A probabilistic method to report predictions from a human liver microsomes stability QSAR model: A practical tool for drug discovery

Journal of Computer-Aided Molecular Design

Volumn 29, Issue 4, 2015, Pages 327-338

  Aliagas, Ignacio ^a   Gobbi, Alberto ^a   Heffron, Timothy ^a   Lee, Man Ling ^a   Ortwine, Daniel F ^a   Zak, Mark ^a   Khojasteh, S Cyrus ^a  

^a GENENTECH INC   (United States)

Author keywords

In vitro clearance; Liver microsomes; Probability; QSAR model

Indexed keywords

COMPUTATIONAL CHEMISTRY; LEARNING SYSTEMS; METABOLISM; MOLECULAR GRAPHICS; REGRESSION ANALYSIS; STABILITY; SYNTHESIS (CHEMICAL);

DRUG DISCOVERY; GENENTECH; HUMAN LIVER MICROSOMES; IN VITRO CLEARANCE; IN-VITRO; LIVER MICROSOMES; METABOLIC STABILITY; PROBABILISTIC METHODS; QSAR MODEL; VITRO LIVER;

FORECASTING;

ANIMAL TISSUE; ARTICLE; CONTROLLED STUDY; DRUG CLEARANCE; DRUG DEVELOPMENT; DRUG METABOLISM; DRUG STABILITY; HIGH THROUGHPUT SCREENING; HUMAN; HUMAN TISSUE; HUMAN VERSUS ANIMAL COMPARISON; IN VITRO STUDY; INTRINSIC CLEARANCE; LIVER CLEARANCE; LIVER MICROSOME; LIVER MICROSOME METABOLISM; MACHINE LEARNING; METABOLIC STABILITY; NONHUMAN; PREDICTION; PRIORITY JOURNAL; PROBABILITY; QUANTITATIVE STRUCTURE ACTIVITY RELATION; RAT; RETROSPECTIVE STUDY; VALIDATION STUDY; BIOLOGICAL MODEL; METABOLISM; PROCEDURES; SUPPORT VECTOR MACHINE;

DRUG;

DRUG DISCOVERY; HUMANS; MICROSOMES, LIVER; MODELS, BIOLOGICAL; PHARMACEUTICAL PREPARATIONS; PROBABILITY; QUANTITATIVE STRUCTURE-ACTIVITY RELATIONSHIP; SUPPORT VECTOR MACHINE;

EID: 84925483254     PISSN: 0920654X     EISSN: 15734951     Source Type: Journal    
DOI: 10.1007/s10822-015-9838-3     Document Type: Article

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