Pharmacokinetic and pharmacodynamic modeling of levetiracetam: investigation of factors affecting the clinical outcome

Real-world interpatient variability in the pharmacokinetics of levetiracetam

BACKGROUND

Levetiracetam (LEV) is an antiepileptic drug (AED) used to treat a variety of seizures in adult and pediatric populations. It is an ideal AED due to its favorable pharmacokinetic (PK) and pharmacodynamic profile and lack of interactions with other AEDs.

METHODS

This retrospective cohort study was designed to identify covariates that affect LEV clearance and volume of distribution and to generate a population PK model. Adults with a seizure history receiving LEV during hospital admission with a minimum of one serum LEV concentration available were included in the study. Population PK modeling and covariate testing was performed with MONOLIX Suite 2020R1 (Lixoft, France).

RESULTS

A total of 162 serum concentrations were collected from 143 patients. Age, sex, body weight descriptors, serum creatinine, creatinine clearance (CrCL), serum albumin, liver enzymes, and total bilirubin were evaluated. Body surface area (BSA) was a significant covariate for the apparent volume of distribution (V/F). The exclusion of BSA as a covariate of V/F increased the objective function value (OFV) 5.6. CrCL was a significant covariate of apparent plasma clearance (CL/F). The exclusion of CrCL increased the OFV by 18.16 and significantly increased the root square error (RSE) % of the between-subject variabilities of the parameters.

CONCLUSION

LEV clearance is an effective predictor of serum concentration. CrCL was a significant covariate influencing LEV clearance, and BSA was found to influence the volume of distribution. Further studies are needed to determine the effect of body weight descriptors on LEV clearance and, ultimately, outcomes.

Real-world analysis of levetiracetam-associated rhabdomyolysis: insights from the FDA adverse event reporting system

BACKGROUND

Levetiracetam, a widely prescribed antiseizure medication, is recognized for its broad-spectrum efficacy, good tolerability, and minimal drug interactions. This study examines the association between levetiracetam and rhabdomyolysis, utilizing real-world data from the FDA Adverse Event Reporting System (FAERS) database to further elucidate its safety profile.

METHODS

This study extracted adverse events related to levetiracetam from the FAERS database (Q1 2013 to Q1 2024). Four types of disproportionality analysis identified rhabdomyolysis as a significant adverse event. Logistic regression assessed risk factors, including gender, age, and severity. A Gaussian Mixture Model analyzed the time-to-onset distribution of rhabdomyolysis, while the impact of concomitant medications on its risk was evaluated using Reporting Odds Ratio (ROR).

RESULTS

Levetiracetam significantly increased rhabdomyolysis risk (ROR = 13.5). Males showed a higher incidence (OR = 2.60). Most adverse events occurred within the first 30 days, with a bimodal onset distribution. Co-administration of antibiotics, antipsychotics, and PPIs elevated the risk while other antiseizure medications did not.

CONCLUSION

This study found a significant association between levetiracetam and the risk of rhabdomyolysis, highlighting the need for increased clinical vigilance in this patient population. Future research should focus on elucidating the underlying mechanisms and optimizing clinical guidelines.

Application of Physiologically Based Pharmacokinetic Modeling to Characterize the Effects of Age and Obesity on the Disposition of Levetiracetam in the Pediatric Population

BACKGROUND

Levetiracetam is an antiseizure medication used for several seizure types in adults and children aged 1 month and older; however, due to a lack of data, pharmacokinetic (PK) variability of levetiracetam is not adequately characterized in certain populations, particularly neonates, children younger than 2 years of age, and children older than 2 years of age with obesity.

OBJECTIVE

This study aimed to address the gap by leveraging PK data from two prospective standard-of-care pediatric trials (n = 88) covering an age range from 1 month to 19 years, including those with obesity (64%), and applying a physiologically based PK (PBPK) modeling framework.

METHODS

A published PBPK model of levetiracetam for children aged 2 years and older was extended to pediatric patients younger than 2 years of age and patients older than 2 years of age with obesity by accounting for the obesity and age-related changes in PK using PK-Sim® software. The prospective pediatric data, along with the literature data for neonates and children younger than 2 years of age, were used to evaluate the extended PBPK models.

