Abstract
An Agent-based computational modeling approach was used to develop a model to simulate individual mammalian cell behavior and its cycle regulation in response to dynamic bioreactor conditions. The model can be used as an in silico cell cycle predictor when provided with data from ongoing bioreactor runs. Rules were developed to regulate the distinct cell cycle events as well as to apply decision-making at the critical cellular checkpoints. The model was constructed and validated using different sets of experimental cell culture conditions with cell culture parameters measured using a flow cytometer and other instrumentation.
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