Handling missed dose of riluzole by population pharmacokinetic model informed remedial regimen
- 1Department of Pharmacy, Hangzhou Linping Hospital of Traditional Chinese Medicine , ,
- 2Research Center for Clinical Pharmacy, Zhejiang University , ,
Abstract
Background: Patients with amyotrophic lateral sclerosis (ALS) frequently exhibit nonadherence characterized by delayed or missed doses while taking riluzole. This study aimed to provide a population pharmacokinetic (PPK) model informed individualized remedial regimens for patients who experience delayed or missed doses of riluzole.
Methods: A PPK model for riluzole was developed via a nonlinear mixed-effect modeling approach based on 3,024 concentration-time points from 72 subjects. The final model was validated by multiple methods. Six remedial regimens for missed doses were simulated for concentration-time profiles under different scenarios, and the optimal remedial regimen was selected based on the least time of concentration beyond the normal range.
Results: The PPK model of riluzole was best described with a two-compartment model with body weight as a covariate of peripheral distribution volume. The typical values of CL/F, V c /F, V p /F and Q were 67 L/h, 242 L, 376 L and 33.1 L/h, respectively. The model was showed acceptable performance by goodness-of-fit, visual predictive check, bootstrap analysis and normalized distribution prediction errors. Model-based remedial regimens for different missed scenarios were proposed.
Conclusion: A riluzole PPK model was developed and internally evaluated using multiple diagnostic approaches. Model-based remedial dosing strategies for different missed-dose scenarios were identified based on predefined PK criteria and Monte Carlo simulations. These exploratory strategies provide quantitative insights into riluzole exposure during nonadherent dosing conditions.
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BibTeX
@article{liu2026handling,
title = {{Handling missed dose of riluzole by population pharmacokinetic model informed remedial regimen}},
author = {Changlong Liu and Qing Tang and Lingyan Yu and Zhenwei Yu},
journal = {Frontiers in pharmacology},
year = {2026},
month = sep,
doi = {10.3389/fphar.2026.1890355},
url = {https://europepmc.org/article/PMC/PMC13661369},
note = {CC BY},
}
RIS
TY - JOUR
TI - Handling missed dose of riluzole by population pharmacokinetic model informed remedial regimen
AU - Changlong Liu
AU - Qing Tang
AU - Lingyan Yu
AU - Zhenwei Yu
PY - 2026
DA - 2026/09/30
JO - Frontiers in pharmacology
DO - 10.3389/fphar.2026.1890355
UR - https://europepmc.org/article/PMC/PMC13661369
AB - Background: Patients with amyotrophic lateral sclerosis (ALS) frequently exhibit nonadherence characterized by delayed or missed doses while taking riluzole. This study aimed to provide a population pharmacokinetic (PPK) model informed individualized remedial regimens for patients who experience delayed or missed doses of riluzole. Methods: A PPK model for riluzole was developed via a nonlinear mixed-effect modeling approach based on 3,024 concentration-time points from 72 subjects. The final model was validated by multiple methods. Six remedial regimens for missed doses were simulated for concentration-time profiles under different scenarios, and the optimal remedial regimen was selected based on the least time of concentration beyond the normal range. Results: The PPK model of riluzole was best described with a two-compartment model with body weight as a covariate of peripheral distribution volume. The typical values of CL/F, V c /F, V p /F and Q were 67 L/h, 242 L, 376 L and 33.1 L/h, respectively. The model was showed acceptable performance by goodness-of-fit, visual predictive check, bootstrap analysis and normalized distribution prediction errors. Model-based remedial regimens for different missed scenarios were proposed. Conclusion: A riluzole PPK model was developed and internally evaluated using multiple diagnostic approaches. Model-based remedial dosing strategies for different missed-dose scenarios were identified based on predefined PK criteria and Monte Carlo simulations. These exploratory strategies provide quantitative insights into riluzole exposure during nonadherent dosing conditions.
SN - 1663-9812
ER -