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通过机器学习算法扩大PAMPA透性的预测局限性

Anita Rácz1, Anna Vincze2, Balázs Volk3

  • 1Plasma Chemistry Research Group, Institute of Materials and Environmental Chemistry, Research Centre for Natural Sciences, Magyar tudósok krt. 2., Budapest H-1117, Hungary.

European journal of pharmaceutical sciences : official journal of the European Federation for Pharmaceutical Sciences
|July 4, 2023
PubMed
概括

这项研究开发了准确的定量结构-特性关系 (QSPR) 模型,使用并行人工膜透性试验 (PAMPA) 数据来预测胃肠道吸收. 这些模型通过提供对新化学化合物的可靠预测来增强药物发现和安全性评估.

关键词:
机器学习是机器学习.神经网络:ADME:一个神经网络.潘帕帕是一个庞巴巴.透性 透性的这就是QSPR.

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