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PLoS One. 2015 Sep 8;10(9):e0137392. doi: 10.1371/journal.pone.0137392. eCollection 2015.

Proportional-Integral-Derivative (PID) Control of Secreted Factors for Blood Stem Cell Culture.

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Institute of Biomaterials and Biomedical Engineering, University of Toronto, Toronto, Ontario, Canada.
Institute of Biomaterials and Biomedical Engineering, University of Toronto, Toronto, Ontario, Canada; The Donnelly Centre, University of Toronto, Toronto, Ontario, Canada; Department of Chemical Engineering and Applied Chemistry, University of Toronto, Toronto, Ontario, Canada; McEwen Centre for Regenerative Medicine, University of Health Network, Toronto, Ontario, Canada.


Clinical use of umbilical cord blood has typically been limited by the need to expand hematopoietic stem and progenitor cells (HSPC) ex vivo. This expansion is challenging due to the accumulation of secreted signaling factors in the culture that have a negative regulatory effect on HSPC output. Strategies for global regulation of these factors through dilution have been developed, but do not accommodate the dynamic nature or inherent variability of hematopoietic cell culture. We have developed a mathematical model to simulate the impact of feedback control on in vitro hematopoiesis, and used it to design a proportional-integral-derivative (PID) control algorithm. This algorithm was implemented with a fed-batch bioreactor to regulate the concentrations of secreted factors. Controlling the concentration of a key target factor, TGF-β1, through dilution limited the negative effect it had on HSPCs, and allowed global control of other similarly-produced inhibitory endogenous factors. The PID control algorithm effectively maintained the target soluble factor at the target concentration. We show that feedback controlled dilution is predicted to be a more cost effective dilution strategy compared to other open-loop strategies, and can enhance HSPC expansion in short term culture. This study demonstrates the utility of secreted factor process control strategies to optimize stem cell culture systems, and motivates the development of multi-analyte protein sensors to automate the manufacturing of cell therapies.

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