Cardiovascular diseases, particularly myocardial infarction, are the main causes of death and long-term health complications worldwide. Post-myocardial infarction cardiac remodeling often leads to heart failure due to the inability to fully restore cardiac function. Architected biomaterials that counteract adverse remodeling by restoring the heart's initial biomechanical function present a promising therapeutic approach. Hence, this study focuses on developing a cardiac patch designed to actively support damaged myocardial tissue, aiming to reduce adverse remodeling and improve heart function after infarction.

Our patch design relies on advanced computational models, including finite element analysis (FEA), neural networks, and machine learning algorithms. These tools are employed to assess various smart topologies and predict optimal designs that enhance the patch’s therapeutic performance. The integration of these models allows for the discovery and optimization of different configurations to enhance mechanical properties.

A metamaterial structure that is particularly suitable for this study exhibits a negative Poisson’s ratio. These structures enhance the patch’s flexibility, allowing it to more effectively mimic the natural movements of the heart tissue. In addition, unit cells of varying sizes are integrated into this design. This technique enables a gradient in porosity and structural dimensions. This is especially useful for reproducing the natural stiffness gradient from infarcted tissue to healthy tissue, ensuring a smoother mechanical integration.

Our ultimate goal is to create a highly customizable and effective solution for heart repair by modulating cardiac tissue remodeling through biomechanical stimuli, which could potentially open new doors in regenerative medicine. By tailoring the patch to each patient’s specific needs, our strategy could lead to better long-term outcomes for those recovering from heart attacks.