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如何在药物发现的先导优化早期阶段识别和消除具有高临床剂量风险的化合物。

How to identify and eliminate compounds with a risk of high clinical dose during the early phase of lead optimisation in drug discovery.

机构信息

GlaxoSmithKline Medicine Research Centre, Stevenage, Hertfordshire, UK.

Research Department of Pharmaceutical and Biological Chemistry, UCL School of Pharmacy, London, UK.

出版信息

Eur J Pharm Sci. 2017 Dec 15;110:37-50. doi: 10.1016/j.ejps.2017.02.017. Epub 2017 Feb 12.

DOI:10.1016/j.ejps.2017.02.017
PMID:28215942
Abstract

An alternative approach has been developed to estimate the clinical dose of new drug molecules at an early stage in the drug discovery process. This approach has been compared to traditional methods using the clinical dose as indicated on the drug label of 136 marketed drugs. At the early stages of drug discovery only in silico predictions or some initial in vitro screening data are normally available, typically parameters such as affinity/potency (pXC50)from isolated enzymes or receptors, measured albumin and phospholipid binding using biomimetic HPLC measurements, and in vitro clearance using P450 enzymes or liver microsomes. The combination of the biomimetic HPLC phospholipid and protein binding provides a drug efficiency max parameter described previously (HPLC DE), and in vitro potency makes it possible to estimate a clinical dose that would result in an efficacious steady state free concentration at the site of action. The influence of the potential discrepancies between the in vitro and a later stage in vivo DE, the whole blood potency, volume of distribution and clearance on the dose estimation has been investigated, using data from a GSK programme profiled during lead optimisation. It was found that drug potency had the greatest influence on estimating the clinical dose. When the estimated dose is low, the impact of other parameters such as the volume of distribution and clearance was much less significant and typically did not affect compound ranking.

摘要

已经开发出一种替代方法来估算新药分子在药物发现过程早期的临床剂量。该方法已通过将 136 种市售药物的药物标签上标明的临床剂量与传统方法进行了比较。在药物发现的早期阶段,通常只能获得基于计算机的预测或一些初步的体外筛选数据,通常是诸如从分离的酶或受体测量的亲和力/效价(pXC50)、使用仿生 HPLC 测量法测量白蛋白和磷脂结合、以及使用 P450 酶或肝微粒体进行体外清除等参数。仿生 HPLC 磷脂和蛋白质结合的组合提供了先前描述的药物效率最大值参数(HPLC DE),并且体外效价使得可以估算出在作用部位产生有效稳态游离浓度的临床剂量。使用在先导优化过程中对 GSK 计划进行的 profiling 获得的数据,研究了在体外和以后的体内 DE、全血效价、分布体积和清除率之间的潜在差异对剂量估算的影响。结果发现,药物效价对估算临床剂量的影响最大。当估计的剂量较低时,分布体积和清除率等其他参数的影响要小得多,通常不会影响化合物的排序。

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