The use of artificial neural networks for the selection of the most appropriate formulation and processing variables in order to predict the in vitro dissolution of sustained release minitablets

AAPS PharmSciTech

Volumn 4, Issue 2, 2003, Pages

  Leane, Michael M ^a,b   Cumming, Iain ^b   Corrigan, Owen I ^a  

^a TRINITY COLLEGE DUBLIN   (Ireland)

^b ELAN PHARMACEUTICALS   (United States)

Author keywords

Artificial neural network; Formulation development; Input feature selection; Minitablet; Sustained release

Indexed keywords

AEROSIL; DRUG; HYDROXYPROPYLMETHYLCELLULOSE; MAGNESIUM STEARATE; MICROCRYSTALLINE CELLULOSE;

ALGORITHM; ARTICLE; ARTIFICIAL NEURAL NETWORK; COMPUTER ANALYSIS; COMPUTER PROGRAM; CONTROLLED STUDY; DRUG DOSAGE FORM; DRUG FORMULATION; DRUG MANUFACTURE; DRUG RELEASE; DRUG SOLUBILITY; ENTERIC COATED TABLET; IN VITRO STUDY; PREDICTION; SUSTAINED RELEASE PREPARATION; ARTIFICIAL INTELLIGENCE; CHEMICAL MODEL; CHEMISTRY; COMPUTER SIMULATION; DELAYED RELEASE FORMULATION; TABLET;

ARTIFICIAL INTELLIGENCE; CHEMISTRY, PHARMACEUTICAL; COMPUTER SIMULATION; DELAYED-ACTION PREPARATIONS; MODELS, CHEMICAL; NEURAL NETWORKS (COMPUTER); SOFTWARE; TABLETS;

EID: 0141652946     PISSN: 15309932     EISSN: 15309932     Source Type: Journal    
DOI: 10.1208/pt040226     Document Type: Article

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