Multi-Agent Systems for Biomedical Simulation: Modeling Vascularization of Porous Scaffolds

  • Hamidreza Mehdizadeh
  • Arsun Artel
  • Eric M. Brey
  • Ali Cinar
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7047)


An interesting application of multi-agent systems (MAS) is in modeling systems that can be represented by independent entities interacting together, the so-called agent-based modeling (ABM). In this paper MAS paradigm is used as a promising technique for representing complex biomedical systems. A brief survey of some ABM of biomedical systems is presented, followed by the description of a multi-layered agent-based framework developed in our own labs to model the process of sprouting angiogenesis (blood vessel formation) within polymeric porous scaffolds used for regenerative medicine. The ABM structure developed and challenges in modeling systems with a large number of rapidly increasing interacting agents are discussed. 2D and 3D case studies are presented to investigate the impact of scaffold pore structure on vessel growth. MAS provides a valuable tool for studying highly complex biological and biomedical systems, and for investigating ways of intervening in such systems.


agent-based simulation agent-based modeling emergent behavior angiogenesis 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    An, G.: In silico experiments of existing and hypothetical cytokine-directed clinical trials using agent-based modeling. Crit. Care Med. 32, 2050–2060 (2004)CrossRefGoogle Scholar
  2. 2.
    Artel, A.: Agent-based techniques in local, autonomous and adaptive decision-making. PhD dissertation: Illinois Institute of Technology (2010)Google Scholar
  3. 3.
    Artel, A., Mehdizadeh, H., Chiu, Y.-C., Brey, E.M., Cinar, A.: An Agent-Based Model for the Investigation of Neovascularization within Porous Scaffolds. Tissue Eng. Part A 17, 2133–2141 (2011)CrossRefGoogle Scholar
  4. 4.
    Ausk, B.J., Gross, T.S., Srinivasan, S.: An agent based model for real-time signaling induced in osteocytic networks by mechanical stimuli. J. Biomech. 39 (2006)Google Scholar
  5. 5.
    Autodesk 3ds Max Products: 3D modeling, animation and rendering software,
  6. 6.
    Brey, E.M., McIntire, L.V., Johnston, C.M., Reece, G.P., Patrick, C.W.: Three-Dimensional, Quantitative Analysis of Desmin and Smooth Muscle Alpha Actin Expression During Angiogenesis. Ann. Biomed. Eng. 32, 1100–1107 (2004)CrossRefGoogle Scholar
  7. 7.
    Brey, E.M., Uriel, S., Greisler, H.P., Patrick Jr., C.W., McIntire, L.V.: Therapeutic Neovascularization: Contributions from Bioengineering. Tissue Engineering 11, 567–584 (2005)CrossRefGoogle Scholar
  8. 8.
    Brown, B.N., Price, I.M., Toapanta, F.R., Dealmeida, D.R., Wiley, C.A., Ross, T.M., Oury, T.D., Vodovotz, Y.: An agent-based model of inflammation and fibrosis following particulate exposure in the lung. Math. Biosci. 231, 186–196 (2011)MathSciNetCrossRefzbMATHGoogle Scholar
  9. 9.
    Carmeliet, P., Jain, R.K.: Angiogenesis in cancer and other diseases. Nature 14, 249–257 (2000)CrossRefGoogle Scholar
  10. 10.
    Chiu, Y.C., Cheng, M.H., Uriel, S., Brey, E.M.: Materials for Engineering Vascularized Adipose Tissue. J. Tissue Viability 20, 37–48 (2011)CrossRefGoogle Scholar
  11. 11.
    Da-Jun, T., Tang, F., Lee, T., Sarda, D., Krishnan, A., Goryachev, A.B.: Parallel Computing Platform for the Agent-Based Modeling of Multicellular Biological Systems. In: Liew, K.-M., Shen, H., See, S., Cai, W. (eds.) PDCAT 2004. LNCS, vol. 3320, pp. 5–8. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  12. 12.
