University of Eastern Finland is funding five Proof of Concept-projects by university’s strategic implementation fund

The University of Eastern Finland opened fall 2025 an internal call for Proof of Concept (PoC) funding to accelerate the commercialization of ideas emerging from research.

The renewed Proof of Concept funding aims to support the development of research-based ideas into practical solutions with a clear pathway to commercial or societal impact.

The funding helps mature ideas towards market entry, follow-on funding (e.g., Business Finland R2B), or broader adoption as service innovations and operational models.

Following Proof of Concept ideas were granted funding:

Suvi-Maria Saarelainen, School of Theology, 12000 €: Existential Health Compass (EWB Compass) – A Mobile Web Application for Existential Health

EWB Compass is a digital mobile web application designed to support users in exploring questions related to meaning, values and identity. The application is grounded in research on existential health and wellbeing theology, offering brief reflection tasks and AI-generated feedback.

Its aim is to provide a new, accessible tool that strengthens psychological balance and helps individuals navigate the existential questions inherent to human life. In this Proof-of-Concept project, the first functional version of the application will be developed and tested in co-creation with users in a university community. The project lays the foundation for wider piloting and further development of the application, and contributes to international research on existential health and digital wellbeing.

Isaac Afara, Department of Applied Physics; 20000 €:  A novel approach for monitoring tissue growth and maturity in cartilage tissue engineering via near infrared spectroscopic assessment of culture media (NIRSense)

Degenerative joint diseases such as osteoarthritis (OA) lead to pain, immobility, and loss of articular cartilage. Although treatments for focal cartilage injuries exist, they often fail to restore long-term function, driving interest in tissue engineering (TE) as a strategy for generating replacement cartilage. Current TE approaches, however, rely largely on trial-and-error, producing engineered tissues that often lack the mechanical and biochemical properties of native cartilage due to the absence of reliable methods for monitoring and controlling the culture process.

To address this gap, we recently developed a novel near-infrared spectroscopy (NIRS)-based optical approach that enables rapid, non-destructive monitoring of tissue growth and maturity by estimating biomarkers released into the culture media during TE. Using a custom-designed liquid cell and machine learning algorithms, the platform (NIRSense) allows accurate, real-time assessment of key biomarkers such as hyaluronan, collagen, and lactate, providing continuous and contamination-free monitoring of tissue development. 

This proof-of-concept project will further expand NIRSense to detect additional biomarkers, including inflammatory cytokines and MMPs, and extend its use to broader cell and tissue culture systems, including disease-model development. These advancements will increase the platform’s versatility and translational value, positioning NIRSense for future commercialization efforts, including a Business Finland R2B application.

Alexey Basharin, Department of Physics and Mathematics; 20000 €: Quantum Anapole Resonator Platform

The QUANTAPOLE Proof-of-Concept project aims to demonstrate a novel giant superconducting anapole resonator that suppresses radiative losses through destructive multipole interference. This “non-radiating” electromagnetic state can significantly enhance the coherence time and energy efficiency of superconducting qubits, addressing one of the major bottlenecks in quantum computing scalability. The urgency of this research has increased following the 2025 Nobel Prize in Physics, which recognized breakthroughs in superconducting qubits and highlighted the need for new approaches to extend quantum coherence.

The project builds on UEF’s pioneering research in anapole photonics conducted within the PREIN Flagship (Academy of Finland) and seeks to advance the technology from TRL 2–3 to TRL 4 through prototype fabrication and cryogenic validation at the OtaNano (VTT/Aalto) infrastructure. The outcomes will include experimental proof of concept qubit resonator, an invention disclosure to UEF Innovation Services, and preparation of a Business Finland Research-to- Business (R2B) proposal.

QUANTAPOLE strengthens UEF’s contribution to Finland’s quantum ecosystem by bridging advanced photonics research and superconducting quantum hardware innovation.

Nihay Laham Karam, A.I.V. Institute for Molecular Sciences; 20000 €: A Novel Gene Therapy Vector for Targeted Treatment of Ischemic Myocardial Infarction

Heart attacks and strokes, resulting from closed vessel and interrupted blood supply, cause millions of deaths every year. In this project, we aim to develop an Advanced Therapy Medicinal Product (ATMP) based on viral vector-mediated angiogenic therapy.

This new vector works specifically in the endothelial cells that line the blood vessels. The vector expresses a novel transgene that can stimulate new vessel growth but also limit scar formation. It is expected that this vector will provide effective therapy for ischemic diseases, which subsequently can save millions of lives.

Arto Mannermaa, School of Medicine (Clinical Medicine); 20000 €: Digital Computational Device for Early Cancer Detection and Monitoring Using cfDNA Fragmentomics

Current cancer diagnostics face significant limitations, including invasiveness, late-stage detection, and inadequate tools for monitoring treatment response or early recurrence. This work introduces a novel, dual-component Artificial Intelligence (AI) methodology designed to address these challenges by rigorously analyzing patterns of tumor-shed cell-free DNA (cfDNA) fragments from a simple blood sample.

The core innovation is the fusion of two specialized AI models: 1) an AI Early Detection Model utilizing fragmentomics, and 2) a Deep Autoencoder (DAE) Prognostic Model that provides a quantitative "Cancer Proportion Metric". This metric provides a superior, dynamic assessment compared to standard methods.

This Proof-of-Concept (PoC) aims to provide the necessary validation to move the technology from concept to clinical proof and secure follow-on R2B funding. To ensure commercial scalability and sustainability, the PoC will overcome read-depth variability by employing a novel hierarchical Bayesian downsampling strategy to pretrain a machine-agnostic AI backbone.

The PoC will validate the methodology's clinical utility by benchmarking the DAE model against ichorCNA and proving its efficacy for: (1) early detection of cancer, (2) real-time monitoring of treatment success, and (3) securing longitudinal data for Minimal Residual Disease (MRD) claims.

By shifting from a simple positive/negative result to a dynamic, quantitative assessment, this technology stands to transform cancer care, enabling more personalized treatment strategies and improving patient outcomes.