在临床实践中整合人群药理动力学建模与精确剂量的推方法
Monika Berezowska1, Isaac S Hayden1, Andrew M Brandon2
1Vesynta Ltd, Innovation Gateway, The London Cancer Hub, Cotswold Road, Sutton, London, UK.
基于模型的精确剂量 (MIPD) 使用人口药理动力学 (popPK) 模型个性化患者治疗. 本指南提供了开发和实施MIPD的最佳实践,以改善药物剂量和患者的治疗结果.
科学领域:
- 药理计量和药物开发研究
- 临床药理学 临床药理学
- 医疗信息学 医疗信息学
背景情况:
- 低于最佳的剂量策略导致不同患者群体的健康不平等.
- 人们越来越需要个性化的患者治疗,推动采用基于模型的精确剂量 (MIPD).
- 人口药理动力学 (popPK) 建模对于个性化药物暴露特征是至关重要的.
研究的目的:
- 为在MIPD软件中开发和使用popPK模型提供标准化指南.
- 整合关于MIPD软件部署和电子健康记录集成的监管指导.
- 探索机器学习对popPK和MIPD的未来影响.
主要方法:
- 文献综述和popPK模型开发建议的综合.
- 巩固监管和咨询机构关于MIPD实施的指导.
- 对将MIPD与电子健康记录集成的技术要求进行分析.
主要成果:
- 建立了 popPK 模型开发和 MIPD 软件应用的最佳实践.
- 总结了MIPD部署和EHR集成的监管要求.
- 确定了机器学习算法在提高精度剂量方面的潜力.
结论:
- 高质量的精确剂量解决方案可以集成到临床工作流程中.
- 标准化指导方针提高了个性化剂量选择的有效性.
- MIPD有可能优化患者的治疗结果并减少健康不平等.
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