Applying machine learning techniques for ADME-Tox prediction: A review

Expert Opinion on Drug Metabolism and Toxicology

Volumn 11, Issue 2, 2015, Pages 259-271

  Maltarollo, Vinícius Gonҫalves ^a   Gertrudes, Jadson Castro ^b   Oliveira, Patrícia Rufino ^b   Honorio, Kathia Maria ^a,b  

^a UNIVERSIDADE FEDERAL DO ABC   (Brazil)

^b UNIVERSITY OF SÃO PAULO   (Brazil)

Author keywords

Absorption; Distribution; Excretion and toxicity of xenobiotics; In silico drug design; Machine learning; Metabolism; Molecular modeling; Pharmacokinetics; Quantitative structure activity relationships

Indexed keywords

XENOBIOTIC AGENT;

BIOLOGICAL ACTIVITY; DRUG ABSORPTION; DRUG BIOAVAILABILITY; DRUG DESIGN; DRUG DISTRIBUTION; DRUG EFFICACY; DRUG EXCRETION; DRUG METABOLISM; DRUG SAFETY; HUMAN; LIPOPHILICITY; MACHINE LEARNING; MULTIPLE LINEAR REGRESSION ANALYSIS; PARTIAL LEAST SQUARES REGRESSION; PHARMACOKINETICS; PRINCIPAL COMPONENT ANALYSIS; QUANTITATIVE STRUCTURE PROPERTY RELATION; REVIEW; SUPPORT VECTOR MACHINE; ARTIFICIAL INTELLIGENCE; BIOLOGICAL MODEL; CHEMISTRY; QUANTITATIVE STRUCTURE ACTIVITY RELATION;

ARTIFICIAL INTELLIGENCE; DRUG DESIGN; HUMANS; MODELS, BIOLOGICAL; QUANTITATIVE STRUCTURE-ACTIVITY RELATIONSHIP; XENOBIOTICS;

EID: 84921292877     PISSN: 17425255     EISSN: 17447607     Source Type: Journal    
DOI: 10.1517/17425255.2015.980814     Document Type: Review

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