Safety screening in early drug discovery: An optimized assay panel

药物发现 药品 药物开发 计算生物学 数据挖掘 计算机科学 药理学 医学 生物信息学 生物
作者
Stefanie Bendels,Caterina Bissantz,Bernhard Fasching,Grégori Gerebtzoff,Wolfgang Guba,Manfred Kansy,Jacques Migeon,Susanne Mohr,Jens‐Uwe Peters,Fabien Tillier,R. Wyler,C. Lerner,Christian Krämer,Hans Richter,Sonia Roberts
出处
期刊:Journal of Pharmacological and Toxicological Methods [Elsevier BV]
卷期号:99: 106609-106609 被引量:73
标识
DOI:10.1016/j.vascn.2019.106609
摘要

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. To select the optimized panel of targets, IC50 values of compounds in the BioPrint® database were used to identify assay “hits” i.e. IC50 ≤ 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. 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 A3 and 5HT2B 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. 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.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
刚刚
NexusExplorer应助贪玩正豪采纳,获得10
1秒前
2秒前
3秒前
elle发布了新的文献求助10
3秒前
李健的小迷弟应助xuanxuan采纳,获得10
6秒前
爱笑若冰发布了新的文献求助10
8秒前
9秒前
落寞的虔完成签到,获得积分10
10秒前
丫头完成签到,获得积分10
12秒前
12秒前
阔达的秀发完成签到,获得积分10
13秒前
Gab_bb发布了新的文献求助10
13秒前
Fantastic完成签到,获得积分10
13秒前
落涙翼完成签到,获得积分10
14秒前
14秒前
15秒前
aliu完成签到,获得积分10
16秒前
迅速雨文完成签到,获得积分10
16秒前
17秒前
19秒前
19秒前
StuXuhao发布了新的文献求助10
21秒前
22秒前
李爱国应助科研通管家采纳,获得10
22秒前
you完成签到,获得积分20
22秒前
搜集达人应助科研通管家采纳,获得10
22秒前
22秒前
22秒前
Hello应助科研通管家采纳,获得10
22秒前
Hello应助科研通管家采纳,获得10
22秒前
木头人应助科研通管家采纳,获得10
23秒前
无花果应助科研通管家采纳,获得10
23秒前
木头人应助科研通管家采纳,获得10
23秒前
研友_VZG7GZ应助科研通管家采纳,获得10
23秒前
英姑应助科研通管家采纳,获得10
23秒前
贪玩正豪发布了新的文献求助10
23秒前
23秒前
彭于晏应助科研通管家采纳,获得10
23秒前
23秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Chemistry and Physics of Carbon Volume 18 800
The Organometallic Chemistry of the Transition Metals 800
The formation of Australian attitudes towards China, 1918-1941 640
Signals, Systems, and Signal Processing 610
全相对论原子结构与含时波包动力学的理论研究--清华大学 500
Elevating Next Generation Genomic Science and Technology using Machine Learning in the Healthcare Industry Applied Machine Learning for IoT and Data Analytics 400
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 物理 内科学 复合材料 催化作用 物理化学 光电子学 电极 细胞生物学 基因 无机化学
热门帖子
关注 科研通微信公众号,转发送积分 6443509
求助须知:如何正确求助?哪些是违规求助? 8257373
关于积分的说明 17586403
捐赠科研通 5502108
什么是DOI,文献DOI怎么找? 2900906
邀请新用户注册赠送积分活动 1877940
关于科研通互助平台的介绍 1717534