Convergence is an approach to problem solving that cuts across disciplinary boundaries. It integrates knowledge, tools, and ways of thinking from life and health sciences, physical, mathematical, and computational sciences, engineering disciplines, and beyond to form a comprehensive synthetic framework for tackling scientific and societal challenges that exist at the interfaces of multiple fields. By merging these diverse areas of expertise in a network of partnerships, convergence stimulates innovation from basic science discovery to translational application. It provides fertile ground for new collaborations that engage stakeholders and partners not only from academia, but also from national laboratories, industry, clinical settings, and funding bodies. The concept of convergence as represented in this report is thus meant to capture two closely relatedbut distinct properties: the convergence of expertise necessary to address a set of research problems, and the formation of the web of partnerships involved in supporting such scientific investigations and enabling the resulting advances to be translated into new forms of innovation and new products.
Many institutions are interested in how they can better facilitate convergent research. Despite the presence of established models, however, cultural and institutional roadblocks can still slow the creation of self-sustaining ecosystems of convergence. Institutions often have little guidance on how to establish effective programs, what challenges they might encounter, and what strategies other organizations have used to solve the problems that arise. The present study was undertaken to address this gap. It aims to explore mechanisms used by organizations and programs to support convergent research and provide informed guidance for the community.