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Updated: Jun 6, 2025

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用SMILES信息预测人类药理动力学参数

Jae-Hee Kwon1, Ja-Young Han1, Minjung Kim1

  • 1Graduate School of Pharmaceutical Sciences, Ewha Womans University, Seoul, 03760, Republic of Korea.

Archives of pharmacal research
|November 26, 2024
PubMed
概括

这项研究开发了人类清除 (CL) 和分布量 (Vd,ss) 的预测模型,使用分子结构上的自然语言处理. 该模型准确地预测了这些药理动力学参数,SMILES数据增强了CL预测.

关键词:
清除许可证的情况机器学习 机器学习药理动力学 药理动力学斯米莱斯 (SMILES) 是一个有趣的小孩.分发的数量分布的数量.

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