Valproate population pharmacokinetics in children

Factors Influencing Plasma Concentrations of Valproic Acid in Pediatric Patients With Epilepsy and the Clinical Significance of CYP2C9 Genotypes in Personalized Valproic Acid Therapy

BACKGROUND

The aim of this study was to investigate the factors affecting plasma valproic acid (VPA) concentration in pediatric patients with epilepsy and the clinical significance of CYP2C9 gene polymorphisms in personalized dosing using therapeutic drug monitoring and pharmacogenetic testing.

METHODS

The medical records of children with epilepsy who underwent therapeutic drug monitoring at our institution between July 2022 and July 2023 and met the inclusion criteria were reviewed. Statistical analysis was performed to determine whether age, sex, blood ammonia, liver function, kidney function, and other characteristics affected the concentration-to-dose ratio of VPA (CDRV) in these patients. To investigate the effect of CYP2C9 polymorphisms on CDRV, DNA samples were collected from patients and the CYP2C9 genotypes were identified using real-time quantitative PCR.

RESULTS

The mean age of 208 pediatric patients with epilepsy was 5.50 ± 3.50 years. Among these patients, 182 had the CYP2C9 *1/*1 genotype, with a mean CDRV (mcg.kg/mL.mg) of 2.64 ± 1.46, 24 had the CYP2C9 *1/*3 genotype, with a mean CDRV of 3.28 ± 1.74, and 2 had the CYP2C9 *3/*3 genotype, with a mean CDRV of 6.46 ± 3.33. There were statistical differences among these 3 genotypes ( P < 0.05). The CDRV in these patients were significantly influenced by age, aspartate aminotransferase, total bilirubin, direct bilirubin, globulin, albumin/globulin ratio, prealbumin, creatinine, and CYP2C9 polymorphisms. In addition, multivariate linear regression analysis identified total bilirubin, direct bilirubin, and CYP2C9 polymorphisms as independent risk factors for high CDRV.

CONCLUSIONS

Liver problems and mutations in the CYP2C9 gene increase VPA levels. This underscores the importance of considering these factors when prescribing VPA to children with epilepsy, thereby enhancing the safety and efficacy of the therapy.

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.

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.

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 Pediatric and Adult Caucasian Patients

(1) Background: The aim of this study was to explore the valproic acid (VPA) pharmacokinetic characteristics in a large population of pediatric and adult Caucasian patients and to establish a robust population pharmacokinetic (PopPK) model. (2) Methods: A total of 2527 serum VPA samples collected from 1204 patients included in a therapeutic drug monitoring program were retrospectively analyzed. Patients were randomly assigned to either a model development group or an external evaluation group. PopPK analysis was performed on 1751 samples from 776 patients with NONMEM using a nonlinear mixed-effect modelling approach. The influence of demographic, anthropometric, treatment and comedication variables on the apparent clearance (CL/F) of VPA was studied. The bootstrap method was used to evaluate the final model internally. External evaluation was carried out using 776 VPA serum samples from 368 patients. (3) Results: A one-compartment model with first-order absorption and elimination successfully described the data. The final model included total body weight, age and comedication with phenytoin, phenobarbital and carbamazepine with a significant impact on VPA elimination. Internal and external evaluations demonstrated the good predictability of the model. (4) Conclusions: A PopPK model of VPA in Caucasian patients was successfully established, which will be helpful for model-informed precision dosing approaches in clinical patient care.

Population pharmacokinetics of unbound valproic acid in pediatric epilepsy patients in China: a protein binding model

PURPOSE

The purpose of this study was to establish a protein binding model of unbound valproic acid (VPA) based on Chinese pediatric patients with epilepsy and provide a reference for clinical medication.

METHODS

A total of 313 patients were included and both their total and unbound VPA concentrations (375 pairs of concentrations) were measured. NONMEM software was used for population pharmacokinetic modeling. The stepwise method was used to screen the potential covariates. Goodness-of-fit plot, bootstrap, and visual predictive check were used for model evaluation. In addition, dose recommendations for typical patients aged 0 to 16 years were proposed by Monte Carlo simulations.

RESULTS

A one-compartment model of first-order absorption and first-order elimination was used to describe the pharmacokinetic characteristics of unbound VPA, and the linear non-saturable binding equation was introduced to describe the protein binding. Body weight, age-based maturation, and co-medicated with lamotrigine could affect the CL/F of unbound and bound VPA. Model evaluation showed satisfactory robustness of the final model. The dosing regimens for children aged 0 to 16 years were proposed based on the final established model.