RESULTS

Overall, 82.4% of data fell within the 90% interval of model-predicted concentrations, with an average fold error within twofold of the accepted criteria. PBPK modeling revealed that children with obesity had lower weight-normalized clearances (0.053 L/h/kg) on average than children without obesity (0.063 L/h/kg). The effect of maturation was well-characterized, resulting in comparable PBPK-simulated, weight-normalized clearances for neonates and children younger than 2 years of age reported from the literature.

CONCLUSIONS

PBPK modeling simulations revealed that the current US FDA-labeled pediatric dosing regimen listed in the prescribing information can produce the required exposure of levetiracetam in these target populations with dose adjustments for children with obesity aged 4 years to younger than 16 years.

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.

Population pharmacokinetics and dosing regimen optimization of levetiracetam in epilepsy during pregnancy

AIMS

The pharmacokinetics of levetiracetam (LEV) significantly changed during pregnancy. It is a great challenge to predict the adjusted doses of LEV to reach the preconception target concentrations. This study aimed to establish a population pharmacokinetic model of LEV in women with epilepsy (WWE) during pregnancy to analyse the factors of pharmacokinetic variability and to develop a model-based individualized dosing regimen.

METHODS

A total of 166 concentration-time points from 37 WWE during pregnancy treated with LEV were collected to analyse LEV pharmacokinetics with nonlinear mixed-effects modelling. The dosing regimen was optimized by Monte Carlo simulations based on the final model.

RESULTS

The LEV pharmacokinetics in pregnant WWE were best described by a 1-compartment model of first-order absorption and elimination. The population typical value of apparent clearance (CL/F) in the final model was estimated to be 3.82 L/h (95% confidence interval 3.283-4.357 L/h) with a relative standard error of 7.2%. Both total body weight (TBW) and trimester of pregnancy were significantly associated with LEV-CL/F during pregnancy; LEV-CL/F increased by 42.72% when TBW increased from 55 to 65 kg from the first trimester to the second trimester. Monte Carlo simulations showed that dosing regimens for LEV should be individualized based on the patient's TBW and trimester of pregnancy to maximize the likelihood of achieving the therapeutic range.

CONCLUSION

This first population pharmacokinetic study of LEV in WWE during pregnancy supports the use of a weight-based and pregnancy-based dosing regimen and can lay a foundation for further optimizing the individualized dosing regimens.

Effect of Nonadherence on Levetiracetam Pharmacokinetics and Remedial Dose Recommendations Using Monte Carlo Simulations

BACKGROUND AND OBJECTIVE

Nonadherence to levetiracetam (LEV) use can result in subtherapeutic concentrations and increase the risk of the occurrence of seizures. The impact of missing LEV doses on its pharmacokinetics and evidence of the appropriate remedial dose is lacking. This study has determined the influence of missed LEV doses on its pharmacokinetics and has explored the appropriate remedial dosage regimens.

METHODS

Monte Carlo simulation was used to assess the impacts of different remedial dosage regimens on LEV concentrations. Simulated LEV concentrations outside the individual therapeutic range were calculated for the compliance scenario and for each of the remedial dosage regimens. The percentage of deviation from the full compliance scenario was also calculated. The regimen with the lowest percentage of deviation was considered the most appropriate.

RESULTS

The suitable LEV remedial dose varied across the delay times. For one missed dose, a remedial regimen with a regular dose followed by the usual dose was suitable for a delay time of less than 6 h, while a replacement with a regular dose followed by a partial dose appeared to be appropriate for a delay time of 6 h and longer. This was justified based on the concerns of LEV toxicity when the remedial dose is close to the next scheduled dose. For two consecutive missed doses, a remedial dose with one and a half of the regular dose was suitable if the gap between that and the next dose was greater than 6 h.

CONCLUSIONS

The appropriate remedial dosage regimen for one and two consecutive missed doses of LEV have been proposed. These remedial regimens, however, should be applied with clinicians' judgment based on the clinical status of the patients.

