Changes in perampanel levels during de-induction: Simulations following carbamazepine discontinuation

Applying Physiologically Based Pharmacokinetic Modeling to Interpret Carbamazepine's Nonlinear Pharmacokinetics and Its Induction Potential on Cytochrome P450 3A4 and Cytochrome P450 2C9 Enzymes

Carbamazepine (CBZ) is commonly prescribed for epilepsy and frequently used in polypharmacy. However, concerns arise regarding its ability to induce the metabolism of other drugs, including itself, potentially leading to the undertreatment of co-administered drugs. Additionally, CBZ exhibits nonlinear pharmacokinetics (PK), but the root causes have not been fully studied. This study aims to investigate the mechanisms behind CBZ's nonlinear PK and its induction potential on CYP3A4 and CYP2C9 enzymes. To achieve this, we developed and validated a physiologically based pharmacokinetic (PBPK) parent-metabolite model of CBZ and its active metabolite Carbamazepine-10,11-epoxide in GastroPlus®. The model was utilized for Drug-Drug Interaction (DDI) prediction with CYP3A4 and CYP2C9 victim drugs and to further explore the underlying mechanisms behind CBZ's nonlinear PK. The model accurately recapitulated CBZ plasma PK. Good DDI performance was demonstrated by the prediction of CBZ DDIs with quinidine, dolutegravir, phenytoin, and tolbutamide; however, with midazolam, the predicted/observed DDI AUClast ratio was 0.49 (slightly outside of the two-fold range). CBZ's nonlinear PK can be attributed to its nonlinear metabolism caused by autoinduction, as well as nonlinear absorption due to poor solubility. In further applications, the model can help understand DDI potential when CBZ serves as a CYP3A4 and CYP2C9 inducer.

Population Pharmacokinetic Analysis of Drug-Drug Interactions Between Perampanel and Carbamazepine Using Enzyme Induction Model in Epileptic Patients

BACKGROUND

Perampanel (PER) is an oral antiepileptic drug and its concomitant use with carbamazepine (CBZ) leads to decreased PER concentrations. However, the magnitude of its influence may vary, depending on the dynamics of the enzyme induction properties of CBZ. This study aimed to develop a population pharmacokinetic (PPK) model considering the dynamics of enzyme induction and evaluate the effect of CBZ on PER pharmacokinetics.

METHODS

We retrospectively collected data on patient background, laboratory tests, and prescribed drugs from electronic medical records. We developed 2 PPK models incorporating the effect of CBZ-mediated enzyme induction to describe time-concentration profiles of PER using the following different approaches: (1) treating the concomitant use of CBZ as a categorical covariate (empirical PPK model) and (2) incorporating the time-course of changes in the amount of enzyme by CBZ-mediated induction (semimechanistic PPK model). The bias and precision of the predictions were investigated by calculating the mean error, mean absolute error, and root mean squared error.

RESULTS

A total of 133 PER concentrations from 64 patients were available for PPK modelling. PPK analyses showed that the co-administration of CBZ increased the clearance of PER. Goodness-of-fit plots indicated a favorable description of the observed data and low bias. The mean error, mean absolute error, and root mean square error values based on the semimechanistic model were smaller than those obtained using the empirical PPK model for predicting PER concentrations in patients with CBZ.

CONCLUSIONS

We developed 2 PPK models to describe PER pharmacokinetics based on different approaches, using electronic medical record data. Our PPK models support the use of PER in clinical practice.

Pharmacokinetics of the CYP3A4 and CYP2B6 Inducer Carbamazepine and Its Drug-Drug Interaction Potential: A Physiologically Based Pharmacokinetic Modeling Approach

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 AUClast ratios and 11/15 DDI Cmax 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.

Changes in perampanel levels during de-induction: Simulations following carbamazepine discontinuation

Objective

To evaluate the time course of changes in perampanel levels when co‐administered with carbamazepine, and following carbamazepine discontinuation, using a physiologically based pharmacokinetic (PBPK) model.

Methods

The PBPK model was developed, verified using clinical PK data, and used to simulate the effect of abrupt discontinuation and down‐titration (75 mg twice daily [bid]/wk) of co‐administered carbamazepine 300 mg bid on the PK of perampanel once daily (qd). Perampanel dose tapering (8‐4 mg) and up‐titration (2‐6 mg) were simulated during abrupt carbamazepine 300 mg bid discontinuation to identify a titration schedule that minimizes changes in perampanel plasma concentrations.

Results

The PBPK model accurately reproduced perampanel plasma concentration‐time profiles from clinical studies in single‐ and multiple‐dose regimen simulations, including multiple‐dose carbamazepine co‐administration. The time course of return to pre‐induced perampanel levels occurred more slowly following carbamazepine down‐titration (~48 days after first down‐titration) vs abrupt discontinuation (~25 days). Perampanel dose tapering (8‐4 mg) at abrupt carbamazepine discontinuation produced minimal changes in steady‐state concentrations, which returned to the levels observed during carbamazepine co‐administration in ~15 days from the time of carbamazepine discontinuation. When perampanel was up‐titrated in the presence of carbamazepine, return to steady state occurred more slowly when carbamazepine was down‐titrated weekly (~45 days) vs abrupt discontinuation (~24 days).

Conclusion

This PBPK model simulated and predicted optimal perampanel dose tapering and up‐titration schedules for maintaining perampanel levels during conversion to monotherapy. These results may guide physicians when managing conversion from perampanel polytherapy with concomitant enzyme‐inducing anti‐seizure medications to monotherapy.