Lamotrigine pharmacokinetics following oral and stable-labeled intravenous administration in young and elderly adult epilepsy patients: Effect of age

Development and Evaluation of Ontogeny Functions of the Major UDP-Glucuronosyltransferase Enzymes to Underwrite Physiologically Based Pharmacokinetic Modeling in Pediatric Populations

Uridine 5'-diphospho-glucuronosyltransferases (UGTs) demonstrate variable expression in the pediatric population. Thus, understanding of age-dependent maturation of UGTs is critical for accurate pediatric pharmacokinetics (PK) prediction of drugs that are susceptible for glucuronidation. Ontogeny functions of major UGTs have been previously developed and reported. However, those ontogeny functions are based on in vitro data (i.e., enzyme abundance, in vitro substrate activity, and so on) and therefore, may not translate to in vivo maturation of UGTs in the clinical setting. This report describes meta-analysis of the literature to develop and compare ontogeny functions for 8 primary UGTs (UGT1A1, UGT1A4, UGT1A6, UGT1A9, UGT2B7, UGT2B10, UGT2B15, and UGT2B17) based on published in vitro and in vivo studies. Once integrated with physiologically based pharmacokinetics modeling models, in vivo activity-based ontogeny functions demonstrated somewhat greater prediction accuracy (mean squared error, MSE: 0.05) compared to in vitro activity (MSE: 0.104) and in vitro abundance-based ontogeny functions (MSE: 0.129).

UGT2B10 is the Major UDP-Glucuronosyltransferase 2B Isoform Involved in the Metabolism of Lamotrigine and is Implicated in the Drug-Drug Interaction with Valproic Acid

Lamotrigine is a phenyltriazine anticonvulsant that is primarily metabolized by phase II UDP-glucuronosyltransferases (UGT) to a quaternary N2-glucuronide, which accounts for ~ 90% of the excreted dose in humans. While there is consensus that UGT1A4 plays a predominant role in the formation of the N2-glucuronide, there is compelling evidence in the literature to suggest that the metabolism of lamotrigine is catalyzed by another UGT isoform. However, the exact identity of the UGT isoform that contribute to the formation of this glucuronide remains uncertain. In this study, we harnessed a robust reaction phenotyping strategy to delineate the identities and its associated fraction metabolized (fm) of the UGTs involved in lamotrigine N2-glucuronidation. Foremost, human recombinant UGT mapping experiments revealed that the N2-glucuronide is catalyzed by multiple UGT isoforms. (i.e., UGT1A1, 1A3, 1A4, 1A9, 2B4, 2B7, and 2B10). Thereafter, scaling the apparent intrinsic clearances obtained from the enzyme kinetic experiments with our in-house liver-derived relative expression factors (REF) and relative activity factors (RAF) revealed that, in addition to UGT1A4, UGT2B10 was involved in the N2-glucuronidation of lamotrigine. This was further confirmed via chemical inhibition in human liver microsomes with the UGT1A4-selective inhibitor hecogenin and the UGT2B10-selective inhibitor desloratadine. By integrating various orthogonal approaches (i.e., REF- and RAF-scaling, and chemical inhibition), we quantitatively determined that the fm for UGT1A4 and UGT2B10 ranged from 0.42 - 0.64 and 0.32 - 0.57, respectively. Finally, we also provided nascent evidence that the pharmacokinetic interaction between lamotrigine and valproic acid likely arose from the in vivo inhibition of its UGT2B10-mediated pathway.

Redefining the age-specific therapeutic ranges of lamotrigine for patients with epilepsy: A step towards optimizing treatment and increasing cost-effectiveness

OBJECTIVE

The pharmacokinetics of lamotrigine exhibits age-related characteristics. Nevertheless, current evidence regarding the therapeutic range of lamotrigine has been derived almost exclusively from studies in adult patients, and the applicability of this therapeutic range to the pediatric population remains unclear. The purpose of this study was to establish the appropriate age-specific therapeutic ranges of lamotrigine corresponding to adequate clinical responses for patients with epilepsy.

METHODS

This prospective cohort study of therapeutic drug monitoring included 582 Chinese epilepsy patients receiving lamotrigine monotherapy. Patients were divided into three age-related subgroups: (1) toddler and school-age group (2-12 years old, n = 168), (2) adolescent group (12-18 years old, n = 171), and (3) adult group (>18 years old, n = 243). Patients with a reduction in seizure frequency of 50 % or greater than baseline were defined as responders, and the remaining patients were non-responders. The relationship between lamotrigine serum concentrations and clinical response was assessed using multivariate logistic regression analysis. A receiver operating characteristic curve was generated to determine the representative cut-off values of lamotrigine trough levels, to distinguish responders from non-responders. The upper margin of the therapeutic range of lamotrigine was determined by developing concentration-effect curves for the three age-related subgroups.

