生物制药分类系统
生物制药
生物制药
人工智能
计算机科学
机器学习
生化工程
人工神经网络
药代动力学
化学
药理学
医学
工程类
生物技术
生药学
体外
生物活性
生物
生物化学
作者
Klosinska-Szmurlo Ewa,Mazurek Aleksander Pawel,Grudzien Monika,Katarzyna Betlejewska-Kielak
出处
期刊:Current Computer - Aided Drug Design
[Bentham Science Publishers]
日期:2016-11-03
卷期号:13 (1): 60-74
被引量:3
标识
DOI:10.2174/1573409912666161018094621
摘要
BACKGROUND: Two main factors, which have an influence on oral absorption from solid, immediate release dosage form, are solubility and permeability. These are considered the main fundamental properties that govern the rate and extent of oral absorption. The significance of these properties has been highlighted in the Biopharmaceutics Classification System (BCS). OBJECTIVE: The concept of this paper was to predict the solubility and permeability of fluoroquinolones using in silico methods based on the assumptions of the BCS. An attempt was also made to determine the place within this system for drugs from the fluoroquinolone group. METHOD: The study was carried out with the use of modern computational techniques which developed based on Artificial Neural Network Ensembles for Binary Classification. RESULTS: Using the values of the physicochemical descriptors of medicinal compounds with labeled BCS class, two classification models were elaborated for solubility and permeability. CONCLUSION: The obtained models helped to predict the provisional class for the following drugs in the BCS. Continuous improvement of computational models may support and can be treated equally with the in vivo data.
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