Pharmacokinetics of lamotrigine in paediatric and young adult epileptic patients--nonlinear mixed effects modelling approach

Population Pharmacokinetics of Lamotrigine and Its N2-Glucuronide Metabolite in Chinese Patients With Epilepsy

BACKGROUND

Lamotrigine is a new antiepileptic drug with substantial interindividual variability in its pharmacokinetics and therapeutic responses. This study aimed to develop population pharmacokinetic (PPK) models of lamotrigine and its N2-glucuronide metabolites for model-informed individualized therapy.

METHODS

A total of 353 plasma concentrations from Chinese patients with epilepsy receiving oral lamotrigine were used to develop a population PPK model using a nonlinear mixed effects modeling method. One- and two-compartment models were applied to the nonmetabolite and metabolite model, respectively. Forward addition and backward elimination were used to establish the final model. Model validation was performed using standard goodness-of-fit, bootstrap, visual predictive checks, and normalized prediction distribution errors. Finally, simulations were performed to propose lamotrigine dosages in different situations to achieve trough concentrations within the reference interval (2.5-15 mg/L).

RESULTS

For both final population PPK models, coadministration with valproic acid (VPA) or enzyme inducer, and body weight significantly affected lamotrigine clearance. The final models for lamotrigine clearance were and for nonmetabolite and metabolite models, respectively. The precision of the PPK parameters was acceptable, and the models exhibited good predictability. Monte Carlo simulations revealed that the lamotrigine dosage administered to patients combined with an enzyme inducer must be tripled that administered with VPA to reach the target trough concentration.

CONCLUSIONS

Variability in the pharmacokinetics of lamotrigine is large. Coadministration of VPA or an enzyme inducer and body weight are the most important factors in lamotrigine clearance in Chinese patients with epilepsy. The developed population PPK models might support further optimization of lamotrigine dosing regimens.

UHPLC-MS/MS for plasma lamotrigine analysis and comparison with a homogenous enzyme immunoassay

Aims: To develop and validate a UHPLC-MS/MS method for lamotrigine (LTG) analysis in human plasma and evaluate its agreement with a homogenous enzyme immunoassay (HEIA). Materials & methods: The UHPLC-MS/MS method was developed and validated according to the USFDA/EMA guidelines. A Bland-Altman plot was used to evaluate the agreement between UHPLC-MS/MS and HEIA. Results: Samples were pretreated with one-step protein precipitation and separated in 2.6 min. The intra- and inter-day bias and imprecisions were -15.8 to 15.0% and less than 11.17%, respectively. The recovery and matrix factor were 98.30 to 111.97%. The mean overestimation of UHPLC-MS/MS compared with HEIA was 21.57%. Conclusion: A rapid, sensitive and robust UHPLC-MS/MS method for plasma LTG analysis was developed and validated and was a 21.57% overestimation compared with HEIA.

Joint use of population pharmacokinetics and machine learning for optimizing antiepileptic treatment in pediatric population

Purpose

Unpredictable drug efficacy and safety of combined antiepileptic therapy is a major challenge during pharmacotherapy decisions in everyday clinical practice. The aim of this study was to describe the pharmacokinetics of valproic acid (VA), lamotrigine (LTG), and levetiracetam (LEV) in a pediatric population using nonlinear mixed-effect modeling, while machine learning (ML) algorithms were applied to identify any relationships among the plasma levels of the three medications and patients' characteristics, as well as to develop a predictive model for epileptic seizures.

Methods

The study included 71 pediatric patients of both genders, aged 2-18 years, on combined antiepileptic therapy. Population pharmacokinetic (PopPK) models were developed separately for VA, LTG, and LEV. Based on the estimated pharmacokinetic parameters and the patients' characteristics, three ML approaches were applied (principal component analysis, factor analysis of mixed data, and random forest). PopPK models and ML models were developed, allowing for greater insight into the treatment of children on antiepileptic treatment.

