A new bioreactor adapts to materials state and builds a growth model for vascular tissue engineering.

Bioreactors are a promising enabling technology for vascular tissue engineering. Beyond their value for the scale-up and manufacturing of tissue-engineered blood vessels, bioreactors represent a potential path toward the understanding of the regeneration process of tissues in vitro, toward the development of mathematical models for growth and remodeling in tissue engineering, and toward the study of pathological conditions. To achieve these promises, bioreactors must overcome the paradigm of a black box for the growth of tissues and become a tool for the study of growth in tissue engineering. An advanced control strategy was developed to study and maximize growth in bioreactors. The aim of this paper is to validate experimentally the ability of this controller to build knowledge during the culture of a tissue-engineered blood vessel. During the experiments, the controller proposed linear regression models, therefore making hypotheses on the parameters that influence growth; then, it chose experiments to refine these models, therefore verifying these hypotheses. These results show that tissue maturation in bioreactors can become more efficient by acquiring information about the process, and by dynamically adapting culture conditions according to this information input.