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: next-generation 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.
Yuan et al. (2026) studied this question.