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Adaptive Dosage Strategy of Levetiracetam in Chinese Epileptic Patients: Focus on Pregnant Women.
- Source :
-
Journal of pharmaceutical sciences [J Pharm Sci] 2024 May; Vol. 113 (5), pp. 1385-1394. Date of Electronic Publication: 2024 Jan 02. - Publication Year :
- 2024
-
Abstract
- There is presently no efficient dose individualization strategy for the use of antiseizure medications in epileptic pregnant patients. This study aimed to develop a population pharmacokinetics model for levetiracetam and propose a tailored adaptive individualized dosage strategy for epileptic pregnant patients. A total of 322 levetiracetam plasma concentrations from 238 patients with epilepsy were included, including 216 women with epilepsy (20.83% of whom were pregnant). The levetiracetam plasma concentration was measured using a validated ultra-performance liquid chromatography-tandem mass spectrometry assay, and the data were modeled using a nonlinear mixed-effects model. The resultant model served as the basis for simulating the dosage adjustment strategy. A one-compartment model with first-order elimination best described the pharmacokinetic data of levetiracetam. The apparent clearance (CL/F) was 3.43 L/h (95% CI 3.30-3.56) and the apparent volume of distribution was 43.7 L (95% CI 40.4-47.0) for a typical individual of 57.2 kg. Pregnancy and body weight were found to be significant covariates of CL/F of levetiracetam. The recommended regimen of levetiracetam could be predicted by the population pharmacokinetic model based on body weight, gestational age, and the daily dose of levetiracetam taken before pregnancy.<br />Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.<br /> (Copyright © 2024 American Pharmacists Association. Published by Elsevier Inc. All rights reserved.)
Details
- Language :
- English
- ISSN :
- 1520-6017
- Volume :
- 113
- Issue :
- 5
- Database :
- MEDLINE
- Journal :
- Journal of pharmaceutical sciences
- Publication Type :
- Academic Journal
- Accession number :
- 38176454
- Full Text :
- https://doi.org/10.1016/j.xphs.2023.12.025