• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

假设驱动的药物设计:提高设计-制造-测试-分析循环的质量和效果。

Hypothesis driven drug design: improving quality and effectiveness of the design-make-test-analyse cycle.

机构信息

Cardiovascular and GastroIntestinal Research Area, AstraZeneca R&D Mölndal, SE-43183 Mölndal, Sweden.

出版信息

Drug Discov Today. 2012 Jan;17(1-2):56-62. doi: 10.1016/j.drudis.2011.09.012. Epub 2011 Sep 22.

DOI:10.1016/j.drudis.2011.09.012
PMID:21963616
Abstract

In drug discovery, the central process of constructing and testing hypotheses, carefully conducting experiments and analysing the associated data for new findings and information is known as the design-make-test-analyse cycle. Each step relies heavily on the inputs and outputs of the other three components. In this article we report our efforts to improve and integrate all parts to enable smooth and rapid flow of high quality ideas. Key improvements include enhancing multi-disciplinary input into 'Design', increasing the use of knowledge and reducing cycle times in 'Make', providing parallel sets of relevant data within ten working days in 'Test' and maximising the learning in 'Analyse'.

摘要

在药物研发中,构建和检验假说、精心开展实验以及分析相关数据以发现新发现和信息的核心过程被称为设计-制作-测试-分析循环。每个步骤都严重依赖于其他三个组件的输入和输出。在本文中,我们报告了我们为改进和整合所有部分以实现高质量想法的顺畅和快速流动所做的努力。主要改进包括增强“设计”的多学科投入,增加“制作”中知识的使用并减少循环时间,在“测试”中提供十日内相关数据的平行集,并最大限度地利用“分析”中的学习。

相似文献

1
Hypothesis driven drug design: improving quality and effectiveness of the design-make-test-analyse cycle.假设驱动的药物设计:提高设计-制造-测试-分析循环的质量和效果。
Drug Discov Today. 2012 Jan;17(1-2):56-62. doi: 10.1016/j.drudis.2011.09.012. Epub 2011 Sep 22.
2
Knowledge-based chemoinformatic approaches to drug discovery.基于知识的药物发现化学信息学方法。
Drug Discov Today. 2006 Dec;11(23-24):1107-14. doi: 10.1016/j.drudis.2006.10.012. Epub 2006 Nov 2.
3
The impact of parallel chemistry in drug discovery.平行化学在药物发现中的影响。
IDrugs. 2006 May;9(5):347-53.
4
[Clinical-pharmacological aspects to accelerate the development process from the preclinical to the clinical phase/1st communication: The contribution of clinical pharmacology].[加速从临床前到临床阶段开发进程的临床药理学方面/首次交流:临床药理学的贡献]
Arzneimittelforschung. 2004;54(5):251-8. doi: 10.1055/s-0031-1296967.
5
Improving drug safety using computational biology.利用计算生物学提高药物安全性。
IDrugs. 2010 Feb;13(2):85-9.
6
Making medicinal chemistry more effective--application of Lean Sigma to improve processes, speed and quality.使药物化学更有效——应用精益西格玛改进流程、提高速度和质量。
Drug Discov Today. 2009 Jun;14(11-12):598-604. doi: 10.1016/j.drudis.2009.03.005. Epub 2009 Mar 11.
7
Better compounds faster: the development and exploitation of a desktop predictive chemistry toolkit.更快地得到更好的化合物:桌面预测化学工具包的开发和利用。
Drug Discov Today. 2012 Sep;17(17-18):923-7. doi: 10.1016/j.drudis.2012.03.003. Epub 2012 Mar 22.
8
New approaches to drug discovery and development: a mechanism-based approach to pharmaceutical research and its application to BNP7787, a novel chemoprotective agent.药物发现与开发的新方法:基于机制的药物研究方法及其在新型化学保护剂BNP7787中的应用。
Cancer Chemother Pharmacol. 2003 Jul;52 Suppl 1:S3-15. doi: 10.1007/s00280-003-0653-5. Epub 2003 Jun 18.
9
In silico prediction of ADME properties: are we making progress?药物代谢动力学(ADME)性质的计算机模拟预测:我们有进展吗?
Curr Opin Drug Discov Devel. 2004 Jan;7(1):36-42.
10
[Development of antituberculous drugs: current status and future prospects].[抗结核药物的研发:现状与未来前景]
Kekkaku. 2006 Dec;81(12):753-74.

引用本文的文献

1
Data-driven recommendation of agents, temperature, and equivalence ratios for organic synthesis.基于数据驱动的有机合成试剂、温度和当量比推荐
Chem Sci. 2025 Sep 5. doi: 10.1039/d5sc04957a.
2
Macromolecular crystallography from an industrial perspective - the impact of synchrotron radiation on structure-based drug discovery.从工业角度看大分子晶体学——同步辐射对基于结构的药物发现的影响。
J Synchrotron Radiat. 2025 Mar 1;32(Pt 2):294-303. doi: 10.1107/S1600577524012281. Epub 2025 Feb 6.
3
How Should we Teach Medicinal Chemistry in Higher Education to Prepare Students for a Future Career as Medicinal Chemists and Drug Designers? - A Teacher's Perspective.
在高等教育中,我们应如何教授药物化学,以使学生为未来成为药物化学家和药物设计师做好准备?——一位教师的视角
ChemMedChem. 2025 Jan 14;20(2):e202400791. doi: 10.1002/cmdc.202400791. Epub 2024 Nov 20.
4
Investigation of acetyl-CoA carboxylase-inhibiting herbicides that exhibit soybean crop selectivity.对表现出大豆作物选择性的乙酰辅酶A羧化酶抑制型除草剂的研究。
Pest Manag Sci. 2025 May;81(5):2511-2521. doi: 10.1002/ps.8469. Epub 2024 Oct 12.
5
Step Forward Cross Validation for Bioactivity Prediction: Out of Distribution Validation in Drug Discovery.用于生物活性预测的向前交叉验证:药物发现中的分布外验证
bioRxiv. 2024 Jul 4:2024.07.02.601740. doi: 10.1101/2024.07.02.601740.
6
Improved Detection of Drug-Induced Liver Injury by Integrating Predicted and Data.整合预测和数据可提高药物性肝损伤的检测率。
Chem Res Toxicol. 2024 Aug 19;37(8):1290-1305. doi: 10.1021/acs.chemrestox.4c00015. Epub 2024 Jul 9.
7
Improved Detection of Drug-Induced Liver Injury by Integrating Predicted and Data.通过整合预测数据和实际数据改进药物性肝损伤的检测
bioRxiv. 2024 Jun 8:2024.01.10.575128. doi: 10.1101/2024.01.10.575128.
8
DrugGym: A testbed for the economics of autonomous drug discovery.DrugGym:自主药物研发经济学的试验平台。
bioRxiv. 2024 Jun 2:2024.05.28.596296. doi: 10.1101/2024.05.28.596296.
9
AiZynth impact on medicinal chemistry practice at AstraZeneca.爱生特(AiZynth)对阿斯利康药物化学实践的影响。
RSC Med Chem. 2024 Feb 16;15(4):1085-1095. doi: 10.1039/d3md00651d. eCollection 2024 Apr 24.
10
Cheminformatics and artificial intelligence for accelerating agrochemical discovery.用于加速农用化学品发现的化学信息学与人工智能
Front Chem. 2023 Nov 29;11:1292027. doi: 10.3389/fchem.2023.1292027. eCollection 2023.