Among cardiovascular diseases, ischemic heart disease remains a leading cause of mortality worldwide. While revascularization shows promise as an effective therapeutic method, the large patient variability in genetics, comorbidities, and response to growth factors increases the complexity of standardized regenerative therapies. This project focuses on developing a novel digital twin of blood vessel growth after cardiac injury, based on genetic information and live imaging data. This will make it possible to reverse engineer the precise genetic interventions needed to produce the desired vasculature, as well as to safely test and improve gene-editing techniques in silico. The project will have broad societal and educational applications. All software packages will be made open-source, and a web interface will be created to help in clinical settings. Immersive educational tools for students will be developed to visualize 3D simulations of vascular growth in partnership with Iowa State’s Virtual Reality Center. The project’s integration of mathematics, gene editing, and computational modeling will help train a new generation of scientists at the nexus of mathematics and medicine. This project develops a novel multiscale digital twin framework to predict and control blood vessel growth by integrating molecular signaling dynamics, cellular migration behavior, sprouting patterns, and tissue-level growth and remodeling. The research will develop (1) a multiscale molecular-to-cel