《生命科学》 2026, 38(2): 221-235

人工智能与多学科融合驱动的生命科学仪器创新

袁银池¹ , 王立伟² , 张爱平¹ , 周 赛¹ , 张丽雯¹ , 陈 赟¹ , 陆 娇^1,* , 张 宇^3,*

¹中国科学院上海生命科学信息中心，中国科学院上海营养与健康研究所，上海 200031 ²上海市科学学 研究所，上海 200031 ³国科大杭州高等研究院生命与健康科学学院，中国科学院大学，杭州 310024

摘　要：

2025年，生命科学仪器领域正经历一场由人工智能、多组学技术与先进制造深度融合所驱动的结构性变革。在此进程中，仪器不再仅作为被动的数据采集工具或实验辅助装置，而是跃升为定义科学边界、重构研究范式并引领产业转型的关键基础设施。这一转变的核心在于技术体系的系统性重构：一方面，观测能力持续逼近物理极限，超分辨成像、无标记检测、单分子追踪及高时空分辨率等前沿手段，使生命过程的研究从静态群体表征迈向动态个体解析；另一方面，关键装备的自主创新取得实质性突破，国产冷冻电镜、质谱仪与超高通量测序平台逐步实现从整机集成到核心元器件自主可控的纵深演进，显著提升产业链安全与技术主权。尤为关键的是，人工智能已深度嵌入仪器全生命周期——从光学与流体系统的设计优化，到实时运行调控，再到多模态数据的语义理解与知识生成，AI正推动“无人实验室”等新型科研组织形态成为现实。与此同时，仪器应用场景亦发生根本性拓展，从传统基础研究延伸至精准医疗、高通量药物筛选、合成生物学及现场快速检测等多元场域，形成科研—临床—产业的闭环联动。在显微成像、单分子分析、空间组学、质谱与色谱联用、流式细胞术及多功能集成平台等方向，一系列标志性技术与产品相继涌现，不仅加速了生命机制的解码进程，也为普惠化、智能化和自主化的下一代生命科学仪器体系奠定了坚实基础。

通讯作者：陆 娇 , Email:jlu@sinh.ac.cn 张 宇 , Email:zy@ucas.ac.cn

Innovation in life science instruments driven by artificial intelligence and interdisciplinary integration

YUAN Yin-Chi¹ , WANG Li-Wei² , ZHANG Ai-Ping¹ , ZHOU Sai¹ , ZHANG Li-Wen¹ , CHEN Yun¹ , LU Jiao^1,* , ZHANG Yu^3,*

¹Shanghai Information Center for Life Sciences, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai 200031, China ²Shanghai Institute for Science of Science, Shanghai 200031, China ³School of Life Science, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou 310024, China

Abstract:

In 2025, the field of life science instrumentation is undergoing a structural transformation driven by the deep integration of artificial intelligence (AI), multi-omics technologies, and advanced manufacturing. Instruments are no longer passive data collectors or auxiliary tools but have evolved into critical infrastructures that actively define scientific frontiers, reshape research paradigms, and catalyze industrial transformation. This shift is underpinned by a systemic reconfiguration of technological capabilities. On one hand, observational limits continue to approach fundamental physical boundaries: nextgeneration modalities—such as super-resolution imaging, label-free detection, single-molecule tracking, and high spatiotemporal resolution—are enabling a transition from static, population-level analyses to dynamic, molecule-resolved interrogation of biological processes. On the other hand, substantial progress has been made in indigenous innovation of core instrumentation; domestical cryo-electron microscopes, mass spectrometers, and ultra-high-throughput sequencers are advancing beyond system-level assembly toward end-to-end autonomy in key components, thereby strengthening technological sovereignty and supply chain resilience. Crucially, AI has become deeply embedded throughout the instrument lifecycle—from optical and fluidic system design, real-time operational control, to semantic interpretation and knowledge extraction from multimodal data—enabling emergent paradigms such as autonomous laboratories. Concurrently, application domains are expanding dramatically, with cutting-edge instruments now bridging fundamental research with clinical diagnostics, high-throughput drug discovery, synthetic biology, and point-of-need testing, thus forging an integrated loop across academia, medicine, and industry. Breakthroughs in microscopy, single-molecule analytics, spatial omics, hyphenated mass and chromatographic techniques, flow cytometry, and multifunctional integrated platforms, are not only accelerating the decoding of biological mechanisms, but also laying the foundation for a new generation of life science instruments characterized by greater intelligence, integration, accessibility, and autonomy.

Communication Author：LU Jiao , Email:jlu@sinh.ac.cn ZHANG Yu , Email:zy@ucas.ac.cn