在抗体开发能力工作流程中评估和纳入体外相关的药物动力学结果

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Tushar Jain¹, Bianka Prinz², Alexander Marker³

¹Department of Computational Biology, Adimab LLC, Mountain View, CA, USA.

|July 31, 2024

概括

预测生物治疗药理动力学 (PK) 行为早期使用体外试验测试减少了动物试验. 将多个体外测量与计算模型相结合,可以提高药物发现PK预测的准确性.

科学领域:

生物制药学发现发现
药理动力学药理动力学
在体外检测中进行检测.

背景情况:

早期预测生物治疗药理动力学 (PK) 行为对于有效的药物发现至关重要.
目前的方法往往需要进行广泛的体内研究,增加成本和动物使用.

研究的目的:

通过整合与PK相关的体外测量来增强经典的可开发性工作流程.
为了验证特定的PK行为体内试验的预测能力.
为改进PK预测开发一种计算方法.

主要方法:

在hFcRn Tg32小鼠中与PK相关的体外测量 (非特异性相互作用,自我相互作用,FcRn相互作用).
利用具有不同物理化学性质的生物治疗药物的多样化数据集.
开发一个结合多个体外数据点的多变量回归模型.

主要成果:

在实验室测量非特异性相互作用,自我相互作用和FcRn相互作用,显示与小鼠清除的高相关性.
结合多个体外评估的计算方法显著改善了PK预测相关性.
研究数据集的多样性增强了研究结果的稳定性.

结论:

将特定的体外试验分析集成到可开发性工作流中,可以可靠地预测生物治疗性PK.
一个利用多个体外数据点的计算模型,与单个测试相比,提供了优越的PK预测.
这种方法可以更早地优先考虑具有良好的PK特性的候选药物,优化资源配置并减少动物使用.

关键词:

抗体是一种抗体.生物治疗药物生物治疗药物开发能力开发能力在Silico预测预测中在体外测量 in vitro测量在活体内评估新生儿的Fc受体.非特异性的非特异性.药物动力学药物动力学自我协会/自我互动

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