Predicting Drug Release Rate of Implantable Matrices and Better Understanding of the Underlying Mechanisms through Experimental Design and Artificial Neural Network-Based Modelling

Benkő Ernő and Ilič Ilija Germa and Kristó Katalin and Regdon Géza (ifj.) and Pannonhalminé Csóka Ildikó and Hódi Klára and Sricic Stane and Sovány Tamás: Predicting Drug Release Rate of Implantable Matrices and Better Understanding of the Underlying Mechanisms through Experimental Design and Artificial Neural Network-Based Modelling.
PHARMACEUTICS, 14 (2). Terjedelem: 16 p-Azonosító: 228. ISSN 1999-4923 (2022)

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Item Type: Journal Article
Journal or Publication Title: PHARMACEUTICS
Date: 2022
Volume: 14
Number: 2
Page Range: Terjedelem: 16 p-Azonosító: 228
ISSN: 1999-4923
Faculty/Unit: Faculty of Pharmacy
Institution: Szegedi Tudományegyetem
Language: English
MTMT rekordazonosító: 32634618
DOI azonosító: https://doi.org/10.3390/pharmaceutics14020228
Date Deposited: 2022. Feb. 09. 10:19
Last Modified: 2022. Feb. 09. 10:19
URI: http://publicatio.bibl.u-szeged.hu/id/eprint/23524
Web of Science® Times Cited: 2 View citing articles in Web of Science®

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