Aug 2026· Small· pp.
e74958
· 2 citations· 124 references
Medicine
TL;DR
This review provides a comprehensive overview of design strategies for in vivo biosensors, categorized into three implantation approaches: material-based implants, injectable microdevices, and surgical implants and discusses the historical development, state-of-the-art examples, and design considerations for each strategy.
Abstract
In vivo biosensing technologies are revolutionizing how health and disease are monitored by enabling continuous, real-time measurement of biomarkers within the body. From the first enzymatic electrode biosensor developed to modern integrated sensing devices, progress in materials science, microelectronics, and bioengineering has expanded the scope of implantable sensors. Key requirements such as high analytical performance, long-term biocompatibility, safe energy supply, and reliable wireless communication must be met for successful clinical translation. Major application areas include metabolic monitoring (exemplified by continuous glucose monitors for diabetes), cardiovascular management, neural interfaces for brain activity, inflammatory disease tracking, oncology, transplant organ monitoring, bladder dysfunction management, and biomechanical strain sensing. This review provides a comprehensive overview of design strategies for in vivo biosensors, categorized into three implantation approaches: material-based implants, injectable microdevices, and surgical implants. We discuss the historical development, state-of-the-art examples, and design considerations for each strategy. A comparative analysis highlights their respective advantages and limitations. Finally, we examine the overarching challenges and future perspectives that will guide the next generation of implantable biosensing devices toward widespread clinical impact.
Functionalized design is presented as an application‐backward, cross‐scale framework that links clinical needs and biomarker–matrix constraints with recognition chemistry, biointerfaces, functional materials, transduction architectures, calibration, data interpretation, manufacturability, and validation.
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