在患有功能障碍的患者中,以生理学为基础的Cefotaxime的药动力学模型
Fatima Zbib1, Anthéa Deschamps1,2, Lionel Velly3,4
1Aix Marseille University, APHM, INSERM, Service de Pharmacologie Clinique et Pharmacosurveillance, INS Institute Neuroscience Syst, Marseille, France.
基于生理学的药物动力学模型准确地预测了健康成年人和慢性病 (CKD) 患者的塞福他西姆药物暴露. 这些模型有助于为弱势群体个性化西福胺剂量.
科学领域:
- 药理动力学和药物新陈代谢
- 计算生物学和生物信息学
背景情况:
- 塞法洛斯波林抗生素Cefotaxime主要通过脏排出.
- 降低功能可能会导致塞福他西姆的暴露增加和潜在的毒性.
- 准确的药理动力学建模对于在功能受损的患者中安全有效地使用药物至关重要.
研究的目的:
- 在健康的欧洲成年人中开发一种基于生理学的药理动力学 (PBPK) 模型,用于塞福他西姆.
- 机械地描述慢性病 (CKD) 对塞福胺药理学的影响.
- 评估该模型对需要重症监护的重症患者的适用性.
主要方法:
- 使用PK-Sim®软件构建了Cefotaxime的PBPK模型.
- 将运输体和酶纳入健康人群的模型中.
- 通过整合病理生理学变化和减少的酶/输送活性,将模型推断为CKD患者.
- 经过验证的模型预测,使用来自重症监护病人的临床常规数据.
主要成果:
- 该PBPK模型在健康受试者和CKD患者中显示出足够的预测性表现.
- 曲线比率下的预测到观察面积通常属于双重接受标准.
- 预测错误是可以接受的,除了在第四阶段CKD患者中观察到的更高误差.
- 该模型在重症监护病人的预测性表现良好,尽管需要进一步评估.
结论:
- 成功开发了全身PBPK模型,用于预测不同人群中塞福他xime的药理动力学.
- 这些PBPK模型代表了优化赛福胺剂量策略的重大进步.
- 这些模型在脆弱的患者群体 (包括患有慢性病和重症监护机构) 中提供了个性化塞福他xime 治疗的潜力.
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