3D-printed architectures are rapidly reshaping the (bio)sensing landscape by enabling fully integrated devices that combine sample preparation, fluid handling, sensing elements, and structural components within a single fabrication workflow, namely all-in-one. Such designs minimize manual assembly, reduce sample volume, and facilitate rapid, on-site, or wearable analysis, addressing key limitations of conventional sensor fabrication. This perspective provides a comprehensive overview of all-in-one 3D-printed (bio)sensors and devices, analyzing recent developments across biomedical, environmental, and wearable applications. We discuss the capabilities of different additive manufacturing techniques, including fused deposition modeling, stereolithography, and digital light processing, and highlight representative devices for sample preconcentration, purification, detection, multiplexed analysis, and integrated electroanalysis. A central focus is on the relationship between materials and function, offering insight into in-house filament preparation, substrate selection, and functionalization strategies for conductive filaments, microchannels, and sensor surfaces. Key challenges and limitations, such as resolution, material conductivity, biomolecule stability, and sustainability considerations, are examined alongside potential solutions, including hybrid printing approaches, low-temperature filaments, chemometrics-assisted design, recycled materials, and standardized protocols. By connecting materials, fabrication strategies, device components, and application requirements, this perspective serves as a practical guide for researchers aiming to design integrated, high-performance, and sustainable 3D-printed (bio)sensing systems. Finally, we outline a roadmap for future developments, emphasizing scalability, customization, and the integration of emerging technologies such as artificial intelligence, chemometrics, and the internet of things, positioning 3D printing as a game-changer for next-generation sensing platforms.
Kalligosfyri et al. (Tue,) studied this question.