Bddcs class prediction for new molecular entities

Molecular Pharmaceutics

Volumn 9, Issue 3, 2012, Pages 570-580

  Broccatelli, Fabio ^a,b   Cruciani, Gabriele ^a   Benet, Leslie Z ^b   Oprea, Tudor I ^c,d,e  

^a UNIVERSITY OF PERUGIA   (Italy)

^b UNIVERSITY OF CALIFORNIA   (United States)

^c UNIVERSITY OF NEW MEXICO SCHOOL OF MEDICINE   (United States)

^d Sunset Molecular Discovery LLC   (United States)

^e TECHNICAL UNIVERSITY OF DENMARK   (Denmark)

Author keywords

ADMET; BDDCS; drug disposition; drug drug interactions; FDA solubility; GRID; machine learning; MIF; VolSurf+

Indexed keywords

CARRIER PROTEIN; DRUG;

ACCURACY; ARTICLE; COMPUTER PROGRAM; DRUG CLASSIFICATION; DRUG METABOLISM; DRUG PENETRATION; DRUG SOLUBILITY; DRUG STRUCTURE; DRUG TRANSPORT; DRUG UPTAKE; FOOD AND DRUG ADMINISTRATION; HUMAN; INTESTINE MUCOSA PERMEABILITY; PREDICTION; PRIORITY JOURNAL; VALIDATION STUDY;

ARTIFICIAL INTELLIGENCE; BIOPHARMACEUTICS; DRUG INTERACTIONS; MODELS, THEORETICAL; PHARMACEUTICAL PREPARATIONS; SOLUBILITY;

EID: 84858039726     PISSN: 15438384     EISSN: 15438392     Source Type: Journal    
DOI: 10.1021/mp2004302     Document Type: Article

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