In Silico Cell Cycle Predictor for Mammalian Cell Culture Bioreactor Using Agent-Based Modeling Approach

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• 作者：Elif S. Bayrak¹ ; ^{ebayrak@amgen.com" class="auth_mail" title="E-mail the corresponding author} ; Tony Wang¹ ; ^{tonyw@amgen.com" class="auth_mail" title="E-mail the corresponding author} ; Matt Jerums¹ ; ^{mjerums@amgen.com" class="auth_mail" title="E-mail the corresponding author} ; Myra Coufal¹ ; ^{mcoufal@amgen.com" class="auth_mail" title="E-mail the corresponding author} ; Chetan Goudar¹ ; ^{cgoudar@amgen.com" class="auth_mail" title="E-mail the corresponding author} ; Ali Cinar² ; ^{cinar@iit.edu" class="auth_mail" title="E-mail the corresponding author} ; Cenk Undey¹ ; ^{cundey@amgen.com" class="auth_mail" title="E-mail the corresponding author}
• 关键词：CHO cells ; Agent-based modeling ; cell cycle ; mammalian cell culture
• 刊名：IFAC-PapersOnLine
• 出版年：2016
• 出版时间：2016
• 年：2016
• 卷：49
• 期：7
• 页码：200-205
• 全文大小：889 K

文摘

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.