一个基于MMAE的抗体-药物联合体的转化生理学基础的药物动力学模型
Hsuan-Ping Chang1, Dhaval K Shah2
1Department of Pharmaceutical Sciences, School of Pharmacy and Pharmaceutical Sciences, The State University of New York at Buffalo, 455 Pharmacy Building, Buffalo, NY, 14214-8033, USA.
Journal of pharmacokinetics and pharmacodynamics
|May 5, 2025
概括
这项研究开发了一种针对抗体-药物合物 (ADC) 的转化生理学基础的药理动力学 (PBPK) 模型. 该模型准确地预测了老鼠,子和人类的ADC分析剂的药理动力学,有助于药物开发.
科学领域:
- 药理学 药理学是指药理学的学科.
- 生物技术是生物技术.
- 计算生物学 计算生物学
背景情况:
- 抗体-药物合物 (ADC) 是一类有前途的向癌症治疗药物.
- 基于生理学的药理动力学 (PBPK) 模型是预测体内药物行为的有价值工具.
- 翻译PBPK模型对于桥梁临床前和临床研究至关重要.
研究的目的:
- 开发一种针对抗体-药物联合体 (ADCs) 的转化生理学基础的药理动力学 (PBPK) 模型.
- 从小鼠到老鼠,子和人类,从小鼠到老鼠,从老鼠到子,从老鼠到人类,从老鼠到老鼠,从老鼠到老鼠,从老鼠到老鼠,从老鼠到老鼠,从老鼠到老鼠,从老鼠到老鼠,从老鼠到老鼠.
- 预测各种物种中ADC分析物的药理动力学 (PK) 概况.
主要方法:
- 针对基于MMAE的ADCs的双结构全身PBPK模型被调整并扩展到各个物种.
- 特定物种的生理和药物相关参数来源于文献.
- 有效载荷释放 (解) 和抗体降解率通过全米缩放和对增强清除的调整进行了优化.
主要成果:
- 翻译PBPK模型成功预测了大鼠,子和人类的ADC分析物的PK概况.
- 在更高的物种中观察到ADC的脱率下降.
- 有效载荷结合对更高物种和人类的ADC清除有更明显的影响.
结论:
- 开发的翻译PBPK模型可以预测ADC分析物PK,包括在动作地点.
- 该模型为建立ADC的暴露-反应关系提供了有价值的见解.
- 该建模框架作为开发其他ADC的PBPK模型的平台.
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