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  <title><![CDATA[PhD Defense by Nate Dwarshuis]]></title>
  <body><![CDATA[<p><strong>Nate Dwarshuis<br />
PhD Thesis Defense Presentation</strong><br />
<br />
<strong>Date</strong>:2021-08-17<br />
<strong>Time</strong>: 1:00 pm<br />
<strong>Location / Meeting Link</strong>: <a href="https://bluejeans.com/286473768/1556">https://bluejeans.com/286473768/1556</a><br />
<br />
<strong>Committee Members:</strong><br />
Krishnendu Roy, PhD (Advisor)</p>

<p>Madhav Dhodapkar, MD</p>

<p>Melissa Kemp, PhD</p>

<p>Wilbur Lam, MD/PhD</p>

<p>Sakis Mantalaris, PhD<br />
<br />
<br />
<strong>Title</strong>: Optimizing T Cell Manufacturing and Quality Using Functionalized Degradable Microscaffolds<br />
<br />
<strong>Abstract</strong>: Adoptive cell therapies (ACT) using CAR T cells have shown promise in treating cancer, but manufacturing large numbers of high quality cells remains challenging. Currently approved T cell expansion technologies involve anti-CD3 and anti-CD28 mAbs, usually mounted on magnetic beads. This method fails to recapitulate many key signals found in vivo and is also heavily licensed by a few companies, limiting its long-term usefulness to manufactures and clinicians. Furthermore, highly potent anti-tumor T cells are generally less-differentiated subtypes such as central memory T cells and stem-memory T cells. Despite this understanding, little has been done to optimize T cell expansion for generating these subtypes, including measurement and feedback control strategies that are necessary for any modern manufacturing process. The goal of this dissertation was to develop a microcarrier-based DMS T cell expansion system and determine biologically-meaningful CQAs and critical process parameters (CPPs) that could be used to optimize for highly-potent T cells. We developed and characterized the DMS system, including quality control steps and also demonstrate the feasiblity of expanding high-quality T cells. Furthermore, we used design of experiments (DOE) methodology to optimize the DMS platform, and develop a computational pipeline to identify and model the effect of measurable CQAs, and CPPs on the final product. Finally, we demonstrated the effectiveness of the DMS platform in vivo. This work lays the groundwork for a novel T cell expansion method which can be utilized at scale for a clinical trial and beyond.</p>

<p>&nbsp;</p>

<p>&nbsp;</p>
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