CONCLUSION

We developed a population pharmacokinetic model of unbound and bound VPA that took account of protein binding. The VPA dosing regimen in pediatric patients with epilepsy needs to be optimized by the body weight, age, and co-medications.

Remedial dosing recommendations for delayed or missed doses of valproic acid in patients with epilepsy based on Monte Carlo simulations

OBJECTIVE

Delayed or missed doses are unavoidable in the pharmacotherapy of epilepsy and significantly compromise the efficacy of antiepileptic drug treatment. An inappropriate remedial regimen can cause seizure relapse or serious adverse events. This study investigated the effect of delayed or missed doses on the pharmacokinetics (PK) of valproic acid (VPA) in patients with epilepsy and established remedial dosing recommendations for nonadherent patients.

METHODS

Monte Carlo simulations are based on all previous population pharmacokinetic models for pediatric, adult and elderly patients with epilepsy. The following four remedial strategies were investigated for each delayed dose: A) A partial dose or a regular dose is taken immediately; a regular dose is taken 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 dose and a partial dose are taken; the next scheduled time is skipped, and the regular regimen is resumed. D) Double doses are taken when missed one dose or two doses, and the regular regimen at the subsequent scheduled time is resumed.

RESULTS

The recommended remedial dose was related to the delay duration and daily dose. Remedial dosing strategies A and B were almost equivalent, whereas Strategy C was recommended when the delayed dose was close to the next scheduled dose. Strategy D was only suggested for delayed two doses.

CONCLUSION

Simulations provide quantitative insight into the remedial regimens for nonadherent patients, and clinicians should select the optimal regimen for each patient based on the individual's status.

Predictive ability of published population pharmacokinetic models of valproic acid in Thai manic patients

WHAT IS KNOWN AND OBJECTIVE

Population pharmacokinetic (PopPK) models of valproic acid (VPA) have been developed to aid individualized drug dosing, but most of these have been based on the treatment of epileptic patients and recent evidence shows that VPA clearance (CL_VPA ) in manic patients differs from that in epileptic patients. In the light of this, the predictive ability of selected VPA PopPK models based on epileptic patients was assessed to determine whether they could be used with patients with mania.

METHODS

VPA PopPK models that were based on the treatment of epileptic patients and developed using a non-linear mixed-effect approach with a one-compartment structure were selected and used to predict the VPA concentrations of a validation data set. The mean absolute prediction error (MAPE) and root mean square error (RMSE) were used to assess the accuracy and precision of the model.

RESULTS

The validation data set consisted of 235 Thai manic patients with a mean age of 39.6 years and a mean weight of 62.8 kg. Five models were selected to predict VPA concentrations in patients suffering from mania, and these were labelled A, C, E, F and G. The results showed that all models sufficiently predicted VPA concentrations in patients with mania, and of the models studied, G provided the most accurate and precise predictions, with MAPE and RMSE of 23% and 29.75, respectively.

WHAT IS NEW AND CONCLUSION

VPA PopPK models developed using patients with epilepsy can also be used for individualized dosing of patients with mania, but before implementation, the accuracy of these models' predictions should be assessed in the target population.

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.

Dextromethorphan Protect the Valproic Acid Induced Downregulation of Neutrophils in Patients with Bipolar Disorder

Objective

Valproic acid (VPA) is an anticonvulsant and commonly long term used as a mood stabilizer for patients with mood disorders. However its chronic effects on the hematological changes were noticed and need to be further evaluated. In this study, we evaluated, in Taiwanese Han Chinese patients with bipolar disorders (BD), the chronic effects of VPA or VPA plus dextromethorphan (DM) on the hematological molecules (white blood cell [WBCs], red blood cells [RBCs], hemoglobin, hematocrit, and platelets).

Methods

In a 12-week, randomized, double-blind study, we randomly assigned BD patients to one of three groups: VPA plus either placebo (VPA＋P, n = 57) or DM (30 mg/day, VPA＋DM30, n = 56) or 60 mg/day (VPA＋DM60, n = 53). The Young Mania Rating Scale and Hamilton Depression Rating Scale were used to evaluate symptom severity, and the hematological molecules were checked.

