ENH proof summary section
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@ -572,23 +572,23 @@ approved T cell expansion technologies involve \acd{3} and \acd{28} \glspl{mab},
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usually mounted on magnetic beads. This method fails to recapitulate many key
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usually mounted on magnetic beads. This method fails to recapitulate many key
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signals found \invivo{} and is also heavily licensed by a few companies,
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signals found \invivo{} and is also heavily licensed by a few companies,
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limiting its long-term usefulness to manufactures and clinicians. Furthermore,
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limiting its long-term usefulness to manufactures and clinicians. Furthermore,
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highly potent anti-tumor T cells are generally less-differentiated subtypes such
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highly potent, anti-tumor T cells are generally less-differentiated subtypes
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as \acrlongpl{tcm} and \acrlongpl{tscm}. Despite this understanding, little has
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such as \acrlongpl{tcm} and \acrlongpl{tscm}. Despite this understanding, little
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been done to optimize T cell expansion for generating these subtypes, including
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has been done to optimize T cell expansion for generating these subtypes,
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measurement and feedback control strategies that are necessary for any modern
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including measurement and feedback control strategies that are necessary for any
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manufacturing process.
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modern manufacturing process.
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The goal of this dissertation was to develop a microcarrier-based \gls{dms} T
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The goal of this dissertation was to develop a microcarrier-based \gls{dms} T
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cell expansion system and determine biologically-meaningful \glspl{cqa} and
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cell expansion system and determine biologically-meaningful \glspl{cqa} and
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\glspl{cpp} that could be used to optimize for highly-potent T cells. In
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\glspl{cpp} that could be used to optimize for highly-potent T cells. In
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\cref{aim1}, we develop and characterized the \gls{dms} system, including
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\cref{aim1}, we develop and characterized the \gls{dms} system, including
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quality control steps. We also demonstrate the feasiblity of expanding
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quality control steps. We also demonstrate the feasibility of expanding
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high-quality T cells. In \cref{aim2a,aim2b}, we use \gls{doe} methodology to
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high-quality T cells. In \cref{aim2a,aim2b}, we use \gls{doe} methodology to
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optimize the \gls{dms} platform, and develop a computational pipeline to
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optimize the \gls{dms} platform, and we develop a computational pipeline to
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identify and model the effect of measurable \glspl{cqa}, and \glspl{cpp} on the
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identify and model the effects of measurable \glspl{cqa} and \glspl{cpp} on the
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final product. In \cref{aim3}, we demonstrate the effectiveness of the \gls{dms}
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final product. In \cref{aim3}, we demonstrate the effectiveness of the \gls{dms}
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platform \invivo{}. This thesis lays the groundwork for a novel T cell expansion
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platform \invivo{}. This thesis lays the groundwork for a novel T cell expansion
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method which can be utilized at scale for a clinical trial and beyond.
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method which can be utilized at scale for clinical trials and beyond.
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\clearpage
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\clearpage
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