diff --git a/tex/thesis.tex b/tex/thesis.tex
index 9f4778b..4bcbebd 100644
--- a/tex/thesis.tex
+++ b/tex/thesis.tex
@@ -581,14 +581,14 @@ modern manufacturing process.
 The goal of this dissertation was to develop a microcarrier-based \gls{dms} T
 cell expansion system and determine biologically-meaningful \glspl{cqa} and
 \glspl{cpp} that could be used to optimize for highly-potent T cells. In
-\cref{aim1}, we develop and characterized the \gls{dms} system, including
-quality control steps. We also demonstrate the feasibility of expanding
-high-quality T cells. In \cref{aim2a,aim2b}, we use \gls{doe} methodology to
-optimize the \gls{dms} platform, and we develop a computational pipeline to
+\cref{aim1}, we developed and characterized the \gls{dms} system, including
+quality control steps. We also demonstrated the feasibility of expanding
+high-quality T cells. In \cref{aim2a,aim2b}, we used \gls{doe} methodology to
+optimize the \gls{dms} platform, and we developed a computational pipeline to
 identify and model the effects of measurable \glspl{cqa} and \glspl{cpp} on the
-final product. In \cref{aim3}, we demonstrate the effectiveness of the \gls{dms}
-platform \invivo{}. This thesis lays the groundwork for a novel T cell expansion
-method which can be utilized at scale for clinical trials and beyond.
+final product. In \cref{aim3}, we demonstrated the effectiveness of the
+\gls{dms} platform \invivo{}. This thesis lays the groundwork for a novel T cell
+expansion method which can be utilized at scale for clinical trials and beyond.
 
 \clearpage
 
@@ -604,39 +604,39 @@ diseases\cite{Fesnak2016,Rosenberg2015}. In 2017, Novartis and Kite Pharma
 received FDA approval for \textit{Kymriah} and \textit{Yescarta} respectively,
 two genetically-modified \gls{car} T cell therapies against B cell malignancies.
 Despite these successes, \gls{car} T cell therapies are constrained by an
-expensive and difficult-to-scale manufacturing process with little control on
-cell quality and phenotype\cite{Roddie2019, Dwarshuis2017}. State-of-the-art T
-cell manufacturing techniques focus on \acd{3} and \acd{28} activation and
-expansion, typically presented on superparamagnetic, iron-based microbeads
-(Invitrogen Dynabead, Miltenyi MACS beads), on nanobeads (Miltenyi TransACT), or
-in soluble tetramers (Expamer)\cite{Roddie2019,Dwarshuis2017,Wang2016,
-  Piscopo2017, Bashour2015}. These strategies overlook many of the signaling
-components present in the secondary lymphoid organs where T cells expand
-\invivo{}. Typically, T cells are activated under close cell-cell contact, which
-allows for efficient autocrine/paracrine signaling via growth-stimulating
-cytokines such as \gls{il2}. Additionally, the lymphoid tissues are comprised of
-\gls{ecm} components such as collagen and stromal cells, which provide signals
-to upregulate proliferation, cytokine production, and pro-survival
+expensive, difficult-to-scale manufacturing process with little control on cell
+quality and phenotype\cite{Roddie2019, Dwarshuis2017}. State-of-the-art T cell
+manufacturing techniques focus on \acd{3} and \acd{28} activation and expansion,
+typically presented on superparamagnetic, iron-based microbeads (Invitrogen
+Dynabead, Miltenyi MACS beads), on nanobeads (Miltenyi TransACT), or in soluble
+tetramers (Expamer)\cite{Roddie2019,Dwarshuis2017,Wang2016, Piscopo2017,
+  Bashour2015}. These strategies overlook many of the signaling components
+present in the secondary lymphoid organs where T cells expand \invivo{}.
+Typically, T cells are activated under close cell-cell contact, which allows for
+efficient autocrine/paracrine signaling via growth-stimulating cytokines such as
+\gls{il2}. Additionally, the lymphoid tissues are comprised of \gls{ecm}
+components such as collagen and stromal cells, which provide signals to
+upregulate proliferation, cytokine production, and pro-survival
 pathways\cite{Gendron2003, Ohtani2008, Boisvert2007, Ben-Horin2004}.
 