Results

Paired t test showed that the WBC, neutrophils, platelets and RBCs were significantly lowered after 12 weeks of VPA＋P or VPA＋DM30 treatment. VPA＋DM60 represented the protective effects in the WBCs, neutrophils, and RBCs but not in the platelets. We further calculated the changes of each hematological molecules after 12 weeks treatment. We found that combination use of DM60 significantly improved the decline in neutrophils induced by the long-term VPA treatment.

Conclusion

Hematological molecule levels were lower after long-term treatment with VPA. VPA＋DM60, which yielded the protective effect in hematological change, especially in the neutrophil counts. Thus, DM might be adjunct therapy for maintaining hematological molecules in VPA treatment.

Estimation of apparent clearance of valproic acid in adult Saudi patients

Background Valproic acid is one of several antiepileptic medications requiring therapeutic drug monitoring due to its complex and wide pharmacokinetic interindividual variability. Objective The objective of this study was to determine the population pharmacokinetics of valproic acid in adult Saudi patients and to identify factors that explain its pharmacokinetic variability. Setting Tertiary referral teaching hospital, Riyadh, Saudi Arabia. Method A retrospective chart review was performed at King Saud University Medical City of patients who received oral valproic acid. The population pharmacokinetic models were developed using Monolix 4.4. After development of the base model, we investigated several covariates including age, sex, weight, total daily dose, and cotherapy with carbamazepine and phenytoin. Main outcome measures the pharmacokinetic parameters of valproic acid and the variables that contributing towards its inter-individual variability. Results The analysis included a total of 54 valproic acid plasma concentrations from 54 patients (42.5% male). The data were sufficiently described by a one-compartment model with linear absorption and elimination processes. Average parameter estimates for valproic acid apparent clearance (CL/F) and apparent volume of distribution (V/F) were 0.14 L/h and 37.7 L (fixed), respectively. The inter-individual variability (coefficients of variation) in CL/F was 12%. The most significant covariates for valproic acid CL/F were age, body weight, total daily dose, and cotherapy with carbamazepine and phenytoin. Conclusion This model showed significant inter-individual variability between subjects. Our findings showed that patient age, body weight, total daily dose, and cotherapy with carbamazepine and phenytoin are the most significant covariates of valproic acid clearance. Collectively, healthcare providers should take these factors in consideration for optimal valproic acid dosage regimen.

Intravenous Valproic Acid Add-On Therapy in Acute Agitation Adolescents With Suspected Substance Abuse: A Report of Six Cases

The aim of this study was to test efficacy and safety of intravenous (IV) valproate for aggression in children and adolescents with mood or conduct disorder and concomitant substance abuse. Six patients received a 20 mg/kg dose of IV valproic acid as an add-on therapy to their standard therapy with second-generation antipsychotics and benzodiazepines. Agitation and general psychopathology were measured at baseline and after the first injection using the Modified Overt Aggression Scale, the Brief Psychiatric Rating Scale, and the Children's Global Assessment Scale. The findings suggested that in emergency psychiatry clinical settings, IV valproate was effective in reducing agitation and aggressive behaviors with a good tolerability profile and better treatment compliance.

Population pharmacokinetics of valproic acid in epileptic children: Effects of clinical and genetic factors

Valproic acid (VPA) is a first-line anti-epileptic drug that is used in the treatment of generalized and partial seizures. Gene variants had been proved to influence the pharmacokinetics (PK) of VPA and contribute to its inter-individual variability (IIV). The aim of this study was to systematically investigate the effects of candidate gene variants (CYPs, UGTs, ABC transporters, and nuclear receptors) on VPA PK in Chinese children with epilepsy. A total of 1065 VPA serum trough concentrations at steady state were collected from 264 epileptic pediatric patients aged 3 months to 16 years. The population pharmacokinetic (PPK) model was developed using a nonlinear mixed effects modelling (NONMEM) approach. For the final PPK model, the oral clearance (CL/F) of VPA was estimated to be 0.259 L/h with IIV of 13.3%. The estimates generated by NONMEM indicated that the VPA CL/F was significantly influenced by patient body weight (increased by an exponent of 0.662), co-administration with carbamazepine (increased CL/F by 22%), and daily dose of VPA (increased by an exponent of 0.22). CL/F in patients with the LEPR rs1137101 variant (668 AG and GG genotypes) was much lower than in patients with the AA genotype (17.8% and 22.6% lower, respectively). However, none of the CYPs or UGTs gene variants was found to influence the PK of VPA in this study. Evaluation by bootstrap and normalized prediction distribution error (NPDE) showed that the final model was stable. The predictive performance was evaluated by goodness-of-fit (GOF) plots and visual predictive checks (VPC), and the results indicated satisfactory precision. Our model suggests a correlation between VPA CL/F and LEPR rs1137101 variants, which might be beneficial in the context of individual dose optimization.