    Dastani, M., van Riemsdijk, M.B., Winikoff, M.: Rich Goal Types in Agent Programming. In: Proc. of 10th Int. Conf. on Autonomous Agents and Multiagent Systems (AAMAS 2011), pp. 405–412 (2011)Google Scholar
  13. 13.
    Grant, M.R., Mostov, K.E., Tlsty, T.D., Hunt, C.A.: Simulating properties of in vitro epithelial cell morphogenesis. PLoS Comput. Biol. 2, e129, Epub. (2006)CrossRefGoogle Scholar
  14. 14.
    Hart, P.E., Nilsson, N.J., Raphael, B.: A Formal Basis for the Heuristic Determination of Minimum Cost Paths. IEEE Transactions on Systems Science and Cybernetics 4, 100–107 (1968)CrossRefGoogle Scholar
  15. 15.
    Levine, H.A., Nilsen-Hamilton, M.: Angiogenesis - A biochemical/mathematical perspective. In: Tutorials in Mathematical Biosciences III; Cell Cycle, Proliferation and Cancer, pp. 23–76 (2006)Google Scholar
  16. 16.
    Liu, G., Qutub, A.A., Vempati, P., Mac Gabhann, F., Popel, A.S.: Module-based multiscale simulation of angiogenesis in skeletal muscle. Theor. Biol. Med. Model. 8 (2011)Google Scholar
  17. 17.
    Muthukkaruppan, V.R., Kubai, L., Auerbach, R.: Tumor-induced neovascularization in the mouse eye. J. Natl. Cancer Inst. 69, 699–708 (1982)Google Scholar
  18. 18.
    North, M.J., Collier, N.T., Vos, J.R.: Experiences Creating Three Implementations of the Repast Agent Modeling Toolkit. ACM Transactions on Modeling and Computer Simulation 16, 1–25 (2006)CrossRefGoogle Scholar
  19. 19.
    O’Neil, C.A., Sattenspiel, L.: Agent-based modeling of the spread of the 1918-1919 flu in three Canadian fur trading communities. Am. J. Hum. Biol. 22, 757–767 (2010)CrossRefGoogle Scholar
  20. 20.
    Papavasiliou, G., Cheng, M.H., Brey, E.M.: Strategies for Vascularization of Polymer Scaffolds. J. Investig. Med. 58, 834–844 (2010)CrossRefGoogle Scholar
  21. 21.
    Railsback, S.F., Lytinen, S.L., Jackson, S.K.: Agent-based Simulation Platforms. Review and Development Recommendations Simulation 82, 609–623 (2006)Google Scholar
  22. 22.
    Repast Home Page: Repast Organization for Architecture and Design, Chicago, IL,
  23. 23.
    Rouwkema, J., Rivron, N.C., van Blitterswijk, C.A.: Vascularization in tissue engineering. Trends Biotechnol. 26, 434–441 (2008)CrossRefGoogle Scholar
  24. 24.
    Thorne, B.C., Bailey, A.M., DeSimone, D.W., Peirce, S.M.: Agent-based modeling of multicell morphogenic processes during development. Birth Defects Res. C. Embryo. Today. 81, 344–353 (2007)CrossRefGoogle Scholar
  25. 25.
    Thorne, B.C., Bailey, A.M., Peirce, S.M.: Combining experiments with multi-cell agent-based modeling to study biological tissue patterning. Brief. Bioinform. 8, 245–257 (2007)CrossRefGoogle Scholar
  26. 26.
    van Riemsdijk, M.B., Dastani, M., Winikoff, M.: Goals in agent systems: A unifying framework. In: Proc. of 7th Int. Conf. on Autonomous Agents and Multiagent Systems (AAMAS 2008), pp. 713–720 (2008)Google Scholar
  27. 27.
    Zhang, L., Chen, L.L., Deisboeck, T.S.: Multi-scale, multi-resolution brain cancer modeling. Math. Comput. Simul. 79, 2021–2035 (2009)MathSciNetCrossRefzbMATHGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Hamidreza Mehdizadeh
    • 1
  • Arsun Artel
    • 1
  • Eric M. Brey
    • 1
    • 2
  • Ali Cinar
    • 1
  1. 1.Illinois Institute of TechnologyChicagoUSA
  2. 2.Research Service, Hines VA HospitalHinesUSA

Personalised recommendations