One of the most important unsolved problems at the crossroads of engineering and medicine is the design of 'bioactive' materials that promote specific control over cellular processes via cell-surface interactions. Achieving the ability to control surface features of synthetic polymers that elicit bioactivity would lead to superior tissue engineering scaffolds, targeted drug delivery materials, antibacterial coatings, and novel diagnostic devices. The limiting challenge to research in this field is the lack of efficient experimental methods for exploring the vast variable space and complex phenomena governing polymer surface structures, chemistry, and their effects on cell response. To provide a new method for high-throughput characterization of cell-polymer interactions in a broad array of biomedical technology areas, this proposal will develop an innovative combinatorial approach to assaying cell response to polymer surface features. This method will allow rapid and efficient hypothesis testing and reductions in sample variance, leading to a more complete understanding of control of cell behavior on synthetic materials. The combinatorial approach proposed here will accomplish this through deposition polymer surface libraries with thousands of rationally designed combinations of compositions, thicknesses, and annealing temperatures each. The libraries can explore diverse surface chemistries, microstructures, and roughnesses. Following physical and chemical characterization, the libraries are cultured with desired cells, exposing the cells to a wide variety of surface features in a single experiment. These library cultures, which can be thought of as a type of """"""""lab-on-a-chip"""""""" technology, are amenable to staining, microscopy, and spectroscopy to determine cell response to hundreds of surface features in a single experiment. Such an approach allows rejection of biomaterial candidates that do not elicit desired biological responses prior to a time-consuming characterization regimen. As a result, structure-property hypothesis are evaluated only for the most promising materials and more rapidly and efficiently than with conventional approaches. This proposal will define the combinatorial polymer surface method, perform a careful statistical analysis of the technique relative to conventional 1-sample-1-measurement approaches, demonstrate coupling of combinatorial surface libraries with high-throughput screening instrumentation, and apply the new method to technologically relevant biomedical polymers.

Agency
National Institute of Health (NIH)
Institute
National Center for Research Resources (NCRR)
Type
Exploratory/Developmental Grants (R21)
Project #
5R21RR017425-02
Application #
6604997
Study Section
Special Emphasis Panel (ZRR1-BT-1 (01))
Program Officer
Farber, Gregory K
Project Start
2002-07-01
Project End
2005-06-30
Budget Start
2003-07-01
Budget End
2004-06-30
Support Year
2
Fiscal Year
2003
Total Cost
$131,447
Indirect Cost
Name
Georgia Institute of Technology
Department
Engineering (All Types)
Type
Schools of Engineering
DUNS #
097394084
City
Atlanta
State
GA
Country
United States
Zip Code
30332
Su, Jing; Meredith, J Carson (2009) Local histogram analysis: detecting cell-microstructure interactions on combinatorial biomaterial libraries. Comb Chem High Throughput Screen 12:626-33
Su, Jing; Zapata, Pedro J; Chen, Chien-Chiang et al. (2009) Local cell metrics: a novel method for analysis of cell-cell interactions. BMC Bioinformatics 10:350
Zapata, Pedro; Su, Jing; Garcia, Andres J et al. (2007) Quantitative high-throughput screening of osteoblast attachment, spreading, and proliferation on demixed polymer blend micropatterns. Biomacromolecules 8:1907-17