Effect of CYP2C19, UGT1A8, and UGT2B7 on valproic acid clearance in children with epilepsy: a population pharmacokinetic model

Retrospective Analysis of Steady-State Sodium Valproate Plasma Concentrations in Chinese Patients With Bipolar Disorder: Impact of Demographic and Clinical Characteristics

BACKGROUND

This study comprehensively examined the demographic and clinical characteristics of patients undergoing valproic acid therapy and explored their potential impact on plasma valproic acid concentrations. All enrolled patients were administered the extended-release formulation. An in-depth investigation of factors, including dose, age, sex, body mass index, co-administered medications, and laboratory test findings, was conducted to evaluate their potential influence on study outcomes.

METHODS

In total, 164 patients met the inclusion criteria and were included in the analysis. The patient age ranged from 13 to 60 years, with a median age of 25.71 years. Most patients (89%) received a daily dose of 1 g valproic acid. Co-administered psychiatric medications included aripiprazole, quetiapine, and lorazepam. Laboratory test results, such as hemoglobin and transaminase levels, were also collected as part of the study.

RESULTS

The average plasma valproic acid plasma concentration was 79.8 mg/L. The dose significantly affected valproic acid concentrations, as a higher percentage of measurements exceeded the therapeutic range at a daily dose of 1 g. Furthermore, females exhibited significantly higher valproic acid concentrations compared with males at the same dose ( P < 0.05). However, different age groups showed no statistically significant differences in valproic acid concentrations ( P > 0.05). The co-administered antipsychotic and antidepressant medications significantly affected valproate concentrations, as reflected in the multiple regression model ( P < 0.01).

CONCLUSIONS

This study offers valuable insights into the demographic and clinical characteristics of patients undergoing valproic acid therapy. It highlights the influence of dose, sex, and concomitant medications on plasma valproic acid concentrations. Overall, these findings can help guide dose adjustments and implement personalized treatment strategies in valproic acid therapy.

Fixed parameters in the population pharmacokinetic modeling of valproic acid might not be suitable: external validation in Chinese adults with epilepsy or after neurosurgery

PURPOSE

This study aims to assess the predictive performance of published valproic acid (VPA) population pharmacokinetic (PPK) models using an external data set in Chinese adults with epilepsy or after neurosurgery.

METHODS

A total of 384 concentrations from 290 Chinese adults with epilepsy or after neurosurgery were used for external validation. Data on published VPA PPK models were extracted from the literature. Prediction-based diagnostics (such as F20 and F30), simulation-based diagnostics, and Bayesian forecasting were used to evaluate the predictability of models.

RESULTS

The results of prediction-based diagnostics of all models were unsatisfactory. Models B, F, and H showed the best prediction performance in simulation-based diagnostics and Bayesian forecasting, demonstrating superior precision and accuracy. Bayesian forecasting demonstrated significant improvements in the model predictability.

CONCLUSION

The published PPK models showed extensive variation in predictive performance for extrapolation among Chinese adults with epilepsy or after neurosurgery patients. Fixed parameters of Vd and Ka in the PPK modeling of VPA might be the reason for the unsatisfied predictive performance. Bayesian forecasting significantly improved model predictability and may help to individualize VPA dosing.

Population pharmacokinetics of valproic acid in children with epilepsy: Implications for dose tailoring when switching from oral syrup to sustained-release tablets

Significant pharmacokinetic (PK) differences exist between different forms of valproic acid (VPA), such as syrup and sustained-release (SR) tablets. This study aimed to develop a population pharmacokinetic (PopPK) model for VPA in children with epilepsy and offer dose adjustment recommendation for switching dosage forms as needed. The study collected 1411 VPA steady-state trough concentrations (Ctrough) from 617 children with epilepsy. Using NONMEM software, a PopPK model was developed, employing a stepwise approach to identify possible variables such as demographic information and concomitant medications. The final model underwent internal and external evaluation via graphical and statistical methods. Moreover, Monte Carlo simulations were used to generate a dose tailoring strategy for typical patients weighting 20-50 kg. As a result, the PK characteristics of VPA were described using a one-compartment model with first-order absorption. The absorption rate constant (ka) was set at 2.64 and 0.46 h-1 for syrup and SR tablets. Body weight and sex were identified as significant factors affecting VPA's pharmacokinetics. The final PopPK model demonstrated acceptable prediction performance and stability during internal and external evaluation. For children taking syrup, a daily dose of 25 mg/kg resulted in the highest probability of achieving the desired target Ctrough, while a dose of 20 mg/kg/day was appropriate for those taking SR tablets. In conclusion, we established a PopPK model for VPA in children with epilepsy to tailor VPA dosage when switching between syrup and SR tablets, aiming to improve plasma VPA concentrations fluctuations.

