both drugs with an increased risk of torsades de pointes, a special form of ventricular tachycardia. The increased risk of both H1-antihistamines was associated with exposure to supratherapeutic doses; for terfenadine the risk was also associated with concomitant exposure to the cytochrome P-450 inhibitors ketoconazole, erythromycin and cimetidine. To predict the size of the population that runs the risk of developing this potentially fatal adverse reaction in the Netherlands, the prevalence of prescribing supratherapeutic doses and the concomitant exposure to terfenadine and cytochrome P-450 inhibitors was studied. Data were obtained from the PHARMO data base in 1990, a pharmacy-based record linkage system encompassing a catchment population of 300,000 individuals. The results of the study showed that the prescribing of supratherapeutic doses and the concomitant exposure to terfenadine and cytochrome P-450 inhibitors was low. Furthermore, the results of a sensitivity analysis showed that the risk of fatal torsades de pointes has to be as high as 1 in 10,000 to cause one death in the Netherlands in one year.
Abstract: Astemizole (Hismanal), an antihistamine agent, has been reported to be associated with ventricular arrhythmias. In this paper we present a case of QT prolongation and torsades de pointes (TdP) in a 77-year-old woman who had been taking astemizole (10 mg/day) for 6 months because of allergic skin disease. At the time of admission, the serum concentration of astemizole and its metabolites was markedly elevated at 15.85 ng/ml, approximately 3 times the normal level. The patient was also taking cimetidine, a known inhibitor of cytochrome P-450 enzymatic activity, and during her admission was diagnosed as having vasospastic angina. To the best of our knowledge, this is the first report of astemizole-induced QT prolongation and TdP in Japan.
Abstract: No Abstract available
Abstract: AIMS: Voriconazole is a new triazole antifungal agent, and is metabolized by the cytochrome P450 isoenzymes CYP2C9, CYP2C19, and, to a lesser extent, by CYP3A4. Phenytoin is an inducer of CYP3A4 activity, and a substrate and inducer of CYP2C9 and CYP2C19. The present studies investigated the pharmacokinetic interactions of voriconazole and phenytoin when coadministered. METHODS: Two placebo-controlled parallel-group studies were conducted in healthy male volunteers. Study A was an open-label study and investigated the effect of phenytoin (300 mg once daily) on the steady-state pharmacokinetics of voriconazole (200 mg and 400 mg twice daily). Study B was a double-blind randomized study to investigate the effects of voriconazole (400 mg twice daily) on the steady-state pharmacokinetics of phenytoin (300 mg once daily). Cmax and AUCtau were compared at days 7, 21, and 28 (Study A), and at days 7 and 17 (Study B). All adverse events were recorded. RESULTS: Study A: 21 subjects were evaluable (10 voriconazole + phenytoin, 11 voriconazole + placebo). For subjects receiving voriconazole (200 mg twice daily) plus phenytoin, the day 21/day 7 ratios for voriconazole Cmax and AUCtau were 60.7%[90% confidence interval (CI) 50.1, 73.6] and 35.9% (90% CI 29.7, 43.3), respectively. Adjusted for voriconazole + placebo, the ratios between the means were 50.7% (90% CI 38.8, 66.1) and 30.6% (90% CI 23.5, 39.7), respectively. When the dose of voriconazole was increased to 400 mg twice daily, the day 28/day 7 ratios for voriconazole Cmax and AUCtau were 134% (90% CI 89.2, 200) and 139% (90% CI 97.3, 199), respectively. Study B: 15 subjects were evaluable for pharmacokinetic assessments (six phenytoin + voriconazole, nine phenytoin + placebo). The ratios between the means for phenytoin + voriconazole/phenytoin + placebo on day 17 vs. day 7 were: phenytoin Cmax 167% (90% CI 144, 193) and phenytoin AUCtau 181% (90% CI 156, 210). All treatments were well tolerated: most adverse events were mild/moderate and transient. CONCLUSIONS: Repeat dose administration of phenytoin decreased the mean steady-state Cmax and AUCtau of voriconazole by approximately 50% and 70%, respectively. Increasing the dose of voriconazole from 200 mg to 400 mg b.d. compensated for this effect. Repeat dose administration of 400 mg b.d. voriconazole increased the mean steady-state Cmax and AUCtau of phenytoin by approximately 70% and 80%, respectively. It is therefore recommended that plasma phenytoin concentrations are monitored and the dose adjusted as appropriate when phenytoin is coadministered with voriconazole.
