Lee Yubeen, Haizan Izzati, Sim Sang Baek, Choi Jin-Ha
School of Chemical Engineering, Clean Energy Research Center, Jeonbuk National University, 567 Baekje-daero, Deokjin-gu, Jeonju-si 54896, Jeonbuk State, Republic of Korea.
Biosensors (Basel). 2025 Jun 5;15(6):362. doi: 10.3390/bios15060362.
Colorimetric-based biosensors are practical detection devices that can detect the presence and concentration of biomarkers through simple color changes. Conventional laboratory-based tests are highly sensitive but require long processing times and expensive equipment, which makes them difficult to apply for on-site diagnostics. In contrast, the colorimetric method offers advantages for point-of-care testing and real-time monitoring due to its flexibility, simple operation, rapid results, and versatility across many applications. In order to enhance the color change reactions in colorimetric techniques, functional nanomaterials are often integrated due to their desirable intrinsic properties. In this review, the working principles of nanomaterial-based detection strategies in colorimetric systems are introduced. In addition, current signal amplification methods for colorimetric biosensors are comprehensively outlined and evaluated. Finally, the latest trends in artificial intelligence (AI) and machine learning integration into colorimetric-based biosensors, including their potential for technological advancements in the near future, are discussed. Future research is expected to develop highly sensitive and multifunctional colorimetric methods, which will serve as powerful alternatives for point-of-care testing and self-testing.
基于比色法的生物传感器是实用的检测设备，可通过简单的颜色变化检测生物标志物的存在和浓度。传统的基于实验室的检测方法灵敏度很高，但需要较长的处理时间和昂贵的设备，这使得它们难以应用于现场诊断。相比之下，比色法因其灵活性、操作简单、结果快速以及在许多应用中的通用性，为即时检测和实时监测提供了优势。为了增强比色技术中的颜色变化反应，功能性纳米材料因其理想的固有特性常被整合进来。在这篇综述中，介绍了比色系统中基于纳米材料的检测策略的工作原理。此外，对比色生物传感器当前的信号放大方法进行了全面概述和评估。最后，讨论了人工智能（AI）和机器学习集成到基于比色法的生物传感器中的最新趋势，包括它们在不久的将来实现技术进步的潜力。未来的研究有望开发出高灵敏度和多功能的比色法，这将成为即时检测和自我检测的有力替代方法。
