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Point of care diagnostic solution for definitive differentiation of true and false threatened preterm labour cases

Project description

Non-invasive device for threatened preterm labour diagnosis

Threatened preterm labour (TPTL) poses a significant risk for preterm births and requires hospitalisation during pregnancy, contributing to 45 million cases annually. Efficient diagnosis of TPTL is crucial for optimising treatments. However, current methods prove ineffective in detecting actual events. The EIC-funded FineBirth project has successfully developed a non-invasive diagnostic device that utilises torsional waves and artificial intelligence to measure cervical tissue consistency, enabling real-time identification of TPTL risks. The device is objective, accurate, and easy to operate. Already subjected to testing in a multicentre clinical study involving over 300 patients across seven sites, the project now aims to further develop and validate its AI software. Additionally, it plans to conduct a multicentre clinical trial and obtain regulatory approval for the innovative diagnostic device.

Objective

Threatened Preterm Labour (TPTL) is the leading cause of preterm births and hospitalization during pregnancy. With 45M cases annually, treatments and resources are not being properly allocated towards the patients who need them. Efficient diagnosis of TPTL is the key to optimizing treatments but, current methods are ineffective at detecting true events.
INNITIUS has developed Fine Birth, the first non-invasive PoC diagnostic device that uses torsional waves and AI to directly measure a patient’s cervical tissue consistency to identify the risk of TPTL in real-time. It is objective, accurate, fast and can be operated by staff with minimal training.
We have reached TRL6, testing the prototype in a multicentre clinical study with +300 patients in 7 sites. We need €2.5M to fully develop and validate our AI software, do a multicentre pivotal clinical trial, and obtain regulatory approval, which we will be able to finalise with the support of the EIC.

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Keywords

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Programme(s)

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Topic(s)

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Funding Scheme

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HORIZON-EIC-ACC-BF - HORIZON EIC Accelerator Blended Finance

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Call for proposal

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(opens in new window) HORIZON-EIC-2022-ACCELERATOR-01

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Coordinator

ULTRASOUND-INNOVATION MEDTECH SOCIEDAD LIMITADA
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 2 342 835,50
Address
AVENIDA SABINO ARANA 8, PLANTA 2
48013 Bilbao
Spain

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SME

The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.

Yes
Region
Noreste País Vasco Bizkaia
Activity type
Private for-profit entities (excluding Higher or Secondary Education Establishments)
Links
Total cost

The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.

€ 3 346 908,00
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