A population pharmacokinetic model taking into account protein binding for the sustained-release granule formulation of valproic acid in children with epilepsy

PURPOSE

The objective of this work was to develop a population pharmacokinetic model for a prolonged-release granule formulation of valproic acid (VPA) in children with epilepsy and to determine the doses providing a VPA trough concentration (C_trough) within the target range (50-100 mg/L).

METHODS

Ninety-eight children (1-17.6 years, 325 plasma samples) were included in the study. The model was built with NONMEM 7.3. The probability to obtain C_trough between 50 and 100 mg/L was determined by the Monte Carlo simulations for doses of 20, 30, 40, and 60 mg/kg/day and body weights between 10 and 70 kg.

RESULTS

A one compartment model, with first-order absorption and flip-flop parameterization and linear elimination, but taking protein binding into account, was used to describe the data. Typical values for unbound VPA clearance and distribution volume were 6.24 L/h/70 kg and 130 L/h/70 kg respectively. Both parameters were related to body weight via allometric models. The highest probability to obtain a C_trough within the target range for 10-kg children was obtained with a 40 mg/kg daily dose, whereas daily doses of 30 and 20 mg/kg were found appropriate for 20 to 30- and ≥ 40-kg children respectively. However, for these same doses, the exposure to unbound VPA could differ by 40%.

CONCLUSIONS

If the present study supports the current dose recommendations of 20-30 mg/kg/day, except for children under 20 kg, who may need higher doses, it also highlights the need for further research on the pharmacokinetics/pharmacodynamic profile of unbound VPA.

A systematic review of population pharmacokinetics of valproic acid

AIMS

Population pharmacokinetics is an essential tool that helps guide individualized dosing regimens. The aims of this systematic review are to provide knowledge concerning population pharmacokinetics of valproic acid (VPA) and to identify factors influencing VPA pharmacokinetic variability.

METHODS

PubMed and Embase databases were systematically searched from inception to June, 2017. Relevant articles from reference lists were also included. All population pharmacokinetic studies of VPA conducted in humans and that employed a nonlinear mixed effect modelling approach were included in this review.

RESULTS

Twenty-six studies were included in this review. Most studies characterized VPA pharmacokinetics as a one-compartment model. Three studies reported a two-compartment model. Body weight, dose and age were significant predictors for VPA volume of distribution (V_d ). The estimated V_d for one-compartment models ranged from 8.4 to 23.3 l. For two-compartment models, peripheral volumes of distribution ranged from 4.08 to 42.1 l. Frequently reported significant predictors for VPA clearance (CL_VPA ) included body weight, VPA dose, concomitant medications, gender and age. The estimated CL_VPA ranged from 0.206 to 1.154 l h^-1 and the inter-individual variability ranged from 13.40 to 35.90%. Two studies reported population pharmacokinetics/pharmacodynamics of VPA in patients with epilepsy. Seventeen studies evaluated the performance of their final models.

CONCLUSIONS

Significant predictors influencing VPA pharmacokinetics as well as model methodologies are highlighted in this review. For clinical application, CL_VPA could be predicted using body weight, VPA dose, concomitant medications, gender or age. For future research, there is a knowledge gap regarding population pharmacokinetics/pharmacodynamics of VPA in a population other than epileptic patients.

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.

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.

The Impact of Anti-Epileptic Drugs on Growth and Bone Metabolism

Epilepsy is a common neurological disorder worldwide and anti-epileptic drugs (AEDs) are always the first choice for treatment. However, more than 50% of patients with epilepsy who take AEDs have reported bone abnormalities. Cytochrome P450 (CYP450) isoenzymes are induced by AEDs, especially the classical AEDs, such as benzodiazepines (BZDs), carbamazepine (CBZ), phenytoin (PT), phenobarbital (PB), and valproic acid (VPA). The induction of CYP450 isoenzymes may cause vitamin D deficiency, hypocalcemia, increased fracture risks, and altered bone turnover, leading to impaired bone mineral density (BMD). Newer AEDs, such as levetiracetam (LEV), oxcarbazepine (OXC), lamotrigine (LTG), topiramate (TPM), gabapentin (GP), and vigabatrin (VB) have broader spectra, and are safer and better tolerated than the classical AEDs. The effects of AEDs on bone health are controversial. This review focuses on the impact of AEDs on growth and bone metabolism and emphasizes the need for caution and timely withdrawal of these medications to avoid serious disabilities.

