Chronic diseases such as cancer, Alzheimer’s disease, and diabetes place a major burden on patients, healthcare systems, and society. Better outcomes depend strongly on earlier diagnosis and closer monitoring over time. Yet this remains difficult when disease signals are present in very small amounts and when current tests depend on taking samples out of the body and processing them in the laboratory. Even when these approaches are less invasive than traditional tissue biopsy, they can still be slow, costly, and limited in their ability to capture rare biomarkers at the earliest stages of disease.

BeNiFIt addresses this challenge by exploring a new way to detect disease biomarkers directly inside the body. The project focuses on intra-body nanoscale communication systems, in which extremely small devices, called nanomachines, move through the bloodstream, sense target biomarkers, and pass information to an on-body gateway that can connect to external medical systems. This approach aims to support a future generation of diagnostic and monitoring tools that are minimally invasive, faster, and more suitable for continuous or repeated use.

Cancer provides the main case study for the project because early-stage cancer detection is especially difficult when biomarker levels are low, unstable, and unevenly distributed in blood. At the same time, the broader vision of BeNiFIt extends beyond cancer. The same scientific and engineering principles could support earlier detection and monitoring for other chronic diseases in which timely identification of molecular signs is important for treatment decisions and patient care.

The overall objective of BeNiFIt is to show that intra-body nanoscale communications can make in vivo biomarker detection feasible and useful for medical diagnostics. To achieve this, the project pursues three connected goals. First, it investigates how nanomachines equipped with biosensing capabilities can detect biomarkers accurately inside the bloodstream, including under low-concentration conditions. Second, it develops a communication architecture that allows these very small devices to share or relay information while respecting strict constraints on size, energy use, and safety in the human body. Third, it builds a multi-scale simulation framework that can model the full system and support the design, evaluation, and optimization of future in-body diagnostic platforms.

Through this pathway, BeNiFIt aims to lay the scientific and technological foundation for faster and less burdensome biomarker-based diagnostics. In the longer term, this could help move healthcare toward earlier intervention, more timely clinical decisions, and more accessible monitoring methods for diseases where speed and sensitivity matter most.