Evaluation of CYP2C19 Genetic Variant and Its Lack of Association with Valproic Acid Plasma Concentrations Among Zhuang and Han Schizophrenia Patients in Guangxi

Purpose

To investigate the CYP2C19 genotype distribution and allelic frequency among the Zhuang and Han schizophrenic populations in Guangxi, examine the correlation between CYP2C19 genetic variants and standardized blood levels of Valproic Acid (VPA) in schizophrenic patients, and evaluate the effects of age, gender, and Body Mass Index (BMI) on standardized VPA blood concentrations.

Patients and Methods

Between February and December 2022, 192 Zhuang and Han schizophrenia patients treated with VPA were studied. Steady-state VPA concentrations were determined using homogeneous enzyme immunoassays, and CYP2C19 *1, *2, and *3 loci via q-PCR. CYP2C19 genotype distributions between Zhuang and Han groups in Nanning were compared using chi-square tests and contrasted with other ethnicities. Non-parametric tests analyzed VPA variations, identifying critical factors through multivariate stepwise regression.

Results

The study identified five CYP2C19 genotypes at the *2 and *3 loci, with the *3/*3 genotype absent in both cohorts. The CYP2C19 distribution in Guangxi Zhuang and Han mirrors, yet diverges significantly from Hui and Kazakh groups. Among 192 subjects, VPA blood levels remained consistent across metabolic types and ages 18-60 but varied significantly by gender. Multivariate analysis revealed gender and BMI as significant factors, overshadowing CYP2C19 genotype and age.

Conclusion

In Guangxi, CYP2C19 genetic variants in Zhuang and Han schizophrenia patients demonstrate statistically indistinguishable allelic and metabolic distributions. Gender and BMI can influence standardized VPA blood concentrations in schizophrenia patients. However, in our study cohort, the CYP2C19 genotype and age are not the primary determinants of standardized VPA blood levels.

Sources of pharmacokinetic and pharmacodynamic variability and clinical pharmacology studies of antiseizure medications in the pediatric population

Multiple treatment options exist for children with epilepsy, including surgery, dietary therapies, neurostimulation, and antiseizure medications (ASMs). ASMs are the first line of therapy, and more than 30 ASMs have U.S. Food and Drug Administration (FDA) approval for the treatment of various epilepsy and seizure types in children. Given the extensive FDA approval of ASMs in children, it is crucial to consider how the physiological and developmental changes throughout childhood may impact drug disposition. Various sources of pharmacokinetic (PK) variability from different extrinsic and intrinsic factors such as patients' size, age, drug-drug interactions, and drug formulation could result in suboptimal dosing of ASMs. Barriers exist to conducting clinical pharmacological studies in neonates, infants, and children due to ethical and practical reasons, limiting available data to fully characterize these drugs' disposition and better elucidate sources of PK variability. Modeling and simulation offer ways to circumvent traditional and intensive clinical pharmacology methods to address gaps in epilepsy and seizure management in children. This review discusses various physiological and developmental changes that influence the PK and pharmacodynamic (PD) variability of ASMs in children, and several key ASMs will be discussed in detail. We will also review novel trial designs in younger pediatric populations, highlight the role of extrapolation of efficacy in epilepsy, and the use of physiologically based PK modeling as a tool to investigate sources of PK/PD variability in children. Finally, we will conclude with current challenges and future directions for optimizing the efficacy and safety of these drugs across the pediatric age spectrum.

