Stratification, Management, and Guidance of Hypertrophic Cardiomyopathy Patients Using Hybrid Digital Twin Solutions

The goal of SMASH-HCM is to develop a digital twin or virtual model of the heart and vascular system with sympathetic nerve control that integrates multi-scale and multi-organ spatiotemporal biophysical data from a multitude of sources. SMASH-HCM's digital twin powered platform will dramatically improve hypertrophic cardiomyopathy (HCM) patient stratification and disease management through stepwise deep phenotyping integrated in clinical and patient-guided workflows.

The aim of this SMASH-HCM study is with available well-characterized clinical data and existing iPSC derived cardiomyocyte data from HCM patients to find better predictors of worse outcomes i.e. potentially lethal arrhythmias, heart failure, sudden cardiac arrest in HCM patients. Additionally with artificial intelligence (AI) to find markers of good outcome so that we could focus more on those who would potentially benefit more from the intense follow up. Additionally our aim is to create a digital twin by collecting all possible clinical data from the HCM patients and also from currently healthy mutation carriers to be able to predicts the clinical out in more personal way and also toddling treatment strategies in more personal manner.