Pharmacokinetics Of Phenytoin Research Articles

Pharmacokinetic profile of phenytoin in dried blood spot with high-performance liquid chromatography-photodiode array.

Phenytoin is a first-line antiepileptic drug with narrow therapeutic range and follows non-linear pharmacokinetics. Pharmacokinetics of phenytoin have been studied in plasma matrix before, however, there were several disadvantages. This study aimed to obtain partial validation data of the analytical method and the pharmacokinetic profile of phenytoin in Dried Blood Spot (DBS) of six healthy subjects. DBS has the advantage of only requiring small sample volumes and could be transported more efficiently. Phenytoin along with carbamazepine as the chosen internal standard was analyzed with a reversed-phase high performance-liquid chromatography system and a photodiode array detector at 205nm. The results of partial validation, which evaluated the linearity, within-run accuracy, and precision, were within the criteria acceptance range. The pharmacokinetic profile showed that average AUC0-t was 83.81 ± 37.32μg.h/mL and AUC0-∞ was 83.65 ± 38.89μg.h/mL with an average ratio of 93%. Previous study quantifying phenytoin in the plasma matrix found the average AUC0-t was 39.41 ± 8.57µg.h/mL and AUC0-∞ was 42.94 ± 9.55µg.h/mL. Despite the difference between parameters of phenytoin analyzed in DBS and plasma matrices, the pharmacokinetic profiles obtained from both matrices were similar indicated by comparable concentration-time curves, thus, proving that DBS matrix can be used interchangeably with the plasma matrix as a more comfortable and effective alternative to phenytoin quantification in blood.

Comprehensive Physiologically Based Pharmacokinetic Model to Assess Drug-Drug Interactions of Phenytoin.

Regulatory agencies worldwide expect that clinical pharmacokinetic drug-drug interactions (DDIs) between an investigational new drug and other drugs should be conducted during drug development as part of an adequate assessment of the drug's safety and efficacy. However, it is neither time nor cost efficient to test all possible DDI scenarios clinically. Phenytoin is classified by the Food and Drug Administration as a strong clinical index inducer of CYP3A4, and a moderate sensitive substrate of CYP2C9. A physiologically based pharmacokinetic (PBPK) platform model was developed using GastroPlus® to assess DDIs with phenytoin acting as the victim (CYP2C9, CYP2C19) or perpetrator (CYP3A4). Pharmacokinetic data were obtained from 15 different studies in healthy subjects. The PBPK model of phenytoin explains the contribution of CYP2C9 and CYP2C19 to the formation of 5-(4'-hydroxyphenyl)-5-phenylhydantoin. Furthermore, it accurately recapitulated phenytoin exposure after single and multiple intravenous and oral doses/formulations ranging from 248 to 900 mg, the dose-dependent nonlinearity and the magnitude of the effect of food on phenytoin pharmacokinetics. Once developed and verified, the model was used to characterize and predict phenytoin DDIs with fluconazole, omeprazole and itraconazole, i.e., simulated/observed DDI AUC ratio ranging from 0.89 to 1.25. This study supports the utility of the PBPK approach in informing drug development.

An analysis of the Michaelis-Menten pharmacokinetics of phenytoin in epileptic Indonesian adults

Background: Phenytoin metabolism has been shown to vary in different ethnic groups. Therefore, the authors studied phenytoin pharmacokinetics in Indonesian adult patients with epilepsy. Objective: The purpose of this study was to determine and analyse the pharmacokinetic parameters of Michaelis Menten Vmax (maximum velocity) and Km (the Michaelis constant) of phenytoin in adult epileptic patients. Method: Twelve adult epileptic patients were chosen on the basis that they had two reliable steady-state phenytoin serum levels at two different daily doses and they required an additional adjustment of phenytoin dosage monotherapy. Result: The Vmax and Km values for adult epileptic patients respectively, ranged from 3.78 to 9.65 mg/kg/day and from 0.71 to 5.58 mg/L and there was no correlation with age and weight (p > 0.05). The Vmax and Km values have shown individual variability. Conclusion: The optimal adjustment of phenytoin dose individually in adult epileptic patients based on Vmax and Km parameters needs to be done to get the desired steady-state level according to the clinical response.

