Abstract

Collagen type I, the main component of the extracellular matrix in vertebrates, is widely used in tissue engineering applications. This is on account that collagen molecules can self-assemble under certain conditions into 3D fibrillar hydrogels. Although there is an extensive body of literature studying collagen self-assembly, there is a lack of systematic understanding on how different experimental factors, such as pH and temperature, and their cumulative effects guide the self-assembly process. In this work, a comprehensive workflow to study the interactive effects of several assembly parameters on the collagen self-assembly process is implemented. This workflow consists of: 1) efficient statistical sampling based on Design of Experiments, 2) high-throughput and automated data collection and 3) automated data analysis. This approach enables to screen several parameters simultaneously and derive a set of mathematical equationsthat link parameters with the kinetics and morphological aspects of collagen self-assembly, and can be used to design collagen constructs with predefinedcharacteristics.

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