QT time prolongation
Adverse drug events
|Elevated creatine kinase|
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Explanations of the substances for patients
We have no additional warnings for the combination of abarelix and cobimetinib. 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 cobimetinib (100%). We do not expect any change in exposure for cobimetinib, 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.
Cobimetinib has a mean oral bioavailability [ F ] of 46%, which is why the maximum plasma levels [Cmax] tend to change with an interaction. The terminal half-life [ t12 ] is rather long at 44 hours and constant plasma levels [ Css ] are only reached after more than 176 hours. The protein binding [ Pb ] is moderately strong at 95%. Since the substance has a low hepatic extraction rate of 0.07, displacement from protein binding [Pb] in the context of an interaction can lead to increased exposure. The metabolism mainly takes place via CYP3A4 and the active transport takes place partly via PGP and UGT2B7.
|Serotonergic Effects a||0||Ø||Ø|
Rating: According to our knowledge, neither abarelix nor cobimetinib increase serotonergic activity.
|Kiesel & Durán b||0||Ø||Ø|
Rating: According to our knowledge, neither abarelix nor cobimetinib increase anticholinergic activity.
QT time prolongation
Rating: In combination, abarelix and cobimetinib can potentially trigger ventricular arrhythmias of the torsades de pointes type.
General adverse effects
|Side effects||∑ frequency||aba||cob|
|Elevated creatine kinase||79.0 %||n.a.||79.0|
|Elevated AST||73.0 %||n.a.||73.0|
|Elevated alkaline phosphatase||71.0 %||n.a.||71.0|
|Elevated ALT||68.0 %||n.a.||68.0|
Rash (16%): cobimetinib
Basal cell carcinoma of skin (4.5%): cobimetinib
Malignant melanoma: cobimetinib
Squamous cell carcinoma: cobimetinib
Gastrointestinal hemorrhage (3.6%): cobimetinib
Hematuria (2.4%): cobimetinib
Hemorrhage (1.2%): cobimetinib
Intracranial hemorrhage: cobimetinib
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 pharmacokinetics, metabolism, and excretion of cobimetinib, a MEK inhibitor, were characterized in healthy male subjects (n = 6) following a single 20 mg (200 μCi) oral dose. Unchanged cobimetinib and M16 (glycine conjugate of hydrolyzed cobimetinib) were the major circulating species, accounting for 20.5% and 18.3% of the drug-related material in plasma up to 48 hours postdose, respectively. Other circulating metabolites were minor, accounting for less than 10% of drug-related material in plasma. The total recovery of the administered radioactivity was 94.3% (±1.6%, S.D.) with 76.5% (±2.3%) in feces and 17.8% (±2.5%) in urine. Metabolite profiling indicated that cobimetinib had been extensively metabolized with only 1.6% and 6.6% of the dose remaining as unchanged drug in urine and feces, respectively. In vitro phenotyping experiments indicated that CYP3A4 was predominantly responsible for metabolizing cobimetinib. From this study, we concluded that cobimetinib had been well absorbed (fraction absorbed, Fa = 0.88). Given this good absorption and the previously determined low hepatic clearance, the systemic exposures were lower than expected (bioavailability, F = 0.28). We hypothesized that intestinal metabolism had strongly attenuated the oral bioavailability of cobimetinib. Supporting this hypothesis, the fraction escaping gut wall elimination (Fg) was estimated to be 0.37 based on F and Fa from this study and the fraction escaping hepatic elimination (Fh) from the absolute bioavailability study (F = Fa × Fh × Fg). Physiologically based pharmacokinetics modeling also showed that intestinal clearance had to be included to adequately describe the oral profile. These collective data suggested that cobimetinib was well absorbed following oral administration and extensively metabolized with intestinal first-pass metabolism contributing to its disposition.
Abstract: BACKGROUND AND OBJECTIVES: Cobimetinib is eliminated mainly through cytochrome P450 (CYP) 3A4-mediated hepatic metabolism in humans. A clinical drug-drug interaction (DDI) study with the potent CYP3A4 inhibitor itraconazole resulted in an approximately sevenfold increase in cobimetinib exposure. The DDI risk for cobimetinib with other CYP3A4 inhibitors and inducers needs to be assessed in order to provide dosing instructions. METHODS: A physiologically based pharmacokinetic (PBPK) model was developed for cobimetinib using in vitro data. It was then optimized and verified using clinical pharmacokinetic data and itraconazole-cobimetinib DDI data. The contribution of CYP3A4 to the clearance of cobimetinib in humans was confirmed using sensitivity analysis in a retrospective simulation of itraconazole-cobimetinib DDI data. The verified PBPK model was then used to predict the effect of other CYP3A4 inhibitors and inducers on cobimetinib pharmacokinetics. RESULTS: The PBPK model described cobimetinib pharmacokinetic profiles after both intravenous and oral administration of cobimetinib well and accurately simulated the itraconazole-cobimetinib DDI. Sensitivity analysis suggested that CYP3A4 contributes ~78 % of the total clearance of cobimetinib. The PBPK model predicted no change in cobimetinib exposure (area under the plasma concentration-time curve, AUC) with the weak CYP3A inhibitor fluvoxamine and a three to fourfold increase with the moderate CYP3A inhibitors, erythromycin and diltiazem. Similarly, cobimetinib exposure in the presence of strong (rifampicin) and moderate (efavirenz) CYP3A inducers was predicted to decrease by 83 and 72 %, respectively. CONCLUSION: This study demonstrates the value of using PBPK simulation to assess the clinical DDI risk inorder to provide dosing instructions with other CYP3A4 perpetrators.