Application of artificial neural networks in the design of controlled release drug delivery systems

Advanced Drug Delivery Reviews

Volumn 55, Issue 9, 2003, Pages 1201-1215

  Sun, Yichun ^a   Peng, Yingxu ^a   Chen, Yixin ^b   Shukla, Atul J ^a  

^a UNIVERSITY OF TENNESSEE HEALTH SCIENCE CENTER   (United States)

^b Tanox Biosystems Inc   (United States)

Author keywords

Artificial neural network; Controlled release; Deconvolution; Design of experiment; Drug delivery systems; Fit factors; Formulation optimization; Response surface methodology

Indexed keywords

CONTROLLED DRUG DELIVERY; DRUG DOSAGE; MATHEMATICAL MODELS;

STATISTIC REPONSE;

NEURAL NETWORKS;

ACETYLSALICYLIC ACID; CARBOXYMETHYLCELLULOSE; CELLABURATE; CONTROSE; EUDRAGIT; HEXADECANOL; HYDROXYETHYLCELLULOSE; HYDROXYPROPYLCELLULOSE; HYDROXYPROPYLMETHYLCELLULOSE; KETOPROFEN; LACTOSE; MACROGOL DERIVATIVE; MAGNESIUM STEARATE; MICROSPHERE; NUPAREIL; POVIDONE; SALBUTAMOL SULFATE; STARCH; THEOPHYLLINE; VERAPAMIL;

ARTIFICIAL NEURAL NETWORK; CONTROLLED DRUG RELEASE; CONTROLLED RELEASE FORMULATION; DATA ANALYSIS; DRUG DELIVERY SYSTEM; DRUG DOSAGE FORM; DRUG FORMULATION; DRUG PELLET; DRUG SOLUBILITY; GENETIC ALGORITHM; PARTICLE SIZE; PRIORITY JOURNAL; PROCESS MODEL; RESPONSE SURFACE METHOD; REVIEW; TABLET HARDNESS;

EID: 0042884376     PISSN: 0169409X     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0169-409X(03)00119-4     Document Type: Article

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