Microfluidic technology plays a crucial role in organ-on-a-chip (OoC) systems by replicating human physiological processes and disease states, significantly advancing biomedical research and drug discovery. This article reviews the design and fabrication processes of microfluidic devices. It also explores how these technologies are integrated into OoC platforms to simulate human physiological environments, highlighting key principles, technological advances, and diverse applications. Through case studies involving the simulation of multiple organs such as the heart, liver, and lungs, the article evaluates the impact of OoC systems’ integrated microfluidic technology on drug screening, toxicity assessment, and personalized medicine. In addition, this article considers technical challenges, ethical issues, and future directions, and looks ahead to further optimizing the functionality and biomimetic precision of OoCs through innovation, emphasizing its critical role in promoting personalized medicine and precision treatment strategies.

Microfluidics is an increasingly popular method for studying cell deformation, with various applications in fields such as cell biology, biophysics, and medical research. Characterizing cell deformation offers insights into fundamental cell processes, such as migration, division, and signaling. This review summarizes recent advances in microfluidic techniques for measuring cellular deformation, including the different types of microfluidic devices and methods used to induce cell deformation. Recent applications of microfluidics-based approaches for studying cell deformation are highlighted. Compared to traditional methods, microfluidic chips can control the direction and velocity of cell flow by establishing microfluidic channels and microcolumn arrays, enabling the measurement of cell shape changes. Overall, microfluidics-based approaches provide a powerful platform for studying cell deformation. It is expected that future developments will lead to more intelligent and diverse microfluidic chips, further promoting the application of microfluidics-based methods in biomedical research, providing more effective tools for disease diagnosis, drug screening, and treatment.

Circulating tumor cells (CTCs) are vital indicators of metastasis and provide a non-invasive method for early cancer diagnosis, prognosis, and therapeutic monitoring. However, their low prevalence and heterogeneity in the bloodstream pose significant challenges for detection. Microfluidic systems, or “lab-on-a-chip” devices, have emerged as a revolutionary tool in liquid biopsy, enabling efficient isolation and analysis of CTCs. These systems offer advantages such as reduced sample volume, enhanced sensitivity, and the ability to integrate multiple processes into a single platform. Several microfluidic techniques, including size-based filtration, dielectrophoresis, and immunoaffinity capture, have been developed to enhance CTC detection. The integration of machine learning (ML) with microfluidic systems has further improved the specificity and accuracy of CTC detection, significantly advancing the speed and efficiency of early cancer diagnosis. ML models have enabled more precise analysis of CTCs by automating detection processes and enhancing the ability to identify rare and heterogeneous cell populations. These advancements have already demonstrated their potential in improving diagnostic accuracy and enabling more personalized treatment approaches. In this review, we highlight the latest progress in the integration of microfluidic technologies and ML algorithms, emphasizing how their combination has changed early cancer diagnosis and contributed to significant advancements in this field.

Cell sorting plays a crucial role in both medical and biological research. As a key passive sorting technique in the field of microfluidics, deterministic lateral displacement (DLD) has been widely applied to cell separation and sorting. This review aims to summarize the latest advances in the optimization of channel design for microfluidic DLD cell sorting. First, we provide an overview of the design elements of microfluidic DLD cell sorting channels, focusing on key factors that affect separation efficiency and accuracy, including channel geometry, fluid dynamics, and the interaction between cells and channel surfaces. Subsequently, we review recent innovations and progress in channel design for microfluidic DLD technology, exploring its applications in biomedical fields and its integration with machine learning. Additionally, we discuss the challenges currently faced in optimizing channel design for microfluidic DLD cell sorting. Finally, based on existing research, we make a summary and put forward prospective views on the further development of this field.

Cancer metastasis is one of the primary reasons for cancer-related fatalities. Despite the achievements of cancer research with microfluidic platforms, understanding the interplay of multiple factors when it comes to cancer cells is still a great challenge. Crosstalk and causality of different factors in pathogenesis are two important areas in need of further research. With the assistance of machine learning, microfluidic platforms can reach a higher level of detection and classification of cancer metastasis. This article reviews the development history of microfluidics used for cancer research and summarizes how the utilization of machine learning benefits cancer studies, particularly in biomarker detection, wherein causality analysis is useful. To optimize microfluidic platforms, researchers are encouraged to use causality analysis when detecting biomarkers, analyzing tumor microenvironments, choosing materials, and designing structures.

Acoutofluidics is an increasingly developing and maturing technical discipline. With the advantages of being label-free, non-contact, bio-friendly, high-resolution, and remote-controllable, it is very suitable for the operation of living cells. After decades of fundamental laboratory research, its technical principles have become increasingly clear, and its manufacturing technology has gradually become popularized. Presently, various imaginative applications continue to emerge and are constantly being improved. Here, we introduce the development of acoustofluidic actuation technology from the perspective of related manipulation applications on living cells. Among them, we focus on the main development directions such as acoustofluidic sorting, acoustofluidic tissue engineering, acoustofluidic microscopy, and acoustofluidic biophysical therapy. This review aims to provide a concise summary of the current state of research and bridge past developments with future directions, offering researchers a comprehensive overview and sparking innovation in the field.