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已发表论文
探讨氟比洛芬异构体在选择性关节置换术后疼痛患者中的群体药代动力学和药物遗传学特征
Authors Yao H, Luo X, Yuan J, Zhang H , An H, Feng Y
Received 25 May 2025
Accepted for publication 26 September 2025
Published 9 October 2025 Volume 2025:19 Pages 9169—9183
DOI https://doi.org/10.2147/DDDT.S542722
Checked for plagiarism Yes
Review by Single anonymous peer review
Peer reviewer comments 3
Editor who approved publication: Professor Anastasios Lymperopoulos
Han Yao,1,* Xingxian Luo,2,* Jinjie Yuan,3 Hong Zhang,1 Haiyan An,1 Yi Feng1
1Department of Anesthesiology, Peking University People’s Hospital, Beijing, People’s Republic of China; 2Department of Pharmacy, Peking University People’s Hospital, Beijing, People’s Republic of China; 3National Institution of Drug Clinical Trial, the First Affiliated Hospital of Soochow University, Suzhou, People’s Republic of China
*These authors contributed equally to this work
Correspondence: Yi Feng, Department of Anesthesiology, Peking University People’s Hospital, Beijing, 100044, People’s Republic of China, Email doctor_yifeng@sina.com
Purpose: Flurbiprofen plays a critical role in clinical pain management. This study aims to elucidate the population pharmacokinetic (PPK) profiles of flurbiprofen’s enantiomers, R(-) and S(+)-flurbiprofen in human subjects, following intravenous administration, while investigating the influence of clinical covariates.
Patients and Methods: PPK modeling of flurbiprofen isomers was based on a prospective study that included a total of 67 patients, each of whom had plasma and cerebrospinal fluid (CSF) samples collected at various time points within 5– 50 min. Nonlinear mixed effects modeling was performed using Phoenix NLME. The final PPK model was validated using both Bootstrap and visual prediction checks. Modeling was used to assess the effect of demographic, biological, and pharmacogenetic (12 SNPs relatived to CYP2C9, ABCB1, PXR, POR and UGT1A9) covariates on clearance (CL) and apparent volume of distribution (Vd) for R(-) and S(+)-flurbiprofen.
Results: A two-compartment model best fit the data. All patients were homozygous for the wild-type CYP2C9 allele. Plasma CL of S(+)-flurbiprofen was significantly influenced by ABCB1 (rs1045642) polymorphisms. For R(-)-flurbiprofen, body surface area (BSA) were related to Vd while POR (rs1057868) polymorphisms were associated with CL. The Vd for both R(-)- and S(+)-flurbiprofen was found to be larger in CSF compared to plasma. Specifically, the final model estimated the Vd of R(-)-flurbiprofen (CSF 79.1 L VS plasma 17.1 L) and S(+)-flurbiprofen (CSF 32.6 L VS plasma 25.6 L), and the CL of R(-)-flurbiprofen (CSF 0.45L·h− 1 VS plasma 11.8L·h− 1 and S(+)-flurbiprofen (0.39 L·h− 1 VS plasma 16.7 L·h− 1), respectively.
Conclusion: Key covariates of S (+)-flurbiprofen was ABCB1 gene polymorphisms and R-flurbiprofen was POR gene polymorphisms and BSA. The findings may provide support for future dose optimization and the development of novel therapeutic approaches.
Keywords: flurbiprofen, enantiomers, cerebrospinal fluid, population pharmacokinetic, gene polymorphsim
1Department of Anesthesiology, Peking University People’s Hospital, Beijing, People’s Republic of China; 2Department of Pharmacy, Peking University People’s Hospital, Beijing, People’s Republic of China; 3National Institution of Drug Clinical Trial, the First Affiliated Hospital of Soochow University, Suzhou, People’s Republic of China
*These authors contributed equally to this work
Correspondence: Yi Feng, Department of Anesthesiology, Peking University People’s Hospital, Beijing, 100044, People’s Republic of China, Email doctor_yifeng@sina.com
Purpose: Flurbiprofen plays a critical role in clinical pain management. This study aims to elucidate the population pharmacokinetic (PPK) profiles of flurbiprofen’s enantiomers, R(-) and S(+)-flurbiprofen in human subjects, following intravenous administration, while investigating the influence of clinical covariates.
Patients and Methods: PPK modeling of flurbiprofen isomers was based on a prospective study that included a total of 67 patients, each of whom had plasma and cerebrospinal fluid (CSF) samples collected at various time points within 5– 50 min. Nonlinear mixed effects modeling was performed using Phoenix NLME. The final PPK model was validated using both Bootstrap and visual prediction checks. Modeling was used to assess the effect of demographic, biological, and pharmacogenetic (12 SNPs relatived to CYP2C9, ABCB1, PXR, POR and UGT1A9) covariates on clearance (CL) and apparent volume of distribution (Vd) for R(-) and S(+)-flurbiprofen.
Results: A two-compartment model best fit the data. All patients were homozygous for the wild-type CYP2C9 allele. Plasma CL of S(+)-flurbiprofen was significantly influenced by ABCB1 (rs1045642) polymorphisms. For R(-)-flurbiprofen, body surface area (BSA) were related to Vd while POR (rs1057868) polymorphisms were associated with CL. The Vd for both R(-)- and S(+)-flurbiprofen was found to be larger in CSF compared to plasma. Specifically, the final model estimated the Vd of R(-)-flurbiprofen (CSF 79.1 L VS plasma 17.1 L) and S(+)-flurbiprofen (CSF 32.6 L VS plasma 25.6 L), and the CL of R(-)-flurbiprofen (CSF 0.45L·h− 1 VS plasma 11.8L·h− 1 and S(+)-flurbiprofen (0.39 L·h− 1 VS plasma 16.7 L·h− 1), respectively.
Conclusion: Key covariates of S (+)-flurbiprofen was ABCB1 gene polymorphisms and R-flurbiprofen was POR gene polymorphisms and BSA. The findings may provide support for future dose optimization and the development of novel therapeutic approaches.
Keywords: flurbiprofen, enantiomers, cerebrospinal fluid, population pharmacokinetic, gene polymorphsim