Abstract: Renal drug interactions can result from competitive inhibition between drugs that undergo extensive renal tubular secretion by transporters such as P-glycoprotein (P-gp). The purpose of this study was to evaluate the effect of itraconazole, a known P-gp inhibitor, on the renal tubular secretion of cimetidine in healthy volunteers who received intravenous cimetidine alone and following 3 days of oral itraconazole (400 mg/day) administration. Glomerular filtration rate (GFR) was measured continuously during each study visit using iothalamate clearance. Iothalamate, cimetidine, and itraconazole concentrations in plasma and urine were determined using high-performance liquid chromatography/ultraviolet (HPLC/UV) methods. Renal tubular secretion (CL(sec)) of cimetidine was calculated as the difference between renal clearance (CL(r)) and GFR (CL(ioth)) on days 1 and 5. Cimetidine pharmacokinetic estimates were obtained for total clearance (CL(T)), volume of distribution (Vd), elimination rate constant (K(el)), area under the plasma concentration-time curve (AUC(0-240 min)), and average plasma concentration (Cp(ave)) before and after itraconazole administration. Plasma itraconazole concentrations following oral dosing ranged from 0.41 to 0.92 microg/mL. The cimetidine AUC(0-240 min) increased by 25% (p < 0.01) following itraconazole administration. The GFR and Vd remained unchanged, but significant reductions in CL(T) (655 vs. 486 mL/min, p < 0.001) and CL(sec) (410 vs. 311 mL/min, p = 0.001) were observed. The increased systemic exposure of cimetidine during coadministration with itraconazole was likely due to inhibition of P-gp-mediated renal tubular secretion. Further evaluation of renal P-gp-modulating drugs such as itraconazole that may alter the renal excretion of coadministered drugs is warranted.
Abstract: This review presents the published clinical pharmacokinetic data for the antifungal agent voriconazole. Aspects regarding absorption, tissue distribution, elimination and kinetic interactions are also discussed.
Abstract: Voriconazole is the first available second-generation triazole with potent activity against a broad spectrum of clinically significant fungal pathogens, including Aspergillus,Candida, Cryptococcus neoformans, and some less common moulds. Voriconazole is rapidly absorbed within 2 hours after oral administration and the oral bioavailability is over 90%, thus allowing switching between oral and intravenous formulations when clinically appropriate. Voriconazole shows nonlinear pharmacokinetics due to its capacity-limited elimination, and its pharmacokinetics are therefore dependent upon the administered dose. With increasing dose, voriconazole shows a superproportional increase in area under the plasma concentration-time curve (AUC). In doses used in children (age < 12 years) voriconazole pharmacokinetics appear to be linear. Steady-state plasma concentrations are reached approximately 5 days after both intravenous and oral administration; however, steady state is reached within 24 hours with voriconazole administered as an intravenous loading dose. The volume of distribution of voriconazole is 2-4.6 L/kg, suggesting extensive distribution into extracellular and intracellular compartments. Voriconazole was measured in tissue samples of brain, liver, kidney, heart, lung as well as cerebrospinal fluid. The plasma protein binding is about 60% and independent of dose or plasma concentrations. Clearance is hepatic via N-oxidation by the hepatic cytochrome P450 (CYP) isoenzymes, CYP2C19, CYP2C9 and CYP3A4. The elimination half-life of voriconazole is approximately 6 hours, and approximately 80% of the total dose is recovered in the urine, almost completely as metabolites. As with other azole drugs, the potential for drug interactions is considerable. Voriconazole shows time-dependent fungistatic activity against Candida species and time-dependent slow fungicidal activity against Aspergillus species. A short post-antifungal effect of voriconazole is evident only for Aspergillus species. The predictive pharmacokinetic/pharmacodynamic parameter for voriconazole treatment efficacy in Candida infections is the free drug AUC from 0 to 24 hour : minimum inhibitory concentration ratio.