Modeling the protein binding non-linearity in population pharmacokinetic model of valproic acid in children with epilepsy: a systematic evaluation study

Background: Several studies have investigated the population pharmacokinetics (popPK) of valproic acid (VPA) in children with epilepsy. However, the predictive performance of these models in the extrapolation to other clinical environments has not been studied. Hence, this study evaluated the predictive abilities of pediatric popPK models of VPA and identified the potential effects of protein binding modeling strategies. Methods: A dataset of 255 trough concentrations in 202 children with epilepsy was analyzed to assess the predictive performance of qualified models, following literature review. The evaluation of external predictive ability was conducted by prediction- and simulation-based diagnostics as well as Bayesian forecasting. Furthermore, five popPK models with different protein binding modeling strategies were developed to investigate the discrepancy among the one-binding site model, Langmuir equation, dose-dependent maximum effect model, linear non-saturable binding equation and the simple exponent model on model predictive ability. Results: Ten popPK models were identified in the literature. Co-medication, body weight, daily dose, and age were the four most commonly involved covariates influencing VPA clearance. The model proposed by Serrano et al. showed the best performance with a median prediction error (MDPE) of 1.40%, median absolute prediction error (MAPE) of 17.38%, and percentages of PE within 20% (F20, 55.69%) and 30% (F30, 76.47%). However, all models performed inadequately in terms of the simulation-based normalized prediction distribution error, indicating unsatisfactory normality. Bayesian forecasting enhanced predictive performance, as prior observations were available. More prior observations are needed for model predictability to reach a stable state. The linear non-saturable binding equation had a higher predictive value than other protein binding models. Conclusion: The predictive abilities of most popPK models of VPA in children with epilepsy were unsatisfactory. The linear non-saturable binding equation is more suitable for modeling non-linearity. Moreover, Bayesian forecasting with prior observations improved model fitness.

Population pharmacokinetics of oxcarbazepine active metabolite in Chinese children with epilepsy

Oxcarbazepine (OXC) is an antiepileptic drug whose efficacy is largely attributed to its monohydroxy derivative metabolite (MHD). Nevertheless, there exists significant inter-individual variability in both the pharmacokinetics and therapeutic response of this drug. The objective of this study is to explore the impact of patients' characteristics and genetic variants on MHD clearance in a population pharmacokinetic (PPK) model of Chinese pediatric patients with epilepsy. The PPK model was developed using a nonlinear mixed effects modeling method based on 231 MHD plasma concentrations obtained from 185 children with epilepsy. The one-compartment model and combined residual model were established to describe the pharmacokinetics of MHD. Forward addition and backward elimination were employed to evaluate the impact of covariates on the model parameters. The model was evaluated using goodness-of-fit, bootstrap, visual predictive checks, and normalized prediction distribution errors. In the two final PPK models, age, estimated glomerular filtration rate (eGFR), and a combined genotype of six variants (rs1045642, rs2032582, rs7668282, rs2396185, rs2304016, rs1128503) were found to significantly reduce inter-individual variability for MHD clearance. The inter-individual clearance equals to 1.38 × (Age/4.74)0.29 × (eGFR/128.66)0.25 × eθABCB-UGT-SCN-INSR for genetic variants included model and 1.30 × (Age/4.74)0.30 × (eGFR/128.66)0.23 for model without genetic variants. The precision of all parameters was deemed acceptable, and the model exhibited good predictability while remaining stable and effective.    Conclusion: Age, eGFR, and genotype may play a significant role in MHD clearance in children with epilepsy. The developed PPK models hold potential utility in facilitating oxcarbazepine dose adjustment in pediatric patients. What is Known: • The adjustment of the oxcarbazepine regimen remains difficult due to the considerable inter- and intra-individual variability of oxcarbazepine pharmacokinetics. • Body weight and co-administration with enzyme-inducing antiepileptic drugs emerge as the most influential factors contributing to the pharmacokinetics of MHD. What is New: • A positive correlation was observed between eGFR and the clearance of MHD in pediatric patients with epilepsy. • We explored the influence of genetic polymorphisms on MHD clearance and identified a combined genotype (ABCB-UGT-SCN-INSR) that exhibited a significant association with MHD concentration.

