从基于人口的PBPK到个性化的虚拟双胞胎:临床验证和医学中的应用
Marta Gonçalves1,2, Pedro Barata3,4,5, Nuno Vale1,2,6
1PerMed Research Group, RISE-Health, Faculty of Medicine, University of Porto, Alameda Professor Hernâni Monteiro, 4200-319 Porto, Portugal.
Journal of clinical medicine
|February 13, 2026
概括
基于生理学的药理动力学 (PBPK) 模型正在转向虚拟双胞胎 (VTs) 以实现个性化医疗. 纳入个体患者数据可以提高药物剂量预测,超越了精准医学的人口层面分析.
科学领域:
- 药理动力学和药物新陈代谢
- 个性化医疗和精确剂量定量
- 计算机生物学和建模
背景情况:
- 基于生理学的药理动力学 (PBPK) 模型预测药物的吸收,分布,新陈代谢和分泌 (ADME).
- 传统的人口级PBPK模型对真正精确的剂量有局限性.
- 转向个人PBPK建模,称为虚拟双胞胎 (VTs),正在获得引力.
研究的目的:
- 通过虚拟双胞胎 (VTs) 来审查从基于人口的PBPK建模到个人PBPK建模的过渡.
- 探索将患者特定数据纳入PBPK模型个性化和预测准确性的影响.
- 讨论评估PBPK模型性能和临床验证的方法.
主要方法:
- 对个人PBPK建模和虚拟双胞胎开发的文献综述.
- 综合人口,生理,表型和基因型数据的研究分析.
- 强调临床验证,比较预测与观察到的药物度.
主要成果:
- 结合患者特定数据的个别PBPK模型 (VTs) 提高了预测性能,特别是在功能等生理参数方面.
- 人口变量可以提高某些患者群体的准确性.
- 包括P450 (CYP) 数据的好处是不一致的.
结论:
- 使用虚拟双胞胎的个人PBPK建模为个性化医学的精确剂量提供了一条道路.
- 临床验证和解决数据限制对于常规实施至关重要.
- 将其集成到数字双胞胎框架中,对临床翻译具有前景.
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