Abstract: Anticholinergic Drug Scale (ADS) scores were previously associated with serum anticholinergic activity (SAA) in a pilot study. To replicate these results, the association between ADS scores and SAA was determined using simple linear regression in subjects from a study of delirium in 201 long-term care facility residents who were not included in the pilot study. Simple and multiple linear regression models were then used to determine whether the ADS could be modified to more effectively predict SAA in all 297 subjects. In the replication analysis, ADS scores were significantly associated with SAA (R2 = .0947, P < .0001). In the modification analysis, each model significantly predicted SAA, including ADS scores (R2 = .0741, P < .0001). The modifications examined did not appear useful in optimizing the ADS. This study replicated findings on the association of the ADS with SAA. Future work will determine whether the ADS is clinically useful for preventing anticholinergic adverse effects.
Abstract: We describe 2 patients who developed prolonged QTc interval on electrocardiogram while being treated with voriconazole. The first patient had undergone induction chemotherapy for acute myelogenous leukemia, and her course had been complicated by invasive aspergillosis and an acute cardiomyopathy. She developed torsades de pointes 3 weeks after starting voriconazole therapy. She was re-challenged with voriconazole without recurrent QTc prolongation or cardiac dysfunction. The second patient had a significantly prolonged QTc interval while on voriconazole therapy. We recommend careful monitoring for QTc prolongation and arrhythmia in patients who are receiving voriconazole, particularly those who have significant electrolyte disturbances, are on concomitant QT prolonging medications, have heart failure such as from a dilated cardiomyopathy, or have recently received anthracycline-based chemotherapy. The potential for synergistic cardiotoxicity must be carefully considered.
Abstract: OBJECTIVE: Posaconazole is an extended-spectrum triazole antifungal agent for the treatment and prophylaxis of invasive fungal infections. This randomized, open-label, parallel-group, multiple-dose study was conducted in healthy adult volunteers to assess the potential for a drug interaction between phenytoin and the posaconazole tablet formulation. METHODS: Subjects were randomly assigned for 10 days to one of the following treatments: posaconazole (200 mg once daily), phenytoin (200 mg once daily), or posaconazole (200 mg once daily) and phenytoin (200 mg once daily). Blood samples were collected on days 1 and 10 for pharmacokinetic evaluation of posaconazole and phenytoin concentrations. RESULTS: A total of 36 healthy men enrolled in the study. On day 1, the maximum plasma concentration (C(max)) and area under the concentration-time curve calculated from time 0-24 h post-dose (AUC(0-24)) were unchanged upon co-administration. At steady state (day 10), co-administration of posaconazole with phenytoin resulted in 44% (p = 0.012) and 52% (p = 0.007) decreases in posaconazole C(max) and AUC(0-24), respectively. These decreases in exposure corresponded with a 90% increase in steady-state clearance of orally administered posaconazole. Phenytoin C(max) and AUC(0-24) were not significantly altered upon co-administration of the two agents, 24% increase in C(max) (p = 0.196) and 25% increase in AUC(0-24) (p = 0.212) values, although inter-subject variability was observed within this group. CONCLUSION: Because co-administration of phenytoin and posaconazole significantly reduces posaconazole exposure and increases phenytoin levels in some subjects, concomitant use of these agents should be avoided unless the benefit outweighs the risk.
