creator Jackson, Robert David 2019 Spring 2019 Thesis Illinois Institute of Technology ChBE / Chemical and Biological Engineering advisor Cinar, Ali Chemical engineering Agent-Based Modeling Biopharmaceuticals Cell Culture High-Performance Computing Python Unstructured Model en This work uses two different techniques for modeling mammalian cell culture: Differential Equation (DE) based Modeling and Agent-Based Modeling (ABM). The development of both models was done in free open-source software instead of the traditional software that requires the purchase of licenses. The DE model was developed in Python and can predict total, viable, and dead cell densities, glucose, lactate, glutamine, ammonia, and product titer. To expand on the detail level capabilities of previous DE models it has added temperature, pH, and dissolved oxygen dependence. The ABM can predict viable cell density, glucose, lactate, and the distribution of the three experimentally detectable cell cycle phases G1G0, S, and G2M. The ABM was developed for high-performance computing to improve on a previous ABM and allow for running at a hundred-fold smaller run-time with a much higher capacity for the amount of agents that can be simulated. born digital application/pdf In Copyright http://rightsstatements.org/page/InC/1.0/ Restricted Access http://hdl.handle.net/10560/islandora:1000833