质谱法和数学PK/PD模型用于决策树引导的共价药物开发
Md Amin Hossain1,2,3, Rutali R Brahme1,2, Brandon C Miller1
1Department of Chemistry and Chemical Biology, Northeastern University;Boston, Massachusetts, 02115, USA.
Nature communications
|February 19, 2025
概括
这项研究引入了对共价药物发现的新工作流程,改进了成功识别和PK/PD建模. 它解决了对共价药物的现有方法的局限性,提高了药物开发效率.
科学领域:
- 药用化学 医学化学
- 药理学 药理学是指药理学的学科.
- 生物化学 生物化学
背景情况:
- 协同药物发现面临挑战,包括高假阳性率和未结合的药理动力学 (PK) 和药理动力学 (PD).
- 现有的生物分析和建模方法不足以确定共价药物开发中的PK和PD参数.
研究的目的:
- 提出一种新的共价药物发现工作流程,解决该领域的关键局限性.
- 引入先进的生物分析方法和完整的蛋白质PK/PD模型,以改善药物开发.
主要方法:
- 开发了一种质谱 (MS) 试验,以量化药物向蛋白质结合 (%向参与).
- 创建了一个完整的蛋白质PK/PD (iPK/PD) 模型,从目标参与数据中确定PK和PD参数.
- 利用决策树来指导共价药物开发过程.
主要成果:
- 该MS测定准确地测量了生物矩阵中的%目标参与率.
- 该iPK/PD模型成功输出了PK和PD参数,适用于各种目标参与度测量.
- 工作流程和模型使用已批准的药物 (ibrutinib, sotorasib) 和各种蛋白质标 (KRAS, BTK, SOD1) 进行了验证.
结论:
- 提出的工作流程,生物分析方法和iPK/PD模型克服了共价药物发现的重大局限性.
- 这种综合方法提高了PK/PD参数的确定,并有效地指导研究人员.
- 这些发现支持开发更有效的共价疗法,包括针对ALS.
相关概念视频
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