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MicroCycle: An Integrated and Automated Platform to Accelerate Drug Discovery
Journal of Medicinal Chemistry ( IF 6.8 ) Pub Date : 2024-01-25 , DOI: 10.1021/acs.jmedchem.3c02029
Cara E Brocklehurst 1 , Eva Altmann 1 , Corentin Bon 1 , Holly Davis 1 , David Dunstan 2 , Peter Ertl 1 , Carol Ginsburg-Moraff 2 , Jonathan Grob 2 , Daniel J Gosling 1 , Guillaume Lapointe 1 , Alexander N Marziale 1 , Heinrich Mues 1 , Marco Palmieri 1 , Sophie Racine 1 , Richard I Robinson 2 , Clayton Springer 2 , Kian Tan 2 , William Ulmer 2 , René Wyler 1
Journal of Medicinal Chemistry ( IF 6.8 ) Pub Date : 2024-01-25 , DOI: 10.1021/acs.jmedchem.3c02029
Cara E Brocklehurst 1 , Eva Altmann 1 , Corentin Bon 1 , Holly Davis 1 , David Dunstan 2 , Peter Ertl 1 , Carol Ginsburg-Moraff 2 , Jonathan Grob 2 , Daniel J Gosling 1 , Guillaume Lapointe 1 , Alexander N Marziale 1 , Heinrich Mues 1 , Marco Palmieri 1 , Sophie Racine 1 , Richard I Robinson 2 , Clayton Springer 2 , Kian Tan 2 , William Ulmer 2 , René Wyler 1
Affiliation
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We herein describe the development and application of a modular technology platform which incorporates recent advances in plate-based microscale chemistry, automated purification, in situ quantification, and robotic liquid handling to enable rapid access to high-quality chemical matter already formatted for assays. In using microscale chemistry and thus consuming minimal chemical matter, the platform is not only efficient but also follows green chemistry principles. By reorienting existing high-throughput assay technology, the platform can generate a full package of relevant data on each set of compounds in every learning cycle. The multiparameter exploration of chemical and property space is hereby driven by active learning models. The enhanced compound optimization process is generating knowledge for drug discovery projects in a time frame never before possible.
中文翻译:
MicroCycle:加速药物发现的集成自动化平台
我们在此描述了模块化技术平台的开发和应用,该平台融合了基于板的微量化学、自动纯化、原位定量和机器人液体处理方面的最新进展,能够快速获取已格式化用于分析的高质量化学物质。该平台使用微尺度化学,消耗最少的化学物质,不仅高效,而且遵循绿色化学原则。通过重新定位现有的高通量检测技术,该平台可以在每个学习周期中生成每组化合物的完整相关数据包。因此,化学和属性空间的多参数探索是由主动学习模型驱动的。增强的化合物优化过程正在以前所未有的时间范围为药物发现项目生成知识。
更新日期:2024-01-25
中文翻译:
![](https://scdn.x-mol.com/jcss/images/paperTranslation.png)
MicroCycle:加速药物发现的集成自动化平台
我们在此描述了模块化技术平台的开发和应用,该平台融合了基于板的微量化学、自动纯化、原位定量和机器人液体处理方面的最新进展,能够快速获取已格式化用于分析的高质量化学物质。该平台使用微尺度化学,消耗最少的化学物质,不仅高效,而且遵循绿色化学原则。通过重新定位现有的高通量检测技术,该平台可以在每个学习周期中生成每组化合物的完整相关数据包。因此,化学和属性空间的多参数探索是由主动学习模型驱动的。增强的化合物优化过程正在以前所未有的时间范围为药物发现项目生成知识。