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结合高通量选和机器学习,预测二进制和三进制无形固体分散配方的形成,用于早期药物发现和开发

Tianshu Lu1,2, Yiyang Wu2, Ping Xiong2

  • 1Institute of Applied Physics and Materials Engineering, University of Macau, Macau, 999078, China.

Pharmaceutical research
|April 3, 2025
PubMed
概括

这项研究将高通量查 (HTS) 与机器学习 (ML) 结合起来,以预测无形固体分散 (ASD). 这种方法有效地识别出有前途的药物配方,在早期药物发现中节省时间和资源.

关键词:
早期的药物发现高通量选的高通量选机器学习是机器学习.固体的分散 固体的分散溶剂蒸发方法是一种溶剂蒸发方法.

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