Population pharmacokinetics of phenytoin in epileptic children and dosage regimens using Monte Carlo simulation

Population pharmacokinetics of phenytoin in epileptic children and dosage regimens using Monte Carlo simulation

Enhanced P-glycoprotein expression under high-altitude hypoxia contributes to increased phenytoin levels and reduced clearance in rats

To study the effect of plateau hypoxia on the concentration of P-glycoprotein (P-gp) substrate phenytoin, Wistar rats are randomly divided into the control group and the hypoxic group, including P-gp inhibited groups respectively. Blood, cerebrospinal fluid, brain tissue, and blood-brain barrier were collected in plain areas at an altitude of 1500 m and plateau areas at an altitude of 4010 m. Evans Blue exclusion was used to assess the integrity of the blood-brain barrier. Western blot and qPCR were used to detect changes in P-gp expression. LC-MS/MS was used to determine the concentration of phenytoin in plasma and cerebrospinal fluid. In the high-altitude plateau group, phenytoin AUC0-t, MRT0-t and t1/2 increased significantly by 60%, 48%, and 61%, respectively, and clearance decreased by 67% (p <0.05 for all parameter). The protein expression of P-gp in the blood-brain barrier of the plateau group was up-regulated 1.84 times and the gene expression was up-regulated 2.21 times. The concentrations of phenytoin in the CSF of rats in the plain and high-altitude groups were 864.7 ± 348.3 and 1000±273.9 ng•mL−1, respectively. However, after inhibiting P-gp, the concentration of phenytoin in the CSF decreased significantly. It indicates that the increased expression of P-gp on the blood-brain barrier may lead to an increase in the amount of phenytoin excreted from the blood into the CSF, which may cause neurotoxic side effects. These results demonstrate significant changes in the pharmacokinetics of phenytoin under hypoxic conditions, supporting the need for careful dose titration for drugs with a narrow therapeutic range under high-altitude conditions.

Phenytoin Pharmacokinetics and Cardiopulmonary Bypass: A Case of Seizures in the Postoperative Period

Phenytoin Pharmacokinetics and Cardiopulmonary Bypass: A Case of Seizures in the Postoperative Period

Population Pharmacokinetic Analysis of Phenytoin After Intravenous Administration of Fosphenytoin in Adult and Elderly Epileptic Patients.

Fosphenytoin, the diphosphate ester salt of phenytoin, is widely used to treat status epilepticus. The aim of this study was to develop a population pharmacokinetic (PPK) model to describe serum phenytoin concentrations after the intravenous administration of fosphenytoin in adult and elderly epileptic patients. Patient backgrounds, laboratory tests, and prescribed drugs were retrospectively collected from electronic medical records. Patients who received fosphenytoin were enrolled. The PPK analysis was performed using NONMEM 7.3.0 with the first-order conditional estimation method with interaction. Age, sex, laboratory tests, and coadministered drugs were selected as candidates for covariates. Significance levels for forward inclusion and backward elimination were set at 0.05 and 0.01, respectively. The study protocol was approved by the Fukuoka Tokushukai Ethics Committee. A total of 340 serum phenytoin concentrations from 200 patients treated with fosphenytoin were available. The median age and body weight of the population were 71 years and 53.4 kg, respectively. A linear 1-compartment model with the conversion rate of fosphenytoin to phenytoin clearly described the pharmacokinetics of phenytoin after the intravenous administration of fosphenytoin. Age was detected as a covariate of clearance (CL): CL (L/h) = 1.99 × (body weight/53.4) × (age/71). Goodness-of-fit plots revealed the high-predictive performance of the final PPK model, and systematic deviations were not observed. The final model was validated by a prediction-corrected visual predictive check and bootstrap analysis. We herein developed a PPK model to describe phenytoin concentrations after the intravenous administration of fosphenytoin. Age was identified as a significant covariate for CL.

