ABSTRACT This research program integrates concepts of biology, physics, and applied mathematics to produce new understanding connecting cell force generation and transmission to migration. A major area of focus is collective cell migration, which underlies essential processes in development of tissues and progression of disease. The long-term vision of this research program is to apply experiment-informed computational models to predict how biochemical perturbations will affect the collective migration. Such models would enable design of methods to control the collective migration, which would lead to therapies with important impacts on human health, such as healing of chronic wounds, slowing invasion of cancer cells, and engineering tissues of desired size and shape. Achieving this modeling capability requires a biophysical approach, because the motion results from physical forces that are produced by the cells in response to biological signaling and transmitted across the cell layer. Although there exist methods to measure the forces, the common methods used are often uninformative for physics-based models of collective motion or for studies of the biochemical signaling that produces the forces. Thus, there is a need to improve upon current methods and to develop new methods to quantify forces while simultaneously connecting to both the physics-based models and the underlying biology. The goals for this 5-year MIRA award are to advance methods in quantifying cell forces in both in vitro and in vivo systems and to apply those methods to build frameworks that enable modeling the relationships between biochemical signaling, forces, and motion in collective cell migration. To accomplish these goals, the research will take two parallel approaches. One approach will improve upon currently available experimental methods to measure forces produced by each cell, including the variation of those forces in space and time. The other approach will develop a new methodology for quantifying cell forces by integrating methods of data science with physics. Importantly, this new methodology will be able to infer cell forces from only images of the cells, meaning it can be applied in complicated cell culture systems and even in vivo. The two approaches will be used to study the collective migration by organizing the research around two complementary frameworks: the first will study collective motion by focusing on the forces associated with local rearrangements between neighboring cells; the second will determine how motion is coordinated across multicellular groups. Together, these two frameworks will provide a means to organize observations about collective migration into a holistic understanding, which will hint at the underlying biological mechanisms and provide an essential step forward towards achieving experiment-informed computational models that can predict the collective migration in applications such as wound healing, cancer invasion, and tissue eng...