Suppr超能文献

早期药物发现中的安全性筛选:优化的检测组合

Safety screening in early drug discovery: An optimized assay panel.

作者信息

Bendels Stefanie, Bissantz Caterina, Fasching Bernhard, Gerebtzoff Grégori, Guba Wolfgang, Kansy Manfred, Migeon Jacques, Mohr Susanne, Peters Jens-Uwe, Tillier Fabien, Wyler René, Lerner Christian, Kramer Christian, Richter Hans, Roberts Sonia

机构信息

Roche Pharma Research and Early Development, Pharmaceutical Sciences, Roche Innovation Center Basel, Switzerland.

Eurofins Cerep Panlabs, Le bois l'Evêque, 86600 Celle L'Evescault, France.

出版信息

J Pharmacol Toxicol Methods. 2019 Sep-Oct;99:106609. doi: 10.1016/j.vascn.2019.106609. Epub 2019 Jul 5.

Abstract

BACKGROUND

Several factors contribute to the development failure of novel pharmaceuticals, one of the most important being adverse effects in pre-clinical and clinical studies. Early identification of off-target compound activity can reduce safety-related attrition in development. In vitro profiling of drug candidates against a broad range of targets is an important part of the compound selection process. Many compounds are synthesized during early drug discovery, making it necessary to assess poly-pharmacology at a limited number of targets. This paper describes how a rational, statistical-ranking approach was used to generate a cost-effective, optimized panel of assays that allows selectivity focused structure-activity relationships to be explored for many molecules. This panel of 50 targets has been used to routinely screen Roche small molecules generated across a diverse range of therapeutic targets. Target hit rates from the Bioprint® database and internal Roche compounds are discussed. We further describe an example of how this panel was used within an anti-infective project to reduce in vivo testing.

METHOD

To select the optimized panel of targets, IC values of compounds in the BioPrint® database were used to identify assay "hits" i.e. IC ≤ 1 μM in 123 different in vitro pharmacological assays. If groups of compounds hit the same targets, the target with the higher hit rate was selected, while others were considered redundant. Using a step-wise analysis, an assay panel was identified to maximize diversity and minimize redundancy. Over a five-year period, this panel of 50 off-targets was used to screen ≈1200 compounds synthesized for Roche drug discovery programs. Compounds were initially tested at 10 μM and hit rates generated are reported. Within one project, the number of hits was used to refine the choice of compounds being assessed in vivo.

RESULTS

95% of compounds from the BioPrint® panel were identified within the top 47-ranked assays. Based on this analytical approach and the addition of three targets with established safety concerns, a Roche panel was created for external screening. hERG is screened internally and not included in this analysis. Screening at 10 μM in the Roche panel identified that adenosine A and 5HT receptors had the highest hit rates (~30%), with 50% of the targets having a hit rate of ≤4%. An anti-infective program identified that a high number of hits in the Roche panel was associated with mortality in 19 mouse tolerability studies. To reduce the severity and number of such studies, future compound selections integrated the panel hit score into the selection process for in vivo studies. It was identified that compounds which hit less targets in the panel and had free plasma exposures of ~2 μM were generally better tolerated.

DISCUSSION

This paper describes how an optimized panel of 50 assays was selected on the basis of hit similarity at 123 targets. This reduced panel, provides a cost-effective screening panel for assessing compound promiscuity, whilst also including many safety-relevant targets. Frequent use of the panel in early drug discovery has provided promiscuity and safety-relevant information to inform pre-clinical drug development at Roche.

摘要

背景

多种因素导致新型药物研发失败,其中最重要的因素之一是临床前和临床研究中的不良反应。早期识别脱靶化合物活性可减少研发中与安全性相关的损耗。针对广泛靶点对候选药物进行体外分析是化合物筛选过程的重要组成部分。在药物早期发现阶段会合成许多化合物,因此有必要在有限数量的靶点上评估多药理学特性。本文描述了如何使用一种合理的统计排序方法来生成一个具有成本效益的优化分析组合,该组合可用于探索许多分子的选择性聚焦构效关系。这个包含50个靶点的分析组合已用于常规筛选罗氏公司针对各种治疗靶点生成的小分子。讨论了来自Bioprint®数据库和罗氏内部化合物的靶点命中率。我们还进一步描述了该分析组合如何在一个抗感染项目中用于减少体内试验的实例。

方法

为了选择优化的靶点分析组合,利用Bioprint®数据库中化合物的IC值来识别分析“命中”情况,即在123种不同的体外药理分析中IC≤1μM。如果几组化合物命中相同的靶点,则选择命中率较高的靶点,而其他靶点则被视为冗余。通过逐步分析,确定了一个分析组合,以最大限度地提高多样性并最小化冗余。在五年时间里,这个包含50个脱靶靶点的分析组合用于筛选为罗氏药物发现项目合成的约1200种化合物。化合物最初在10μM浓度下进行测试,并报告产生的命中率。在一个项目中,命中次数用于优化体内评估化合物的选择。

结果

来自Bioprint®分析组合的95%的化合物在排名前47的分析中被识别出来。基于这种分析方法并增加了三个存在既定安全问题的靶点,创建了一个用于外部筛选的罗氏分析组合。hERG在内部进行筛选,不包括在本分析中。在罗氏分析组合中以10μM浓度进行筛选发现,腺苷A和5HT受体的命中率最高(约30%),50%的靶点命中率≤4%。一个抗感染项目发现,罗氏分析组合中的大量命中与19项小鼠耐受性研究中的死亡率相关。为了降低此类研究的严重性和数量,未来的化合物选择将分析组合命中分数纳入体内研究的选择过程。结果发现,在分析组合中命中靶点较少且游离血浆暴露量约为2μM的化合物通常耐受性更好。

讨论

本文描述了如何基于123个靶点的命中相似性选择一个包含50种分析的优化分析组合。这个精简后的分析组合为评估化合物的多配体性提供了一个具有成本效益的筛选组合,同时还包括许多与安全性相关的靶点。在药物早期发现中频繁使用该分析组合为罗氏公司的临床前药物开发提供了多配体性和与安全性相关的信息。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验