ENH spruce up the T cell activation section
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@ -2339,6 +2339,40 @@ CONCLUSIONS: We developed a simplified, semi-closed system for the initial selec
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publisher = {Springer Science and Business Media {LLC}},
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}
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@InCollection{Azuma2019,
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author = {Miyuki Azuma},
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booktitle = {Co-signal Molecules in T Cell Activation},
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publisher = {Springer Singapore},
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title = {Co-signal Molecules in T-Cell Activation},
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year = {2019},
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pages = {3--23},
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doi = {10.1007/978-981-32-9717-3_1},
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}
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@Article{Luckheeram2012,
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author = {Rishi Vishal Luckheeram and Rui Zhou and Asha Devi Verma and Bing Xia},
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journal = {Clinical and Developmental Immunology},
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title = {{CD}4+ T Cells: Differentiation and Functions},
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year = {2012},
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pages = {1--12},
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volume = {2012},
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doi = {10.1155/2012/925135},
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publisher = {Hindawi Limited},
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}
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@Article{OConnor2012,
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author = {Roddy S. O'Connor and Xueli Hao and Keyue Shen and Keenan Bashour and Tatiana Akimova and Wayne W. Hancock and Lance C. Kam and Michael C. Milone},
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journal = {The Journal of Immunology},
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title = {Substrate Rigidity Regulates Human T Cell Activation and Proliferation},
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year = {2012},
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month = {jun},
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number = {3},
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pages = {1330--1339},
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volume = {189},
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doi = {10.4049/jimmunol.1102757},
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publisher = {The American Association of Immunologists},
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}
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@Comment{jabref-meta: databaseType:bibtex;}
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@Comment{jabref-meta: grouping:
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109
tex/thesis.tex
109
tex/thesis.tex
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@ -783,7 +783,7 @@ operator to load, feed, and harvest the cell product. Grex bioreactors have been
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using to grow \glspl{til}\cite{Jin2012} and virus-specific T
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cells\cite{Gerdemann2011}.
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\subsection{overview of T cell quality}
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\subsection{overview of T cell quality}\label{sec:background_quality}
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T cells are highly heterogeneous and can exist in a variety of states and
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subtypes, many of which can be measured (at least indirectly) though biomarkers
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@ -840,49 +840,74 @@ using retro- or lentiviral vectors as their means of gene-editing must be tested
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for replication competent vectors\cite{Wang2013} and for contamination via
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bacteria or other pathogens.
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\subsection*{current T cell manufacturing technologies}
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\subsection*{T cell activation}
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Despite these success of T cell therapies (especially \gls{car} T cell
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therapies) they are constrained by an expensive and difficult-to-scale
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manufacturing process\cite{Roddie2019, Dwarshuis2017}.
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% Despite these success of T cell therapies (especially \gls{car} T cell
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% therapies) they are constrained by an expensive and difficult-to-scale
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% manufacturing process\cite{Roddie2019, Dwarshuis2017}.
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Of critical concern, state-of-the-art manufacturing techniques focus only on
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Signal 1 and Signal 2-based activation via \acd{3} and \acd{28} \glspl{mab},
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typically presented on a microbead (Invitrogen Dynabead, Miltenyi MACS beads) or
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nanobead (Miltenyi TransACT), but also in soluble forms in the case of antibody
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tetramers (Expamer)\cite{Wang2016, Piscopo2017, Roddie2019, Bashour2015}. These
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strategies overlook many of the signaling components present in the secondary
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lymphoid organs where T cells normally expand. Typically, T cells are activated
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under close cell-cell contact via \glspl{apc} such as \glspl{dc}, which present
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peptide-\glspl{mhc} to T cells as well as a variety of other costimulatory
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signals. These close quarters allow for efficient autocrine/paracrine signaling
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among the expanding T cells, which secrete gls{il2} and other cytokines to
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assist their own growth.
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In order for T cells to be expanded \exvivo{} they must be activated with a
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stimulatory signal (Signal 1) and a costimulatory signal (Signal 2). \invivo{}
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Signal 1 is administered via the \gls{tcr} and the CD3 receptor when \glspl{apc}
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present a peptide via \gls{mhc} that the T cell in question is able to
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recognize. Signal 2 is administered via CD80 and CD86 which are also present on
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\glspl{apc} and is necessary to prevent the T cell from becoming anergic. While
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these two signal are the bare minimum to trigger a T cell to expand, there are
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many other potential signals present. T cells have many other costimulatory
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receptors such as OX40, 4-1BB and ICOS which are costimulatory along with CD28,
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and \glspl{apc} have corresponding ligands for these depending on the nature of
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the pathogen they have detected\cite{Azuma2019}. Furthermore, T cells exist in
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high cell density within the secondary lymphoid organs, which allows efficient
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cytokine cross-talk in an autocrine and paracrine manner. These cytokines are
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responsible for expansion (in the case of \il{2}) and subset differentiation (in
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the case of many others)\cite{Luckheeram2012}. By tuning the signal strength and
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duration of Signal 1, Signal 2, the various costimulatory signals, and the
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cytokine milieu, a variety of T cell phenotypes can be actualized.
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A variety of solutions have been proposed to make the T cell expansion process
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more physiological. One strategy is to use modified feeder cell cultures to
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provide activation signals similar to those of \glspl{dc}\cite{Forget2014}.
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While this has the theoretical capacity to mimic several key components of the
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lymph node, it is hard to reproduce on a large scale due to the complexity and
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inherent variability of using cell lines in a fully \gls{gmp}-compliant manner.
