Population pharmacokinetic modeling of steady state clearance of carbamazepine and its epoxide metabolite from sparse routine clinical data

Handling Delayed or Missed Dose of Antiseizure Medications: A Model-Informed Individual Remedial Dosing

BACKGROUND AND OBJECTIVES

Delayed or missed antiseizure medications (ASMs) doses are common during long-term or lifelong antiepilepsy treatment. This study aims to explore optimal individualized remedial dosing regimens for delayed or missed doses of 11 commonly used ASMs.

METHODS

To explore remedial dosing regimens, Monte Carlo simulation was used based on previously identified and published population pharmacokinetic models. Six remedial strategies for delayed or missed doses were investigated. The deviation time outside the individual therapeutic range was used to evaluate each remedial regimen. The influences of patients' demographics, concomitant medication, and scheduled dosing intervals on remedial regimens were assessed. RxODE and Shiny in R were used to perform Monte Carlo simulation and recommend individual remedial regimens.

RESULTS

The recommended remedial regimens were highly correlated with delayed time, scheduled dosing interval, and half-life of the ASM. Moreover, the optimal remedial regimens for pediatric and adult patients were different. The renal function, along with concomitant medication that affects the clearance of the ASM, may also influence the remedial regimens. A web-based dashboard was developed to provide individualized remedial regimens for the delayed or missed dose, and a user-defined module with all parameters that could be defined flexibly by the user was also built.

DISCUSSION

Monte Carlo simulation based on population pharmacokinetic models may provide a rational approach to propose remedial regimens for delayed or missed doses of ASMs in pediatric and adult patients with epilepsy.

Evaluation of clinical and genetic factors in the population pharmacokinetics of carbamazepine

Aims

Carbamazepine can cause hypersensitivity reactions in ~10% of patients. An immunogenic effect can be produced by the electrophilic 10,11‐epoxide metabolite but not by carbamazepine. Hypothetically, certain single nucleotide polymorphisms might increase the formation of immunogenic metabolites, leading ultimately to hypersensitivity reactions. This study explores the role of clinical and genetic factors in the pharmacokinetics (PK) of carbamazepine and 3 metabolites known to be chemically reactive or formed through reactive intermediates.

Methods

A combination of rich and sparse PK samples were collected from healthy volunteers and epilepsy patients. All subjects were genotyped for 20 single nucleotide polymorphisms in 11 genes known to be involved in the metabolism or transport of carbamazepine and carbamazepine 10,11‐epoxide. Nonlinear mixed effects modelling was used to build a population‐PK model.

Results

In total, 248 observations were collected from 80 subjects. A 1‐compartment PK model with first‐order absorption and elimination best described the parent carbamazepine data, with a total clearance of 1.96 L/h, central distribution volume of 164 L and absorption rate constant of 0.45 h⁻¹. Total daily dose and coadministration of phenytoin were significant covariates for total clearance of carbamazepine. EPHX1‐416G/G genotype was a significant covariate for the clearance of carbamazepine 10,11‐epoxide.

Conclusion

Our data indicate that carbamazepine clearance was affected by total dose and phenytoin coadministration, but not by genetic factors, while carbamazepine 10,11‐epoxide clearance was affected by a variant in the microsomal epoxide hydrolase gene. A much larger sample size would be required to fully evaluate the role of genetic variation in carbamazepine pharmacokinetics, and thereby predisposition to carbamazepine hypersensitivity.

Iron supplements in nursing home patients associated with reduced carbamazepine absorption

Persons in nursing homes receive a number of medications that may interfere with the pharmacokinetics of carbamazepine (CBZ). The aim of our study was to determine factors that may affect the pharmacokinetics of CBZ in elderly nursing home patients.

METHODS

CBZ concentration data collected from 60 nursing homes across the US were evaluated. Inclusion criteria included residency in a nursing home for at least 2 months, age 65 years or older, a stable dosing regimen of CBZ for at least 4 weeks (considered steady state), available CBZ concentration, and complete information regarding all co-medications. Using a nonlinear mixed-effects model, the data were adequately described by a one-compartment model with first-order absorption and elimination. Goodness-of-fit plots, plausibility of parameter estimates, visual predictive check and nonparametric bootstrap were used to evaluate the models.

