oaioai:farfar.pharmacy.bg.ac.rs:123456789/1446

Računarski modeli za predviđanje rastvorljivosti lekova

Abstract

Aqueous solubility of a drug is a factor which can significantly influence its oral bioavailability, and can also affect the drug distribution in the body. Consideration of aqueous solubility in early stages of drug discovery and development is vital in reducing the incidence of late-stage drug development failures. The application of computational models for solubility prediction could provide the screening of combinatorial libraries, helping single-out potentially problematic and eliminate compounds with inadequate solubility. In addition to the prediction of solubility from chemical structure, the interpretation of such models can give an insight into structure-solubility relationships and can guide the optimization of structures in order to provide better solubility whilst retaining the activity of the investigated drugs. Development of such models is a complex process that requires consideration of numerous factors which can impact the final model's performance. Different solubility modeling approaches are discussed in this article. Despite intensive research on model development, prediction of the solubility of diverse drugs remains a challenging task. The quality of available experimental data used for modeling of solubility is increasingly recognized as one of the main causes for the limited reliability of many of the proposed models. Therefore, the full potential of the developed modeling methods will only be achieved by greater availability of reliable data obtained by same experimental methodology.Rastvorljivost leka u vodi je faktor koji može značajno da utiče na bioraspoloživost peroralno primenjenog leka, kao i na njegovu raspodelu u organizmu. Razmatranjem rastvorljivosti u ranim fazama otkrića i razvoja leka smanjuje se mogućnost neuspeha u daljem razvoju leka. Računarske metode za predviđanje rastvorljivosti lekova omogućavaju analizu kombinatornih baza podataka, identifikaciju potencijalno problematičnih jedinjenja i isključivanje onih čija je rastvorljivost neadekvatna. Pored predviđanja rastvorljivosti na osnovu hemijske strukture, analizom ovih modela moguće je detaljnije razjasniti odnose hemijske strukture i rastvorljivosti ispitivanih lekova i optimizovati strukture u cilju poboljšanja rastvorljivosti, pri čemu bi njihova aktivnost ostala nepromenjena. Razvoj ovakvih modela je kompleksan proces koji zahteva razmatranje velikog broja faktora koji mogu uticati na uspešnost predviđanja konačnog modela. U ovom radu su prikazani različiti pristupi koji se koriste u razvoju računarskih modela za predviđanje rastvorljivosti. I pored intenzivnog rada na razvoju ovih modela tokom protekle decenije, pouzdanost predviđanja rastvorljivosti lekova različitih struktura još uvek ostaje veliki izazov. Kvalitet dostupnih eksperimentalnih podataka koji se koriste u modelovanju rastvorljivosti se u sve većoj meri prepoznaje kao jedan od glavnih uzroka ograničene pouzdanosti većine do sada predloženih modela. Iskorišćenje punog potencijala razvijenih pristupa modelovanja rastvorljivosti uslovljeno je širom dostupnošću pouzdanih podataka za rastvorljivost određenih pod identičnim eksperimentalnim uslovima

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FarFar - Repository of the Faculty of Pharmacy, University of Belgrade

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oaioai:farfar.pharmacy.bg.ac.rs:123456789/1446Last time updated on 11/19/2019View original full text link

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