Recent progresses in the exploration of machine learning methods as in-silico ADME prediction tools

In-silico methods have been explored as potential tools for assessing ADME and ADME regulatory properties particularly in early drug discovery stages. Machine learning methods, with their ability in classifying diverse structures and complex mechanisms, are well suited for predicting ADME and ADME r...

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Veröffentlicht in:	Advanced drug delivery reviews 2015-06, Vol.86, p.83-100
Hauptverfasser:	Tao, L., Zhang, P., Qin, C., Chen, S.Y., Zhang, C., Chen, Z., Zhu, F., Yang, S.Y., Wei, Y.Q., Chen, Y.Z.
Format:	Artikel
Sprache:	eng
Schlagworte:	Absorption ADME Computer Simulation Distribution Drug discovery Excretion Humans Machine Learning Metabolism Models, Biological Molecular descriptors Pharmaceutical Preparations - metabolism Pharmacokinetics QSAR
Online-Zugang:	Volltext
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