MAIN FINDINGS

The final data set consisted of 345 CBZ concentrations from 99 subjects (38 males, 61 females). The population estimate of apparent clearance (CL/F) for a 70-kg person was 3.69 L/hr (RSE 6.9%). Residents were receiving either immediate (93.9%) or extended release (6.1%) formulation of CBZ and the Ka of each formulation was fixed to literature values. Age, sex, and co-medications had no effect on CL/F and apparent volume of distribution. Iron supplementation, which was taken by 16% of the residents, resulted in a 33% decrease in bioavailability (p < 0.001). No other medications were found to have an effect.

CONCLUSIONS

Results from this pharmacokinetic study indicate that use of iron supplementation is associated with a reduction in absorption of CBZ and may need to be considered when dosing CBZ in patients taking iron supplementation.

Pharmacokinetic interactions and dosing rationale for antiepileptic drugs in adults and children

AIMS

Population pharmacokinetic modelling has been widely used across many therapeutic areas to identify sources of variability, which are incorporated into models as covariate factors. Despite numerous publications on pharmacokinetic drug-drug interactions (DDIs) between antiepileptic drugs (AEDs), such data are not used to support the dose rationale for polytherapy in the treatment of epileptic seizures. Here we assess the impact of DDIs on plasma concentrations and evaluate the need for AED dose adjustment.

METHODS

Models describing the pharmacokinetics of carbamazepine, clobazam, clonazepam, lamotrigine, levetiracetam, oxcarbazepine, phenobarbital, phenytoin, topiramate, valproic acid and zonisamide in adult and paediatric patients were collected from the published literature and implemented in NONMEM v7.2. Taking current clinical practice into account, we explore simulation scenarios to characterize AED exposure in virtual patients receiving mono- and polytherapy. Steady-state, maximum and minimum concentrations were selected as parameters of interest for this analysis.

RESULTS

Our simulations show that DDIs can cause major changes in AED concentrations both in adults and children. When more than one AED is used, even larger changes are observed in the concentrations of the primary drug, leading to significant differences in steady-state concentration between mono- and polytherapy for most AEDs. These results suggest that currently recommended dosing algorithms and titration procedures do not ensure attainment of appropriate therapeutic concentrations.

CONCLUSIONS

The effect of DDIs on AED exposure cannot be overlooked. Clinical guidelines must consider such covariate effects and ensure appropriate dosing recommendations for adult and paediatric patients who require combination therapy.

The influence of CYP2C8*3 on carbamazepine serum concentration in epileptic pediatric patients

The aim of the present study was to investigate the distribution of CYP2C8 variants *3 and *5, as well as their effect on carbamazepine pharmacokinetic properties, in 40 epileptic pediatric patients on carbamazepine treatment. Genotyping was conducted using polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP), and allele-specific (AS)-PCR methods, and steady-state carbamazepine plasma concentrations were determined by high performance liquid chromatography (HPLC). The CYP2C8 *3 and *5 polymorphisms were found at frequencies of 17.5 and 0.0%, respectively. After dose adjustment, there was a difference in daily dose in CYP2C8*3 carriers compared to non carriers [mean ± standard deviation (SD): 14.19 ± 5.39 vs. 15.46 ± 4.35 mg/kg; p = 0.5]. Dose-normalized serum concentration of carbamazepine was higher in CYP2C8*3 (mean ± SD: 0.54 ± 0.18 vs. 0.43 ± 0.11 mg/mL, p = 0.04), and the observed correlation between weight-adjusted carbamazepine dose and carbamazepine concentration after dose adjustment was significant only in CYP2C8*3 non carriers (r = 0.52, p = 0.002). However, the population pharmacokinetic analysis failed to demonstrate any significant effect of CYP2C8 *3 polymorphism on carbamazepine clearance [CL L/h = 0.215 + 0.0696*SEX+ 0.000183*DD]. The results indicated that the CYP2C8*3 polymorphism might not be of clinical importance for epilepsy treatment in pediatric populations.

Carbamazepine

This chapter includes the aspects of carbamazepine. The drug is synthesized by the use of 5H-dibenz[b,f]azepine and phosgene followed by subsequent reaction with ammonia. Carbamazepine is generally used for the treatment of seizure disorders and neuropathic pain, it is also important as off-label for a second-line treatment for bipolar disorder and in combination with an antipsychotic in some cases of schizophrenia when treatment with a conventional antipsychotic alone has failed. Other uses may include attention deficit hyperactivity disorder, schizophrenia, phantom limb syndrome, complex regional pain syndrome, borderline personality disorder, and posttraumatic stress disorder. The chapter discusses the drug metabolism and pharmacokinetics and presents various methods of analysis of this drug such electrochemical analysis, spectroscopic analysis, and chromatographic techniques of separation. It also discusses its physical properties such as solubility characteristics, X-ray powder diffraction pattern, and thermal methods of analysis. The chapter is concluded with a discussion on its biological properties such as activity, toxicity, and safety.