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.

Population pharmacokinetics of cefquinome in pigs

This study was performed in 145 pigs to develop a population pharmacokinetics (PPK) model by i.m. administration of cefquinome (CEQ) at the dose of 2 mg/kg in the neck muscle. Serum physiological and biochemical parameters for each pig were determined before administration. After administration, 2-4 samples were collected at random, with the sampling point evenly distributed in the three periods (<1 h, 1-4 h and >4 h). The plasma concentration of CEQ was determined by high performance liquid chromatography with UV detector. The pharmacostatistical analyses of concentration-time data, weight, age, gender, serum physiological and biochemical parameters were performed with nonlinear mixed effect modeling (NONMEM). A one-compartmental model with first-order absorption and elimination adequately described the data from the study group. The optimal random effect model of pharmacokinetics parameters was of log-normal distribution and the residual errors assumed a mixed-type model (proportional and additive) to best explain intra-individual variability. Covariate analysis showed that body weight is positively correlated with apparent volume of distribution (V/F) and body clearance (CL/F). The typical PPK parameters of Ka , CL, and V were 0.564/h, 5.15 L/h, and 1.36 L, respectively.

Population pharmacokinetics of valproic acid in pediatric patients with epilepsy: considerations for dosing spinal muscular atrophy patients

Valproic acid (VPA) dosing strategies used in recent clinical trials in patients with spinal muscular atrophy (SMA) have utilized a paradigm of monitoring trough levels to estimate drug exposure with subsequent dose titration. The validity of this approach remains uncertain and could be improved by understanding sources of pharmacokinetic variability. A population pharmacokinetic analysis of VPA in pediatric patients with epilepsy was recently performed. The pooled data set included 52 subjects with epilepsy, ages 1 to 17 years, who received intravenous and/or various oral formulations. The data was best fit by a 2-compartment model; inclusion of age and weight reduced intersubject variability for clearance (41%), central volume (70%), and peripheral volume (42%) over the base model. The final model for clearance and volume parameters was clearance = 0.854 · (weight/70)(0.75); central volume of distribution = 10.3 · (weight/70)(1.0) · (age/8.5)(-0.267); peripheral volume of distribution = 4.08 · (weight/70)(1.0); and intercompartmental clearance = 5.34 · (weight/70)(0.75). Application of the model to data from a clinical trial in SMA patients suggests altered kinetics, perhaps based on underlying physiologic differences such as alterations in lean body mass. Future studies in SMA should incorporate modeling and simulation techniques to support individualized dosing and further assess if additional patient-specific factors necessitate alternative dosing strategies.

[Pharmacokinetic modelling of valproate in epileptic patients]

INTRODUCTION

The aim of our study was to develop and use a population pharmacokinetic model for assessment of individual valproate clearance in children and young adults suffering from epilepsy.

MATERIAL AND METHODS

The analysis was performed using 52 steady-state concentrations of valproate collected from 26 epileptic patients during the routine clinical practice in our hospital. The mean values of age and total body weight were 19.92 years and 57.12 kg, respectively. NONMEM software with ADVAN 1 subroutine was used for model building and assessing the influence of different covariates. A validation set of 20 epileptic patients (one blood sample per a patient) was used to estimate predicted performances of the pharmacokinetic model.

RESULTS

The typical mean value of the clearance of valproate estimated by the base model in our population was 0.3 77 I/h. Out of five considered covariates (total body weight, age, total daily dose, gender and polytherapy) only the age of the patients was a significant determinant of the clearance of valproate. The final regression model for the clearance of valproate was as following: CL (l/h) = 0.223 + 0.00819 * AGE CONCLUSION: The derived pharmacokinetical model describes the clearance of valproate in relation to patient's age in the observed population. it will help to improve the seizure control in young patients with epilepsy in Serbian population.

