More than 9% of the US population suffers from diabetes, and the associated healthcare costs are among the highest of the major diseases. There is currently no cure for diabetes, and treatment to control blood sugar entails frequent insulin injections but does not prevent long-term complications such as blindness and heart disease. Pancreatic cell transplantation to restore the production of insulin is severely limited by the scarcity of donor tissue. Converting stem cells to insulin-producing cells may provide an answer, but there are still many challenges that prevent the production of sufficient numbers of these cells. Using experiments and computational modeling, this project is systematically developing an improved biomanufacturing system that will increase the production rate of pancreatic cells while at a lower cost. The planned work is providing interdisciplinary training for undergraduate and graduate students in STEM fields with an emphasis on biomanufacturing. Educational and outreach activities include summer workshops for high school students, featuring laboratory research, and lectures relevant to stem cell manufacturing.
In this interdisciplinary project, a process is being engineered using automated stirred-suspension bioreactor cultivation for the conversion of human pluripotent stem cells (hPSCs) to functional beta-cells and further maturation to enhanced beta-cells (eBCs). Computational modeling, based on population balance equations, is being combined with bioreactor experimentation to screen and select conditions in a systematic and rational fashion for optimal beta-cell yields with lower costs. Efficiency and reproducibility in the biomanufacturing process are key goals in this process engineering approach. In particular, the following specific aims are being pursued: 1) differentiating hPSCs to immature beta-cells in stirred suspension bioreactors; 2) inducing the maturation of hPSC-derived beta-cells to functional eBCs in bioreactor culture; and 3) producing beta-cells from hPSCs and driving their maturation to eBCs in a fully automated bioprocess. The utilization of quantitative models will result in a rule-based design for hPSC differentiation and bioprocessing and is compatible with quality-by-design concepts in pharmaceutical development.