 A variety of solutions have been proposed to make the T cell expansion process
-more physiological. Including feeder cell cultures\cite{Forget2014} and
+more physiological. These include feeder cell cultures\cite{Forget2014} and
 biomaterials-based methods such as lipid-coated microrods or 3D scaffold
 gels\cite{Cheung2018,Delalat2017,meyer15_immun,Lambert2017} that attempt to
 recapitulate the cellular membrane, large interfacial contact area,
 3D-structure, or soft surfaces T cells normally experience \invivo{}. While
-these have been shown to activation and expand T cells, they either are not
+these have been shown to activate and expand T cells, they either are not
 scalable (in the case of feeder cells) or still lack many of the signals and
 cues T cells experience as the expand. Additionally, none have been shown to
 preferentially expand highly-potent T cell necessary for anti-cancer therapies.
-Such high potency cells including subtypes with low differentiation state such
+Such high potency cells are subtypes with low differentiation state such
 as \gls{tscm} and \gls{tcm} cells or CD4 cells, all of which have been shown to
 be necessary for durable responses\cite{Xu2014, Fraietta2018, Gattinoni2011,
   Gattinoni2012,Wang2018, Yang2017}. Methods to increase memory and CD4 T cells
 in the final product are needed. Furthermore, \gls{qbd} principles such as
 discovering and validating novel \glspl{cqa} and \glspl{cpp} in the space of T
 cell manufacturing are required to reproducibly manufacture these subtypes and
-ensure low-cost and safe products with maximal effectiveness in the clinic
+ensure low-cost and safe products with maximal effectiveness in the clinic.
 
 This dissertation describes a novel \acrlong{dms}-based method derived from
 porous microcarriers functionalized with \acd{3} and \acd{28} \glspl{mab} for
@@ -654,11 +654,11 @@ emulate the large contact surface area that occurs between T cells and
 \section*{hypothesis}
 
 The hypothesis of this dissertation was that using \glspl{dms} created from
-off-the-shelf microcarriers and coated with activating \glspl{mab} would lead to
-higher quantity and quality T cells as compared to state-of-the-art bead-based
-expansion. We also hypothesized that T cells have measurable biological
-signatures that are predictive of downstream outcomes and phenotypes. The
-objective of this dissertation was to develop this platform, test its
+off-the-shelf microcarriers and coated with activating \glspl{mab} would
+increase quantity and quality of T cells as compared to state-of-the-art
+bead-based expansion. We also hypothesized that such T cells have measurable
+biological signatures that are predictive of downstream outcomes and phenotypes.
+The objective of this dissertation was to develop this platform, test its
 effectiveness both \invitro{} and \invivo{}, and develop computational pipelines
 to discover novel \glspl{cpp} and \glspl{cqa} that can be translated to a
 manufacturing environment and a clinical trial setting.
@@ -683,10 +683,10 @@ The specific aims of this dissertation are outlined in
 
 In this first aim, we demonstrated the process for manufacturing \glspl{dms},
 including quality control steps that are necessary for translation of this
-platform into a scalable manufacturing setting. We also demonstrate that the
+platform into a scalable manufacturing setting. We also demonstrated that the
 \gls{dms} platform leads to higher overall expansion of T cells and higher
 overall fractions of potent memory and CD4+ subtypes desired for T cell
-therapies. Finally, we demonstrate \invitro{} that the \gls{dms} platform can be
+therapies. Finally, we showed \invitro{} that the \gls{dms} platform can be
 used to generate functional \gls{car} T cells targeted toward CD19.
 
 \subsection*{aim 2: develop methods to control and predict T cell quality}
@@ -705,7 +705,7 @@ accomplished through two sub-aims:
 \subsection*{aim 3: confirm potency of T cells from novel T cell expansion
   process using \invivo{} xenograft mouse model}
 
-In this final aim, we demonstrate the effectiveness of \gls{dms}-expanded T
+In this final aim, we demonstrated the effectiveness of \gls{dms}-expanded T
 cells compared to state-of-the-art beads using \invivo{} mouse models for
 \gls{all}.
 
@@ -732,27 +732,28 @@ manipulation\cite{Kirouac2008, Little2006, Pirnay2012, Rousseau2013}. This is
 further compounded by the lack of standardization and limited regulation.
 
 In order to overcome these barriers, adopting a systemic approach to cell
-manufacturing using \acrlong{qbd} principles will be extremely
+manufacturing using \acrfull{qbd} principles will be extremely
 important\cite{Kirouac2008}. In \gls{qbd}, the objective is to reproducibly
 manufacturing products which minimizes risk for downstream stakeholders (in this
-case, the patient). Broadly, this entails determining \acrlongpl{cqa} and
-\acrlongpl{cpp} and incorporating them into models which can explain and predict
-the cell manufacturing process.
+case, the patient). This entails determining \acrlongpl{cqa} and \acrlongpl{cpp}
+and incorporating them into models which can explain and predict the cell
+manufacturing process.
 
