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Title:3D printing of biological machines for biology and medicine
Author(s):Chan, Vincent
Director of Research:Bashir, Rashid
Doctoral Committee Chair(s):Bashir, Rashid; Kong, Hyun Joon
Doctoral Committee Member(s):Saif, M. Taher A.; Schook, Lawrence B.
Department / Program:Bioengineering
Degree Granting Institution:University of Illinois at Urbana-Champaign
Subject(s):3D printing
biological machines
microvascular stamp
rat heart cells
Abstract:A cell-based biological machine is a set of sub-components consisting of living cells and cell-instructive micro-environments that interact to perform a prescribed task. Cell types such as neurons, muscle cells, and endothelial cells can be programmed for sensing, information processing, actuation, protein expression, or transport. By combining clusters of these different cell types, complex biological machines can be created for specific applications in health, security, and the environment. The potential benefits and social implications of these systems are enormous. In health, biological machines can enhance tissues and organs by engineering a collection of cells to sense drug levels in the bloodstream, process it, and instruct secretory cells to counteract it. In security, ‘noses’ can be grown that are comparable or even more sensitive than that of dogs to identify explosives or toxic substances during airport screenings. In the environment, biological robots or organisms can be produced to swim toward an oil spill, degrade it into harmless byproducts, and replicate as needed. Although this may seem like the stuff of science fiction, many scientists and researchers believe that some or all of these ideas could become a reality in the near-future. The realization of biological machines and their sub-components will require the development of enabling technologies. These technologies will be critical in studying the building blocks of the biological machinery. An intelligent and instructive micro-environment is critical in our efforts to understand and design cellular systems. The cells have to thrive, communicate, and proliferate in such a micro-environment while performing their designated functions. These ‘instructive’ and ‘designer’ 2D and 3D micro-environments should form the scaffolding of biological machines, and have spatially controlled mechanical and chemical properties to control their functionalities. Advancements in enabling technologies that can fabricate the desired intelligent scaffold will greatly expedite our progress in developing biological machines. Our central hypothesis is that by integrating 3D printing technology with appropriate biomaterials, we will have the capability to create spatially controlled 2D and 3D micro-environments that have the desired permeability, mechanical stiffness, chemical properties, and number of cell adhesion sites. With this technology, we will be able to build simple biological machines with prescribed tasks. In particular, we propose building two simple biological machines with the following functionalities: (i) a microvascular stamp that can pattern new blood vessels, and (ii) a locomotive bio-robot that can walk in fluid. These modules can potentially interact as sub-components for more complex biological machines. Please refer to the posters for detailed information and accomplishments of these two biological machines. The idea of building biological machines with living cells is an innovative approach that is being developed as a new scientific discipline by the NSF Science and Technology Center (STC) entitled Emerging Behaviors of Integrated Cellular Systems (EBICS). New technological platforms are essential to bridge molecular scale interactions with macroscale behavior of complex multi-cellular systems. Our work to introduce 3D printing technology as one of these platforms will not only advance our long-term goal of creating complex biological machines, but also significantly enhance our understanding of emergent biological behaviors under integrated biochemical and physical cues at the cellular, cell network, and cell population levels.
Issue Date:2013-05-24
Rights Information:Copyright 2012 Vincent Chan
Date Available in IDEALS:2013-05-24
Date Deposited:2013-05

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