Organ failure and tissue damage are major health problems. The current therapy of organ transplantation is inadequate because of the shortage of available donor organs, resulting in long waiting times. A promising alternative is tissue engineering, which seeks to create functional tissues to replace or repair damaged tissues using biomaterial-substitutes (scaffolds). Scaffolds have stringent design requirements, such a three-dimensional (3D) internal-porous structure, patient-specific geometry, and appropriate materials and mechanical properties to encourage the growth of functional living tissues. Current scaffold manufacturing methods typically adopt a trial-and-error approach, which does not consider comprehensive interactions among design, material and process and results in scaffolds with unpredictable properties. The goal of this EArly-concept Grant for Exploratory Research (EAGER) project is to develop an intelligent system to guide the optimization of shape, materials and process parameters, resulting in a smart decision matrix for designing and manufacturing 3D scaffolds.

The objective of this project is to research an SOA (Service Oriented Architecture) based integrated technical and social networking platform that enables effective human-human collaboration and communication among the domains of product (3D porous scaffold), process (Fused Deposition Modelling-FDM) and material (thermoplastic polycaprolactone-PCL). This smart platform, enabled by semantic web technology and social network analysis, embeds the capability of intelligent configurations of design and manufacturing solutions; therefore promoting information and knowledge reuse and cost reduction. Although the focus of this work is on porous PCL scaffolds using the FDM process, the knowledge-driven, smart platform can be extended to other biomanufacturing methods.

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Syracuse University
United States
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