マルヤマ タクミ
Maruyama Takumi
丸山 拓実 所属 その他 その他 職種 薬剤師 |
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論文種別 | 原著 |
言語種別 | 英語 |
査読の有無 | 査読あり |
表題 | Comparison of the predictive accuracy of the physiologically based pharmacokinetic (PBPK) model and population pharmacokinetic (PPK) model of vancomycin in Japanese patients with MRSA infection. |
掲載誌名 | 正式名:Journal of infection and chemotherapy : official journal of the Japan Society of Chemotherapy 略 称:J Infect Chemother ISSNコード:14377780/1341321X |
掲載区分 | 国外 |
巻・号・頁 | pp.10.1016/j.jiac.2023.08.017 |
著者・共著者 | Maruyama Takumi, Kimura Toshimi, Ebihara Fumiya, Kasai Hidefumi, Matsunaga Nobuaki, Hamada Yukihiro |
担当区分 | 筆頭著者 |
発行年月 | 2023/09 |
概要 | INTRODUCTION:The latest therapeutic drug monitoring guidelines for vancomycin (VCM) recommend that area under the concentration-time curve is estimated based on model-informed precision dosing and used to evaluate efficacy and safety. Therefore, we predicted VCM concentrations in individual methicillin-resistant Staphylococcus aureus-infected patients using existing a physiologically based pharmacokinetic (PBPK) model and 1- and 2-compartment population pharmacokinetic (PPK) models and confirmed and verified the accuracy of the PBPK model in estimating VCM concentrations with the PPK model.METHODS:The subjects of the study are 20 patients, and the predicted concentrations were evaluated by comparing the observed and predicted trough and peak values of VCM concentrations for individual patients.RESULTS:The results showed good correlation between the observed and predicted trough and peak concentrations of VCM was observed generally in the PBPK model, R2 values of 0.72, 0.62, and 0.40 with trough values of 0.49, 0.40, and 0.34 with peak values for PBPK model, 1-compartment, and 2-compartment model, respectively.CONCLUSIONS:Although the performance of the PBPK model is not as predictive as the PPK model, generally similar predictive trends were obtained, suggesting that it may be a valuable tool for rapid and accurate prediction of AUC for VCM. |
DOI | 10.1016/j.jiac.2023.08.017 |
PMID | 37673298 |