Prognostic assessment of valvular aortic disease treatment coupling Immunological and biomechanical profiles
Protego aims to develop a predictive methodology combining immunological and biomechanical profiles to optimize treatment timing and outcomes for patients with aortic valve diseases, reducing complications.
Projectdetails
Introduction
Aortic valve diseases are degenerative conditions that develop progressively and insidiously. Once symptoms become evident, life expectancy is significantly reduced. While treatments for these pathologies are widely available, there remains a remarkably high rate of procedural complications.
Impact of Complications
These complications have been shown to have a negative impact on cardiac mortality and the likelihood of rehospitalization for heart failure. This underscores the need for further technological advancements.
Objective
Protego's objective is to determine whether a combination of immunological and biomechanical profiles in patients with aortic valve diseases can effectively predict post-treatment prognosis. My goal is to develop an innovative, validated, and clinically applicable methodology that can identify the best treatment options and predict post-procedural outcomes while minimizing complications.
Methodology
This methodology will serve to determine the timing of treatment for patients with valvular aortic diseases and assess whether the proposed treatment is likely to be beneficial preoperatively, while also minimizing the risk of post-procedural complications. I will achieve this by combining imaging analysis, deep learning algorithms, in silico models, and in vitro tests.
Key Objectives
My approach involves the following key objectives:
- Creating a multi-physics digital twin of patients with aortic valve diseases.
- Developing a validated, high-fidelity model for treatment with quantification of post-treatment outcomes.
- Generating a proof of concept for a clinically applicable predictive model trained using both immunological profiles and biomechanical features of patients.
Conclusion
This innovative approach will provide a deeper understanding of how clinical and biomechanical outcomes correlate with the amplification of inflammation, helping us comprehend the interaction between biomarkers and negative post-treatment prognosis in patients with aortic valve diseases.
Financiële details & Tijdlijn
Financiële details
Subsidiebedrag | € 1.498.295 |
Totale projectbegroting | € 1.498.295 |
Tijdlijn
Startdatum | 1-10-2024 |
Einddatum | 30-9-2029 |
Subsidiejaar | 2024 |
Partners & Locaties
Projectpartners
- POLITECNICO DI MILANOpenvoerder
- HUMANITAS UNIVERSITY
Land(en)
Vergelijkbare projecten binnen European Research Council
Project | Regeling | Bedrag | Jaar | Actie |
---|---|---|---|---|
Clonal hematopoesis of indeterminate potential and degenerative aortic valve stenosisThis project aims to investigate the impact of DNMT3A mutations on aortic valve stenosis progression and cardiac fibrosis, seeking biomarkers and therapeutic targets for high-risk patients. | ERC Advanced... | € 2.225.906 | 2022 | Details |
Real-time Multiscale Imaging of Pathological Calcification - Zooming in on Aortic Valve CalcificationDeveloping a designer tissue imaging platform to dynamically study extracellular matrix changes in Calcifying Aortic Valve Disease, aiming to uncover mechanisms for future drug therapies. | ERC Advanced... | € 2.500.000 | 2025 | Details |
Pushing Boundaries in Pre-clinical Aortopathy ResearchThis project aims to unravel mechanisms of syndromic thoracic aortic aneurysm and develop effective therapies using patient-derived aorta-on-a-chip models for pre-clinical research. | ERC Starting... | € 1.494.848 | 2024 | Details |
Advanced human models of the heart to understand cardiovascular diseaseHeart2Beat aims to develop innovative 3D human cardiac models using microfluidic technology to enhance understanding and treatment of cardiovascular diseases through personalized medicine. | ERC Advanced... | € 2.500.000 | 2023 | Details |
Using CARDIac simulations to run in-silicO clinical TRIALSThis project aims to develop a GPU-accelerated computational platform for simulating cardiac pathologies and device responses, integrating uncertainty quantification to enhance in-silico clinical trials. | ERC Starting... | € 1.499.423 | 2022 | Details |
Clonal hematopoesis of indeterminate potential and degenerative aortic valve stenosis
This project aims to investigate the impact of DNMT3A mutations on aortic valve stenosis progression and cardiac fibrosis, seeking biomarkers and therapeutic targets for high-risk patients.
Real-time Multiscale Imaging of Pathological Calcification - Zooming in on Aortic Valve Calcification
Developing a designer tissue imaging platform to dynamically study extracellular matrix changes in Calcifying Aortic Valve Disease, aiming to uncover mechanisms for future drug therapies.
Pushing Boundaries in Pre-clinical Aortopathy Research
This project aims to unravel mechanisms of syndromic thoracic aortic aneurysm and develop effective therapies using patient-derived aorta-on-a-chip models for pre-clinical research.
Advanced human models of the heart to understand cardiovascular disease
Heart2Beat aims to develop innovative 3D human cardiac models using microfluidic technology to enhance understanding and treatment of cardiovascular diseases through personalized medicine.
Using CARDIac simulations to run in-silicO clinical TRIALS
This project aims to develop a GPU-accelerated computational platform for simulating cardiac pathologies and device responses, integrating uncertainty quantification to enhance in-silico clinical trials.
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Engineering a living human Mini-heart and a swimming Bio-robot
The project aims to develop advanced in vitro human cardiac models, including a vascularized mini-heart and a bio-robot, to better assess cardiotoxicity and improve understanding of cardiovascular disease.