UNITI · Project

Predictive Software That Matches Tinnitus Patients to the Right Treatment Combination

healthTestedTRL 5

uniti.tinnitusresearch.net

Imagine over 10% of people hear a constant ringing in their ears that no doctor can reliably fix — because nobody knows which treatment works for which patient. UNITI built a kind of intelligent matching system: it pools clinical, genetic, and hearing data from thousands of patients across Europe, then uses prediction algorithms to figure out which combination of therapies will actually help a specific person. Think of it like a recommendation engine, but instead of suggesting movies, it suggests the right mix of treatments based on your personal profile. They even ran a clinical trial to test whether their predictions actually hold up in practice.

By the numbers

10%+

Share of general population affected by tinnitus

Population that considers tinnitus their major health issue

Expected increase in European tinnitus prevalence by 2050

0.68

Heritability score for bilateral tinnitus in men

Consortium partners across 9 countries

Total project deliverables produced

The business problem

What needed solving

Tinnitus affects over 10% of the European population, yet there is no consensus on treatment — doctors essentially guess which therapy to try, wasting time and money while patients suffer. With prevalence expected to double by 2050, the cost of ineffective trial-and-error treatment will become unsustainable for healthcare systems and insurers alike.

The solution

What was built

UNITI built ensemble-based prediction models that combine clinical data from multiple sources using a voting scheme, plus an in-silico model paired with a clinical decision support system (DSS) designed to recommend optimal treatment combinations for individual tinnitus patients. These were validated through a randomized controlled trial across 15 deliverables.

Audience

Who needs this

Digital health companies building clinical decision support platformsHearing aid and audiology device manufacturersHealth insurers covering ENT and audiology treatmentsENT clinic chains and audiology practice networksPharma companies developing tinnitus therapeutics

Business applications

Who can put this to work

MedTech / Digital Health

SME

Target: Companies developing clinical decision support software or digital therapeutics platforms

If you are a digital health company building treatment guidance tools — UNITI developed ensemble-based prediction models and a decision support system (DSS) that matches tinnitus patients to optimal treatment combinations using clinical, genetic, and audiological data. With over 10% of the population affected by tinnitus, integrating these validated models into your platform could open a massive addressable market.

Hearing Aid & Audiology Devices

enterprise

Target: Hearing aid manufacturers and audiology device companies

If you are a hearing device manufacturer looking to differentiate your product line — UNITI created an in-silico model combining electrophysiological and experimental data on ear-brain communication. This could power smarter, more personalized sound therapy features embedded in your devices. With tinnitus prevalence expected to double by 2050, a data-driven treatment add-on is a strong competitive advantage.

Health Insurance & Managed Care

enterprise

Target: Health insurers and managed care organizations covering ENT and audiology services

If you are a health insurer dealing with rising costs from ineffective tinnitus treatments — UNITI's predictive computational model identifies which therapy combinations work for specific patient profiles, potentially reducing trial-and-error treatment cycles. Since 1% of the population considers tinnitus their major health issue, better treatment matching could significantly cut long-term care costs.

Frequently asked

Quick answers

What would it cost to license or integrate UNITI's prediction models?

The project data does not include licensing costs or pricing models. UNITI was a publicly funded research project coordinated by University Hospital Regensburg. Licensing terms would need to be negotiated directly with the consortium, likely through the coordinator.

Can these models work at industrial scale with real patient populations?

UNITI validated its prediction models through a randomized controlled trial (RCT) with multiple patient groups receiving combination therapies. The models were trained on data from existing databases across 14 partner organizations in 9 countries. Scaling to production clinical systems would require regulatory clearance and integration with existing health IT infrastructure.

Who owns the intellectual property — can we license the algorithms?

IP from EU-funded RIA projects typically belongs to the consortium partners who generated it. The in-silico model and ensemble prediction models are key protectable assets. Contact the coordinator at University Hospital Regensburg to discuss licensing or collaboration opportunities.

Has this been tested in real clinical settings?

Yes. UNITI ran a randomized controlled trial where different patient groups received combination therapies targeting both the auditory and central nervous systems. Predictive factors extracted from existing databases were tested for their prognostic relevance in this clinical setting.

What kind of data does the system need to make predictions?

The system uses clinical, epidemiological, medical, genetic, and audiological data, including signals reflecting ear-brain communication. It requires patient phenotyping and genotyping data, which means clinics would need to collect or already have these data types available.

Does this comply with medical device regulations in Europe?

The in-silico model was specifically designed to facilitate international regulatory acceptance. Based on available project data, the deliverable on the in-silico model explicitly mentions demonstrating relevance and reliability to accelerate regulatory acceptance. Full CE marking or MDR compliance would still need to be pursued.

Is there ongoing support or development after the project ended?

The project closed in September 2023. The consortium included 14 partners with 3 industry players who may continue development. Check the project website at uniti.tinnitusresearch.net for post-project activity and continuation plans.

Consortium

Who built it

The UNITI consortium brings together 14 partners from 9 European countries, combining 7 universities and 3 research organizations with 3 industry players (21% industry ratio) and 1 SME. The coordinator is University Hospital Regensburg in Germany, a major clinical center with direct access to patient populations. The strong academic majority signals deep scientific rigor, while the industry presence — though modest — indicates some commercial translation intent. The geographic spread across Belgium, Switzerland, Cyprus, Germany, Greece, Spain, Hungary, Italy, and Sweden provides access to diverse patient populations and regulatory environments, which strengthens the clinical validation of the prediction models.

KLINIKUM DER UNIVERSITAET REGENSBURGCoordinator · DE
VILABS (CY) LTDparticipant · CY
UNIVERSITAETSKLINIKUM WUERZBURG - KLINIKUM DER BAYERISCHEN JULIUS-MAXIMILIANS-UNIVERSITATparticipant · DE
OTTO-VON-GUERICKE-UNIVERSITAET MAGDEBURGparticipant · DE
ETHNIKO KAI KAPODISTRIAKO PANEPISTIMIO ATHINONparticipant · EL
ISTITUTO DI RICERCHE FARMACOLOGICHE MARIO NEGRIparticipant · IT
CHARITE - UNIVERSITAETSMEDIZIN BERLINparticipant · DE
KAROLINSKA INSTITUTETparticipant · SE
SPHYNX TECHNOLOGY SOLUTIONS AGparticipant · CH
SERVICIO ANDALUZ DE SALUDparticipant · ES
KATHOLIEKE UNIVERSITEIT LEUVENparticipant · BE
EREVNITIKO PANEPISTIMIAKO INSTITOUTO SYSTIMATON EPIKOINONION KAI YPOLOGISTONparticipant · EL
FUNDACION PARA LA INVESTIGACION BIOSANITARIA DE ANDALUCIA ORIENTAL-ALEJANDRO OTEROthirdparty · ES

How to reach the team

University Hospital Regensburg (Germany) — contact via SciTransfer for a warm introduction to the research team

Order a report on this consortium See KLINIKUM DER UNIVERSITAET REGENSBURG profile →

Next steps

Talk to the team behind this work.

Want to explore licensing the UNITI prediction models or integrating the decision support system into your product? SciTransfer can connect you directly with the research team and help structure the collaboration.

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