Estimation of Phenytoin Pharmacokinetic Parameters in Saudi Epileptic Patients

Objective: This study aimed to assess the population pharmacokinetics of phenytoin in Saudi patients and identify factors affecting therapeutic parameters. Method: A retrospective chart review was performed at King Saud University Medical City on patients treated with oral phenytoin. We used Monolix 4.4. for population pharmacokinetic modeling. A base model was developed to investigate several covariates, including age, gender, weight, total daily dose (TTD), and liver function test results. Results: The analysis included a total of 81 phenytoin plasma concentrations from 43 patients (70% male). Patients’ mean (± SD) age was 41 (±18.7) years and body weight was 65.4 (±17.7) kg. The patients received a phenytoin TDD of 330.5 (±104.5) mg/day, resulting in a trough concentration of 11.2 (±10.3) mg/L. The data were sufficiently described by the one-compartment open model with linear absorption and nonlinear elimination processes. Average parameter estimates for phenytoin volume of distribution (V), maximal elimination rate (Vmax), and Michaelis-Menten constant (Km) were 0.61 L/h/kg, 6.12 mg/kg/day, and 5.33 mg/L, respectively. The most significant covariates on phenytoin Vmax and Km were the age and body weight of the patients, along with valproic acid (VPA) cotherapy. Conclusion: The population pharmacokinetic model of phenytoin in Saudi patients found significant interindividual variability between subjects, which was affected by the patients’ age, body weight, and VPA cotherapy as the most significant covariates on phenytoin Vmax and Km. To provide guidance in drug dosage decisions, further studies are required to evaluate all factors that may potentially influence the pharmacokinetics of phenytoin.

Silymarin as a flavonoid-type P-glycoprotein inhibitor with impact on the pharmacokinetics of carbamazepine, oxcarbazepine and phenytoin in rats

P-glycoprotein (P-gp) is an efflux transporter involved in drug-resistant epilepsy and some flavonoids have been targeted as effective P-gp inhibitors. Herein, we assessed the impact of silymarin on the pharmacokinetics of three antiepileptic drugs (AEDs) in rats. Animals were pretreated with silymarin, verapamil (positive control) or vehicle (negative control) 1 h before AEDs administration (carbamazepine (25 mg/kg), oxcarbazepine (OXC) (50 mg/kg), or phenytoin (100 mg/kg)). Multiple blood samples were collected after AED dosing, and a non-compartmental analysis was performed. An independent study was also conducted to investigate the effects of silymarin on the OXC plasma-to-brain distribution. Silymarin altered the pharmacokinetics of OXC, increasing its peak plasma concentration by 50% and its extent of systemic exposure by 41%, which had also impact on brain drug concentrations. These findings support that the co-administration of silymarin and OXC should continue to be explored as a strategy to reverse the pharmacoresistance in epilepsy.

Fosphenytoin Population Pharmacokinetics in the Acutely Ill Pediatric Population*

The purpose of this study is to describe the pharmacokinetics of phenytoin in pediatric patients receiving fosphenytoin. Retrospective, population pharmacokinetic analysis. Emergency department or PICU of a large tertiary care children's hospital. Patients less than 19 years old who received fosphenytoin in the PICU or emergency center for treatment of seizures from January 2011 to June 2017 were included. Population pharmacokinetic analysis was performed with NONMEM v7.3 (Icon Plc, Dublin, Ireland). Simulation was performed to determine optimal loading dose and maintenance dosing regimens. A total of 536 patients (55.4% male; median age, 3.4 yr [interquartile range, 0.92-8.5 yr]) met study criteria. Fosphenytoin was administered at median 15.1 mg/kg/dose (interquartile range, 6.3-20.7 mg/kg/dose). Mean serum concentrations of 17.5 ± 7.8 mg/L were at a median 4.2 hours (interquartile range, 2.5-7.8 hr) after a dose. A pharmacokinetic model with two compartments, allometrically scaled fat-free mass on all parameters, and serum creatinine and concomitant phenobarbital use on clearance had the best fit. Simulation demonstrated that a 20 mg/kg loading dose followed by 6 mg/kg/dose every 8 hours had the greatest percentage of concentrations in the 10-20 mg/L range, with reduced doses to achieve therapeutic in patients with reduced kidney function. A loading dose of 20 mg/kg followed by 6 mg/kg/dose every 8 hours based on fat-free mass is a reasonable empiric strategy for attainment and maintenance of therapeutic trough concentrations. Concomitant phenobarbital use may increase clearance of phenytoin and fosphenytoin dose reductions should occur in patients with reduced kidney function.

Radiosynthesis of 11C-phenytoin Using a DEGDEE Solvent for Clinical PET Studies.

