Priprava, in vitro i in vivo evaluacija bioadhezivnih mikrosfera s algino-pektinom: ispitivanje utjecaja polimera pomoću multiple poredbene analize

Ionotropic gelation was used to entrap aceclofenac into algino-pectinate bioadhesive microspheres as a potential drug carrier for the oral delivery of this anti-inflammatory drug. Microspheres were investigated in vitro for possible sustained drug release and their use in vivo as a gastroprotective system for aceclofenac. Polymer concentration and polymer/drug ratio were analyzed for their influence on microsphere properties. The microspheres exhibited good bioadhesive property and showed high drug entrapment efficiency. Drug release profiles exhibited faster release of aceclofenac from alginate microspheres whereas algino-pectinate microspheres showed prolonged release. Dunett\u27s multiple comparison analyis suggested a significant difference in percent inhibition of paw edema when the optimized formulation was compared to pure drug. It was concluded that the algino-pectinate bioadhesive formulations exhibit promising properties of a sustained release form for aceclofenac and that they provide distinct tissue protection in the stomach.U radu je opisana priprava algino-pektinskih bioadhezivnih mikrosfera protuupalnog lijeka aceklofenaka metodom ionotropnog geliranja. In vitro je ispitivana mogućnost postupnog oslobađanja ljekovite tvari iz mikrosfera te mogućnost upotrebe mikrosfera kao gastroprotektivnog sustava za isporuku aceklofenaka in vivo. Ispitivan je utjecaj koncentracije polimera i omjera polimera i lijeka na svojstva mikrosfera. Mikrosfere su bile bioahezivne i sadržavale su veliki udio lijeka. Oslobađanje aceklofenaka iz alginatnih mikrosfera bilo je brže, a iz mikrosfera s algino-pektinom usporeno. Dunnetova multipla analiza ukazuje na značajnu razliku u postotku inhibicije edema šape kada se usporede optimizirana formulacija i čista ljekovita tvar. Može se zaključiti da su bioadhezivne mikrosfere s algino-pektinom povoljne za usporeno oslobađanje aceklofenaka te da pružaju umjerenu zaštitu sluznice želuca

Učinak topljivosti na kinetiku oslobađanja vodotopljivih i vodonetopljivih lijekova iz matriksnog sustava na bazi HPMC

The purpose of the present research work was to observe the effects of drug solubility on the release kinetics of water soluble verapamil hydrochloride and insoluble aceclofenac from polymer based matrix formulations. Matrix formulations were prepared by the direct compression method. The formulations were evaluated for various physical parameters. Along with the dynamics of water uptake and erosion, SEM and in vitro drug release of tablets were studied. Applying an exponential equation, it was found that the kinetics of soluble drug release followed anomalous non-Fickian diffusion transport whereas insoluble drug showed zero-order release. SEM study showed pore formation on the tablet surface that differed depending on drug solubility. t-Test pointed to a significant difference in the amount of both drugs released due to their difference in solubility. Solubility of the drug affects the kinetics and the mechanism of drug release.Cilj rada bio je praćenje učinka topljivosti na kinetiku oslobađanja vodotopljivog verapamil hidroklorida i netopljivog lijeka aceklofenaka iz matriksnih sustava na bazi hidrofilnog polimera. Matriksni sustavi pripravljeni su izravnom metodom kompresije. Uz ispitivanje uobičajenih fizikalnih svojstava, ispitivana je i dinamika primanja vode, te erozija, SEM i in vitro oslobađanje ljekovite tvari iz tableta. Primjenom eksponencijalne jednadžbe utvrđeno je da mehanizam oslobađanja topljivih lijekova slijedi anomalni ne-Fickov difuzijski transport, dok netopljivi lijekovi slijede kinetiku nultog reda. SEM ispitivanja pokazala su pore na površini matriksa ovisne o topljivosti ljekovite tvari. T-test ukazuje da količina oslobođenog lijeka značajno ovisi o njegovoj topljivosti. Topljivost lijeka ima značajan učinak na kinetiku i mehanizam oslobađanja

Predictive Modelling in pharmacokinetics: from in-silico simulations to personalized medicine

Pharmacokinetic parameters assessment is a critical aspect of drug discovery and development, yet challenges persist due to limited training data. Despite advancements in machine learning and in-silico predictions, scarcity of data hampers accurate prediction of drug candidates’ pharmacokinetic properties. The study highlights current developments in human pharmacokinetic prediction, talks about attempts to apply synthetic approaches for molecular design, and searches several databases, including Scopus, PubMed, Web of Science, and Google Scholar. The article stresses importance of rigorous analysis of machine learning model performance in assessing progress and explores molecular modeling (MM) techniques, descriptors, and mathematical approaches. Transitioning to clinical drug development, article highlights AI (Artificial Intelligence) based computer models optimizing trial design, patient selection, dosing strategies, and biomarker identification. In-silico models, including molecular interactomes and virtual patients, predict drug performance across diverse profiles, underlining the need to align model results with clinical studies for reliability. Specialized training for human specialists in navigating predictive models is deemed critical. Pharmacogenomics, integral to personalized medicine, utilizes predictive modeling to anticipate patient responses, contributing to more efficient healthcare system. Challenges in realizing potential of predictive modeling, including ethical considerations and data privacy concerns, are acknowledged. AI models are crucial in drug development, optimizing trials, patient selection, dosing, and biomarker identification and hold promise for streamlining clinical investigations.</p