Population pharmacokinetics of topiramate in Chinese children with epilepsy

OBJECTIVE

Topiramate, a broad-spectrum antiepileptic drug, exhibits substantial inter-individual variability in both its pharmacokinetics and therapeutic response. The aim of this study was to investigate the influence of patient characteristics and genetic variants on topiramate clearance using population pharmacokinetic (PPK) models in a cohort of Chinese pediatric patients with epilepsy.

METHOD

The PPK model was constructed using a nonlinear mixed-effects modeling approach, utilizing a dataset comprising 236 plasma concentrations of topiramate obtained from 181 pediatric patients with epilepsy. A one-compartment model combined with a proportional residual model was employed to characterize the pharmacokinetics of topiramate. Covariate analysis was performed using forward addition and backward elimination to assess the influence of covariates on the model parameters. The model was thoroughly evaluated through goodness-of-fit analysis, bootstrap, visual predictive checks, and normalized prediction distribution errors. Monte Carlo simulations were utilized to devise topiramate dosing strategies.

RESULT

In the final PPK models of topiramate, body weight, co-administration with oxcarbazepine, and a combined genotype of GKIR1-UGT (GRIK1 rs2832407, UGT2B7 rs7439366, and UGT1A1 rs4148324) were identified as significant covariates affecting the clearance (CL). The clearance was estimated using the formulas CL (L/h) = 0.44 × (BW⁄11.7)0.82 × eOXC for the model without genetic variants and CL (L/h) = 0.49 × (BW⁄11.7)0.81 × eOXC × eGRIK1-UGT for the model incorporating genetic variants. The volume of distribution (Vd) was estimated using the formulas Vd (L) = 6.6 × (BW⁄11.7). The precision of all estimated parameters was acceptable. Furthermore, the model demonstrated good predictability, exhibiting stability and effectiveness in describing the pharmacokinetics of topiramate.

CONCLUSION

The clearance of topiramate in pediatric patients with epilepsy may be subject to the influence of factors such as body weight, co-administration with oxcarbazepine, and genetic polymorphism. In this study, PPK models were developed to better understand and account for these factors, thereby improving the precision and individualization of topiramate therapy in children with epilepsy.

Successful LC-MS/MS assay development and validation for determination of valproic acid and its metabolites supporting proactive pharmacovigilance

Valproic acid (VPA) is a well-documented contributor to liver injury, which is likely caused by the formation of its toxic metabolites. Monitoring VPA and its metabolites is very meaningful for the pharmacovigilance, but the availability of a powerful assay is a prerequisite. In this study, for the first time, a sensitive and specific LC-MS/MS method was developed and validated to simultaneously quantify the concentrations of VPA and its six pestering isomer metabolites (3-OH-VPA, 4-OH-VPA, 5-OH-VPA, 2-PGA, VPA-G, and 2-ene-VPA) in human plasma, using 5-OH-VPA-d7 and VPA-d6 as the internal standards (ISs). We also figured out another tricky problem that the concentrations of the parent drug and the metabolites vary widely. Of note, after protein precipitation and dilution with acetonitrile (ACN) and 50% ACN successively, the analytes and the ISs were successfully separated on a Kinetex C18 column. Intriguingly, sacrificing its signal intensity by elevated collision energy of VPA finally achieved the simultaneous determination. As expected, the method showed great linearity (r > 0.998) over the concentration ranges for all analytes. The inter-day and intra-day accuracy and precision were both acceptable. The method was successfully applied in 127 children with epilepsy. This novel assay will support the VPA-associated pharmacovigilance in the future.

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.

Effects of UGT1A, CYP2C9/19 and ABAT polymorphisms on plasma concentration of valproic acid in Chinese epilepsy patients

Aim: To evaluate the association between genetic polymorphisms and plasma concentration-to-dose ratio of valproic acid (CDRV) in Chinese epileptic patients. Methods: A total of 46 epileptic patients treated with valproic acid therapy were enrolled. 18 SNPs in nine genes related to valproic acid were directly sequenced with Sanger methods. Results: Patients carrying UGT1A6 heterozygous genotypes had significantly lower CDRV than those carrying the wild-type genotypes. In contrast, patients with the homozygote genotypes of CYP2C9 and ABAT had higher CDRV than those with the wild-type genotypes and patients with the heterozygous genotypes of CYP2C19 had higher CDRV. Conclusion: Detection of genetic polymorphism in these genes might facilitate an appropriate dose of valproic acid for epileptic patients. Further studies with larger cohorts are necessary to underpin these observations.