Objective(s):Phenytoin is an antiepileptic drug that is used worldwide. The whole-body pharmacokinetics of this drug have been extensively studied using 11C-phenytoin in small animals. However, because of the limited production amounts that are presently available, clinical 11C-phenytoin PET studies to examine the pharmacokinetics of phenytoin in humans have not yet been performed. We aimed to establish a new synthesis method to produce large amounts of 11C-phenytoin to conduct human studies. Methods: [11C] methane was produced using an in-house cyclotron by the 14N (p, α) 11C nuclear reaction of 5 % of hydrogen containing 95 % of nitrogen gas. About 30 GBq of 11C-methane was then transferred to a homogenization cell containing Fe2O3 powder mixed with Fe granules heated at 320 0C to yield 11C-phosgene. Xylene, 1,4-dioxane, and diethylene glycol diethyl ether (DEGDEE) were investigated as possible reaction solvents. Results:The ratio of 11C-phenytoin radioactivity to the total 11C radioactivity in the reaction vessel (reaction efficiency) was 7.5% for xylene, 11% for 1,4-dioxane, and 37% for DEGDEE. The synthesis time was within 45 min from the end of bombardment until obtaining the final product. The radioactivity produced was more than 4.1 GBq in 10 mL of saline at the end of synthesis. The specific activity of the product ranged from 1.7 to 2.2 GBq/μmol. The quality of the [11C] phenytoin injection passed all criteria required for clinical use. Conclusion:The use of DEGDEE as a solvent enabled the production of a large amount of 11C-phenytoin sufficient to enable PET studies examining the human pharmacokinetics of phenytoin.

The role of pharmacogenetics of cytochrome P450s in phenytoin-induced DRESS syndrome.

Anil et al. (2017) report a patient who presented with drug rash with eosinophilia and systemic symptom (DRESS) syndrome. It may be induced by various drugs. In the mentioned report DRESS syndrome has been attributed to phenytoin use.CYP2C9 is a genetically polymorphic enzyme, and decreased metabolism of many drugs has been reported in the subjects carrying variants of rs1799853 and rs1057910, which were designated as CYP2C9*2 and *3. rs3758581, the variant investigated by Anil et al., is a genetic variant of CYP2C19 (not that of CYP2C9, as stated and discussed in the report). CYP2C19 is also a highly genetically polymorphic enzyme, and rs3758581 may be present in 40 different haplotypes of CYP2C19 including *2 and *17 (for detailed information: www.pharmvar.org/gene/CYP2C19). Detection of rs3758581 is not sufficient because the patient presented by Anil H et al. may have CYP2C19*2, CYP2C19*17, or any other variant due to the co-appearance of other possible genetic variations. It is of importance to perform the correct genetic analysis because CYP2C19*2 is associated with low enzyme activity but CYP2C19*17 is associated with increased enzyme activity.CYP2C9 is a major enzyme responsible for the metabolism of phenytoin. CYP2C9*2 (rs1799853) and *3 (rs1057910) should be considered in a Caucasian subject. CYP2C19 (especially *2 and *17) and ABCB1 polymorphisms may also be considered for the evaluation of the patient. Additionally, serum phenytoin levels would be helpful to understand the contribution of genetic polymorphisms on the pharmacokinetics of phenytoin in the patients presenting side effects like DRESS syndrome.

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

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. 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. 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. 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.

Changes in the Pharmacokinetics of Phenytoin in Dextran Sulfate Sodium-Induced Ulcerative Colitis in Mice.

We previously demonstrated that the expression levels of drug-metabolizing enzymes, cytochrome P450 (CYP) enzymes, in the liver are significantly decreased in a murine model of ulcerative colitis (UC). In this study, we investigated changes in the pharmacokinetics of phenytoin, a CYP2C substrate drug, in the presence of UC. Colitis was induced by feeding male mice 3.5% dextran sulfate sodium (DSS) dissolved in drinking water for 10 days. The messenger RNA (mRNA) expression of CYP2C29 and CYP2C37 and the protein expression of CYP2C in the liver were evaluated via real-time reverse transcription-polymerase chain reaction and Western blotting, respectively. In DSS-treated animals, both mRNA and protein expression levels of CYP2C in the liver were significantly reduced relative to those in control animals (by 20%-40%). Phenytoin (30 mg/kg) was administered orally in a single dose to mice, and plasma concentrations were measured. Plasma concentrations of phenytoin were higher in the DSS-treated group than in the control group at 12, 24, and 36 hours after administration. Animals given DSS also exhibited a higher area under the plasma concentration-time curve extrapolated to infinity (AUCinf, 315 μg·h/mL), a delayed elimination half-life ( T1/2, 8.1 hours), and a decreased body clearance (CL/F, 3.52 mL/h) compared with that of control animals (AUCinf, 215 μg·h/mL; T1/2, 3.6 h; CL/F, 5.58 mL/h). This study indicated that the presence of UC decreases CYP2C expression levels in the liver, thereby delaying the metabolism of CYP2C substrates, including phenytoin, and increasing blood concentrations of these substrates.