Results

Results from the PopPK model showed that the kinetics of LEV, LTG, and VA were best described by a one compartment model with first-order absorption and elimination kinetics. Reliance on random forest model is a compelling vision that shows high prediction ability for all cases. The main factor that can affect antiepileptic activity is antiepileptic drug levels, followed by body weight, while gender is irrelevant. According to our study, children's age is positively associated with LTG levels, negatively with LEV and without the influence of VA.

Conclusion

The application of PopPK and ML models may be useful to improve epilepsy management in vulnerable pediatric population during the period of growth and development.

Polymorphisms Affecting the Response to Novel Antiepileptic Drugs

Epilepsy is one of the most frequent chronic neurologic disorders that affects nearly 1% of the population worldwide, especially in developing countries. Currently, several antiepileptic drugs (AEDs) are available for its therapy, and although the prognosis is good for most patients, 20%-30% amongst them do not reach seizure freedom. Numerous factors may explain AED-resistance such as sex, age, ethnicity, type of seizure, early epilepsy onset, suboptimal dosing, poor drug compliance, alcohol abuse, and in particular, genetic factors. Specifically, the interindividual differences in drug response can be caused by single nucleotide polymorphisms (SNPs) in genes encoding for drug efflux transporters, for the brain targets of AEDs, and for enzymes involved in drug metabolism. In this review, we used the PubMed database to retrieve studies that assessed the influence of SNPs on the pharmacokinetic (PK), pharmacodynamic (PD), and efficacy of new antiepileptic drugs. Our results showed that polymorphisms in the ABCB1, ABCC2, UGT1A4, UGT2B7, UGT2B15, CYP2C9, and CYP2C19 genes have an influence on the PK and efficacy of AEDs, suggesting that a genetic pre-evaluation of epileptic patients could help clinicians in prescribing a personalized treatment to improve the efficacy and the safety of the therapy.

Effects of genetic polymorphism of drug-metabolizing enzymes on the plasma concentrations of antiepileptic drugs in Chinese population

As a chronic brain disease, epilepsy affects ~50 million people worldwide. The traditional antiepileptic drugs (AEDs) are widely applied but showing various problems. Although the new AEDs have partially solved the problems of traditional AEDs, the current clinical application of traditional AEDs are not completely replaced by new drugs, particularly due to the large individual differences in drug plasma concentrations and narrow therapeutic windows among patients. Therefore, it is still clinically important to continue to treat patients using traditional AEDs with individualized therapeutic plans. To date, our understanding of the molecular and genetic mechanisms regulating plasma concentrations of AEDs has advanced rapidly, expanding the knowledge on the effects of genetic polymorphisms of genes encoding drug-metabolizing enzymes on the plasma concentrations of AEDs. It is increasingly imperative to summarize and conceptualize the clinical significance of recent studies on individualized therapeutic regimens. In this review, we extensively summarize the critical effects of genetic polymorphisms of genes encoding drug-metabolizing enzymes on the plasma concentrations of several commonly used AEDs as well as the clinical significance of testing genotypes related to drug metabolism on individualized drug dosage. Our review provides solid experimental evidence and clinical guidance for the therapeutic applications of these AEDs.

Concept and utility of population pharmacokinetic and pharmacokinetic/pharmacodynamic models in drug development and clinical practice

Due to frequent clinical trial failures and consequently fewer new drug approvals, the need for improvement in drug development has, to a certain extent, been met using model-based drug development. Pharmacometrics is a part of pharmacology that quantifies drug behaviour, treatment response and disease progression based on different models (pharmacokinetic - PK, pharmacodynamic - PD, PK/PD models, etc.) and simulations. Regulatory bodies (European Medicines Agency, Food and Drug Administration) encourage the use of modelling and simulations to facilitate decision-making throughout all drug development phases. Moreover, the identification of factors that contribute to variability provides a basis for dose individualisation in routine clinical practice. This review summarises current knowledge regarding the application of pharmacometrics in drug development and clinical practice with emphasis on the population modelling approach.

