Imagine a tiny electronic chip that acts like a lock and key to detect specific proteins in your blood. When a disease-related protein 'unlocks' the chip, it changes the electrical charge, signaling a problem. This allows doctors to see exactly how a patient is responding to medication in real-time instead of guessing through trial and error.
Major depressive disorder treatment currently relies on a costly and slow trial-and-error process. There are no existing serum-based tests to predict which personalized therapy will work for a patient.
A miniaturized graphene-based biosensor system on silicon wafers capable of parallel, label-free detection of multiple protease biomarkers in serum.
If you are a psychiatric clinic dealing with the high cost and variability of treating major depressive disorder — this project developed a graphene biosensor that predicts therapy response. This reduces the trial-and-error period for finding effective treatments and lowers hospitalization times.
If you are a diagnostic firm dealing with the need for miniaturized, high-precision testing tools — this project developed a multiplexed readout matrix on silicon wafers. This allows for the parallel detection of multiple biomarkers with low material consumption.
If you are a pharma company dealing with the need to monitor protease activity in oncology or immunology — this project developed a label-free sensing mechanism. This provides a tool for real-time activity analysis of biomarkers to validate drug efficacy.
Based on available project data, specific unit costs or pricing models are not provided.
The project integrates biosensors on silicon wafers with a multiplexed readout matrix, which is a standard path for industrial scaling in semiconductor manufacturing.
Based on available project data, specific patent or licensing details are not mentioned, though the project aims to secure EU industrial leadership in the value chain.
The system is designed as a rapid, easy-to-use test using serum samples, intended for point-of-care diagnostic and therapy prediction tools.
The project period runs from 2023-10-01 to 2027-09-30, suggesting the technology will be developed and validated through September 2027.
The consortium is well-balanced for commercialization, featuring a 33% industry ratio with 2 SMEs and 2 larger industrial/research entities (Graphenea and VTT). The mix of 3 universities and 1 research center ensures a pipeline from fundamental graphene research to clinical validation and semiconductor integration.
Professor Alexey Tarasov, Kaiserslautern University of Applied Sciences
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