Impact of Genetic Polymorphisms on Phenytoin Pharmacokinetics and Clinical Outcomes in the Middle East and North Africa Region.

BackgroundGenetic polymorphisms are known to influence outcomes with phenytoin yet effects in the Middle East and North Africa region are poorly understood.ObjectivesThe objective of this systematic review was to evaluate the impact of genetic polymorphisms on phenytoin pharmacokinetics and clinical outcomes in populations originating from the Middle East and North Africa region, and to characterize genotypic and allelic frequencies within the region for genetic polymorphisms assessed.MethodsMEDLINE (1946–3 May, 2017), EMBASE (1974–3 May, 2017), Pharmacogenomics Knowledge Base, and Public Health Genomics Knowledge Base online databases were searched. Studies were included if genotyping and analyses of phenytoin pharmacokinetics were performed in patients of the Middle East and North Africa region. Study quality was assessed using a National Institutes of Health assessment tool. A secondary search identified studies reporting genotypic and allelic frequencies of assessed genetic polymorphisms within the Middle East and North Africa region.ResultsFive studies met the inclusion criteria. CYP2C9, CYP2C19, and multidrug resistance protein 1 C3435T variants were evaluated. While CYP2C9*2 and *3 variants significantly reduced phenytoin metabolism, the impacts of CYP2C19*2 and *3 variants were unclear. The multidrug resistance protein 1 CC genotype was associated with drug-resistant epilepsy, but reported impacts on phenytoin pharmacokinetics were conflicting. Appreciable variability in minor allele frequencies existed both between and within countries of the Middle East and North Africa region.Conclusions CYP2C9 decrease-of-function alleles altered phenytoin pharmacokinetics in patients originating from the Middle East and North Africa region. The impacts of CYP2C19 and multidrug resistance protein 1 C3435T variants on phenytoin pharmacokinetic and clinical outcomes are unclear and require further investigation. Future research should focus on the clinical outcomes associated with phenytoin therapy.PROSPERO 2017: CRD42017057850

MDR1 Gene Polymorphism and Phenytoin Pharmacokinetics in Epilepsy

MDR1 Gene Polymorphism and Phenytoin Pharmacokinetics in Epilepsy

Using Team-based Learning to Teach a Hybrid Pharmacokinetics Course Online and in Class

Objective. To compare the effectiveness of face-to-face and online team-based learning (TBL) to teach phenytoin pharmacokinetics. Design. A TBL format was used to teach an online cohort of 222 pharmacy students and two face-to-face cohorts (Tampa and Las Vegas) of pharmacy students. Students in all cohorts completed individual and team readiness tests (iRATs and tRATs), and a self-assessment survey to determine teamwork and content understanding. Knowledge retention questions also were added to the final examination. Assessment. Mean scores on iRATs were: 54% for the Tampa group; 72% for the Las Vegas group; and 58% for the online. Mean tRAT scores were 78.5% for the Tampa cohort and 82.2% for the Las Vegas cohort, compared to 89.5% for the online cohort. The mean tRAT scores for the online cohorts were significantly higher than those of the face-to-face cohorts. Data from the teamwork survey provided evidence of positive interactions among teams for all cohorts. Conclusion. Team-based learning can be an effective method for teaching applied pharmacokinetics in both face-to-face and online classes.

Pharmacokinetic model analysis of interaction between phenytoin and capecitabine.

Recent reports have shbown an increase in serum phenytoin levels resulting in phenytoin toxicity after initiation of luoropyrimidine chemotherapy. To prevent phenytoin intoxication, phenytoin dosage must be adjusted. We sought to develop a pharmacokinetic model of the interaction between phenytoin and capecitabine. We developed the phenytoin-capecitabine interaction model on the assumption that fluorouracil (5-FU) inhibits cytochrome P450 (CYP) 2C9 synthesis in a concentration- dependent manner. The plasma 5-FU concentration after oral administration of capecitabine was estimated using a conventional compartment model. Nonlinear pharmacokinetics of phenytoin was modeled by incorporating the Michaelis-Menten equation to represent the saturation of phenytoin metabolism. The resulting model was fitted to data from our previously-reported cases. The developed phenytoincapecitabine interaction model successfully described the profiles of serum phenytoin concentration in patients who received phenytoin and capecitabine concomitantly. The 50% inhibitory 5-FU concentration for CYP2C9 synthesis and the degradation rate constant of CYP2C9 were estimated to be 0.00310 ng/mL and 0.0768 day-1, respectively. This model and these parameters allow us to predict the appropriate phenytoin dosage schedule when capecitabine is administered concomitantly. This newly-developed model accurately describes changes in phenytoin concentration during concomitant capecitabine chemotherapy, and it may be clinically useful for predicting appropriate phenytoin dosage adjustments for maintaining serum phenytoin levels within the therapeutic range.