The Pharmacokinetics of Levetiracetam in Critically Ill Adult Patients: An Intensive Care Unit Clinical Study

The aim of this study was to investigate levetiracetam pharmacokinetics in critically ill adult intensive care patients and to identify pathophysiological factors affecting its kinetics. Fourteen critically ill patients in an intensive care unit were enrolled in the study and received intravenous levetiracetam. Blood samples were collected at specific time points to determine the levetiracetam pharmacokinetics. Patient characteristics such as renal function, demographics, disease severity, organ dysfunction, and biochemical laboratory tests were evaluated for their influence on the kinetics of levetiracetam. Estimated glomerular filtration rate (eGFR) had a statistically significant (p = 0.001) effect on levetiracetam clearance. None of the other patient characteristics had a statistically significant effect on the pharmacokinetics. Simulations of dosing regimens revealed that even typically administered doses of levetiracetam may result in significantly increased concentrations and risk of drug toxicity in patients with impaired renal function. The Acute Physiology and Chronic Health Evaluation II (APACHE II) score differed significantly among the three groups with different epileptic activity (p = 0.034). The same groups also differed in terms of renal function (p = 0.031). Renal dysfunction should be considered when designing levetiracetam dosage. Patients with a low APACHE II score had the lowest risk of experiencing epileptic seizures.

Population Pharmacokinetics of Levetiracetam: a Systematic Review

BACKGROUND

The use of levetiracetam (LEV) has been increasing given its favorable pharmacokinetic profile. Numerous population pharmacokinetic studies for LEV have been conducted. However, there are some discrepancies regarding factors affecting its pharmacokinetic variability. Therefore, this systematic review aimed to summarize significant predictors for LEV pharmacokinetics as well as the need for dosage adjustments.

METHODS

We performed a systematic search for population pharmacokinetic studies of LEV conducted using a nonlinear-mixed effect approach from PubMed, Scopus, CINAHL Complete, and Science Direct databases from their inception to March 2020. Information on study design, model methodologies, significant covariate-parameter relationships, and model evaluation was extracted. The quality of the reported studies was also assessed.

RESULTS

A total of 16 studies were included in this review. Only two studies were conducted with a two-compartment model, while the rest were performed with a one-compartment structure. Bodyweight and creatinine clearance were the two most frequently identified covariates on LEV clearance (CLLEV). Additionally, postmenstrual age (PMA) or postnatal age (PNA) were significant predictors for CLLEV in neonates. Only three studies externally validated the models. Two studies conducted pharmacodynamic models for LEV with relatively small sample size.

CONCLUSION

Significant predictors for LEV pharmacokinetics are highlighted in this review. For future research, a population pharmacokinetic-pharmacodynamic model using a larger sample size should be conducted. From a clinical perspective, the published models should be externally evaluated before clinical implementation.

Population Pharmacokinetics of Levetiracetam: A Systematic Review

BACKGROUND

Levetiracetam has been widely used as a treatment option for different types of epilepsy in both adults and children. Because of its large between-subject variability, several population pharmacokinetic studies have been performed to identify its pharmacokinetic covariates, and thus facilitate individualised therapy.

OBJECTIVE

The aim of this review was to provide a synopsis for population pharmacokinetic studies of levetiracetam and explore the identified influencing covariates.

METHODS

We systematically searched the PubMed and Embase databases from inception to 30 June 2020. The information on study designs, target population, model characteristics, and identified covariates was summarised. Moreover, the pharmacokinetic profiles were compared among neonates, children, and adults.

RESULTS

Fourteen studies were included, among which two involved neonates, four involved children, two involved both children and adults, and six involved adults only. The median value of apparent clearance for children (0.074 L/h/kg [range 0.038-0.079]) was higher than that for adults (0.054 L/h/kg [range 0.039-0.061]). Body weight was found to significantly influence the apparent clearance and volume of distribution, whereas renal function influenced the clearance. Likewise, coadministration with enzyme-inducing antiepileptic drugs (such as carbamazepine and phenytoin) increased the drug clearance by 9-22%, whereas coadministration with valproate acid decreased it by 18.8%.

CONCLUSION

Levetiracetam dose regimen is dependent on the body size and renal function of patients. Further studies are needed to evaluate levetiracetam pharmacokinetics in neonates and pregnant women.