Population-Based Assessments of Clinical Drug-Drug Interactions: Qualitative Indices or Quantitative Measures?

Population-based assessments of drug-drug interactions have become more common since the introduction and acceptance of the population pharmacokinetic approach. Unlike traditional methods, population-based studies provide clinically relevant results that can be applied directly to a target patient population. Furthermore, population-based studies do not demand the traditional requirements of intensive pharmacokinetic sampling, rigorous inpatient stays, or stringent assessment schedules. As such, the population-based approach can effectively be used to confirm known drug-drug interactions and further characterize anticipated interactions. A prospectively designed analysis can also reveal drug-drug interactions that might otherwise have gone undetected with traditional methods. Ultimately, these results could help to alleviate clinicians' concerns about using widely marketed drugs in combination therapies and also reduce patients' risk of experiencing unacceptable side effects. This article intends to provide a balanced overview of the population-based approach and its merits, drawbacks, and potential utility in the assessment of drug-drug interactions during clinical drug development.

The effect of poor compliance on the pharmacokinetics of carbamazepine and its epoxide metabolite using Monte Carlo simulation

AIM

To study the effects of delayed and missed doses (poor compliance) on the pharmacokinetics of carbamazepine (CBZ) and its main active metabolite carbamazepine-10,11-epoxide (CBZE) in Chinese epilepsy patients using Monte Carlo simulation.

METHODS

CBZ and CBZE time-concentration profiles in various scenarios were generated based on a population pharmacokinetic study in Chinese epilepsy patients using Monte Carlo simulation. The scenarios included patients given multiple doses of CBZ that ranged from 100 to 300 mg three times daily or from 200 to 300 mg every 12 h. The therapeutic range of CBZ and CBZE for each scenario was estimated to assess the effect of delayed or missed doses and to design corresponding rescue regimens. Moreover, the impact of body weight, absorption rate and co-therapy with other antiepileptic drugs (phenytoin, phenobarbital and valproic acid) on the dosage recommendation was investigated in the event of poor compliance.

RESULTS

The risk for a sub-therapeutic range of CBZ and CBZE was increased in a dose-dependent manner in both two and three times daily regimens when delayed or missed doses occurred. The effects of poor compliance was less prominent on the lower daily doses compared with those on the higher daily doses. The dose recommendations, in the event of poor compliance, were time related and dose dependent. Patient body weight, absorption rate and co-therapy with phenytoin, phenobarbital and valproic acid had no significant impact on the dose recommendation.

CONCLUSION

Patients with epilepsy should take the delayed doses as soon as they remember, and partial missed doses may need to be taken near or at the next scheduled time.

Population pharmacokinetics of carbamazepine in elderly patients

BACKGROUND

Carbamazepine is a commonly used antiepileptic drug in elderly patients. This study analyzed prospective data collected as part of a randomized, double-blinded trial of newly diagnosed epilepsy patients. The aims of this study were to determine the pharmacokinetic parameters and their variability of carbamazepine in elderly patients and to quantify the effect of covariates on these parameters.

METHODS

Prospectively collected carbamazepine concentrations from 121 patients aged 60 years or older were used to develop a population pharmacokinetic model. Data were analyzed by a nonlinear mixed effects model (NONMEM). A 1-compartment model with first-order absorption and elimination was used to characterize the time course of carbamazepine concentration. Model evaluation and the predictive performance of the final model were assessed using the nonparametric bootstrap approach.

RESULTS

The apparent clearance (CL/F) of carbamazepine in this community-dwelling elderly population was estimated to be 3.59 L/h with an interindividual variability of 18.1%. The CL/F increases 23% in patients comedicated with phenytoin. The volume of distribution (V/F) was estimated to be 102 L with an interindividual variability of 74.7%.

CONCLUSIONS

Carbamazepine clearance was not associated with body weight or any parameterization of body size nor was age or race or any marker of hepatic or renal function in community dwelling elderly patients. Elderly patients on concurrent phenytoin therapy may require a smaller 23% higher dose on average, about half that reported for younger patients.

