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基于模型的瑞马唑仑在全身麻醉患者中的精准给药
Authors Chen Y, Zhang ZJ, Zhang XF, Peng Y, Jiao Z, Wu JX
Received 10 September 2024
Accepted for publication 3 April 2025
Published 16 June 2025 Volume 2025:19 Pages 5099—5109
DOI https://doi.org/10.2147/DDDT.S495604
Checked for plagiarism Yes
Review by Single anonymous peer review
Peer reviewer comments 3
Editor who approved publication: Professor Manfred Ogris
Yueting Chen,1,* Zuo-Jing Zhang,2,* Xiao-Feng Zhang,2 Yuan Peng,2 Zheng Jiao,1,* Jing-Xiang Wu2,*
1Department of Pharmacy, Shanghai Chest Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, People’s Republic of China; 2Department of Anesthesiology, Shanghai Chest Hospital, Shanghai Jiao Tong University, School of Medicine, Shanghai, People’s Republic of China
*These authors contributed equally to this work
Correspondence: Zheng Jiao, Department of Pharmacy, Shanghai Chest Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, People’s Republic of China, Email jiaozhen@online.sh.cn Jing-Xiang Wu, Department of Anesthesiology, Shanghai Chest Hospital, Shanghai Jiao Tong University School of Medicine, Xuhui District, Shanghai, 200030, People’s Republic of China, Tel +86 021-22200000-3302, Fax +86 021-32260806, Email wjx1132@163.com
Purpose: This study aimed to characterize the pharmacokinetics/pharmacodynamics (PK/PD) of remimazolam in patients under general anesthesia using a population analysis and to develop a web-based dashboard tool that directly displays the optimal dosing regimen for general anesthesia.
Patients and Methods: A total of 20 patients received remimazolam for general anesthesia, during which intensive arterial blood samples and bispectral index (BIS) values were collected. A population PK/PD model was established, and goodness-of-fit and visual predictive check plots were utilized to evaluate the model’s accuracy. Additionally, RxODE and Shiny in R were used to design a web-based dashboard tool to recommend optimal dosing regimens.
Results: The three-compartment model with first elimination best described the PK profiles of remimazolam. PK parameters were weight-adjusted via allometric scaling. The correlation between drug exposure and the BIS was optimally characterized through an effect compartment model employing an inhibitory sigmoid Emax model. In addition, a web-based dashboard tool was created to offer initial personalized dosing strategies for general anesthesia procedures, enhanced by graphical representations of the PK/PD profiles associated with the recommended dosing regimens.
Conclusion: The developed population PK/PD model effectively captured the dose-exposure-response relationship for remimazolam, allowing for the optimization of personalized dosing strategies.
Keywords: general anesthesia, monte carlo simulation, optimized dosing regimens, population pharmacokinetics/pharmacodynamics models, remimazolam, web-based dashboard