RESULTS

The median trough levels of lamotrigine were significantly higher in responders than in non-responders from all three age-related groups (P < 0.0001). Results of logistic regression analysis revealed that higher serum concentrations of lamotrigine predicted a higher probability that seizure frequency would be reduced by more than 50 % compared to baseline (adjusted odds ratio: 1.228, 95 % CI: 1.137-1.327; P < 0.0001), and younger children were less likely to be responders (adjusted odds ratio: 1.027, 95 % CI: 1.012-1.043; P = 0.001). Based on a trade-off between sensitivity and specificity, the optimal cut-off values for lamotrigine trough concentrations corresponding to clinical response were 3.29 mg/L, 2.06 mg/L, and 1.61 mg/L in the toddler and school-age group, adolescent group, and adult group, respectively. By reducing interpatient variability, the results of the concentration-effect curves suggested no additional clinical benefit from a continued increase of doses for lamotrigine concentrations exceeding 9.08 mg/L, 8.43 mg/L, and 10.38 mg/L in the toddler and school-age group, adolescent group, and adult group, respectively. In conclusion, the therapeutic ranges of lamotrigine trough concentrations corresponding to adequate clinical response were 3.29-9.08 mg/L in the toddler and school-age group, 2.06-8.43 mg/L in the adolescent group, and 1.61-10.38 mg/L in the adult group.

CONCLUSIONS

The study determined age-specific therapeutic ranges corresponding to optimal clinical efficacy for lamotrigine. Our findings lay the foundation for catalyzing novel opportunities to optimize treatment and reduce therapeutic costs. Based on the age-specific therapeutic ranges identified in this study, individualized and cost-effective algorithms for lamotrigine treatment of epilepsy patients may be developed and validated in larger cohort studies of therapeutic drug monitoring.

Alzheimer's Disease and Epilepsy: A Perspective on the Opportunities for Overlapping Therapeutic Innovation

Early-onset Alzheimer's disease (AD) is associated with variants in amyloid precursor protein (APP) and presenilin (PSEN) 1 and 2. It is increasingly recognized that patients with AD experience undiagnosed focal seizures. These AD patients with reported seizures may have worsened disease trajectory. Seizures in epilepsy can also lead to cognitive deficits, neuroinflammation, and neurodegeneration. Epilepsy is roughly three times more common in individuals aged 65 and older. Due to the numerous available antiseizure drugs (ASDs), treatment of seizures has been proposed to reduce the burden of AD. More work is needed to establish the functional impact of seizures in AD to determine whether ASDs could be a rational therapeutic strategy. The efficacy of ASDs in aged animals is not routinely studied, despite the fact that the elderly represents the fastest growing demographic with epilepsy. This leaves a particular gap in understanding the discrete pathophysiological overlap between hyperexcitability and aging, and AD more specifically. Most of our preclinical knowledge of hyperexcitability in AD has come from mouse models that overexpress APP. While these studies have been invaluable, other drivers underlie AD, e.g. PSEN2. A diversity of animal models should be more frequently integrated into the study of hyperexcitability in AD, which could be particularly beneficial to identify novel therapies. Specifically, AD-associated risk genes, in particular PSENs, altogether represent underexplored contributors to hyperexcitability. This review assesses the available studies of ASDs administration in clinical AD populations and preclinical studies with AD-associated models and offers a perspective on the opportunities for further therapeutic innovation.

Estrogen profile- and pharmacogenetics-based lamotrigine dosing regimen optimization: Recommendations for pregnant women with epilepsy

During pregnancy, various physiological changes occur that can alter the pharmacokinetics of antiepileptic drugs, such as lamotrigine (LTG). Anticipating the change in LTG dose required to achieve a pre-pregnancy target concentration is challenging. This study aimed to develop a refined population pharmacokinetic (PopPK) model of LTG in pregnant women with epilepsy (WWE) to identify factors explaining the variability in pharmacokinetics and to establish a model-informed individualized dosing regimen. On that basis, a coarsened model containing only clinical variables was also developed to examine its predictive performance compared to the refined model. In total, 322 concentration-time points from 51 pregnant WWE treated with LTG were employed to establish a refined PopPK model that included endogenous estrogen profiles, variants of candidate genes encoding LTG-metabolizing enzymes and -transporter proteins, and other clinical variables and a coarsened model that included only clinical variables, respectively. Data from an additional 11 patients were used for external validation of these two models. A nonlinear mixed-effect modeling approach was used for PopPK analysis of LTG. The standard goodness-of-fit method, bootstrap, normalized prediction distribution errors and external evaluation were adopted to estimate the stability and predictive performance of the candidate models. Akaike information criterion (AIC) was used to compare the goodness of fit between these two models. A lower AIC indicates a better fit of the data and the preferred model. Recommended dosing regimens for pregnant WWE were selected using Monte Carlo simulation based on the established optimal model. In the refined PopPK model, the population mean of apparent LTG clearance (CL/F) in pregnant WWE was estimated to be 2.82 L/h, with an inter-individual variability of 23.6%. PopPK analysis indicated that changes in estrogen profile during pregnancy were the predominant reason for the significant variations in LTG-CL/F. Up to the 3rd trimester, the concentration accumulation effect of E2 increased LTG-CL/F by 5.109 L/h from baseline levels. Contrary to effect of E2, E3 as the main circulating estrogen in pregnancy with a peak value of 34.41 ng/mL is 1000-fold higher than that in non-pregnancy reduced LTG-CL/F by 1.413 L/h. In addition, the UGT2B7 rs4356975 C > T and ABCB1 rs1128503 A > G variants may contribute to a better understanding of the inter-individual variability in LTG-CL/F. LTG-CL/F was 1.66-fold higher in UGT2B7 rs4356975 CT or TT genotype carriers than in CC genotype carriers. In contrast, ABCB1 rs1128503 GG genotype carriers had only 71.9% of the LTG-CL/F of AA or AG genotype carriers. In the coarsened PopPK model, the gestational age was a promising predictor of changes in LTG-CL/F. When comparing these two models, the refined PopPK model was favored over the coarsened PopPK model (AIC = -30.899 vs. -20.017). Monte Carlo simulation based on optimal PopPK model revealed that the LTG dosage administered to carriers of the UGT2B7 rs4356975 CT or TT genotype required a 33-50% increase to reach the pre-pregnancy target concentration, and carriers of the ABCB1 rs1128503 GG genotype required a 33-66% lower dose of LTG than carriers of the ABCB1 rs1128503 AA or AG genotype. Changes in estrogen profile during pregnancy was a better predictor of variations in LTG-CL/F than gestational age. The developed model based on estrogen profile and pharmacogenetics can serve as a foundation for further optimization of dosing regimens of LTG in pregnant WWE.