Abstract: BACKGROUND: Adverse effects of anticholinergic medications may contribute to events such as falls, delirium, and cognitive impairment in older patients. To further assess this risk, we developed the Anticholinergic Risk Scale (ARS), a ranked categorical list of commonly prescribed medications with anticholinergic potential. The objective of this study was to determine if the ARS score could be used to predict the risk of anticholinergic adverse effects in a geriatric evaluation and management (GEM) cohort and in a primary care cohort. METHODS: Medical records of 132 GEM patients were reviewed retrospectively for medications included on the ARS and their resultant possible anticholinergic adverse effects. Prospectively, we enrolled 117 patients, 65 years or older, in primary care clinics; performed medication reconciliation; and asked about anticholinergic adverse effects. The relationship between the ARS score and the risk of anticholinergic adverse effects was assessed using Poisson regression analysis. RESULTS: Higher ARS scores were associated with increased risk of anticholinergic adverse effects in the GEM cohort (crude relative risk [RR], 1.5; 95% confidence interval [CI], 1.3-1.8) and in the primary care cohort (crude RR, 1.9; 95% CI, 1.5-2.4). After adjustment for age and the number of medications, higher ARS scores increased the risk of anticholinergic adverse effects in the GEM cohort (adjusted RR, 1.3; 95% CI, 1.1-1.6; c statistic, 0.74) and in the primary care cohort (adjusted RR, 1.9; 95% CI, 1.5-2.5; c statistic, 0.77). CONCLUSION: Higher ARS scores are associated with statistically significantly increased risk of anticholinergic adverse effects in older patients.
Abstract: No Abstract available
Abstract: The objective of this study was to evaluate the pharmacokinetics of voriconazole and the potential correlations between pharmacokinetic parameters and patient variables in liver transplant patients on a fixed-dose prophylactic regimen. Multiple blood samples were collected within one dosing interval from 15 patients who were initiated on a prophylactic regimen of voriconazole at 200 mg enterally (tablets) twice daily starting immediately posttransplant. Voriconazole plasma concentrations were measured using high-pressure liquid chromatography (HPLC). Noncompartmental pharmacokinetic analysis was performed to estimate pharmacokinetic parameters. The mean apparent systemic clearance over bioavailability (CL/F), apparent steady-state volume of distribution over bioavailability (Vss/F), and half-life (t1/2) were 5.8+/-5.5 liters/h, 94.5+/-54.9 liters, and 15.7+/-7.0 h, respectively. There was a good correlation between the area under the concentration-time curve from 0 h to infinity (AUC0-infinity) and trough voriconazole plasma concentrations. t1/2, maximum drug concentration in plasma (Cmax), trough level, AUC0-infinity, area under the first moment of the concentration-time curve from 0 h to infinity (AUMC0-infinity), and mean residence time from 0 h to infinity (MRT0-infinity) were significantly correlated with postoperative time. t1/2, lambda, AUC0-infinity, and CL/F were significantly correlated with indices of liver function (aspartate transaminase [AST], total bilirubin, and international normalized ratio [INR]). The Cmax, last concentration in plasma at 12 h (Clast), AUMC0-infinity, and MRT0-infinity were significantly lower in the presence of deficient CYP2C19*2 alleles. Donor characteristics had no significant correlation with any of the pharmacokinetic parameters estimated. A fixed dosing regimen of voriconazole results in a highly variable exposure of voriconazole in liver transplant patients. Given that trough voriconazole concentration is a good measure of drug exposure (AUC), the voriconazole dose can be individualized based on trough concentration measurements in liver transplant patients.
