CArdiovascular Risk Assessment in MEnopausaL women via multimodal data analysis enabling personalized prevention strategies

Women’s cardiovascular health is an urgent clinical unmet need as reported by the European Society of Cardiology (ESC), as cardiovascular disease (CVD) risk in women still tends to be underestimated by clinicians and women themselves. CVD is under-diagnosed, under-treated and poorly understood, more so in women in the 40-60 age group, when personalised risk assessment and prevention can have a positive impact on their health.
In this context, CARAMEL will deliver an innovative personalised prevention model aimed at women 40-60yrs based upon a risk assessment stratification model considering sex and gender specific risk factors and a self-assessment and self-management approach using innovative digital technologies, empowering women to optimise their cardiovascular health.
The proposed CVD-Risk Assessment and Stratification scheme will only be possible by the cumulative risk factors analysis, fueled by AI, emerging from a wide number of different data sources, including clinical data from EHR, medical imaging, biomarkers, metabolomics, lifestyle information (sleep, physical activity, diet) from large cohorts and biobanks.
A consortium composed by 25 partners and Affiliated Entities coming from 11 countries, composed by 9 clinical entities, 6 research organisations and 10 industry and SMEs will develop, test and validate the personalised prevention program in observational and interventional studies in clinical sites in Colombia, Croatia, Greece, Lithuania and Spain. To that end, engagement of women aged 40-60, will take place from the onset on the co-design and co-creation of the studies and the self-management app ecosystem to be developed. Likewise, Gender in research will be mainstreamed all along the intervention.
CARAMEL will also deliver policy recommendation and clinical guidelines supporting the design and update of CVD Plans by health authorities and healthcare providers, considering novel AI based risk models, applicable to women aged 40-60 yrs.