Dosing Recommendations for Lamotrigine in Children: Evaluation Based on Previous and New Population Pharmacokinetic Models

Lamotrigine is a broad-spectrum antiepileptic drug with high interindividual variability in serum concentrations in children. The aims of this study were to evaluate the predictive performance of pediatric population pharmacokinetic (PPK) models published on lamotrigine, to build a new model with our monitoring data and to evaluate the current recommended doses. A validation cohort included patients treated with lamotrigine who had a serum level assayed during therapeutic drug monitoring (TDM). PPK models published in the literature were first applied to the validation cohort. We assessed their predictive performance using mean prediction errors, root mean squared errors, and visual predictive checks. A new model was then built using the data. Dose simulations were performed to evaluate the doses recommended. We included 270 lamotrigine concentrations ranging from 0.5 to 17.9 mg/L from 175 patients. The median (range) age and weight were 11.8 years (0.8-18 years) and 32.7 kg (8-110 kg). We tested 6 PPK models; most had acceptable bias and precision but underestimated the variability of the cohort. We built a 1-compartment model with first-order absorption and elimination, allometric scaling, and effects of inhibitor and inducer comedications. In our cohort, 22.6% of trough concentrations were below 2.5 mg/L. In conclusion, we proposed a PPK model that can be used for TDM of lamotrigine in children. In our population, a high percentage of children had low trough concentrations of lamotrigine. As the intervals of recommended doses are large, we suggest aiming at the higher range of doses to reach the target concentration.

Effect of Age-Related Factors on the Pharmacokinetics of Lamotrigine and Potential Implications for Maintenance Dose Optimisation in Future Clinical Trials

BACKGROUND AND AIMS

In this study, we evaluate the performance of allometric concepts to predict the implications of age and size on the pharmacokinetics of lamotrigine, and assess the dose rationale across different age groups from 0.2 to 91 years.

METHODS

An allometrically scaled pharmacokinetic model was developed using adolescent and adult data, taking into account the effect of comedications. Model parameters were then used to extrapolate lamotrigine pharmacokinetics to older adults (> 65 years), children (4-12 years) and infants and toddlers (0.2-2.0 years). In addition, simulations were performed to identify the implication of different doses and dosing regimens for each population, so as to ensure steady-state concentrations within a predefined reference range.

RESULTS

The pharmacokinetics of lamotrigine was best described using a one-compartment model with first-order absorption and elimination. Carbamazepine, phenytoin, and valproic acid changed systemic clearance (CL) by + 76.5, + 129, and - 47.4%, respectively. Allometric principles allowed accurate extrapolation of disposition parameters to older adults and children older than 4 years of age. A maturation function was required to describe changes in exposure in younger patients. Compared with adults, a child aged 1.7 years has a 31.5% higher CL, after correcting for body weight. Patients > 65 years of age showed a decrease in CL of approximately 15%.

CONCLUSION

Population pharmacokinetic models are usually limited to a subgroup of patients, which may mask the identification of factors contributing to interindividual variability. The availability of an integrated model including the whole patient population provides insight into the role of age-related changes in the disposition of lamotrigine, and potential implications for maintenance dose optimisation in any future trials.

TRIAL REGISTRATION

According to GlaxoSmithKline's Clinical Trial Register, data from the GlaxoSmithKline studies LAM100034 and LEP103944, corresponding to ClinicalTrials.gov identifiers NCT00113165 and NCT00264615, used in this work, have been used in previous publications (doi: https://doi.org/10.1212/01.wnl.0000277698.33743.8b , https://doi.org/10.1111/j.1528-1167.2007.01274.x ).

Effects of Comedication and Genetic Factors on the Population Pharmacokinetics of Lamotrigine: A Prospective Analysis in Chinese Patients With Epilepsy

