QT time prolongation
Adverse drug events
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Explanations of the substances for patients
We have no additional warnings for the combination of abarelix and isradipine. Please also consult the relevant specialist information.
The reported changes in exposure correspond to the changes in the plasma concentration-time curve [ AUC ]. We do not expect any change in exposure for abarelix, when combined with isradipine (100%). We do not expect any change in exposure for isradipine, when combined with abarelix (100%).
The pharmacokinetic parameters of the average population are used as the starting point for calculating the individual changes in exposure due to the interactions.
The bioavailability of abarelix is unknown. The terminal half-life [ t12 ] is rather long at 316.8 hours and constant plasma levels [ Css ] are only reached after more than 1267.2 hours. The protein binding [ Pb ] is 97.5% strong. The metabolism via cytochromes is currently still being worked on.
Isradipine has a low oral bioavailability [ F ] of 20%, which is why the maximum plasma level [Cmax] tends to change strongly with an interaction. The terminal half-life [ t12 ] is 8 hours and constant plasma levels [ Css ] are reached after approximately 32 hours. The protein binding [ Pb ] is moderately strong at 95%. The metabolism mainly takes place via CYP3A4.
|Serotonergic Effects a||0||Ø||Ø|
Rating: According to our knowledge, neither abarelix nor isradipine increase serotonergic activity.
|Kiesel & Durán b||0||Ø||Ø|
Rating: According to our knowledge, neither abarelix nor isradipine increase anticholinergic activity.
QT time prolongation
Rating: In combination, abarelix and isradipine can potentially trigger ventricular arrhythmias of the torsades de pointes type.
General adverse effects
|Side effects||∑ frequency||aba||isr|
|Peripheral edema||19.7 %||n.a.||19.7|
|Myocardial infarction||0.8 %||n.a.||0.8|
|Transient ischemic attack||0.8 %||n.a.||0.8|
Based on your answers and scientific information, we assess the individual risk of undesirable side effects. These recommendations are intended to advise professionals and are not a substitute for consultation with a doctor. In the restricted test version (alpha), the risk of all substances has not yet been conclusively assessed.
Abstract: The QT interval corrected for heart rate (QTc) is believed to reflect sympathovagal balance. It has also been established that beta-blockers and dihydropyridine-type calcium channel blockers (DHPCCB) influence the autonomic nervous system. This study tested the hypothesis that QTc interval length is a predictor of the blood pressure reduction induced by beta1-selective beta-blockers or DHPCCB. The predictive values of pretreatment heart rate and of the heart rate change with therapy were also evaluated. The authors conducted an historical reanalysis of 5 clinical trials that looked at the antihypertensive effects of beta-blockers (nebivolol) or DHPCCB (amlodipine, felodipine, isradipine, nifedipine). Correlation and quintile analyses were performed to measure the association between QTc interval, heart rate, or heart rate change and therapeutic blood pressure response. Separate analyses were undertaken for beta-blockers and DHPCCB. Seventy-three and 98 hypertensive subjects respectively were included in the beta-blocker and DHPCCB analyses. QTc interval, pretreatment heart rate, and heart rate change with therapy were not associated with therapeutic blood pressure response. In this study, QTc interval length, pretreatment heart rate, and heart rate change with therapy were not good predictors of the blood pressure response to beta1-selective beta-blockers or DHPCCB in hypertensive subjects.
Abstract: OBJECTIVES: To study whether NOS1AP single nucleotide polymorphisms (SNPs), rs10494366 T>G and rs10918594 C>G, modify the heart-rate-corrected QT (QTc) prolonging effect of calcium channel blockers. BACKGROUND: Common variation in the NOS1AP gene has been associated with QT interval variation in several large population samples. NOS1 is presumed to influence intracellular calcium. METHODS: The prospective population-based Rotterdam Study includes 16 603 ECGs from 7565 participants (>or=55 years), after exclusion of patients with left ventricular hypertrophy, left and right bundle branch block, as well as carriers of pacemakers. The endpoint was the length of the QTc interval in calcium channel blocker users and non-users with the minor alleles compared with the major alleles (wild type). We used a repeated-measurement analysis, adjusted for all known confounders. RESULTS: Use of verapamil was associated with a significant QTc interval prolongation [6.0 ms 95% confidence interval (CI) 1.7; 10.2] compared with non-users. Furthermore, users of verapamil with the rs10494366 GG genotype showed significantly more QTc prolongation than users with the TT genotype [25.4 ms (95% CI: 5.9-44.9)] (P value for multiplicative interaction 0.0038). Users of isradipine with the GG genotype showed more QTc prolongation than users with the TT genotype [19.8 ms (95% CI: 1.9-37.7)]; however, SNP rs10494366 did not modify the effect on QTc interval on a multiplicative scale (P=0.3563). SNP rs10918594 showed similar results. CONCLUSION: In conclusion, we showed that the minor alleles of both NOS1AP SNPs significantly potentiate the QTc prolonging effect of verapamil.
Abstract: Drug discovery and development is a high-risk enterprise that requires significant investments in capital, time and scientific expertise. The studies of xenobiotic metabolism remain as one of the main topics in the research and development of drugs, cosmetics and nutritional supplements. Antihypertensive drugs are used for the treatment of high blood pressure, which is one the most frequent symptoms of the patients that undergo cardiovascular diseases such as myocardial infraction and strokes. In current cardiovascular disease pharmacology, four drug clusters - Angiotensin Converting Enzyme Inhibitors, Beta-Blockers, Calcium Channel Blockers and Diuretics - cover the major therapeutic characteristics of the most antihypertensive drugs. The pharmacokinetic and specifically the metabolic profile of the antihypertensive agents are intensively studied because of the broad inter-individual variability on plasma concentrations and the diversity on the efficacy response especially due to the P450 dependent metabolic status they present. Several computational methods have been developed with the aim to: (i) model and better understand the human drug metabolism; and (ii) enhance the experimental investigation of the metabolism of small xenobiotic molecules. The main predictive tools these methods employ are rule-based approaches, quantitative structure metabolism/activity relationships and docking approaches. This review paper provides detailed metabolic profiles of the major clusters of antihypertensive agents, including their metabolites and their metabolizing enzymes, and it also provides specific information concerning the computational approaches that have been used to predict the metabolic profile of several antihypertensive drugs.