Bio

B.S. ​Johns Hopkins University, 1997Ph.D. ​University of Virginia, 2002Post-Doc ​University of Virginia, 2004

"We use computational modeling to design new regenerative therapies for treating patients with diabetes, heart disease, and musculoskeletal disease."

Shayn Peirce-Cottler, Professor of Biomedical Engineering

Dr. Peirce-Cottler was born in Madison, Wisconsin and raised in Chapel Hill, NC. She received Bachelors of Science degrees in Biomedical Engineering and Engineering Mechanics from The Johns Hopkins University in 1997. She was a 4-time varsity letter winner in Women's Swimming, an Academic All-American, competed in the NCAA Div. III National Championships, and captained the team her senior year in college. She earned her Ph.D. in the Department of Biomedical Engineering at the University of Virginia in 2002. 

After a 2-year Post Doc at UVA, Dr. Peirce-Cottler joined the faculty in the Biomedical Engineering Department in 2004 as an Assistant Professor. Dr. Peirce-Cottler develops and uses computational models, in conjunction with novel experimental assays, to study complex, dynamic, and multi-cell biological systems. Her research focuses on understanding how heterogeneous cell behaviors and their interactions enable tissues to adapt over time, during physiological growth and in response to disease. Her multi-scale computational models employ agent-based modeling to bridge protein-level mechanisms with tissue-level, functional outcomes. Her research spans basic science discovery to the design of therapies for regenerative medicine. Specific areas of interest include acute and chronic inflammation, microvascular network patterning, and the role of stem cells in orchestrating tissue regeneration. 

Dr. Peirce-Cottler has taught courses on engineering and design, entrepreneurship, computational systems modeling, and cell and molecular biology to undergraduate students, graduate students, and medical school students. Dr. Peirce-Cottler is a past recipient of MIT Technology Review’s “TR100 Young Innovator Award” and the National Biomedical Engineering Society’s “Rita Schaffer Young Investigator Award”. She was recently elected into the American Institute for Medical and Biological Engineering College of Fellows. She is currently the President-Elect for The Microcirculatory Society and Chairs the NIH Modeling and Analysis of Biological Systems (MABS) Study Section.

Awards

  • MIT Technology Review's Top 100 Young Investigators 2004
  • Rita Shaffer Young Investigator Award 2004
  • Fellow of the American Institute for Medical and Biological Engineering 2016

Research Interests

  • Biomedical Data Sciences
  • Materials and Advanced Manufacturing for Biological Applications
  • Biotechnology and Biomolecular Engineering (Biomolecular Design, Cellular and Molecular Bioengineering)
  • Computational Systems Biology
  • Cardiovascular Engineering

Selected Publications

  • In Silico and In Vivo Experiments Reveal M-CSF Injections Accelerate Regeneration Following Muscle Laceration. Ann Biomed Eng. 2016 Oct 7. [Epub ahead of print] ABS Martin KS, Kegelman CD, Virgilio KM, Passipieri JA, Christ GJ, Blemker SS, Peirce SM. (2016)
  • Monocytes are recruited from venules during arteriogenesis in the murine spinotrapezius ligation model. Arterioscler Thromb Vasc Biol. 34(9):2012-22. Bruce AC, Kelly-Goss MR, Heuslein JL, Meisner JK, Price RJ, Peirce SM. (2014)
  • Multiscale Computational Models of Complex Biological Systems. Annu Rev Biomed Eng. 15:137-54. Walpole J, Papin JA, Peirce SM. (2013)
  • IFATS Series: The Role of Human Adipose-Derived Stromal Cells in Inflammatory Microvascular Remodeling and Evidence of a Perivascular Phenotype. Stem Cells. Stem Cells. 26(10):2682-90. Amos P.J., Shang H., Bailey A.M., Taylor A., Katz A.J., Peirce S.M. (2008).
  • Multicellular Simulation Predicts Microvascular Patterning and In Silico Tissue Assembly. FASEB Journal.10.1096/fj.03-0933fje. Peirce SM*, Van Gieson EJ*, & Skalak TC. (2004)

Courses Taught

  • BME 6101 Graduate Physiology I
  • BME 4550 Systems Bioengineering Modeling and Experimentation