Sources of Interindividual Variability

The efficacy, safety, and tolerability of drugs are dependent on numerous factors that influence their disposition. A dose that is efficacious and safe for one individual may result in sub-therapeutic or toxic blood concentrations in others. A significant source of this variability in drug response is drug metabolism, where differences in presystemic and systemic biotransformation efficiency result in variable degrees of systemic exposure (e.g., AUC, C_max, and/or C_min) following administration of a fixed dose.Interindividual differences in drug biotransformation have been studied extensively. It is recognized that both intrinsic factors (e.g., genetics, age, sex, and disease states) and extrinsic factors (e.g., diet , chemical exposures from the environment, and the microbiome) play a significant role. For drug-metabolizing enzymes, genetic variation can result in the complete absence or enhanced expression of a functional enzyme. In addition, upregulation and downregulation of gene expression, in response to an altered cellular environment, can achieve the same range of metabolic function (phenotype), but often in a less predictable and time-dependent manner. Understanding the mechanistic basis for variability in drug disposition and response is essential if we are to move beyond the era of empirical, trial-and-error dose selection and into an age of personalized medicine that will improve outcomes in maintaining health and treating disease.

Appropriate use of essential medicines in the elderly: a comparison of the WHO essential medicines list and PIM criteria

PURPOSE

The elderly are not only threatened by bad medicines (overtreatment) but also by undertreatment with "good" medicines. Symmetry is required in any patient-centred approach to properly treat older people. The purpose of this study was to perfect the development of an EML and criteria according to the advantages of each and promote the appropriate use of essential medicines in the elderly.

METHOD

We compared the EML with four PIM criteria and calculated the proportion of essential medicines included in the criteria. We also summarized the rationale for including medicines in each criterion and analysed higher risk drugs and drug risks.

RESULTS

Of essential medicines, 26% are included in at least one criterion as PIM. In 11 drug categories of the EML, more than 50% of drugs of each category are included in at least one criterion, and in four categories, all drugs are included. The potentially inappropriate essential medicines (PIEMs) for the elderly focus on cardiovascular drugs and central nervous system drugs. Fifty-nine drugs have been explicitly identified as increasing the risk of falls, increasing mortality and/or having inappropriate long-term use, and the main risk of PIEMs is falls (30.3% of PIEMs). Additionally, 17.9% of essential medicines are labelled as positive drugs in START and/or FORTA (A/B).

CONCLUSION

Improving medication information for the elderly in the EML and establishing an essential medicines list for the elderly will promote appropriate drug use in older people worldwide.

Computational Approaches in Preclinical Studies on Drug Discovery and Development

Because undesirable pharmacokinetics and toxicity are significant reasons for the failure of drug development in the costly late stage, it has been widely recognized that drug ADMET properties should be considered as early as possible to reduce failure rates in the clinical phase of drug discovery. Concurrently, drug recalls have become increasingly common in recent years, prompting pharmaceutical companies to increase attention toward the safety evaluation of preclinical drugs. In vitro and in vivo drug evaluation techniques are currently more mature in preclinical applications, but these technologies are costly. In recent years, with the rapid development of computer science, in silico technology has been widely used to evaluate the relevant properties of drugs in the preclinical stage and has produced many software programs and in silico models, further promoting the study of ADMET in vitro. In this review, we first introduce the two ADMET prediction categories (molecular modeling and data modeling). Then, we perform a systematic classification and description of the databases and software commonly used for ADMET prediction. We focus on some widely studied ADMT properties as well as PBPK simulation, and we list some applications that are related to the prediction categories and web tools. Finally, we discuss challenges and limitations in the preclinical area and propose some suggestions and prospects for the future.

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.