Pharmacogenetic Aspects of Drug Metabolizing Enzymes and Transporters in Pediatric Medicine: Study Progress, Clinical Practice and Future Perspectives

As the activity of certain drug metabolizing enzymes or transporter proteins can vary with age, the effect of ontogenetic and genetic variation on the activity of these enzymes is critical for the accurate prediction of treatment outcomes and toxicity in children. This makes pharmacogenetic research in pediatrics particularly important and urgently needed, but also challenging. This review summarizes pharmacogenetic studies on the effects of genetic polymorphisms on pharmacokinetic parameters and clinical outcomes in pediatric populations for certain drugs, which are commonly prescribed by clinicians across multiple therapeutic areas in a general hospital, organized from those with the most to the least pediatric evidence among each drug category. We also further discuss the research status of the gene-guided dosing regimens and clinical implementation of pediatric pharmacogenetics. More and more drug-gene interactions are demonstrated to have clinical validity for children, and pharmacogenomics in pediatrics have shown evidence-based benefits to enhance the efficacy and precision of existing drug dosing regimens in several therapeutic areas. However, the most important limitation to the implementation is the lack of high-quality, rigorous pediatric prospective clinical studies, so adequately powered interventional clinical trials that support incorporation of pharmacogenetics into the care of children are still needed.

Pharmacogenetics-based population pharmacokinetic analysis and dose optimization of valproic acid in Chinese southern children with epilepsy: Effect of ABCB1 gene polymorphism

Objective: The aim of this study was to establish a population pharmacokinetic (PPK) model of valproic acid (VPA) in pediatric patients with epilepsy in southern China, and provide guidance for individualized medication of VPA therapy. Methods: A total of 376 VPA steady-state trough concentrations were collected from 103 epileptic pediatric patients. The PPK parameter values for VPA were calculated by using the nonlinear mixed-effects modeling (NONMEM) method, and a one-compartment model with first-order absorption and elimination processes was applied. Covariates included demographic information, concomitant medications and selected gene polymorphisms. Goodness-of-fit (GOF), bootstrap analysis, and visual predictive check (VPC) were used for model evaluation. In addition, we used Monte Carlo simulations to propose dose recommendations for different subgroup patients. Results: A significant effect of the patient age and ABCB1 genotypes was observed on the VPA oral clearance (CL/F) in the final PPK model. Compared with patients with the ABCB1 rs3789243 AA genotype, CL/F in patients with GG and AG genotypes was increased by 8% and reduced by 4.7%, respectively. The GOF plots indicated the satisfactory predictive performance of the final model, and the evaluation by bootstrap and VPC showed that a stable model had been developed. A table of individualized dosing regimens involving age and ABCB1 genotype was constructed based on the final PPK model. Conclusion: This study quantitatively investigated the effects of patient age and ABCB1 rs3789243 variants on the pharmacokinetic variability of VPA. The PPK models could be beneficial to individual dose optimization in epileptic children on VPA therapy.

Published population pharmacokinetic models of valproic acid in adult patients: a systematic review and external validation in a Chinese sample of inpatients with bipolar disorder

BACKGROUND

This study reviewed all published valproic acid (VPA) population pharmacokinetic (PPK) models in adult patients and assessed them using external validation methods to determine predictive performance.

METHODS

Thirteen published PPK models (labeled with letters A to M) not restricted to children were identified in PubMed, Embase, and Web of Science databases. They were evaluated in a sample totaling 411 serum concentrations from 146 adult inpatients diagnosed with bipolar disorder in a Chinese hospital. Serum concentrations of VPA were analyzed by validated ultra-performance liquid chromatography-tandem mass spectrometry. Performance was assessed by 4 tests (prediction-based diagnostics, visual predictive checks, normalized prediction distribution error, and Bayesian forecasting).

