期刊文献+

智能高通量筛选技术加速医药小分子合成

Autonomous high-throughput screening technology for accelerating drug molecule discovery and synthesis
原文传递
导出
摘要 医药小分子的发现与合成是新药研发过程中重要的决速步之一,而基于传统人工的小分子设计与合成方法已经逐渐难以满足现代人类社会对新型药物分子的迭代与开发速度的需要.近期涌现出来的化学人工智能与高通量筛选技术是突破传统研发效率瓶颈的新方向,本评述将从智能化学筛选装置出发,着重讨论利用人工智能决策算法驱动自动化高通量筛选装置的发展现状,主要包括:(1)高通量筛选装置技术.综述批式与流式两类主流高通量筛选装置形式,并讨论强化筛选反应的化工强化手段与适配于高通量反应的分析表征技术.(2)驱动高通量筛选的智能决策算法.概述驱动自动化装置实现智能自主探索目标性质优化与高质量实验数据产生的自主决策算法.最后对未来智能高通量筛选技术如何进一步发展以加速医药小分子合成展开了讨论. The discovery and synthesis of pharmaceutical small molecules is one of the important decisive steps in the process of new drug research and development.The traditional small molecule design and synthesis methods,however,is becoming increasingly difficult to meet the iteration and development speed of new drug molecules in modern human society.The recent emergence of chemical artificial intelligence and high-throughput screening(HTS)technology is a new direction to break through the bottleneck of traditional research and development efficiency.This review will focus on the development status of automatic HTS device driven by artificial intelligence decision algorithm,mainly including:(1)High-throughput screening device technology.Batch and flow HTS modes,reaction process intensification for HTS screening,and the analytical characterization technology for HTS are discussed.(2)Intelligent decision-making algorithm for driving HTS,discussing the autonomous decision algorithms for driving the automation device to realize intelligent autonomous exploration,target property optimization and high-quality experimental data generation.Finally,this review will discuss how to further develop intelligent HTS technology to accelerate the synthesis of pharmaceutical molecules in the future.
作者 陈杰 郑娴 阮怡翔 莫一鸣 Jie Chen;Xian Zheng;Yixiang Ruan;Yiming Mo(College of Chemical and Biological Engineering,Zhejiang University,Hangzhou 310063,China;ZJU-Hangzhou Global Scientific and Technological Innovation Center,Hangzhou 311215,China)
出处 《中国科学:化学》 CAS CSCD 北大核心 2023年第1期79-94,共16页 SCIENTIA SINICA Chimica
基金 国家科技部重点研发计划(编号:2021YFA1502700) 国家自然科学基金(编号:22108242)资助项目。
关键词 高通量筛选 智能决策算法 医药小分子 大数据 high-throughput screening artificial intelligence drug discovery big data
  • 相关文献

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部