Vastag Mónika, Keseru György M
Gedeon Richter plc, Gyömroi út, Budapest, Hungary.
Curr Opin Drug Discov Devel. 2009 Jan;12(1):115-24.
Predictive, cost effective and fast evaluation of CNS penetration or unbound brain levels of NCEs, or both, presents a considerable challenge in preclinical screening in the pharmaceutical industry. It is evident that neither a single in vitro model nor a set of physicochemical parameters is capable of predicting complex in vivo measures, such as brain distribution or blood-brain barrier (BBB) penetration, accurately. Various in vitro and in silico strategies have been developed to model drug action as a function of BBB properties, with models that provide sufficient predictivity, reliability and throughput to be favored by the pharmaceutical industry. This review gives a practical summary of in vitro and in silico approaches to evaluate BBB penetration.
在制药行业的临床前筛选中,对新化学实体(NCEs)的中枢神经系统(CNS)渗透或游离脑内水平进行预测性、成本效益高且快速的评估面临着相当大的挑战。显然,无论是单一的体外模型还是一组物理化学参数,都无法准确预测复杂的体内指标,如脑部分布或血脑屏障(BBB)渗透。已经开发了各种体外和计算机模拟策略来将药物作用建模为血脑屏障特性的函数,那些具有足够预测性、可靠性和通量的模型受到制药行业的青睐。本综述对评估血脑屏障渗透的体外和计算机模拟方法进行了实用总结。