RESULTS

Models K and L, developed in large samples of Chinese and Thai patients, showed good performance in our Chinese dataset. Models H and J demonstrated good performance in Tests 2 and 3 of the 4 tests, respectively. Another 7 models exhibited intermediate performance. The models with the worst performance, F and M, could not be improved by Bayesian forecasting.

CONCLUSION

In our validation study the most important factors contributing to good performance were absence of children, Asian ethnicity, one-compartment models and inclusion of body weight and VPA dose in previously published models.

Population pharmacokinetics of valproic acid in adult Chinese patients with bipolar disorder

PURPOSE

To develop and validate a population pharmacokinetic (PPK) model of valproic acid (VPA) in adult Chinese patients with bipolar disorder, and provide guidance for individualized therapy in this population.

METHODS

A total of 1104 serum concentrations from 272 patients were collected in this study. The data analysis was performed using a nonlinear mixed-effects modeling approach. Covariates included demographic parameters, biological characteristics, and concomitant medications. Bootstrap validation (1000 runs), normalized prediction distribution error (NPDE), and external validation of 50 patients were employed to evaluate the final model.

RESULTS

A one-compartment model with first-order absorption and elimination was developed for VPA extended-release tablets. VPA clearance was significantly influenced by three variables: sex (12% higher in male patients), daily dose (increasing with the 0.13 exponent), and body weight (increasing with the 0.56 exponent). Typical values for the absorption rate constant (K_a), apparent clearance (CL/F), and apparent distribution volume (V/F) for a female patient weighing 70 kg administered VPA 1000 mg/day were 0.18 h^-1, 0.46 L/h, and 12.84 L, respectively. The results of model evaluation indicated a good stable and precise performance of the final model.

CONCLUSIONS

A qualified PPK model of VPA was developed in Chinese patients with bipolar disorder. This model could be used as a suitable tool for the personalization of VPA dosing for bipolar patients.

Effect of CYP2C19 polymorphisms on serum valproic level acid in Chinese Han patients with schizophrenia

Valproic acid is an anticonvulsant, which is also widely used for treating psychiatric disorders. Some clinical trials have demonstrated benefits of valproic acid augmentation therapy in schizophrenia. Interindividual variability in valproic acid dose and serum concentration may reflect functional consequences of genetic polymorphisms in genes encoding drug-metabolizing enzymes. The aim of this study was to determine the relationship between serum concentrations of valproic acid and single nucleotide polymorphisms of the cytochrome P450 (CYP) 2C19 gene in patients with schizophrenia. All patients had been receiving fixed dose of valproic acid for at least 2 weeks. The daily doses were 0.5–1.5 g. No other drugs except olanzapine were coadministered. Serum concentrations of valproic acid were measured using the ultra-high performance liquid chromatography method with mass-spectrometric detection. The CYP2C19 (CYP2C19*2 G681A rs4244285 and CYP2C19*3 G636A rs4986893) genotypes were identified by real-time PCR analyses. The mean concentration/dose ratios of valproic acid were significantly higher in patients with CYP2C19 *1/*2 genotype (P < 0.01) or CYP2C19 *2/*3 genotype (P < 0.01) than in those with CYP2C12 *1/*1 genotype. The mean concentration/dose ratios of valproic acid were significantly higher in patients with 1 (P < 0.01) or 2 (P < 0.01) mutated alleles for CYP2C19 than in those without mutated alleles. And the post hoc analysis revealed that the result has acceptable statistical (power (1 – β) = 0.8486 at type I  level of 0.05) to support the observed significant associations for CYP2C19 SNPs and serum C/D ratios of valproic acid. The findings of this study suggest that the genetic polymorphisms of CYP2C19 significantly affect the steady-state serum concentrations of valproic acid in Chinese Han population. The determination of the CYP2C19 genotypes may be useful for dosing adjustment in schizophrenia patients on valproic acid therapy.

Factors Influencing Sodium Valproate Serum Concentrations in Patients with Epilepsy Based on Logistic Regression Analysis

Background

We aimed to explore the risk factors that affect the serum concentration of sodium valproate (VPA-Na) in patients with epilepsy and to provide references for the rationale of the use of VPA-Na.

