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采用自动机器学习 (AutoML) 方法来促进在中的ADMET属性预测

Herim Han1, Bilal Shaker2, Jin Hee Lee3

  • 1NamuICT R&D Center, NamuICT, Seoul 07793, Republic of Korea.

Journal of chemical information and modeling
|March 14, 2025
PubMed
概括

我们开发了一个人工智能驱动的机器学习模型来预测11个吸收,分布,新陈代谢,分泌和毒性 (ADMET) 属性. 该工具通过改进化合物设计和降低失败率来提高早期药物发现.

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Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
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