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

• Hauptverfasser: Ernő Benkő (Verfasst von), Ilija German Ilič (Verfasst von), Katalin Kristó (Verfasst von), Géza Regdon (Verfasst von), Ildikó Csóka (Verfasst von), Klára Pintye-Hódi (Verfasst von), Stane Srčič (Verfasst von), Tamás Sovány (Verfasst von)
• Format: Buch
• Veröffentlicht: MDPI AG, 2022-01-01T00:00:00Z.
• Schlagworte: article
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There is a growing interest in implantable drug delivery systems (DDS) in pharmaceutical science. The aim of the present study is to investigate whether it is possible to customize drug release from implantable DDSs through drug-carrier interactions. Therefore, a series of chemically similar active...