Material/Methods

The enzyme-multiplied immunoassay technique was used to determine the serum VPA-NA concentrations of 109 patients, and the results were retrospectively analyzed and summarized. A multivariate logistic regression model was used to analyze substandard serum VPA-Na concentrations.

Results

Fifty-six patients (51.38%) treated with VPA-Na tablets were within the effective treatment range of 50–100 μg/mL, while 53 patients (48.62%) were out of the treatment range. The results indicated that the standard-reaching rate of serum drug concentration in the juvenile group was higher than that in the adult and elderly groups; the standard-reaching rates of serum drug concentrations in the low-dose group and the intermediate-dose group were lower than that in the high-dose group; and the standard-reaching rate of serum drug concentration in the group receiving carbapenems in combination was lower than that in the non-combination group; all differences were statistically significant. The combination with carbapenems and enzyme inducers was an independent risk factor for VPA-Na serum concentration below the target level in hospitalized patients.

Conclusions

To improve clinical efficacy and reduce the occurrence of adverse reactions, there is a need for therapeutic drug monitoring of VPA-Na. Moreover, individual administration should be implemented when VPA-Na tablets are used in the treatment of epilepsy because of the significant fluctuation in VPA-Na blood concentration.

CYP2C19 & UGT1A6 genetic polymorphisms and the impact on Valproic acid-induced weight gain in people with epilepsy: Prospective genetic association study

OBJECTIVES

To study the association between CYP2C19*2 (681 G > A) and UGT1A6*2 (552A > C) polymorphisms on Valproic acid (VPA)-induced weight gain in People with epilepsy (PWE).

METHODS

We recruited PWE on VPA monotherapy and genotyped for CYP2C19 and UGT1A6 polymorphisms. Association between CYP2C19 polymorphism and weight gain was the primary outcome parameter. We followed them up monthly for six months and recorded Body mass index (BMI), drug compliance, side effects, food frequency, physical activity.

RESULTS

Of 108 participants recruited, we assessed the association between the polymorphism and weight gain in 101 PWE for CYP2C19*2 and 103 PWE for UGT1A6*2 polymorphism. The proportion of participants with weight gain was higher in those with poor and intermediate metabolizer genotypes of CYP2C19 (*1/*2 and *2/*2) compared to extensive metabolizers (*1/*1) [53.3 % vs 31.7 %, RR 1.68, 95 % CI (1.01-2.79), P = 0.03]. However, CYP2C19*2 allele did not show an increased risk of weight gain over the CYP2C19*1 allele. No association could be demonstrated with UGT1A6 genotypes and weight gain. In logistic regression analysis, CYP2C19*2 carrier genotype was the independent predictor of weight gain. OR 2.89 [95% CI (1.07-7.84)]. There were no significant association with serum TSH, fT4, testosterone, and valproate levels with CYP2C19 or UGT1A6 polymorphisms.

SIGNIFICANCE

People with epilepsy carrying CYP2C19 polymorphisms (*1/*2) and (*2/*2) had 3 times higher risk of VPA-induced weight gain compared to wild type (*1/*1).

Modulation of the transport of valproic acid through the blood-brain barrier in rats by the Gastrodia elata extracts

HEADINGS ETHNOPHARMACOLOGICAL RELEVANCE

Valproic acid (VPA) is primarily used as a medicine for the treatment of seizures. Gastrodia elata (G. elata) extract has been used as an alternative medicine for epilepsy patients. Cotreatment with VPA and G. elata extract is commonly prescribed in Taiwan and mainland China. Nevertheless, the mechanism of the blood-brain barrier (BBB) transportation effect of G. elata extract on VPA has not been characterized.

AIM OF STUDY

Our hypothesis is that G. elata extract modulates the BBB penetration of VPA through specific transporter transfer.

MATERIALS AND METHODS

A validated liquid chromatography-tandem mass spectrometry and multiple microdialysis method was developed to simultaneously monitor VPA in the blood and brain of rats. To investigate the mechanism of BBB modulation by the G. elata extract on VPA in the brain, cyclosporin A, a P-glycoprotein (P-gp) inhibitor and organic anion transporting polypeptide (OATP) inhibitor, was coadministered with the G. elata extract and VPA.