Population pharmacokinetics of lamotrigine with data from therapeutic drug monitoring in German and Spanish patients with epilepsy

This study develops a population pharmacokinetic model for lamotrigine (LTG) in Spanish and German patients diagnosed with epilepsy. LTG steady-state plasma concentration data from therapeutic drug monitoring were collected retrospectively from 600 patients, with a total of 1699 plasma drug concentrations. The data were analyzed according to a one-compartment model using the nonlinear mixed effect modelling program. The influences of origin (Germany or Spain), sex, age, total body weight, and comedication with valproic acid (VPA), levetiracetam, and enzyme-inducing antiepileptic drugs (phenobarbital [PB], phenytoin [PHT], primidone [PRM], and carbamazepine [CBZ]) were investigated using step-wise generalized additive modelling. The final regression model for LTG clearance (CL) was as follows: CL(L/h) = 0.028*total body weight*e(-0.713*VPA)*e0.663*PHT*e0.588*(PB or PRM)*e0.467*CBZ*e0.864*IND, where IND refers to two or more inducers added to LTG treatment; this factor as well as VPA, PHT, PB, PRM, and CBZ take a value of zero or one according to their absence or presence, respectively. The administration of inducers led to a significant increase in mean LTG CL (values of 0.045-0.070 L/h/kg vs. 0.028 L/h/kg being reached in monotherapy), whereas VPA led to a significant decrease in CL (0.014 L/h/kg). Thus, comedication with these analyzed drugs can partly explain the interindividual variability in population LTG CL, which decreased from the basic model by more than 40%. The proposed model may be very useful for clinicians in establishing initial LTG dosage guidelines. However, the interindividual variability remaining in the final model (clearance coefficient of variation close to 30%) make these a priori dosage predictions imprecise and justifies the need for LTG plasma level monitoring to optimize dosage regimens. Thus, this final model allows easy implementation in clinical pharmacokinetic software and its application in dosage individualization using the Bayesian approach.

A PLS-based extractive spectrophotometric method for simultaneous determination of carbamazepine and carbamazepine-10,11-epoxide in plasma and comparison with HPLC

Carbamazepine (CBZ) undergoes enzyme biotransformation through epoxidation with the formation of its metabolite, carbamazepine-10,11-epoxide (CBZE). A simple chemometrics-assisted spectrophotometric method has been proposed for simultaneous determination of CBZ and CBZE in plasma. A liquid extraction procedure was operated to separate the analytes from plasma, and the UV absorbance spectra of the resultant solutions were subjected to partial least squares (PLS) regression. The optimum number of PLS latent variables was selected according to the PRESS values of leave-one-out cross-validation. A HPLC method was also employed for comparison. The respective mean recoveries for analysis of CBZ and CBZE in synthetic mixtures were 102.57 (+/-0.25)% and 103.00 (+/-0.09)% for PLS and 99.40 (+/-0.15)% and 102.20 (+/-0.02)%. The concentrations of CBZ and CBZE were also determined in five patients using the PLS and HPLC methods. The results showed that the data obtained by PLS were comparable with those obtained by HPLC method.

Inherent correlation between dose and clearance in therapeutic drug monitoring settings: possible misinterpretation in population pharmacokinetic analyses

During the course of therapeutic drug monitoring (TDM), doses are adjusted to attain a target concentration range and a correlation between clearance (CL) and dose is introduced. In population pharmacokinetic analyses of such TDM data, CL has frequently been modeled as a function of dose. This paper demonstrates by simulation methodology that the TDM process does indeed introduce a correlation between dose and CL which can be interpreted as a nonlinearity. Using literature values of carbamazepine pharmacokinetics, three steady-state concentrations were simulated following a standard 1000 mg total daily dose (TDD) regimen in 100 in silico subjects. A set of clinical rules was established to adjust the TDD based on these three concentrations, as might be done in the clinical setting. Another set of concentrations using these TDM-derived TDDs for each subject (600-1600 mg) was simulated. A standard population pharmacokinetic analysis of the post-TDM data was conducted using NONMEM. This process was replicated 100 times to estimate the type II error rate. When CL was modeled without TDD, plots of WRES versus PRED demonstrated a clear pattern, as did the delta plots of CL (CL minus TVCL) versus TDD, suggesting the covariate TDD should be incorporated into the model. After TDD was included in the model for CL, the objective function value decreased by an average of 75.7 (p < 0.001). In addition, the inter-individual variability in CL expressed as a coefficient of variation decreased by an average of 9.9% and the diagnostic plots improved. Although CL was simulated to be independent of TDD, it was identified as an important covariate using standard approaches in a simulated TDM setting in 100% of the replicated simulation studies. The TDM process introduces a correlation between CL and TDD that can be misinterpreted as nonlinearity in the system.