Applications of machine learning in drug discovery and development

Drug discovery and development pipelines are long, complex and depend on numerous factors. Machine learning (ML) approaches provide a set of tools that can improve discovery and decision making for well-specified questions with abundant, high-quality data. Opportunities to apply ML occur in all stag...

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Veröffentlicht in:	Nature reviews. Drug discovery 2019-06, Vol.18 (6), p.463-477
Hauptverfasser:	Vamathevan, Jessica, Clark, Dominic, Czodrowski, Paul, Dunham, Ian, Ferran, Edgardo, Lee, George, Li, Bin, Madabhushi, Anant, Shah, Parantu, Spitzer, Michaela, Zhao, Shanrong
Format:	Artikel
Sprache:	eng
Schlagworte:	631/114/1305 631/154 631/1647/245 692/699 Algorithms Animals Bioinformatics Biomarkers Biomedical and Life Sciences Biomedicine Biotechnology Cancer Research Clinical decision making Clinical trials Datasets Decision making Drug Design Drug discovery Drug Discovery - methods Gene expression Humans Identification Laboratories Machine Learning Medicinal Chemistry Methods Molecular biology Molecular Medicine Neural Networks, Computer Pharmaceutical industry Pharmaceutical research Pharmacology/Toxicology R&D Research & development Review Article Software Technology application
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