Over the last fifteen years sophisticated computing has kept pace with all the new “-omics” of biological research-genomics, proteomics, just to name a few. “Now we have the tools to integrate what we've been identifying and labeling,” says Assistant Professor of Biomedical Engineering Shayn Peirce, who has won several recent accolades for work tackling what she sees as the central problem of the postgenomic era: How do the many genes and gene products now identified work together across multiple length and time scales and during development, maturation and adaptation to assemble functional tissues?

Enter computing. Shayn’s group has developed a dynamic, quantitative computational model of blood vessel growth that simulates, cell-by-cell, experiments in the lab. Her model tracks thousands of cell "agents" as they move, multiply, and adapt in response to a set of rules (mined from independent literature) representing the myriad of factors that orchestrate cell behavior. “We’re in the vanguard of simulating cells' interactions with each other and their environment in a computational way,” says Peirce. Each cell in the simulation responds on its own to the entire set of rules and to external stimuli, and the cumulative response is a new arrangement of cells-for example, a remodeled blood vessel network.

The Biomedical Engineering Society awarded Peirce its 2004 Young Investigator Award for capturing in silico a discovery made in vivo-namely, that blood pressure and a growth factor can be used to guide how and where the tiniest new blood vessels will grow. This type of hybrid experimentation-computation is a hallmark of the new field of Systems Biology, where theory, data, and modeling interrelate to capture how sets of particular molecular signals can account for complex properties of whole tissues.

For example, to test if a certain growth factor could help adipose-derived progenitor cells (stem cells from human fat) to grow more blood vessels, Peirce first tests her hypothesis in the model. If the simulation shows increased vascularity, she knows what to look for in the lab. When lab work leads to a new rule on cell behavior, it is used to enhance the model. This fundamentally iterative process helps Peirce discover if a readily available source of adult stem cells can give rise to daughter cells that support or ignite the assembly of new microvessels.

Multicellular computational models like Peirce’s are one of the technologies that will revolutionize drug discovery and speed the success of tissue engineering. “The sweeping thing to say is that the model is really for figuring out which aspects of a system you can predictably change,” says Peirce. “An added benefit is that you deepen the investigation at the bench. You really get intellectually intimate with the biological system.”