Abstract: No Abstract available
Abstract: No Abstract available
Abstract: AIMS: To assess the role of MDR1 and gamma-aminobutyric acid receptor-gamma 2 sub unit (GABRG2) gene polymorphism in seizure susceptibility in generalized seizure (GS) and febrile seizure (FS) patients and to evaluate MDR1 C3435T gene polymorphism's role in absorption of the anti-epileptic drug, phenytoin (PHT) in a cohort of patients. METHODS: One hundred twenty-seven cases of seizure (86 GS and 41 FS) patients were analyzed for MDR1 C3435T and GABRG2 C588T gene polymorphisms using restriction fragment length polymorphism-polymerase chain reaction. Serum PHT levels were analyzed. RESULTS: The T allele of MDR1 C3435T and GABRG2 C588T gene polymorphism was higher in GS in the Indian population compared with controls. From the data in GS, CT and TT genotype carriers of the MDR1 gene and TT genotype carriers of the GABRG2 gene had more recurrent seizures compared with others. MDR1 T allele carriers in the seizure reoccurrence (SR) group of GS and FS were high compared with the well-controlled seizure group (with no seizures after treatment). TT genotype carriers in SR group were high in FS (with regard to MDR1 gene polymorphism) and GS (with regard to GABRG2 gene polymorphism) compared with a well-controlled seizure group. MDR1 C3435T gene polymorphism affects serum PHT levels (p<0.015). Association of dose PHT ratio and genotype groups of MDR1 C3435T gene polymorphism showed a significant association (p<0.05). MDR1*CC genotype was more common in cases with low serum PHT levels.In addition, it is evident that CT and TT genotype carriers have a high percentage of SR with elevated serum PHT levels. CONCLUSIONS: Our results show that the MDR1 3435T and GABRG2 588T alleles play a role in seizure occurrence. Moreover, the MDR1 3435T allele also affects PHT absorption. We suggest MDR1 C3435T and GABRG2 C588T genotyping would be of value in order to lower the risk of concentration-dependent drug toxicity and for better patient management.
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: P-glycoprotein (P-gp), an ATP-dependant efflux pump transports a wide range of substrates across cellular membranes. Earlier studies have identified drug efflux due to the over-expression of P-gp as one of the causes for the resistance of phenytoin, an anti-epileptic drug (AED). While no clear evidence exists on the specific characteristics of phenytoin association with the human P-gp, this study employed structure-based computational approaches to identify its binding site and the underlying interactions. The identified site was validated with that of rhodamine, a widely accepted reference and an experimental probe. Further, an in silico proof-of-concept for phenytoin interactions and its decreased binding affinity with the closed-state of human P-gp model was provided in comparison with other AEDs. This is the first report to provide insights into the phenytoin binding site and possibly better explain its efflux by P-gp.
Abstract: AIM: Conducting PK studies in pregnant women is challenging. Therefore, we asked if a physiologically-based pharmacokinetic (PBPK) model could be used to predict the disposition in pregnant women of drugs cleared by multiple CYP enzymes. METHODS: We expanded and verified our previously published pregnancy PBPK model by incorporating hepatic CYP2B6 induction (based on in vitro data), CYP2C9 induction (based on phenytoin PK) and CYP2C19 suppression (based on proguanil PK), into the model. This model accounted for gestational age-dependent changes in maternal physiology and hepatic CYP3A, CYP1A2 and CYP2D6 activity. For verification, the pregnancy-related changes in the disposition of methadone (cleared by CYP2B6, 3A and 2C19) and glyburide (cleared by CYP3A, 2C9 and 2C19) were predicted. RESULTS: Predicted mean post-partum to second trimester (PP : T2 ) ratios of methadone AUC, Cmax and Cmin were 1.9, 1.7 and 2.0, vs. observed values 2.0, 2.0 and 2.6, respectively. Predicted mean post-partum to third trimester (PP : T3 ) ratios of methadone AUC, Cmax and Cmin were 2.1, 2.0 and 2.4, vs. observed values 1.7, 1.7 and 1.8, respectively. Predicted PP : T3 ratios of glyburide AUC, Cmax and Cmin were 2.6, 2.2 and 7.0 vs. observed values 2.1, 2.2 and 3.2, respectively. CONCLUSIONS: Our PBPK model integrating prior physiological knowledge, in vitro and in vivo data, allowed successful prediction of methadone and glyburide disposition during pregnancy. We propose this expanded PBPK model can be used to evaluate different dosing scenarios, during pregnancy, of drugs cleared by single or multiple CYP enzymes.
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: 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.