Age-related differences in susceptibility to cisplatin-induced renal toxicity

Limited experimental models exist to assess drug toxicity in pediatric populations. We recently reported how a multi-age rat model could be used for pre-clinical studies of comparative drug toxicity in pediatric populations. The objective of this study was to expand the utility of this animal model, which previously demonstrated an age-dependent sensitivity to the classic nephrotoxic compound, gentamicin, to another nephrotoxicant, namely cisplatin (Cis). Sprague-Dawley rats (10, 25, 40 and 80 days old) were injected with a single dose of Cis (0, 1, 3 or 6 mg kg(-1) i.p.). Urine samples were collected prior and up to 72 h after treatment in animals that were >or= 25 days old. Several serum, urinary and 'omic' injury biomarkers as well as renal histopathology lesions were evaluated. Statistically significant changes were noted with different injury biomarkers in different age groups. The order of age-related Cis-induced nephrotoxicity was different than our previous study with gentamicin: 80 > 40 > 10 > 25 day-old vs 10 >or= 80 > 40 > 25-day-old rats, respectively. The increased levels of kidney injury molecule-1 (Kim-1: urinary protein/tissue mRNA) provided evidence of early Cis-induced nephrotoxicity in the most sensitive age group (80 days old). Levels of Kim-1 tissue mRNA and urinary protein were significantly correlated to each other and to the severity of renal histopathology lesions. These data indicate that the multi-age rat model can be used to demonstrate different age-related sensitivities to renal injury using mechanistically distinct nephrotoxicants, which is reflected in measurements of a variety of metabolite, gene transcript and protein biomarkers.

Potential relationships between transaminase abnormality and valproic acid clearance or serum carnitine concentrations in Japanese epileptic patients

This study tested the hypothesis that the determinants of mild liver injury are prerequisites for more severe idiosyncratic hepatotoxicity. This study verified whether the possible risk factors for rare idiosyncratic valproic acid (VPA)-induced hepatotoxicity, VPA clearance and/or serum carnitine concentrations are common to those for a mild elevation in transaminases in VPA-treated patients. VPA clearance was calculated in 172 Japanese patients with epilepsy, using a non-linear mixed-effects regression program. Carnitine concentrations were determined in a subset of 60 patients. The relationships between VPA clearance, carnitine concentration and levels of transaminases and ammonia were evaluated by Pearson's correlation coefficients. The final model of VPA apparent clearance (CL/F) was as follows: CL/F (L h−1) = 0.012 × (BW/40)0.34 × dose0.55 × 0.90gender × 1.32PHT × 1.11CBZ × 1.12PB, where BW = total body weight (kg); gender = 1 if female, 0 if male; PHT/CBZ/PB = 1 if phenytoin, carbamazepine, or phenobarbital, respectively, is coadministrated, otherwise 0. Either a higher VPA clearance or acyl/free carnitine ratio and a lower total and/or free carnitine concentration, but not VPA concentration, were associated with the mild elevation in transaminases or ammonia. These results support the initial hypothesis, while also helping to clarify the mechanism of severe idiosyncratic hepatotoxicity with VPA.

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.

Mechanism-based concepts of size and maturity in pharmacokinetics

Growth and development can be investigated using readily observable demographic factors such as weight and age. Size is the primary covariate and can be referenced to a 70-kg person with allometry using a coefficient of 0.75 for clearance and 1 for volume. The use of these coefficients is supported by fractal geometric concepts and observations from diverse areas in biology. Fat free mass (FFM) might be expected to do better than total body weight when there are wide variations in fat affecting body composition. Clearance pathways develop in the fetus before birth. The use of postnatal age as a descriptor of maturation is unsatisfactory because birth may occur prematurely; therefore postmenstrual age is a superior predictor of elimination function. A sigmoid E(max) model (Hill equation) describes gradual maturation of clearance in early life leading to a mature adult clearance achieved at a later age.

Population pharmacokinetics of valproate in Chinese children with epilepsy

AIM

The aim of the present study is to establish a population pharmacokinetic (PPK) model of valproate (VPA) in Chinese epileptic children to promote the reasonable use of anti-epileptic drugs.