A Comprehensive Review on the Predictive Performance of the Sheiner-Tozer and Derivative Equations for the Correction of Phenytoin Concentrations

In settings where free phenytoin concentrations are not available, the Sheiner-Tozer equation-Corrected total phenytoin concentration = Observed total phenytoin concentration/[(0.2 × Albumin) + 0.1]; phenytoin in µg/mL, albumin in g/dL-and its derivative equations are commonly used to correct for altered phenytoin binding to albumin. The objective of this article was to provide a comprehensive and updated review on the predictive performance of these equations in various patient populations. A literature search of PubMed, EMBASE, and Google Scholar was conducted using combinations of the following terms: Sheiner-Tozer, Winter-Tozer, phenytoin, predictive equation, precision, bias, free fraction. All English-language articles up to November 2015 (excluding abstracts) were evaluated. This review shows the Sheiner-Tozer equation to be biased and imprecise in various critical care, head trauma, and general neurology patient populations. Factors contributing to bias and imprecision include the following: albumin concentration, free phenytoin assay temperature, experimental conditions (eg, timing of concentration sampling, steady-state dosing conditions), renal function, age, concomitant medications, and patient type. Although derivative equations using varying albumin coefficients have improved accuracy (without much improvement in precision) in intensive care and elderly patients, these equations still require further validation. Further experiments are also needed to yield derivative equations with good predictive performance in all populations as well as to validate the equations' impact on actual patient efficacy and toxicity outcomes. More complex, multivariate predictive equations may be required to capture all variables that can potentially affect phenytoin pharmacokinetics and clinical therapeutic outcomes.

Pharmacogenetics of ATP binding cassette transporter - MDR1 gene polymorphism (C3435T) and response to antiepileptic drug phenytoin pharmacokinetics in epilepsy

Background: Epilepsy is a common chronic neurological condition that is characterized by recurrent unprovoked seizures. A synonymous C to T variant at position 3435 (3435C N T) is one common polymorphism of the multidrug resistant 1 (MDR1) gene, which encodes the major transmembrane efflux transporter P-glycoprotein and form an important class of proteins for regulating pharmacokinetics. Phenytoin, a widely used anti-epileptic drug, exhibits marked inter-individual variation in Pharmacokinetics and attributed to genetic factors such as MDR1 polymorphism. Objective: The present study was undertaken to investigate the influence of MDR1 variant genotypes on Phenytoin Pharmacokinetics in the epileptic patients from Saudi Arabia. Material andmethods: 25 epileptic individuals with non-responders to phenytoin monotherapy and 25 epileptic subjects with responders to phenytoin monotherapy were recruited after getting their informed consent and genotyped for MDR1 (3435C N T) polymorphisms by Polymerase chain reaction-restriction fragment length polymorphisms (PCR-RFLP Method). Allele frequencies were derived from genotypic data Phenytoin plasma levels were analyzed by reverse phase HPLC method and Pharmacokinetic parameters were estimated by non-compartmental analysis using PK solutions software. Results: The MDR1 (3435C N T) polymorphism was seen to be in Hardy–Weinberg equilibrium and showed significant allelic association and genotypic association between non responders and responders to phenytoin (P b 0.01). The pharmacokinetics parameters in homozygous mutant group showed longer half-life (t1/ 2= 33.26 hrs) and less clearance rate (CL=0.42 L/hr) when compared to wild type group (t 1/2=19.2 hrs, CL=0.8 L/hr). Conclusion: Our finding suggest that the MDR1 genetic polymorphism influences Phenytoin Pharmacokinetics. So the therapeutic outcome of MDR1 (C3435T) genotype together with pharmacokinetic measurements might be useful in the context of improving the individualized efficacy of therapy in non-responders to phenytoin.