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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 equations that link parameters with the kinetics and morphological aspects of collagen self‐assembly, and can be used to design collagen constructs with predefined characteristics. [ABSTRACT FROM AUTHOR]