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

Povzetek

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.

Ključne besede

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;

Podatki

Jezik: Angleški jezik
Leto izida:
Tipologija: 1.01 - Izvirni znanstveni članek
Organizacija: UL FFA - Fakulteta za farmacijo
UDK: 678.7:615
COBISS: 94193411 Povezava se bo odprla v novem oknu
ISSN: 1999-4923
Št. ogledov: 101
Št. prenosov: 41
Ocena: 0 (0 glasov)
Metapodatki: JSON JSON-RDF JSON-LD TURTLE N-TRIPLES XML RDFA MICRODATA DC-XML DC-RDF RDF

Ostali podatki

Sekundarni jezik: Slovenski jezik
Sekundarne ključne besede: Zdravila;Polimeri;
Vrsta dela (COBISS): Članek v reviji
Strani: str. 1-16
Letnik: ǂVol. ǂ14
Zvezek: ǂiss. ǂ2
Čas izdaje: 2022
DOI: 10.3390/pharmaceutics14020228
ID: 15504123