{"title":"重症新生儿万古霉素的生理学药代动力学模型:评估病理生理变化的影响。","authors":"Weiwei Shuai MSc, Jing Cao MSc, Miao Qian MMed, Zhe Tang MSc","doi":"10.1002/jcph.6107","DOIUrl":null,"url":null,"abstract":"<p>Dosing vancomycin for critically ill neonates is challenging owing to substantial alterations in pharmacokinetics (PKs) caused by variability in physiology, disease, and clinical interventions. Therefore, an adequate PK model is needed to characterize these pathophysiological changes. The intent of this study was to develop a physiologically based pharmacokinetic (PBPK) model that reflects vancomycin PK and pathophysiological changes in neonates under intensive care. PK-sim software was used for PBPK modeling. An adult model (model 0) was established and verified using PK profiles from previous studies. A neonatal model (model 1) was then extrapolated from model 0 by scaling age-dependent parameters. Another neonatal model (model 2) was developed based not only on scaled age-dependent parameters but also on quantitative information on pathophysiological changes obtained via a comprehensive literature search. The predictive performances of models 1 and 2 were evaluated using a retrospectively collected dataset from neonates under intensive care (chictr.org.cn, ChiCTR1900027919), comprising 65 neonates and 92 vancomycin serum concentrations. Integrating literature-based parameter changes related to hypoalbuminemia, small-for-gestational-age, and co-medication, model 2 offered more optimized precision than model 1, as shown by a decrease in the overall mean absolute percentage error (50.6% for model 1; 37.8% for model 2). In conclusion, incorporating literature-based pathophysiological changes effectively improved PBPK modeling for critically ill neonates. Furthermore, this model allows for dosing optimization before serum concentration measurements can be obtained in clinical practice.</p>","PeriodicalId":22751,"journal":{"name":"The Journal of Clinical Pharmacology","volume":"64 12","pages":"1552-1565"},"PeriodicalIF":0.0000,"publicationDate":"2024-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Physiologically Based Pharmacokinetic Modeling of Vancomycin in Critically Ill Neonates: Assessing the Impact of Pathophysiological Changes\",\"authors\":\"Weiwei Shuai MSc, Jing Cao MSc, Miao Qian MMed, Zhe Tang MSc\",\"doi\":\"10.1002/jcph.6107\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Dosing vancomycin for critically ill neonates is challenging owing to substantial alterations in pharmacokinetics (PKs) caused by variability in physiology, disease, and clinical interventions. Therefore, an adequate PK model is needed to characterize these pathophysiological changes. The intent of this study was to develop a physiologically based pharmacokinetic (PBPK) model that reflects vancomycin PK and pathophysiological changes in neonates under intensive care. PK-sim software was used for PBPK modeling. An adult model (model 0) was established and verified using PK profiles from previous studies. A neonatal model (model 1) was then extrapolated from model 0 by scaling age-dependent parameters. Another neonatal model (model 2) was developed based not only on scaled age-dependent parameters but also on quantitative information on pathophysiological changes obtained via a comprehensive literature search. The predictive performances of models 1 and 2 were evaluated using a retrospectively collected dataset from neonates under intensive care (chictr.org.cn, ChiCTR1900027919), comprising 65 neonates and 92 vancomycin serum concentrations. Integrating literature-based parameter changes related to hypoalbuminemia, small-for-gestational-age, and co-medication, model 2 offered more optimized precision than model 1, as shown by a decrease in the overall mean absolute percentage error (50.6% for model 1; 37.8% for model 2). In conclusion, incorporating literature-based pathophysiological changes effectively improved PBPK modeling for critically ill neonates. Furthermore, this model allows for dosing optimization before serum concentration measurements can be obtained in clinical practice.</p>\",\"PeriodicalId\":22751,\"journal\":{\"name\":\"The Journal of Clinical Pharmacology\",\"volume\":\"64 12\",\"pages\":\"1552-1565\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-08-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"The Journal of Clinical Pharmacology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1002/jcph.6107\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"The Journal of Clinical Pharmacology","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/jcph.6107","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Physiologically Based Pharmacokinetic Modeling of Vancomycin in Critically Ill Neonates: Assessing the Impact of Pathophysiological Changes
Dosing vancomycin for critically ill neonates is challenging owing to substantial alterations in pharmacokinetics (PKs) caused by variability in physiology, disease, and clinical interventions. Therefore, an adequate PK model is needed to characterize these pathophysiological changes. The intent of this study was to develop a physiologically based pharmacokinetic (PBPK) model that reflects vancomycin PK and pathophysiological changes in neonates under intensive care. PK-sim software was used for PBPK modeling. An adult model (model 0) was established and verified using PK profiles from previous studies. A neonatal model (model 1) was then extrapolated from model 0 by scaling age-dependent parameters. Another neonatal model (model 2) was developed based not only on scaled age-dependent parameters but also on quantitative information on pathophysiological changes obtained via a comprehensive literature search. The predictive performances of models 1 and 2 were evaluated using a retrospectively collected dataset from neonates under intensive care (chictr.org.cn, ChiCTR1900027919), comprising 65 neonates and 92 vancomycin serum concentrations. Integrating literature-based parameter changes related to hypoalbuminemia, small-for-gestational-age, and co-medication, model 2 offered more optimized precision than model 1, as shown by a decrease in the overall mean absolute percentage error (50.6% for model 1; 37.8% for model 2). In conclusion, incorporating literature-based pathophysiological changes effectively improved PBPK modeling for critically ill neonates. Furthermore, this model allows for dosing optimization before serum concentration measurements can be obtained in clinical practice.