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利用治疗药物监测浓度建立加巴喷丁群体药代动力学模型

Development of a Population Pharmacokinetic Gabapentin Model Leveraging Therapeutic Drug Monitoring Concentrations.

作者信息

Al-Zubaydi Firas, Wassef Andrew, Kagan Leonid, Brunetti Luigi

机构信息

Department of Pharmacy Practice, Ernest Mario School of Pharmacy, Rutgers, The State University of New Jersey, 160 Frelinghuysen Road, Piscataway, NJ 08854, USA.

Department of Pharmaceutics, College of Pharmacy, University of Baghdad, Baghdad 10071, Iraq.

出版信息

Pharmaceutics. 2024 Nov 25;16(12):1514. doi: 10.3390/pharmaceutics16121514.

Abstract

Gabapentin has variable pharmacokinetics (PK), which contributes to difficulty in dosing and increased risk of adverse events. The objective of this study was to leverage gabapentin concentrations from therapeutic drug monitoring (TDM) to develop a population PK (popPK) model and characterize significant covariates that impact gabapentin PK. Data were retrospectively collected from 82 hospitalized adult patients with TDM gabapentin concentrations. Renal function indicators (i.e., estimated glomerular filtration rate, creatinine clearance, acute kidney injury), body weight parameters (i.e., actual body weight, ideal body weight, adjusted body weight, lean body weight, body mass index, obesity status), fasting plasma glucose levels, and diagnosis of type 2 diabetes were tested as potential covariates. A popPK model was developed in MONOLIX (2020R1, Lixoft, France). : A one-compartment model best described gabapentin PK with first-order absorption, dose-dependent bioavailability, first-order elimination, and no lag time. Population parameter estimates for the volume of distribution (V), and clearance (Cl) were 44.61 L, and 5.73 L/h, respectively. Serum creatinine was a significant covariate on Cl. : The popPK model highlights the importance of renal function in the interindividual variability of gabapentin PK and suggests that diabetes and body weight parameters have no impact on gabapentin PK. Moreover, our study supports the utility of leveraging data obtained from clinical TDM for popPK model development.

摘要

加巴喷丁具有可变的药代动力学(PK),这导致给药困难和不良事件风险增加。本研究的目的是利用治疗药物监测(TDM)中的加巴喷丁浓度来建立群体药代动力学(popPK)模型,并确定影响加巴喷丁PK的重要协变量。数据回顾性收集自82例住院成年患者的TDM加巴喷丁浓度。对肾功能指标(即估计肾小球滤过率、肌酐清除率、急性肾损伤)、体重参数(即实际体重、理想体重、调整体重、瘦体重、体重指数、肥胖状态)、空腹血糖水平和2型糖尿病诊断作为潜在协变量进行了测试。在MONOLIX(2020R1,Lixoft,法国)中建立了一个popPK模型。:一个一室模型最能描述加巴喷丁的PK,具有一级吸收、剂量依赖性生物利用度、一级消除且无滞后时间。分布容积(V)和清除率(Cl)的群体参数估计分别为44.61L和5.73L/h。血清肌酐是Cl的一个显著协变量。:popPK模型突出了肾功能在加巴喷丁PK个体间变异性中的重要性,并表明糖尿病和体重参数对加巴喷丁PK没有影响。此外,我们的研究支持利用从临床TDM获得的数据进行popPK模型开发的实用性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e4c0/11678411/f7b2ddcee3a7/pharmaceutics-16-01514-g001a.jpg

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