
VET EX MACHINA LIMITED
VET EX MACHINA LIMITED
1 Projects, page 1 of 1
Open Access Mandate for Publications and Research data assignment_turned_in Project2025 - 2029Partners:UPV, University of Warwick, FLUIDINOVA SA, UPC, CPI +8 partnersUPV,University of Warwick,FLUIDINOVA SA,UPC,CPI,ASPHALION,CONSULTECH,RCSI,Newcastle University,POLITO,VET EX MACHINA LIMITED,Separeco,SITEC PHARMABIO SLFunder: European Commission Project Code: 101178398Funder Contribution: 6,453,740 EURBone atrophy and fractures, resulting from trauma, infections, osteoporosis, or cancer, are global health concerns. Standard care with cement and bone grafts has limitations. Synthetic polymers like polymethyl methacrylate risk leakage, spinal issues, and poor healing. Donor shortages for allogenic bone grafting and invasive procedures pose risks such as rejection and viral transmission. HYDROHEAL innovates with hydrogel formulations to address bone strength challenges by treating vertebral and alveolar fractures. HYDROHEAL aims to develop safe, sustainable scaling, and cost-effective formulations using renewable biomaterials for targeted drug delivery, aligning closely with the EU Circular Economy Action Plan and Chemicals Strategy for Sustainability. It is ready to introduce a new era in fracture therapy. The proposed self-solidifying hydrogels release active pharmaceutical ingredients locally upon external stimulation, potentially improving treatment efficacy, preventing infections, and speeding up fracture healing. The objectives of the project are: 1. Develop novel injectable hydrogel formulations combining natural substance derivates to enhance healing, inhibit bacterial growth, and monitor therapy progress in vivo. 2. Simultaneously manufacture carriers as micro- and nano-particles, surface-functionalized to incorporate pharmaceutical agents, releaseable upon external stimuli for tailored drug release. 3. Validate safe and optimized hydrogel formulations for treating vertebral and alveolar bone fractures through in vitro and in vivo tests. 4. Demonstrate scalable and sustainable biomaterial manufacturing through safe design methods, machine learning, and predictive life cycle assessment. 5. Develop machine learning and hybrid digital modeling methods, combining adaptive design of experiments and physics-based modeling with advanced characterization techniques.
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