Real-Time Software-Hardware Integration for Dynamic Control of Tissue Mechanical Environments

About This Grant

Mechanical forces drive tissue function and pathophysiology, yet current high-throughput systems for drug development rarely incorporate mechanical forces, and those that do typically do not allow dynamic, feedback- based control over the forces acting on cells and/or engineered tissues. We propose to integrate key technologies developed by our team members: 1) rapid algorithms for directly estimating contractility of excitable tissues; 2) GPU-acceleration approaches for rapid computing; 3) externally triggered smart materials that can change their mechanical properties in response to magnetic fields; and 4) high-throughput engineered tissue platforms. This integration will allow us to create a high-throughput system that allows for real-time control over tissue mechanical loading based on the mechanical forces produced by the tissue. For this technology-development application, we propose milestone-driven efforts to optimize, validate, and integrate these technologies into a user-friendly, graphical-user-interface (GUI) supported platform. The approach we propose is unique in that the software-to-hardware interfacing, driven by imaging, can readily be adapted in the future by the research community, without requiring costly, user-dependent, one-time-use pure hardware-based approaches. The ability to parallelize the algorithm for computing tissue deformation, direct deformation estimation (DDE), will allow for dramatic acceleration of computing deformation, to the point that it can be computed in real-time, thereby allowing for magnetically-responsive biomaterials to be triggered in response to image-based data on contractility. We will demonstrate integration of our software-hardware interfacing based feedback approach by performing mechano-pharmacologic screens in skeletal muscle engineered from murine myoblasts and cardiac muscle engineered from human induced pluripotent stem cells. We will apply diverse loading regimes to the tissues, in combination with drugs known to have differential effects in mechanically loaded skeletal and heart muscle. We will also create tools for mining the resulting mechano-pharmacologic data. We envision that this technology will be broadly enabling for studies in mechanobiology and for improving translation of drug screens.