Ernő Benkő (Author), Ilija Ilić (Author), Katalin Kristó (Author), Géza Regdon (Author), Ildikó Csóka (Author), Klára Pintyé-Hodi (Author), Stanko Srčič (Author), Tamás Sovány (Author)

Abstract

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 ingredients (APIs) was mixed with different matrix-forming materials and was then compressed directly. Compression and dissolution interactions were examined by FT-IR spectroscopy. Regarding the effect of the interactions on drug release kinetics, a custom-made dissolution device designed for implantable systems was used. The data obtained were used to construct models based on artificial neural networks (ANNs) to predict drug dissolution. FT-IR studies confirmed the presence of H-bond-based solid-state interactions that intensified during dissolution. These results confirmed our hypothesis that interactions could significantly affect both the release rate and the amount of the released drug. The efficiencies of the kinetic parameter-based and point-to-point ANN models were also compared, where the results showed that the point-to-point models better handled predictive inaccuracies and provided better overall predictive efficiency.

Keywords

interakcija med zdravili;interakcija med pomožnimi snovmi;nerazgradljivost;matrične tablete;nadzorovano sproščanje;načrtovanje eksperimentov;umetne nevronske mreže;drug–excipient interaction;polymers;nondegradable;matrix tablet;controlled release;design of experiments;artificial neural networks;

Data

Language: English
Year of publishing:
Typology: 1.01 - Original Scientific Article
Organization: UL FFA - Faculty of Pharmacy
UDC: 678.7:615
COBISS: 94193411 Link will open in a new window
ISSN: 1999-4923
Views: 101
Downloads: 41
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Other data

Secondary language: Slovenian
Secondary keywords: Zdravila;Polimeri;
Type (COBISS): Article
Pages: str. 1-16
Volume: ǂVol. ǂ14
Issue: ǂiss. ǂ2
Chronology: 2022
DOI: 10.3390/pharmaceutics14020228
ID: 15504123