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CARE-KNEEOA

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In Silico Clinically-Viable Assistive Tools for Prediction and Rehabilitation of...

In Silico Clinically-Viable Assistive Tools for Prediction and Rehabilitation of Knee Osteoarthritis Knee osteoarthritis (KOA) is a leading cause of disability worldwide, with ~14% prevalence in Europeans aged over 40. KOA prevalence continues to rise, thus far, with no cure or proven prevention protocols. Nonetheless, an aberran... see more

31/08/2027

UNIVERSITY OF EAST...

302K€

Project Budget: 302K€

Project leader

ITASUOMEN YLIOPISTO No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

PARTICIPATION DEPralty Sin fecha límite de participación.

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Financing granted El organismo HORIZON EUROPE notifico la concesión del proyecto The day 2023-12-01

HORIZON-MSCA-2022-PF-01-01: MSCA Postdoctoral Fellowships 2022 Expected Outcome:

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characteristics of the participant

Este proyecto no cuenta con búsquedas de partenariado abiertas en este momento.

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No hay información privada compartida para este proyecto. Habla con el coordinador.

3 Participantes

UNIVERSITY OF EASTERN FINLAN...

302.33K€ | Leader

BOARD OF TRUSTEES OF THE LEL...

STANFORD

N.D. | participant

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Project duration: 44 months Date Start: 2023-12-01
End date: 2027-08-31

Project leader

ITASUOMEN YLIOPISTO No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Project Budget 302K€

participation deadline Sin fecha límite de participación.

Project description Knee osteoarthritis (KOA) is a leading cause of disability worldwide, with ~14% prevalence in Europeans aged over 40. KOA prevalence continues to rise, thus far, with no cure or proven prevention protocols. Nonetheless, an aberrant knee mechanobiological environment is known to accelerate KOA development. Tailored rehabilitation, aiming to favorably alter knee biomechanics and restore the joint, has shown great potential to postpone or decelerate KOA progression. But current rehabilitation protocols are based on indirect measures of knee biomechanics, often leading to suboptimal outcomes. Computational models have offered great potential for simulating knee mechanical response in functional activities, though none are developed in a holistic and individualized context. More importantly, they lack the prediction capability of tissue degeneration/regeneration to loading and the potential for clinical use, i.e., are not automated and fast and cannot use out-of-lab motion data. In this project, I will develop and validate highly personalized in silico tools to quantify knee cartilage mechanobiological degenerative/regenerative response geared towards out-of-lab and clinical use for predicting KOA progression in different functional activities, allowing personalized rehabilitation. The multiphysics computational models, assisted with artificial intelligence (AI), will be validated at different spatial scales using in vitro tissue and cell level experiments and in vivo joint loading and quantitative medical images. This multidisciplinary project bridges together complementary skill sets of Dr. Esrafilian, Profs. Korhonen’s and Delp’s teams, with their expertise in biomechanics, computational modeling, biochemistry, biology, and AI. The beyond state-of-the-art models of this research can make a profound impact on early-stage KOA prediction and treatment planning, potentially increasing the quality of life in KOA individuals and reducing the need for surgical interventions.

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