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主讲人简介：
Prof. Joachim Kohnis the director of the New Jersey Center for Biomaterials, and the Chair of the International College of Fellows of Biomaterials Science and Engineering.He has 69 issued US Patents on novel biomaterials and seven companies have licensed his technologies.Prof. Kohn has received many awards and honors, including the prestigious Thomas Alva Edison Patent Award, and the Clemson Award. His research interests ranges from synthetic polymer chemistry and materials science to drug delivery, cell biology, tissue engineering, and regenerative medicine.He pioneered the use of combinatorial and computational methods for the optimization of biomaterials for specific medical applications. He discovered "pseudo-poly(amino acid)s"- a new class of polymers, which have been used to develop medical devices for implantationin about 100,000 patients.
报告摘要：
Our newly developed combinatorial biomaterials discovery paradigm uses parallel synthesis of polymer libraries, rapid screening and characterization, and computational modeling of cell-biomaterial interactions to identify promising lead polymers for use in the design of specific medical implants. Within the overall development path, from design to FDA clearance of the device, the initial material optimization can be a significant effort. Since the time, cost, and risk of this initial material discovery effort can be substantial, there has been a pronounced tendency to focus research and development programs on well-established polymers, such as poly(lactic acid), rather than on the design of materials that are specifically optimized for their intended application.
Our efforts to develop combinatorial approaches to biomaterials design require (i) the availability of parallel synthesis techniques to generate libraries of polymers, (ii) efficient assays for the rapid characterization of bio-relevant material properties, and (iii) computational methods to efficiently model different biological responses in the presence of polymers. Here we report on the integration of these methodologies and illustrate the potential of this approach. The bio-relevant polymer properties within a library of polymers were studied using efficient screening techniques to determine fibrinogen adsorption, gene expression in macrophages, and growth of fetal rat lung fibroblasts. A Surrogate (semi-empirical) Model was developed (i) to determine molecular-scale polymer properties that correlate to various biological responses and (ii) to predict fibrinogen adsorption and cell growth on polymeric surfaces. Recently obtained results will be reported on the application of this approach to the development of several innovative biomaterials products.
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