Using Real-World Data to Externally Evaluate Population Pharmacokinetic Models of Dexmedetomidine in Children and Infants

Sean McCann, Victoria E. Helfer,Stephen J. Balevic,Chi D. Hornik,Stuart L. Goldstein,Julie Autmizguine, Marisa Meyer,Amira Al-Uzri, Sarah G. Anderson,Elizabeth H. Payne, Sitora Turdalieva,Daniel Gonzalez

JOURNAL OF CLINICAL PHARMACOLOGY(2024)

引用 0|浏览2
暂无评分
摘要
Dexmedetomidine is a sedative used in both adults and off-label in children with considerable reported pharmacokinetic (PK) interindividual variability affecting drug exposure across populations. Several published models describe the population PKs of dexmedetomidine in neonates, infants, children, and adolescents, though very few have been externally evaluated. A prospective PK dataset of dexmedetomidine plasma concentrations in children and young adults aged 0.01-19.9 years was collected as part of a multicenter opportunistic PK study. A PubMed search of studies reporting dexmedetomidine PK identified five population PK models developed with data from demographically similar children that were selected for external validation. A total of 168 plasma concentrations from 102 children were compared with both population (PRED) and individualized (IPRED) predicted values from each of the five published models by quantitative and visual analyses using NONMEM (v7.3) and R (v4.1.3). Mean percent prediction errors from observed values ranged from -1% to 120% for PRED, and -24% to 60% for IPRED. The model by James et al, which was developed using similar "real-world" data, nearly met the generalizability criteria from IPRED predictions. Other models developed using clinical trial data may have been limited by inclusion/exclusion criteria and a less racially diverse population than this study's opportunistic dataset. The James model may represent a useful, but limited tool for model-informed dosing of hospitalized children.
更多
查看译文
关键词
dexmedetomidine,external validation,pediatrics,pharmacokinetics,population PK model
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要