Advancing transistor-based point-of-care (POC) biosensors: additive manufacturing technologies and device integration strategies for real-life sensing

Abstract

Infectious pathogens pose a significant threat to public health and healthcare systems, making the development of a point-of-care (POC) detection platform for their early identification a key focus in recent decades. Among the numerous biosensors developed over the years, transistor-based biosensors, particularly those incorporating nanomaterials, have emerged as promising candidates for POC detection, given their unique electronic characteristics, compact size, broad dynamic range, and real-time biological detection capabilities with limits of detection (LODs) down to zeptomolar levels. However, the translation of laboratory-based biosensors into practical applications faces two primary challenges: the cost-effective and scalable fabrication of high-quality transistor sensors and functional device integration. This review is structured into two main parts. The first part examines recent advancements in additive manufacturing technologies—namely in screen printing, inkjet printing, aerosol jet printing, and digital light processing—and evaluates their applications in the mass production of transistor-based biosensors. While additive manufacturing offers significant advantages, such as high quality, cost-effectiveness, rapid prototyping, less instrument reliance, less material waste, and adaptability to diverse surfaces, challenges related to uniformity and yield remain to be addressed before these technologies can be widely adopted for large-scale production. The second part focuses on various functional integration strategies to enhance the practical applicability of these biosensors, which is essential for their successful translation from laboratory research to commercialization. Specifically, it provides a comprehensive review of current miniaturized lab-on-a-chip systems, microfluidic manipulation, simultaneous sampling and detection, wearable implementation, and integration with the Internet of Things (IoT).