izpis_h1_title_alt

Predicting drug release rate of implantable matrices and better understanding of the underlying mechanisms through experimental design and artificial neural network-based modelling
ID Benkő, Ernő (Avtor), ID German Ilić, Ilija (Avtor), ID Kristó, Katalin (Avtor), ID Regdon, Géza (Avtor), ID Csóka, Ildikó (Avtor), ID Pintye-Hódi, Klára (Avtor), ID Srčič, Stanko (Avtor), ID Sovány, Tamás (Avtor)

.pdfPDF - Predstavitvena datoteka, prenos (3,15 MB)
MD5: 3F29228395A6E5068F5B1B2F31BE2596
URLURL - Izvorni URL, za dostop obiščite https://www.mdpi.com/1999-4923/14/2/228 Povezava se odpre v novem oknu

Izvleček
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.

Jezik:Angleški jezik
Ključne besede:drug–excipient interaction, polymers, non-degradable polymers, matrix tablet, controlled release, design of experiments, artificial neural networks
Vrsta gradiva:Članek v reviji
Tipologija:1.01 - Izvirni znanstveni članek
Organizacija:FFA - Fakulteta za farmacijo
Status publikacije:Objavljeno
Različica publikacije:Objavljena publikacija
Leto izida:2022
Št. strani:16 str.
Številčenje:Vol. 14, iss. 2, art. 228
PID:20.500.12556/RUL-137104 Povezava se odpre v novem oknu
UDK:678.7:615
ISSN pri članku:1999-4923
DOI:10.3390/pharmaceutics14020228 Povezava se odpre v novem oknu
COBISS.SI-ID:94193411 Povezava se odpre v novem oknu
Datum objave v RUL:01.06.2022
Število ogledov:721
Število prenosov:120
Metapodatki:XML DC-XML DC-RDF
:
Kopiraj citat
Objavi na:Bookmark and Share

Gradivo je del revije

Naslov:Pharmaceutics
Skrajšan naslov:Pharmaceutics
Založnik:MDPI
ISSN:1999-4923
COBISS.SI-ID:517949977 Povezava se odpre v novem oknu

Licence

Licenca:CC BY 4.0, Creative Commons Priznanje avtorstva 4.0 Mednarodna
Povezava:http://creativecommons.org/licenses/by/4.0/deed.sl
Opis:To je standardna licenca Creative Commons, ki daje uporabnikom največ možnosti za nadaljnjo uporabo dela, pri čemer morajo navesti avtorja.
Začetek licenciranja:01.02.2022

Sekundarni jezik

Jezik:Slovenski jezik
Ključne besede:interakcija med zdravili, interakcija med pomožnimi snovmi, nerazgradljivost, matrične tablete, nadzorovano sproščanje, načrtovanje eksperimentov, umetne nevronske mreže, zdravila, polimeri

Projekti

Financer:Drugi - Drug financer ali več financerjev
Program financ.:CEEPUS Mobility
Številka projekta:CIII-RS-1113-01-1718-M-113871

Financer:Drugi - Drug financer ali več financerjev
Program financ.:Hungary, Ministry of Innovation and Technology, National Research, Development, and Innovation Fund
Številka projekta:TKP2021-EGA-32

Podobna dela

Podobna dela v RUL:
Podobna dela v drugih slovenskih zbirkah:

Nazaj