Lamotrigine (LTG) is a second-generation anti-epileptic drug widely used for focal and generalized seizures in adults and children, and as a first-line medication in pregnant women and women of childbearing age. However, LTG pharmacokinetics shows high inter-individual variability, thus potentially leading to therapeutic failure or side effects in patients. This prospective study aimed to establish a population pharmacokinetics model for LTG in Chinese patients with epilepsy and to investigate the effects of genetic variants in uridine diphosphate glucuronosyltransferase (UGT) 1A4, UGT2B7, MDR1, ABCG2, ABCC2, and SLC22A1, as well as non-genetic factors, on LTG pharmacokinetics. The study population consisted of 89 patients with epilepsy, with 419 concentrations of LTG. A nonlinear mixed effects model was implemented in NONMEM software. A one-compartment model with first-order input and first-order elimination was found to adequately characterize LTG concentration. The population estimates of the apparent volume of distribution (V/F) and apparent clearance (CL/F) were 12.7 L and 1.12 L/h, respectively. The use of valproic acid decreased CL/F by 38.5%, whereas the co-administration of rifampicin caused an increase in CL/F of 64.7%. The CL/F decreased by 52.5% in SLC22A1-1222AA carriers. Patients with the ABCG2-34AA genotype had a 42.0% decrease in V/F, whereas patients with the MDR1-2677TT and C3435TT genotypes had a 136% increase in V/F. No obvious genetic effect of UGT enzymes was found relative to the concentrations of LTG in Chinese patients. Recommended dose regimens for patients with different gene polymorphisms and comedications were estimated on the basis of Monte Carlo simulations and the established model. These findings should be valuable for developing individualized dosage regimens in adult and adolescent Chinese patients 13–65 years of age.

Remedial dosing recommendations for delayed or missed doses of lamotrigine in pediatric patients with epilepsy using Monte Carlo simulations

OBJECTIVE

This study investigated the effect of delayed or missed doses on the pharmacokinetics (PK) of lamotrigine (LTG) in children with epilepsy and established remedial dosing recommendations for nonadherent patients.

METHODS

The Monte Carlo simulation based on a published LTG population PK model was used to assess the effect of different scenarios of nonadherence and the subsequently administered remedial regimens. The following three remedial approaches were investigated for each delayed dose: A) A partial dose was administered immediately, and the regular dose was administered at the next scheduled time. B) The delayed dose was administered immediately, followed by a partial dose at the next scheduled time. C) The delayed and partial doses were coadministered immediately, the next scheduled dose was skipped, and the regular dosing was resumed at the subsequent scheduled time. The most appropriate remedial regimen was that with the shortest deviation time from the individual therapeutic window.

RESULTS

The effect of nonadherence on PK was dependent on the delay duration and daily dose, and the recommended remedial dose was related to the delay duration and concomitant antiepileptic drugs. Remedial dosing strategies A and B were almost equivalent, whereas C showed a larger PK deviation time. If one dose was missed, double doses were not recommended for the next scheduled time.

CONCLUSIONS

Simulations provide quantitative insight into the remedial regimens for nonadherent patients, and clinicians should select the optimal regimen based on the status of patients.

Adjustment of the area under the concentration curve by terminal rate constant for bioequivalence assessment in a parallel-group study of lamotrigine

AIM

A new strength of lamotrigine extended-release formulation unexpectedly failed to show bioequivalence with the existing strengths at the same dose in a parallel-group study. We report the post-hoc analyses conducted to identify the cause and propose an approach for future evaluations in similar situations.

METHODS

A seemingly bimodal distribution of the half-life among the study participants prompted the use of terminal-phase-rate-constant-adjusted area under the concentration curve as the endpoint for bioequivalence assessment. Population pharmacokinetic modelling was also performed to assess the bimodal distribution of apparent clearance and the potential treatment effects on bioavailability.

RESULTS

The cause for failing to achieve bioequivalence appeared to be a biased representation of a bimodal clearance distribution between the groups. The pharmacokinetic modelling with a mixture routine identified two subpopulations: 88% had a mean clearance of 1.99 l h-1 ; 12% had a mean clearance of 0.64 l h-1 . The low-clearance population was unequally represented by 13% and 4% of subjects in the reference and test groups, respectively, and treatment appeared to have no significant effect on oral bioavailability. The bioequivalence comparison using the adjusted area concluded with a 90% confidence interval of 0.91-1.06, suggesting that treatment had no significant effect on bioavailability and the formulations would meet regulatory criteria for bioequivalence.

CONCLUSIONS

The adjustment of the area under the concentration curve adjusted by terminal-phase rate constant should be considered for situational application in bioequivalence assessment when there are multiple clearance subpopulations in a parallel-group study.

