Magnetoresistive (MR) sensors have been successfully applied in many technologies, in particular readout electronics and smart systems for multiple signal addressing and readout. When single sensors are used, the requirements relate to spatial resolution and localized field sources. The integration of MR sensors in adaptable media (e.g. flexible, stretchable substrates) offers the possibility to merge the magnetic detection with mechanical functionalities. In addition, the precision of a micrometric needle can benefit greatly from the integration of MR sensors with submicrometric resolution. In this paper, we demonstrate through several detailed examples how advanced MR sensors can be integrated with the systems described above, and also with microfluidic technologies. Here, the challenges of handling liquids over a chip combine with those for miniaturization of microelectronics for MR readout. However, when these are overcome, the result is an integrated system with added functionalities, capable of answering the demand in biomedicine and biochemistry for lab-on-a-chip devices.

Cancer kills millions of individuals every year all over the world (Global Cancer Observatory). The physiological and biomechanical processes underlying the tumor are still poorly understood, hindering researchers from creating new, effective therapies. Inconsistent results of preclinical research, in vivo testing, and clinical trials decrease drug approval rates. 3D tumor‐on‐a‐chip (ToC) models integrate biomaterials, tissue engineering, fabrication of microarchitectures, and sensory and actuation systems in a single device, enabling reliable studies in fundamental oncology and pharmacology. This review includes a critical discussion about their ability to reproduce the tumor microenvironment (TME), the advantages and drawbacks of existing tumor models and architectures, major components and fabrication techniques. The focus is on current materials and micro/nanofabrication techniques used to manufacture reliable and reproducible microfluidic ToC models for large‐scale trial applications.