RESULTS

The pharmacokinetic results demonstrated that the VPA penetration ratio of the BBB, determined by the area under the concentration curve (AUC) ratio of VPA (AUC_brain/AUC_blood), was approximately 0.36. After treatment with the G. elata extract (1 and 3 g/kg, p.o. for 5 consecutive days), the VPA penetration ratios were significantly enhanced to 1.47 and 1.02, respectively. However, in the experimental group coadministered cyclosporin A, the G. elata extract was unable to enhance the BBB transportation of VPA. Instead, the VPA penetration ratio in the brain was suppressed back to 0.38.

CONCLUSIONS

The present study reveals that the enhancement effect of the transporter mechanism of G. elata extract on VPA transport into the brain occurs through the OATP transporter but not the P-gp transporter.

Influence of UGT2B7 and UGT1A6 polymorphisms on plasma concentration to dose ratio of valproic acid in Chinese epileptic children

We explored the potential effects of genetic variations on the concentration to dose ratio (CDR) of valproic acid (VPA) in paediatric epilepsy patients.Two hundred and twenty-nine epileptic children on VPA monotherapy were included, and the VPA trough concentrations at steady-state of all subjects were determined.Nineteen single nucleotide polymorphisms (SNPs) of seven selected genes related to the metabolising enzymes and transporters of VPA were identified, and their influences on CDR_VPA (a logarithmic transformation was performed if abnormally distributed) were evaluated.UGT2B7 rs7668258 (C>T) TT genotype was associated with a decrease in lnCDR_VPA among epileptic children receiving VPA monotherapy (β=-0.191, p = 0.036). Significantly lower lnCDR_VPA was also observed in paediatric patients with UGT1A6 rs2070959 (A>G) GG genotype compared to those AA genotype (β=-0.270, p = 0.021).This research indicated that UGT2B7 rs7668258 (C>T) and UGT1A6 rs2070959 (A>G) polymorphisms may be correlated to the normalised plasma concentrations of VPA in Chinese epileptic children. The associations could be abolished after Bonferroni's correction and our findings need to be validated in further and larger investigations.

Pharmacogenetics of Carbamazepine and Valproate: Focus on Polymorphisms of Drug Metabolizing Enzymes and Transporters

Pharmacogenomics can identify polymorphisms in genes involved in drug pharmacokinetics and pharmacodynamics determining differences in efficacy and safety and causing inter-individual variability in drug response. Therefore, pharmacogenomics can help clinicians in optimizing therapy based on patient's genotype, also in psychiatric and neurological settings. However, pharmacogenetic screenings for psychotropic drugs are not routinely employed in diagnosis and monitoring of patients treated with mood stabilizers, such as carbamazepine and valproate, because their benefit in clinical practice is still controversial. In this review, we summarize the current knowledge on pharmacogenetic biomarkers of these anticonvulsant drugs.

Impact of gender, albumin, and CYP2C19 polymorphisms on valproic acid in Chinese patients: a population pharmacokinetic model

OBJECTIVE

This prospective study aimed to establish the valproic acid (VPA) population pharmacokinetic model in Chinese patients and realise personalised medication on the basis of population pharmacokinetics.

METHODS

The patients' clinical information and VPA plasma concentrations were collected from The General Hospital of Taiyuan Iron & Steel (Group) Corporation (TISCO). Nonlinear mixed-effect modelling was used to build the population pharmacokinetic model. To characterise the pharmacokinetic data, a one-compartment pharmacokinetic model with first-order absorption and elimination was used. The first-order conditional estimation with η-ε interaction was applied throughout the model-developing procedure. The absorption rate constant (Ka) was fixed at 2.38 hour^-1, and the impact of covariates on clearance and apparent volume of distribution were also explored. Medical records of 60 inpatients were reviewed prospectively and the objective function value (OFV) of the base model and final model were 851.813 and 817.622, respectively.

RESULTS

Gender was identified as the covariate that had a significant impact on the volume of distribution, and albumin and CYP2C19 genotypes influenced clearance.

CONCLUSION

Bootstrap and VPC indicated that a reliable model had been developed that was based on the simulation results, and a simple-to-use dosage regimen table was created to guide clinicians for VPA drug dosing.