Sensor-based Characterization and Control of Additive Biomanufacturing Processes

According to data provided by the U.S. Department of Health and Human Services, the waiting list of organ transplantation as of April 2021 is approximately 107,550 out of which 90,908 patients are waiting for a kidney and 11,871 are waiting for a liver. In 2020, only 39,000 transplants were performed. A promising potential solution to this organ shortage crisis is rapid development of drugs for end-stage kidney and liver failure and the fabrication of organs using additive biomanufacturing (Bio-AM) processes. While progress toward industrial-scale production of 3D-bioprinted tissue models and organs remains hindered by various biological and tissue engineering challenges, such as vascularization and innervation, quality Bio-AM is impeded by lack of integrated process monitoring and control strategies. This dissertation aims to address the compelling need to incorporate sensing and control with Bio-AM processes, which are currently open-loop processes and improve the scalability and reliability of additively biomanufactured products.
The specific aim is to develop a closed loop-controlled additive biomanufacturing process capable of fabricating 3D-bioprinted biological constructs (mini-tissues) of controlled mechanical properties. The proposed methodology is based on the use of embedded sensors and real-time material property sensing for feedback control of the bioprinted constructs mechanical property. There are three objectives of this dissertation: (1) experimenting and modeling the processes to understand the causal effect of process-material interactions on Bio-AM defects, (2) use of sensors to detect defects during printing, (3) prevention of the propagation of defects through closed-loop process control.

This will help us understand the fundamentals of the bio-physical process interactions that govern the quality of printed biological tissue through empirical investigation of the sensor-based data This will also provide us with a real-time monitoring, closed-loop quality control strategy to prevent the propagation of quality defects by executing corrective actions during the whole duration of the printing process.