印度狼疮性肾炎患者服用霉酚酸酯的群体药代动力学和有限采样策略

IF 2.8 4区 医学 Q2 MEDICAL LABORATORY TECHNOLOGY Therapeutic Drug Monitoring Pub Date : 2024-10-01 Epub Date: 2024-05-09 DOI:10.1097/FTD.0000000000001213
Kévin Koloskoff, Ritika Panwar, Manish Rathi, Sumith Mathew, Aman Sharma, Pierre Marquet, Sylvain Benito, Jean-Baptiste Woillard, Smita Pattanaik
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引用次数: 0

摘要

背景:霉酚酸被广泛用于治疗狼疮性肾炎(LN):霉酚酸被广泛用于治疗狼疮性肾炎(LN)。然而,它的药代动力学非常复杂,个体间差异很大。本研究旨在开发一种群体药代动力学(popPK)模型和一种3样本有限采样策略(LSS),以优化印度LN患者的治疗药物监测:每位接受霉酚酸治疗的 LN 患者在稳态用药前和用药后 1、2、4、6 小时采集 5 份血样。将人口统计学参数作为协变量进行测试,以解释个体间的差异。使用 Monolix 和随机近似期望最大化算法进行了 PopPK 分析。利用最大后验贝叶斯估计法,从 500 个模拟药代动力学(PK)曲线中得出 LSS,以估计个体 PK 参数和曲线下面积(AUC)。将 LSS 计算出的 AUC 与使用梯形法则和所有模拟样本计算出的 AUC 进行了比较:本研究共纳入了 51 名患者。根据 245 个霉酚酸浓度,使用伽马分布的双吸收 1 室模型最符合数据。没有一个协变量能明显改善该模型。利用诊断图、预测校正视觉预测检查和引导法对该模型进行了内部验证。最佳 LSS 包括用药后 1、2 和 4 小时的样本,在外部数据集中表现出良好的性能(均方根误差为 21.9%;平均偏差为 -4.20%):本研究开发的 popPK 模型能充分估计霉酚酸在印度成年 LN 患者中的 PK 值。这种简单的LSS可以在常规实践中根据AUC优化TDM。
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Population Pharmacokinetics and Limited Sampling Strategy of Mycophenolate Mofetil for Indian Patients With Lupus Nephritis.

Background: Mycophenolic acid is widely used to treat lupus nephritis (LN). However, it exhibits complex pharmacokinetics with large interindividual variability. This study aimed to develop a population pharmacokinetic (popPK) model and a 3-sample limited sampling strategy (LSS) to optimize therapeutic drug monitoring in Indian patients with LN.

Methods: Five blood samples from each LN patient treated with mycophenolic acid were collected at steady-state predose and 1, 2, 4, and 6 hours postdose. Demographic parameters were tested as covariates to explain interindividual variability. PopPK analysis was performed using Monolix and the stochastic approximation expectation-maximization algorithm. An LSS was derived from 500 simulated pharmacokinetic (PK) profiles using maximum a posteriori Bayesian estimation to estimate individual PK parameters and area under the curve (AUC). The LSS-calculated AUC was compared with the AUC calculated using the trapezoidal rule and all the simulated samples.

Results: A total of 51 patients were included in this study. Based on the 245 mycophenolic acid concentrations, a 1-compartmental model with double absorption using gamma distributions best fitted the data. None of the covariates improved the model significantly. The model was internally validated using diagnostic plots, prediction-corrected visual predictive checks, and bootstrapping. The best LSS included samples at 1, 2, and 4 hours postdose and exhibited good performances in an external dataset (root mean squared error, 21.9%; mean bias, -4.20%).

Conclusions: The popPK model developed in this study adequately estimated the PK of mycophenolic acid in adult Indian patients with LN. This simple LSS can optimize TDM based on the AUC in routine practice.

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来源期刊
Therapeutic Drug Monitoring
Therapeutic Drug Monitoring 医学-毒理学
CiteScore
5.00
自引率
8.00%
发文量
213
审稿时长
4-8 weeks
期刊介绍: Therapeutic Drug Monitoring is a peer-reviewed, multidisciplinary journal directed to an audience of pharmacologists, clinical chemists, laboratorians, pharmacists, drug researchers and toxicologists. It fosters the exchange of knowledge among the various disciplines–clinical pharmacology, pathology, toxicology, analytical chemistry–that share a common interest in Therapeutic Drug Monitoring. The journal presents studies detailing the various factors that affect the rate and extent drugs are absorbed, metabolized, and excreted. Regular features include review articles on specific classes of drugs, original articles, case reports, technical notes, and continuing education articles.
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