As high-quality and high-throughput biological data at multiple different levels of spatial scale (gene through tissue) become increasingly available, we are tempted to define the cause-and-effect biological relationships that span across spatial scales with greater mechanistic detail. Doing so provides an opportunity to probe, for example, how receptor-ligand interactions in the membrane of one cell impacts the migratory behaviors of a neighboring cell, and, ultimately the mechanical properties of a remodeling blood vessel—and vice versa. Because these relationships are often complex, dynamic, and spatially heterogeneous, it becomes useful to employ multiscale computational modeling approaches that integrate biological phenomena in experimentally relevant ways. Agent-based modeling (ABM), which can simulate the behaviors of individual cells within a tissue, has recently been positioned as a linker to continuum models at both lower and higher levels of scale. In this talk, we will discuss some of the recent multiscale models that have coupled ABM with continuum modeling approaches at lower and higher levels of biological scale, including molecular level kinetics models of growth factor-ligand interactions and constrained mixture models of blood vessel biomechanics, respectively. We will focus on the conceptual methodologies that have underpinned how ABM were linked to other types of models, the technical challenges of interfacing other models with ABM, the types of simulation experiments that can be insightful, and the model validation approaches used in these examples.