数据在量化系统的开发和应用中的作用 药理学模型 药理学模型
Jason R Chan1, Abhishek Gulati2, Mary E Spilker3
1Global PK/PD & Pharmacometrics, Eli Lilly and Company, Indianapolis, IN, USA. jrchan@lilly.com.
量化系统药理学 (QSP) 使用集成数据和数学建模来了解药物效应和疾病. 本综述详细介绍了QSP模型开发和解释的关键数据类型,来源和质量考虑因素.
科学领域:
- 药理学 药理学是指药理学的学科.
- 系统生物学 系统生物学
- 计算生物学 计算生物学
背景情况:
- 定量系统药理学 (QSP) 是一个跨学科领域.
- QSP集成了数学建模,生物知识和实验数据.
- 它旨在了解复杂的药物作用和生理系统中的疾病进展.
研究的目的:
- 探索在QSP模型开发中使用的各种数据类型.
- 为了确定这些数据的来源.
- 分析数据质量对QSP模型解释的影响.
主要方法:
- 关于QSP中的数据类型和来源的文献综述.
- 在QSP模型构建中分析数据整合策略.
- 在QSP中讨论数据质量评估.
主要成果:
- QSP模型利用各种数据,包括临床前,临床和"omics"数据.
- 来自不同来源的数据集成带来了挑战.
- 数据质量显著影响了QSP模型预测的可靠性.
结论:
- 了解数据类型,来源和质量对于强大的QSP模型开发至关重要.
- 高质量,良好的特征数据提高了QSP模型的预测能力.
- 这一综述为基于数据的QSP应用提供了一个框架.
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