Journal
PHARMACEUTICS
Volume 13, Issue 2, Pages -Publisher
MDPI
DOI: 10.3390/pharmaceutics13020270
Keywords
physiologically based pharmacokinetic (PBPK) modeling; carbamazepine; carbamazepine-10; 11-epoxide; drug– drug interactions (DDIs); induction
Categories
Funding
- German Federal Ministry of Education and Research (BMBF) [031L0161C]
- Deutsche Forschungsgemeinschaft (DFG, German Research Foundation)
- Saarland University
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A physiologically based pharmacokinetic model of carbamazepine and its metabolite was developed for drug-drug interaction prediction, demonstrating good performance in predicting interactions with other drugs. The model, based on plasma concentration-time profiles and urine measurements, will be freely available for use in the Open Systems Pharmacology model repository.
The anticonvulsant carbamazepine is frequently used in the long-term therapy of epilepsy and is a known substrate and inducer of cytochrome P450 (CYP) 3A4 and CYP2B6. Carbamazepine induces the metabolism of various drugs (including its own); on the other hand, its metabolism can be affected by various CYP inhibitors and inducers. The aim of this work was to develop a physiologically based pharmacokinetic (PBPK) parent-metabolite model of carbamazepine and its metabolite carbamazepine-10,11-epoxide, including carbamazepine autoinduction, to be applied for drug-drug interaction (DDI) prediction. The model was developed in PK-Sim, using a total of 92 plasma concentration-time profiles (dosing range 50-800 mg), as well as fractions excreted unchanged in urine measurements. The carbamazepine model applies metabolism by CYP3A4 and CYP2C8 to produce carbamazepine-10,11-epoxide, metabolism by CYP2B6 and UDP-glucuronosyltransferase (UGT) 2B7 and glomerular filtration. The carbamazepine-10,11-epoxide model applies metabolism by epoxide hydroxylase 1 (EPHX1) and glomerular filtration. Good DDI performance was demonstrated by the prediction of carbamazepine DDIs with alprazolam, bupropion, erythromycin, efavirenz and simvastatin, where 14/15 DDI AUC(last) ratios and 11/15 DDI C-max ratios were within the prediction success limits proposed by Guest et al. The thoroughly evaluated model will be freely available in the Open Systems Pharmacology model repository.
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