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Others have proposed biomaterials-based solutions to circumvent this problem,
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including lipid-coated microrods\cite{Cheung2018}, 3D-scaffolds via either
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Matrigel\cite{Rio2018} or 3d-printed lattices\cite{Delalat2017}, ellipsoid
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beads\cite{meyer15_immun}, and \gls{mab}-conjugated \gls{pdms}
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beads\cite{Lambert2017} that respectively recapitulate the cellular membrane,
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large interfacial contact area, 3D-structure, or soft surfaces T cells normally
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experience \textit{in vivo}. While these have been shown to provide superior
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expansion compared to traditional microbeads, no method has been able to show
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preferential expansion of functional memory and CD4 T cell populations.
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Generally, T cells with a lower differentiation state such as memory cells have
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been shown to provide superior anti-tumor potency, presumably due to their
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higher potential to replicate, migrate, and engraft, leading to a long-term,
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durable response\cite{Xu2014, Gattinoni2012, Fraietta2018, Gattinoni2011}.
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Likewise, CD4 T cells are similarly important to anti-tumor potency due to their
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cytokine release properties and ability to resist exhaustion\cite{Wang2018,
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Yang2017}, and no method exists to preferentially expand the CD4 population
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compared to state-of-the-art systems.
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\invitro{}, T cells can be activated in a number of ways but the simplest and
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most common is to use \glspl{mab} that cross-link the CD3 and CD28 receptors,
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which supply Signal 1 and Signal 2 without the need for antigen (which also
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means all T cells are activated and not just a few specific clones). Additional
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signals may be supplied in the form of cytokines (eg \il{2}, \il{7}, or \il{15})
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or feeder cells\cite{Forget2014}.
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As this is a critical unit operation in the manufacturing of T cell therapies, a
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number of commercial technologies exist to activate T cells\cite{Wang2016,
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Piscopo2017, Roddie2019, Bashour2015}. The simplest is to use \acd{3} and
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\acd{28} \gls{mab} bound to a 2D surface such as a plate, and this can be
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ackomplished in a \gls{gmp} manner as soluble \gls{gmp}-grade \glspl{mab} are
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commericially available. A similar but distinct method along these lines is to
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use multivalent activators such as ImmunoCult (StemCell Technologies) or Expamer
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(Juno Therapeutics) which may have increased cross-linking capacity compared to
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traditional \glspl{mab}. Beyond soluble protein, \glspl{mab} against CD3 and
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CD28 can be mounted on magnetic microbeads (\SIrange{3}{5}{\um} in diameter)
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such as DynaBeads (Invitrogen) and MACSbeads (\miltenyi{}), which are easier to
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separate using magnetic washing plates. Magnetic nanobeads such as TransAct
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(\miltenyi{}) work by a similar principle except they can be removed via
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centrifugation rather than a magnetic washing plate. Cloudz (RnD Systems) are
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another bead-based T cell expansion which mounts \acd{3} and \acd{28}
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\glspl{mab} on alginate microspheres, which are not only easily degradable but
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are also softer, which can have a positive impact on T cell activation and
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phenotype\cite{Lambert2017, OConnor2012}.
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A problem with all of these commercial solutions is that they only focus on
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Signal 1 and Signal 2 and ignore the many other physiological cues present in
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the secondary lymphoid organs. A variety of novel T cell activation and
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expansion solutions have been proposed to overcome this. One strategy is to use
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modified feeder cell cultures to provide activation signals similar to those of
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\glspl{dc}\cite{Forget2014}. While this has the theoretical capacity to mimic
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several key components of the lymph node, it is hard to reproduce on a large
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scale due to the complexity and inherent variability of using cell lines in a
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fully \gls{gmp}-compliant manner. Others have proposed biomaterials-based
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solutions to circumvent this problem, including lipid-coated
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microrods\cite{Cheung2018}, 3D-scaffolds via either Matrigel\cite{Rio2018} or
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3d-printed lattices\cite{Delalat2017}, ellipsoid beads\cite{meyer15_immun}, and
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\gls{mab}-conjugated \gls{pdms} beads\cite{Lambert2017} that respectively
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recapitulate the cellular membrane, large interfacial contact area,
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3D-structure, or soft surfaces T cells normally experience \textit{in vivo}.
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While these are in theory much easier to produce and \gls{qc} compared to feeder
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cells, none have been demonstrated to demonstrably expand high quality T cells
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as outlined in \cref{sec:background_quality}.
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\subsection*{integrins and T cell signaling}
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@ -922,8 +947,6 @@ stimulated in the presence of collagen I\cite{Boisvert2007}.
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\subsection*{the role of IL15 in memory T cell proliferation}
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% get lots of sources from here: https://www.sciencedirect.com/science/article/pii/S0165247809002387
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\il{15} is a cytokine that is involved with the proliferation and homeostasis of
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memory T cells. Its role in the work of this dissertation is the subject of
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further exploration in \cref{aim2b}.
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@ -1000,7 +1023,7 @@ possible. While there are many types of \glspl{doe} depending on the nature
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of the parameters and the goal of the experimenter, they all share common
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principles:
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% BACKGROUND cite montgomery, because I feel like it
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% BACKGROUND cite wu hamada... because I feel like it
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\begin{description}
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\item [randomization --] The order in which the runs are performed should
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ideally be as random as possible. This is to mitigate against any confounding
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