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Methodologies to assess brain drug delivery in lead optimization.

机译:评估铅优化中脑部药物输送的方法。

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摘要

In the area of lead optimization for potential CNS-active drugs in medicinal chemistry, there is a great need for experimental methodologies that can generate data relevant to estimates of free (unbound) drug exposure within the CNS. The methods chosen have to be efficient and have to measure a pharmacologically relevant entity. The lack of methods for generating such data is probably linked with the lack of successful lead optimization strategies within CNS drug discovery. This article evaluates available methods for estimating drug delivery to the brain, and discusses the relevance of the methods from the perspective of CNS exposure to free drug. It is suggested that the extent of drug delivery is the most important investigative parameter, since permeability (rate of transfer) can vary within a relatively wide range and still allow effects within the CNS. Following this suggestion would shift the focus from the current way of thinking and could lead to the development of less lipophilic compounds than are currently being investigated. It is concluded that an extensive collection of quality data on brain drug delivery, transporter affinities and in vivo behavior is urgently required so as to be able to build relevant predictive in vitro and in silico models for the future. These models need to be much more focused on the asymmetry of active transport across the BBB than on permeability data.
机译:在药物化学中潜在的中枢神经系统活性药物的铅优化领域中,非常需要能够生成与中枢神经系统中自由(未结合)药物暴露量估计有关的数据的实验方法。选择的方法必须有效并且必须测量药理上相关的实体。缺乏生成此类数据的方法可能与中枢神经系统药物发现中缺乏成功的铅优化策略有关。本文评估了估计向大脑输送药物的可用方法,并从中枢神经系统暴露于游离药物的角度讨论了这些方法的相关性。由于药物的渗透性(转移率)可以在相对较宽的范围内变化,并且仍能在中枢神经系统内发挥作用,因此,药物的输送程度是最重要的研究参数。遵循这一建议将把重点从当前的思维方式转移到其他地方,并导致开发出比目前正在研究的更少的亲脂性化合物。结论是,迫切需要广泛收集有关脑药物递送,转运蛋白亲和力和体内行为的质量数据,以便能够建立相关的体外和计算机模拟预测模型。这些模型需要更加关注跨BBB的主动传输的不对称性,而不是渗透率数据。

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