Accelerating compound synthesis in drug discovery: the role of digitalisation and automation

IF 3.6 4区 医学 Q2 BIOCHEMISTRY & MOLECULAR BIOLOGY
David F. Nippa, Alexander J. Boddy, Kenneth Atz, Uwe Grether, Hayley Binch and Rainer E. Martin
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引用次数: 0

Abstract

The Design-Make-Test-Analyse (DMTA) cycle relies on efficient compound synthesis, yet the synthesis (“Make”) process remains a significant bottleneck, especially for complex molecules. This opinion letter explores how digitalisation and automation are accelerating the entire synthesis process. It details their current integration, from AI-powered synthesis planning and streamlined sourcing to automated reaction setup, monitoring, purification, and characterisation. FAIR data principles are emphasised as crucial for building robust predictive models and enabling interconnected workflows. Finally, the future of fully integrated, data-driven synthesis with tools like “Chemical ChatBots” and the evolving skill set required for medicinal chemists in this increasingly digital and automated landscape are discussed.

Abstract Image

加速药物发现中的化合物合成:数字化和自动化的作用。
设计-制造-测试-分析(DMTA)循环依赖于高效的化合物合成,但合成(“制造”)过程仍然是一个重要的瓶颈,特别是对于复杂分子。这封意见信探讨了数字化和自动化如何加速整个合成过程。它详细介绍了他们目前的集成,从人工智能驱动的合成计划和简化的采购到自动化反应设置、监测、纯化和表征。FAIR数据原则被强调为构建稳健的预测模型和实现相互关联的工作流程的关键。最后,讨论了未来完全集成的、数据驱动的合成工具,如“化学聊天机器人”,以及在这个日益数字化和自动化的环境中,药物化学家所需的不断发展的技能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
5.80
自引率
2.40%
发文量
129
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