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首页> 外文期刊>Journal of Medicinal Chemistry >Graphical model for estimating oral bioavailability of drugs in humans and other species from their Caco-2 permeability and in vitro liver enzyme metabolic stability rates.
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Graphical model for estimating oral bioavailability of drugs in humans and other species from their Caco-2 permeability and in vitro liver enzyme metabolic stability rates.

机译:通过其Caco-2渗透性和体外肝酶代谢稳定率估算药物在人和其他物种中的口服生物利用度的图形模型。

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摘要

This paper describes a graphical model for simplifying in vitro absorption, metabolism, distribution, and elimination (ADME) data analysis through the estimation of oral bioavailability (%F) of drugs in humans and other species. This model integrates existing in vitro ADME data, such as Caco-2 permeability (P(app)) and metabolic stability (percent remaining - %R) in liver S9 or microsomes, to estimate %F into groups of low, medium, or high regions. To test the predictive accuracy of our model, we examined 21 drugs and drug candidates with a wide range of oral bioavailability values, which represent approximately 10 different therapeutic areas in humans, rats, dogs, and guinea pigs. In vitro data from model compounds were used to define the boundaries of the low, medium, and high regions of the %F estimation plot. On the basis of the in vitro data, warfarin (93%), indomethacin (98%), timolol (50%), and carbamazepine (70%) were assigned to the high %F region; propranolol (26%) and metoprolol (38%) to medium %F region; and verapamil (22%) and mannitol (18%) to the low %F region. Similarly, the %F of 11 drug candidates from Elastase Inhibitor, NK1/NK2 antagonist, and anti-viral projects in rats, guinea pigs, and dogs were correctly estimated. This model estimates the oral bioavailability ranges of neutral, polar, esters, acidic, and basic drugs in all species. For a large number of drug candidates, this graphical model provides a tool to estimate human oral bioavailability from in vitro ADME data. When combined with the high throughput in vitro ADME screening process, it has the potential to significantly accelerate the processes of lead identification and optimization.
机译:本文介绍了一种图形模型,用于通过估计人类和其他物种药物的口服生物利用度(%F)来简化体外吸收,代谢,分布和消除(ADME)数据分析。该模型整合了现有的体外ADME数据,例如肝S9或微粒体中的Caco-2渗透性(P(app))和代谢稳定性(剩余百分比-%R),以将%F估计为低,中或高组地区。为了测试模型的预测准确性,我们检查了21种具有广泛口服生物利用度值的药物和候选药物,这些药物分别代表人,大鼠,狗和豚鼠的10个不同治疗领域。来自模型化合物的体外数据用于定义%F估计图的低,中和高区域的边界。根据体外数据,华法林(93%),消炎痛(98%),噻吗洛尔(50%)和卡马西平(70%)被分配到高%F区;普萘洛尔(26%)和美托洛尔(38%)至中等%F区域;维拉帕米(22%)和甘露醇(18%)到低%F区域。同样,正确估计了来自弹性蛋白酶抑制剂,NK1 / NK2拮抗剂和抗病毒项目在大鼠,豚鼠和狗中的11种候选药物的%F。该模型估算了所有物种中中性,极性,酯类,酸性和碱性药物的口服生物利用度范围。对于大量候选药物,此图形模型提供了一种工具,可根据体外ADME数据估算人类口服生物利用度。当与高通量体外ADME筛选过程结合使用时,它有可能显着加速潜在客户识别和优化过程。

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