Journal of Clinical Pediatrics ›› 2026, Vol. 44 ›› Issue (1): 84-90.doi: 10.12372/jcp.2026.25e1110
• Literature Review • Previous Articles
YAO Yunlu, XU Haixin, LIU Xinzhu, CHEN Jihui, BU Shuhong(
)
Received:2025-09-05
Accepted:2025-12-06
Published:2026-01-15
Online:2026-01-05
CLC Number:
YAO Yunlu, XU Haixin, LIU Xinzhu, CHEN Jihui, BU Shuhong. Clinical practice and challenges of model-informed precision dosing with vancomycin in pediatrics[J].Journal of Clinical Pediatrics, 2026, 44(1): 84-90.
Table 1
Comparative analysis of different MIPD model methods"
| 模型类型 | 侧重人群与应用场景 | 主要优势 | 主要局限与挑战 |
|---|---|---|---|
| 群体药代动力学(PPK) | 常规患者群体:基于已知协变量(如年龄、肾功能)进行TDM和剂量个体化 | 方法学成熟,监管认可度高;善于量化个体间差异;适用于临床稀疏采样数据 | 外推受限:难以准确外推至模型开发未覆盖的特殊人群;机制描述相对简化 |
| 生理药代动力学(PBPK) | 特殊人群:儿童、孕妇、器官损伤患者等(数据稀缺人群);预测复杂相互作用的影响 | 机制驱动:生物学基础强,可解释性高;强大的跨人群(如成人至儿童)外推能力 | 构建复杂:所需生理及药物参数众多且获取困难;参数不确定性可能累积 |
| 人工智能(AI) | 大数据/异构数据情景:整合EHR、组学等多源数据;预测复杂终点(疗效/毒性) | 数据驱动:强大的非线性模式识别能力;能处理高维复杂数据;模型可动态学习 | 可解释性差(黑箱问题);高度依赖训练数据质量,易过拟合;监管验证标准有待完善 |
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