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

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

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...

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Bibliographic Details
Main Authors: Ernő Benkő, Ilija German Ilič, Katalin Kristó, Géza Regdon, Ildikó Csóka, Klára Pintye-Hódi, Stane Srčič, Tamás Sovány
Format: Article
Language:English
Published: MDPI AG 2022-01-01
Series:Pharmaceutics
Subjects:
drug–excipient interaction
polymers
nondegradable
matrix tablet
controlled release
design of experiments
Online Access:https://www.mdpi.com/1999-4923/14/2/228

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https://www.mdpi.com/1999-4923/14/2/228

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