Date of Award


Document Type


Degree Name

Master of Science (MS)


Electrical and Computer Engineering (Holcomb Dept. of)

Committee Member

Dr. Richard Groff, Committee Chair

Committee Member

Dr. Sarah Harcum

Committee Member

Dr. Adam Hoover


In the last three decades, biopharmaceuticals such as human growth hormone have been used to treat many diseases from HIV/AIDS to different types of cancer. Controlling the growth of recombinant cells, such as Escherichia coli (E. coli), is essential for productivity and efficiency of biopharmaceutical manufacturing. The cell growth can be controlled by regulating feed rate as the limiting factor. Hence, a robust and efficient feed controller – that only uses common industrial sensors – is desired. In this thesis, a controller is presented which can set the appropriate feed rate based on the metabolic state of E. coli. A robust metabolic state detector is designed which can detect whether the cells are in oxidative or overflow metabolism. And the controller periodically adjusts the feed rate based on the response of the cells. The controller, named BOOM II, maintains the cells close to the boundary of oxidative and overflow (BOOM) metabolism. Specifically, during a probe interval, the metabolic state detector exponentially increases the feed rate to the bioreactor. Then, by inspecting the real-time estimated oxygen uptake rate (OUR), the metabolic state is evaluated as oxidative if the sensitivity ratio (SR) signal passes a threshold, otherwise the metabolic state is considered to be in overflow. The performance of the BOOM II controller was validated by several fermen-tations and benchmarked against a robust and industrially tested controller that uses an exponential feed controller. Experiments that used the BOOM II controller re-sulted in higher cell densities, lower waste product levels and utilized less glucose than the parallel fermentation, using the exponential feed controller. The controller also detected metabolic changes to the culture due to growth phase shifts and re-combinant protein induction and adjusted the feed rate due to these disturbances. Since the BOOM II controller is based on metabolism fundamental concepts, it has the potential to work on different strains of E. coli, other bacteria, yeast and possibly mammalian cells.



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