Integration of combinatorial synthesis, rapid screening, and computational modeling in biomaterials development

被引:69
作者
Smith, JR
Seyda, A
Weber, N
Knight, D
Abramson, S
Kohn, J [1 ]
机构
[1] Rutgers State Univ, Dept Mech & Aerosp Engn, Piscataway, NJ 08854 USA
[2] Rutgers State Univ, Ctr Computat Design, Piscataway, NJ 08854 USA
[3] Rutgers State Univ, Dept Chem & Biol Chem, Piscataway, NJ 08854 USA
[4] Rutgers State Univ, New Jersey Ctr Biomat, Piscataway, NJ 08854 USA
关键词
biocompatibility; biodegradable; biological applications of polymers; computer modeling; proteins;
D O I
10.1002/marc.200300193
中图分类号
O63 [高分子化学(高聚物)];
学科分类号
070305 ; 080501 ; 081704 ;
摘要
The advent of high-throughput combinatorial synthesis techniques in drug discovery has stimulated efforts to apply these techniques to the discovery of biomaterials. To be of practical utility, 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 biorelevant material properties, and (iii) computational methods to efficiently model different biological responses in the presence of polymers. Here we report the integration of these methodologies and illustrate the potential of this approach to accelerate the development of new biomaterials. The parallel synthesis of a library of 112 biodegradable polyarylates has been reported previously. This library was used to develop efficient screening techniques to determine biorelevant polymer properties (fibrinogen adsorption, gene expression in macrophages, growth of fetal rat lung fibroblasts (RLFs)). A Surrogate (semiempirical) Model was developed (i) to determine molecular-scale polymer properties that correlate to various biological responses, and (ii) to predict fibrinogen adsorption and RLF growth on polymeric surfaces. For 38 out of 45 polymers, the model predicted the amount of fibrinogen adsorbed correctly within the error of the experimental measurements. The growth of rat lung fibroblasts was correctly predicted by the model for 41 out of 48 polymers.
引用
收藏
页码:127 / 140
页数:14
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