METHODS

Sparse data of VPA serum concentrations from 417 epileptic children were collected. These patients were divided into 2 groups: the PPK model group (n=317) and the PPK valid group (n=100). The PPK parameter values of VPA were calculated by NONMEM software using the data of the PPK model group. A basic model and a final model were set up. To validate the 2 models, the concentrations of PPK valid group were predicted by each model, respectively. The mean prediction error (MPE), mean squared prediction error (MSPE), root mean squared prediction error (RMSPE), weight residues (WRES), and the 95% confidence intervals (95% CI) were also calculated. Then, the values between the 2 models were compared.

RESULTS

The PPK of VPA was determined by a 1-compartment model with a first-order absorption process. The basic model was: Ka=3.09 (h(-1)), V/F=20.4 (L), CL/F=0.296 (L/h). The final model was: Ka=0.251+2.24 x (1-HS) (h(-1)), V/F=2.88+0.157 x WT (L), CL/F=0.106(0.98 x CO)+ 0.0157 x AGE (L/h). For the basic model, the MPE, MSPE, RMSPE, WRES, and the 95% CI were -23.53 (-30.36, -16.70), 3728.96 (2872.72, 4585.20), 39.62 (34.34, 44.90), and -0.06 (-0.14, 0.02), respectively. For the final model, the MPE, MSPE, RMSPE, WRES, and the 95% CI were -1.16 (-4.85, 2.53), 1002.83 (1050.64, 1143.61), 23.04 (21.12, 24.96), and 0.08 (-0.04, 0.20), respectively. The final model was more optimal than the basic model.

CONCLUSION

The PPK model of VPA in Chinese epileptic children was successfully established. It will be valuable to facilitate individualized dosage regimens.

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.

Population pharmacokinetics of cyclosporine in clinical renal transplant patients

Population pharmacokinetics of cyclosporine (CsA) in clinical renal transplant patients has been reported in the present study. A total of 2,548 retrospective drug monitoring data points were collected from 120 renal transplant patients receiving CsA. Population modeling was performed using the NONMEM (nonlinear mixed-effect modeling) program, using a one-compartment model with first-order absorption and elimination. The final regression model for CsA clearance (CL/F) with the influence of six significant covariates, comprising postoperative days (POD), total bilirubin level (TBIL, micromolar concentration), current body weight (CBW, kilograms), age (years), concurrent metabolic inhibitors of cyclosporine (INHI), and hematocrit (HCT, percentage), has been established and expressed as CL/F=28.5 -- 1.24 . POD -- 0.252 . (TBIL -- 11)+0.188 . (CBW -- 58) --0.191 . (Age -- 42) -- 2.45 . INHI -- 0.212 . (HCT-- 28) (liters per hour). The values in parentheses represent the median level for each of the corresponding covariates. The population estimates for CL/F (28.5 l/h), V/F (volume of distribution, 133 l), and interpatient variability (CV%=19.7%) for CL/F were achieved, respectively. The population model was further validated by internal and external approaches, and was demonstrated to be effective and stable. Moreover, simulation was conducted to facilitate the individualized treatment based on patient information and the final model.

Nonparametric population modeling of valproate pharmacokinetics in epileptic patients using routine serum monitoring data: implications for dosage

Therapeutic drug monitoring (TDM) of valproate (VAL) is important in the optimization of its therapy. The aim of the present work was to evaluate the ability of TDM using model-based, goal-oriented Bayesian adaptive control for help in planning, monitoring, and adjusting individualized VAL dosing regimens. USC*PACK software and routine TDM data were used to estimate population and individual pharmacokinetics of two commercially available VAL formulations in epileptic adult and pediatric patients on chronic VAL monotherapy. The population parameter values found were in agreement with values reported earlier. A statistically significant (P < 0.001) difference in median values of the absorption rate constant was found between enteric-coated and sustained-release VAL formulations. In our patients (aged 0.25-53 years), VAL clearance declined with age until adult values were reached at about age 10. Because of the large interindividual variability in PK behavior, the median population parameter values gave poor predictions of the observed VAL serum concentrations. In contrast, the Bayesian individualized models gave good predictions for all subjects in all populations. The Bayesian posterior individualized PK models were based on the population models described here and where most patients had two (a peak and a trough) measured serum concentrations. Repeated consultations and adjusted dosage regimens with some patients allowed us to evaluate any possible influence of dose-dependent VAL clearance on the precision of total VAL concentration predictions based on TDM data and the proposed population models. These nonparametric expectation maximization (NPEM) population models thus provide a useful tool for planning an initial dosage regimen of VAL to achieve desired target peak and trough serum concentration goals, coupled with TDM soon thereafter, as a peak-trough pair of serum concentrations, and Bayesian fitting to individualize the PK model for each patient. The nonparametric PK parameter distributions in these NPEM population models also permit their use by the new method of 'multiple model' dosage design, which allows the target goals to be achieved specifically with maximum precision. Software for both types of Bayesian adaptive control is now available to employ these population models in clinical practice.

