Kévin Koloskoff, Ritika Panwar, Manish Rathi, Sumith Mathew, Aman Sharma, Pierre Marquet, Sylvain Benito, Jean-Baptiste Woillard, Smita Pattanaik
{"title":"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","authors":"Kévin Koloskoff, Ritika Panwar, Manish Rathi, Sumith Mathew, Aman Sharma, Pierre Marquet, Sylvain Benito, Jean-Baptiste Woillard, Smita Pattanaik","doi":"10.1097/FTD.0000000000001213","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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%).</p><p><strong>Conclusions: </strong>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.</p>","PeriodicalId":23052,"journal":{"name":"Therapeutic Drug Monitoring","volume":" ","pages":"567-574"},"PeriodicalIF":2.8000,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Population Pharmacokinetics and Limited Sampling Strategy of Mycophenolate Mofetil for Indian Patients With Lupus Nephritis.\",\"authors\":\"Kévin Koloskoff, Ritika Panwar, Manish Rathi, Sumith Mathew, Aman Sharma, Pierre Marquet, Sylvain Benito, Jean-Baptiste Woillard, Smita Pattanaik\",\"doi\":\"10.1097/FTD.0000000000001213\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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%).</p><p><strong>Conclusions: </strong>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.</p>\",\"PeriodicalId\":23052,\"journal\":{\"name\":\"Therapeutic Drug Monitoring\",\"volume\":\" \",\"pages\":\"567-574\"},\"PeriodicalIF\":2.8000,\"publicationDate\":\"2024-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Therapeutic Drug Monitoring\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1097/FTD.0000000000001213\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/5/9 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q2\",\"JCRName\":\"MEDICAL LABORATORY TECHNOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Therapeutic Drug Monitoring","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1097/FTD.0000000000001213","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/5/9 0:00:00","PubModel":"Epub","JCR":"Q2","JCRName":"MEDICAL LABORATORY TECHNOLOGY","Score":null,"Total":0}
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.
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.