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Predictive Performance of Pharmacokinetic Model-Based Virtual Trials of Vancomycin in Neonates: Mathematics Matches Clinical Observation
Clinical Pharmacokinetics ( IF 4.5 ) Pub Date : 2022-05-06 , DOI: 10.1007/s40262-022-01128-z
Bu-Fan Yao 1 , Yue-E Wu 1 , Bo-Hao Tang 1 , Guo-Xiang Hao 1 , Evelyne Jacqz-Aigrain 2, 3 , John van den Anker 4, 5, 6 , Wei Zhao 1, 7
Affiliation  

Background and Objective

Vancomycin is frequently used to treat Gram-positive bacterial infections in neonates. However, there is still no consensus on the optimal initial dosing regimen. This study aimed to assess the performance of pharmacokinetic model-based virtual trials to predict the dose–exposure relationship of vancomycin in neonates.

Methods

The PubMed database was searched for clinical trials of vancomycin in neonates that reported the percentage of target attainment. Monte Carlo simulations were performed using nonlinear mixed-effect modeling to predict the dose–exposure relationship, and the differences in outcomes between virtual trials and real-world data in clinical studies were calculated.

Results

A total of 11 studies with 14 dosing groups were identified from the literature to evaluate dose–exposure relationships. For the ten dosing groups where the surrogate marker for exposure was the trough concentration, the mean ± standard deviation (SD) for the target attainment between original studies and virtual trials was 3.0 ± 7.3%. Deviations between − 10 and 10% accounted for 80% of the included dosing groups. For the other four dosing groups where the surrogate marker for exposure was concentration during continuous infusion, all deviations were between − 10 and 10%, and the mean ± SD value was 2.9 ± 4.5%.

Conclusion

The pharmacokinetic model-based virtual trials of vancomycin exhibited good predictive performance for dose–exposure relationships in neonates. These results might be used to assist the optimization of dosing regimens in neonatal practice, avoiding the need for trial and error.



中文翻译:

基于药代动力学模型的万古霉素虚拟试验在新生儿中的预测性能:数学与临床观察相匹配

背景与目的

万古霉素常用于治疗新生儿革兰氏阳性菌感染。然而,对于最佳初始给药方案仍未达成共识。本研究旨在评估基于药代动力学模型的虚拟试验的性能,以预测新生儿万古霉素的剂量-暴露关系。

方法

在 PubMed 数据库中搜索了报告目标达到百分比的新生儿万古霉素临床试验。使用非线性混合效应模型进行蒙特卡罗模拟以预测剂量-暴露关系,并计算临床研究中虚拟试验和真实世界数据之间的结果差异。

结果

从文献中确定了总共 11 项研究,包括 14 个给药组,以评估剂量-暴露关系。对于暴露的替代标记是谷浓度的 10 个剂量组,原始研究和虚拟试验之间目标达到的平均值 ± 标准偏差 (SD) 为 3.0 ± 7.3%。- 10% 和 10% 之间的偏差占所包含剂量组的 80%。对于其他四个剂量组,其中暴露的替代标记是连续输注期间的浓度,所有偏差都在 - 10% 和 10% 之间,平均值 ± SD 值为 2.9 ± 4.5%。

结论

基于药代动力学模型的万古霉素虚拟试验对新生儿的剂量-暴露关系表现出良好的预测性能。这些结果可用于帮助优化新生儿实践中的给药方案,避免反复试验的需要。

更新日期:2022-05-06
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