Machine Learning Uncovers Food- and Excipient-Drug Interactions

Inactive ingredients and generally recognized as safe compounds are regarded by the US Food and Drug Administration (FDA) as benign for human consumption within specified dose ranges, but a growing body of research has revealed that many inactive ingredients might have unknown biological effects at...

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Veröffentlicht in:	Cell reports (Cambridge) 2020-03, Vol.30 (11), p.3710-3716.e4
Hauptverfasser:	Reker, Daniel, Shi, Yunhua, Kirtane, Ameya R., Hess, Kaitlyn, Zhong, Grace J., Crane, Evan, Lin, Chih-Hsin, Langer, Robert, Traverso, Giovanni
Format:	Artikel
Sprache:	eng
Schlagworte:	Abietanes - chemistry Abietanes - pharmacology Animals ATP Binding Cassette Transporter, Subfamily B, Member 1 - metabolism Biological Assay Cell Biology data science Diterpenes - pharmacology drug delivery Drug Interactions excipient-drug interactions Excipients - chemistry Female Food food-drug interactions Glucuronosyltransferase - antagonists & inhibitors Glucuronosyltransferase - metabolism Hep G2 Cells Humans inactive ingredients Life Sciences & Biomedicine Machine Learning Mice, Inbred BALB C Pharmaceutical Preparations - metabolism pharmacokinetics pharmacology Retinyl Esters - pharmacology Science & Technology Swine United States United States Food and Drug Administration virtual screening
Online-Zugang:	Volltext
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