Sodium valproate induces apoptosis in the rat hepatoma cell line, FaO

Sodium valproate (VPA) is clinically employed as an anti-convulsant and, to a lesser extent, mood stabilizer. While the incidence of toxicity associated with the clinical use of valproate is low, serious hepatotoxicity makes up a significant percentage. Rats treated with high doses of sodium valproate are subject to hepatotoxicity, and the study of the molecular mechanisms underlying this phenomenon may shed further light on the human situation. Exposure to sodium valproate results in the down regulation in rat liver of several transcripts whose products are involved in cellular energy homeostasis, resulting in time-dependent fluctuations in cellular ATP, possibly resulting in cell death. To further examine this, classical markers of apoptosis were examined in the rat hepatoma cell line FaO following sodium valproate exposure. Concentrations greater than 300 microM sodium valproate resulted in a transient wave of apoptosis, as assessed by chromatin condensation and DNA fragmentation assay. Analysis indicated that Fas-ligand and caspase-11 expression were increased at the transcriptome level, while caspase-3 was activated at the proteome level during the exposure period. These data demonstrates that sodium valproate causes cell death through apoptosis in a rat liver cell line, and provides information on the possible molecular mechanisms underlying this phenomenon in vivo.

Population pharmacokinetics of intravenous valproic acid in Korean patients

OBJECTIVE

To determine population-based pharmacokinetic parameters for intravenous valproic acid, and the factors influencing these parameters, in Korean adults.

METHODS

Valproic acid concentrations were obtained using a peak and trough sampling scheme for 102 Korean epileptic patients who were not taking concurrent antiepileptic medication. Three hundred and fifty-four serum concentrations were analysed according to a one-compartment model with a mixed effect modelling method (NONMEM Ver 5.0). The influence of body-weight (kg), height, daily valproic acid dose (mg/day), body mass index (kg/m2), sex, and age on volume of distribution (Vd) and clearance (CL) was assessed in the course of analysis.

RESULTS

Vd and CL of valproic acid increased with body-weight. No significant influence of the other screened covariates was observed. The final regression model was: [equation: see text]. Interindividual variabilities (coefficient of variation) for CL and Vd were 32 and 18%, respectively. Residual error including intraindividual variability was 26.7%.

CONCLUSION

The current results may be used as a basic reference to optimize drug therapy with intravenous valproic acid. Further research on the paediatric population is necessary to confirm the non-linearity of the relation between body-weight and Vd.

Pharmacokinetic and pharmacodynamic effects of clonazepam in children with epilepsy treated with valproate: a preliminary study

The authors report the use of the quantitative pharmaco-EEG (QPEEG) technique to study the pharmacokinetics (PK) and pharmacodynamics (PD) of clonazepam (CZP) in four epileptic children who suffered uncontrolled seizures despite long-term valproate (VPA) therapy. After a single dose of CZP (0.05 mg/kg, PO), blood samples were collected at 0, 0.5, 1.0, 1.5, 2.0, 3.0, 4.0, 8.0, 12.0, and 24.0 hours. CZP and VPA concentrations were measured by HPLC or GC assay, respectively. At each blood collection time point, EEG signals (60 s) were recorded for brain electrical activity mapping, and the power percentage average (PPA) of each frequency band was calculated. The relationship between drug concentrations and their corresponding PPA of each frequency band was analyzed. VPA steady-state drug concentrations (Css) were within the therapeutic range and not affected by CZP. The peak concentration (Cmax) of CZP and the time intervals from dosing to Cmax (Tmax) were 20.9 ng/mL to 113.8 ng/mL and 1 hour to 1.5 hours, respectively. There was no significant correlation between VPA concentrations and the PPA of any of the EEG frequency bands. CZP blood concentrations showed significant correlation with PPA in 3 of the 4 patients. Our results suggested CZP could affect fast wave activities in proportion to CZP blood concentrations. We propose that QPEEG is a promising technique to study the PK and PD of selected anti-epileptic drugs.