Optimizing the performance of in silico ADMET general models according to local requirements: MARS approach. Solubility estimations as case study

Journal of Chemical Information and Modeling

Volumn 49, Issue 12, 2009, Pages 2837-2850

  Oyarzabal, Julen ^a   Pastor, Joaquin ^b   Howe, Trevor J ^a  

^a JOHNSON AND JOHNSON   (United States)

^b JANSSEN RESEARCH AND DEVELOPMENT   (Belgium)

Author keywords

[No Author keywords available]

Indexed keywords

DECISION MAKING; DIGITAL LIBRARIES; SCAFFOLDS; SOLUBILITY;

ADAPTIVE RANKINGS; EXPERIMENTAL CONDITIONS; EXPERIMENTAL PROCEDURE; IN-SILICO MODELS; LABORATORY SOURCE; PREDICTIVE MODELING; SOLUBILITY ESTIMATION; VIRTUAL LIBRARIES;

PREDICTIVE ANALYTICS;

ABSORPTION; ARTICLE; BIOLOGY; DRUG DEVELOPMENT; HIGH THROUGHPUT SCREENING; METHODOLOGY; MONTE CARLO METHOD; REPRODUCIBILITY; SOLUBILITY;

ABSORPTION; COMPUTATIONAL BIOLOGY; DRUG DISCOVERY; HIGH-THROUGHPUT SCREENING ASSAYS; MONTE CARLO METHOD; REPRODUCIBILITY OF RESULTS; SOLUBILITY;

EID: 73349120606     PISSN: 15499596     EISSN: 1549960X     Source Type: Journal    
DOI: 10.1021/ci900308u     Document Type: Article

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