SciTransfer
PHOREVER · Project

AI-Powered Miniaturized Blood Diagnostic Device for Early Cancer and Stroke Detection

healthPrototypeTRL 4

Imagine a tiny lab-on-a-chip that can spot microscopic bubbles released by cells into your blood. These bubbles act like messengers that reveal if a disease like cancer is starting or if a stroke has occurred. By using light and AI, this device catches these messengers even when they are incredibly small, allowing for a fast diagnosis right at the patient's bedside.

By the numbers
80 nm
minimum detectable extracellular vesicle size
2.5 µm
OCT resolution
4
flow cytometry wavelengths (405, 488, 633, 785 nm)
The business problem

What needed solving

Current imaging tools like CT and MRI cannot see the molecular mechanisms of cancer or stroke. Detecting the tiny blood vesicles that hold this information is currently imperfect because they are too small for standard equipment.

The solution

What was built

A multi-sensing PoC platform comprising 2 photonic integrated circuits and 3 microfluidic chips. It includes a pre-cursor prototype that integrates flow cytometry, fluorescence sensing, and OCT.

Audience

Who needs this

Medical device manufacturersClinical diagnostic laboratoriesOncology research centersNeurology clinics specializing in stroke
Business applications

Who can put this to work

Medical Diagnostics
enterprise
Target: Point-of-Care (PoC) device manufacturer

If you are a device manufacturer dealing with the lack of portable, high-precision blood analysis tools — this project developed a compact platform using photonic integrated circuits that detects extracellular vesicles down to 80 nm. This allows for rapid, bedside diagnosis of stroke and pancreatic cancer.

Biotechnology
SME
Target: Liquid biopsy startup

If you are a biotech company dealing with the difficulty of identifying disease-specific proteins on ultra-small vesicles — this project developed a multi-sensing platform combining flow cytometry and fluorescence. It enables the identification of biomarkers on vesicles sized 50-200 nm to monitor cancer progression.

Healthcare IT
mid-size
Target: AI Health-Tech provider

If you are a software provider dealing with complex biological datasets that are hard to interpret — this project developed AI algorithms that correlate measurement data from blood samples with medical records. This transforms raw optical data into actionable diagnostic insights for stroke classification.

Frequently asked

Quick answers

What is the estimated cost or price of the device?

Based on available project data, there is no specific information regarding the unit cost or market price of the device.

Can this technology be produced at an industrial scale?

The project utilizes photonic integrated circuits (PICs) and microfluidic chips, which are typically scalable manufacturing technologies, though specific industrial scale-up data is not provided.

How is the intellectual property or licensing handled?

Based on available project data, the specific IP and licensing terms are not disclosed in the provided summary.

How does this integrate into existing hospital workflows?

The device is designed as a compact point-of-care (PoC) tool, meaning it is intended for use at the site of patient care rather than requiring transport to a central lab.

What is the timeline for market availability?

The project period runs from 2023-01-01 to 2026-12-31, suggesting the technology will be in development and prototype stages until the end of 2026.

Consortium

Who built it

The consortium is well-balanced for technology transfer, consisting of 8 partners across 4 countries. With an industry ratio of 38% (including 3 industrial partners and 2 SMEs), there is a strong commercial orientation. The mix of 2 universities and 3 research institutes ensures the deep technical expertise required for the complex integration of photonics and microfluidics.

How to reach the team

Contact the EREVNITIKO PANEPISTIMIAKO INSTITOUTO SYSTIMATON EPIKOINONION KAI YPOLOGISTON in Greece.

Next steps

Talk to the team behind this work.

Contact us to explore licensing opportunities for the PHOREVER PIC-based diagnostic platform.

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