Artificial neural networks in the optimization of a nimodipine controlled release tablet formulation

European Journal of Pharmaceutics and Biopharmaceutics

Volumn 74, Issue 2, 2010, Pages 316-323

  Barmpalexis, Panagiotis ^a   Kanaze, Feras Imad ^b   Kachrimanis, Kyriakos ^a   Georgarakis, Emanouil ^a  

^a ARISTOTLE UNIVERSITY OF THESSALONIKI   (Greece)

^b Pharmaceutical Industry   (Greece)

Author keywords

Artificial neural networks; Controlled release; Euclidian distance; Nimodipine; Pruning

Indexed keywords

HYDROXYPROPYLMETHYLCELLULOSE; MACROGOL 4000; NIMODIPINE; POVIDONE;

ANALYTIC METHOD; ARTICLE; ARTIFICIAL NEURAL NETWORK; CONTROLLED RELEASE FORMULATION; CONTROLLED STUDY; DRUG EFFICACY; DRUG RELEASE; DRUG SOLUBILITY; EXPERIMENTAL DESIGN; INDEPENDENT VARIABLE; INTERMETHOD COMPARISON; MULTIPLE LINEAR REGRESSION ANALYSIS; RESPONSE VARIABLE; TABLET FORMULATION;

CHEMISTRY, PHARMACEUTICAL; COMPUTER SIMULATION; DELAYED-ACTION PREPARATIONS; LINEAR MODELS; NEURAL NETWORKS (COMPUTER); NIMODIPINE; POLYMERS; SOLUBILITY; TABLETS;

EID: 75749137666     PISSN: 09396411     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ejpb.2009.09.011     Document Type: Article

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