Population pharmacokinetic models of lamotrigine in different age groups of Chinese children with epilepsy

PURPOSE

The study aims to establish population pharmacokinetic (PPK) models of lamotrigine (LTG) in different age groups of epileptic children by nonlinear mixed effect modelling(NONMEM), and provide essential tools and theoretical basis for individualised optimal drug dose.

METHODS

Cases of 473 epileptic children were divided into infant, toddler and preschool age (≤6 years) (n = 211), school age (6-12 years) (n = 171) and adolescence age (>12 years) (n = 81). A total of 625 steady-state serum trough concentration samples were extracted. The clinical information included demography, medication, serum concentration data and blood biochemical parameters. PPK models of LTG were established by NONMEM program, using first-order absorption and elimination. Demography and drug combination was investigated for influence on apparent clearance (CL) and apparent volume of distribution (Vd). To assess the accuracy and precision of the different ages and whole-age model, the mean prediction error (MPE), mean absolute error (MAE) and root mean squared error (RMSE) were compared.

RESULTS

The final model of LTG in different ages stage and whole age was as follows: (1) infant, toddler and preschool age CL = 0.715 × [(WEIG/16.25)^0.655] × (0.458^VPA) × (1.99^IND), V = 10.4; (2) school age CL(L/h) = 1.01 × (WEIG/30)^0.399 × 0.465^VPA × 1.98^IND, Vd(L) = 17.7; (3) adolescence age CL(L/h) = 1.49 × (WEIG/51.5)^0.509 × 0.498^VPA × 1.7^IND, Vd(L) = 23.1; (4) whole age CL = 0.945 × [(WEIG/25)^0.645] × (0.463^VPA) × (1.94^IND), V = 16.7 × (WEIG/25)^0.919 (WEIG, total body weight; VPA, combination with valproate, yes = 1, no = 0; IND, combination with enzyme inducer, yes = 1, no = 0). The values of MPE, MAE and RMSE in age-stage-specific models were less than the ones in the whole-age model, which suggests the age-stage-specific models have better precision and accuracy than the whole-age model.

CONCLUSION

PPK models of LTG in different age groups of epileptic children were successfully established. Weight and combination therapy were identified as significant covariates on LTG clearance. Compared with the whole-age model, the age-specific models are more reliable.

Pharmacokinetics of lamotrigine and its metabolite N-2-glucuronide: Influence of polymorphism of UDP-glucuronosyltransferases and drug transporters

AIMS

This study aimed to develop a population pharmacokinetic model for quantitative evaluation of the influence of genetic variants in metabolic enzymes and transporters on lamotrigine pharmacokinetics while taking into account the influence of various clinical, biochemical and demographic factors.

METHODS

We included 100 patients with epilepsy on stable dosing with lamotrigine as mono or adjunctive therapy. Lamotrigine and lamotrigine N-2-glucuronide concentrations were determined in up to two plasma samples per patient. Patients were genotyped for UGT1A4, UGT2B7, ABCB1 and SLC22A1. Population pharmacokinetic analysis was performed by non-linear mixed effects modelling. Prior knowledge from previous pharmacokinetic studies was incorporated to stabilize the modelling process. A parent-metabolite model was developed to get a more detailed view on the covariate effects on lamotrigine metabolism.

RESULTS

With a base model absorption rate (interindividual variability) was estimated at 1.96 h(-1) (72.8%), oral clearance at 2.32 l h(-1) (41.4%) and distribution volume at 77.6 l (30.2%). Lamotrigine clearance was associated with genetic factors, patient's weight, renal function, smoking and co-treatment with enzyme inducing or inhibiting drugs. In patients with UGT2B7-161TT genotype clearance was lower compared with GT and GG genotypes. Clearance was particularly high in patients with UGT2B7 372 GG genotype (compared with AA genotype it was 117%; 95% CI 44.8, 247% higher).

CONCLUSIONS

Variability in lamotrigine pharmacokinetics is large and quantification of its sources may lead to more precise individual treatment. Genotyping for UGT2B7 may be useful in various clinical settings.