This study aims to leverage digital twin technology for simulating drug interventions in myocardial infarction (MI) patients. By integrating genetic, clinical, and imaging data from the UK Biobank, we seek to develop personalized cardiac models capable of accurately predicting individual cardiac responses to various drugs. The objectives of this research include:
Investigating how genetic and environmental factors influence drug responses in MI patients.
Validating the feasibility of digital twin technology in cardiovascular drug testing.
Providing potential personalized therapeutic strategies to support clinical decision-making.
The scientific rationale of this research lies in employing innovative digital modeling to bridge the gap between generalized clinical trials and individual patient care.