-\Glspl{cqa} are measurable properties of the product that can be used to define
-its functionality and hence quality. \glspl{cqa} are important for defining the
-characteristics of a `good' product (release criteria) but also for ensuring
+\Glspl{cqa} are measurable properties of the product that are used to define its
+functionality and hence quality. \glspl{cqa} are important for defining the
+characteristics of a ``good'' product (release criteria) but also for ensuring
 that a process is on track to making such a product (process control). In the
 space of cell manufacturing, examples of \glspl{cqa} include markers on the
 surface of cells and readouts from functional assays such as killing assays. In
 general, these are poorly understood if they exist at all.
 
+%% TODO IL2 use here is wonky
 \glspl{cpp} are parameters which may be tuned and varied to control the outcome
-of process and the quality of the final product. In cell manufacturing, these
-are poorly understood. Examples in the cell manufacturing space include the type
-of media used and the amount of \il{2} added. Once \glspl{cpp} are known, they
-can be optimized to ensure that costs are minimized and potency of the cellular
-product is maximized.
+of process and the quality of the final product. Examples include the type of
+media used and the amount of \il{2} added. While these can be easy to control,
+the effect they have on the final outcome is generally unknown. Once \glspl{cpp}
+are known, they can be optimized to ensure that costs are minimized and potency
+of the cellular product is maximized.
 
 The topic of discovering novel \glspl{cpp} and \glspl{cqa} in the context of
 this work are discussed further in \cref{sec:background_doe} and
@@ -767,12 +768,13 @@ theory the technology developed in this dissertation could theoretically apply
 to any T cell-based therapy with little to no modification.
 
 One of the first successful T cell-based immunotherapies against cancer is
-\glspl{til}\cite{Rosenberg2015}. This method works by taking tumor specimens
-from a patient, allowing the tumor-reactive lymphocytes to expand \exvivo{}, and
-then administered back to the patient along with a high dose of
-\il{2}\cite{Rosenberg1988}. In particular, \gls{til} therapy has shown robust
-results in treating melanoma\cite{Rosenberg2011}, although \glspl{til} have been
-found in other solid tumors such as gastointestinal, cervical, lung, and
+\glspl{til}\cite{Rosenberg2015}. This method works by excising tumor fragments
+from a patient, allowing the tumor-reactive lymphocytes to expand \exvivo{} from
+within these fragments, and then administered these lymphocytes back to the
+patient along with a high dose of \il{2}\cite{Rosenberg1988}. In particular,
+\gls{til} therapy has shown robust results in treating
+melanoma\cite{Rosenberg2011}, although \glspl{til} have been found in other
+solid tumors such as gastointestinal, cervical, lung, and
 ovarian\cite{Rosenberg2015, Wang2014, Foppen2015, Solinas2017, June2007,
   Santoiemma2015}, and their presence is generally associate with favorable
 outcomes\cite{Clark1989}. \glspl{til} are heterogeneous cell mixtures and
@@ -795,26 +797,27 @@ T cells with transduced \glspl{tcr} were first designed to overcome the
 limitations of \glspl{til}\cite{Rosenberg2015, Wang2014}. In this case, T cells
 are transduced \exvivo{} with a lentiviral vector to express a \gls{tcr}
 targeting a tumor antigen. T cells transduced with \glspl{tcr} have shown robust
-results in melanoma patients\cite{Robbins2011}, synovial
-sarcoma\cite{Morgan2006}, and others\cite{Ikeda2016}. To date, there are over
-200 clinical trials using T cells with transduced \glspl{tcr}.
+results against melanoma \cite{Robbins2011}, synovial sarcoma\cite{Morgan2006},
+and others\cite{Ikeda2016}. To date, there are over 200 clinical trials using T
+cells with transduced \glspl{tcr}.
 
 While transduced \glspl{tcr} offer some flexibility in retargeting T cells
 toward relevant tumor antigens, they are still limited in that they can only
-target antigens that are presented via \gls{mhc} complexes. \acrlong{car} T
-cells overcome this limitation by using linking a \gls{tcr}-independent antigen
-recognition domain with the stimulatory and costimulatory machinery of a T cell
-\gls{car} T cells were first demonstrated in 1989, where the authors swapped the
+target antigens that are presented via \gls{mhc}. \Acrlong{car} T cells overcome
+this limitation by linking a \gls{tcr}-independent antigen recognition domain
+with the stimulatory and costimulatory machinery of a T cell. \gls{car} T cells
+were first demonstrated in 1989, where the authors swapped the
 antigen-recognition domains of a native \gls{tcr} with a that of a foreign
 \gls{tcr}\cite{Gross1989}. Since then, this method has progressed to using an
-\gls{scfv} with a CD3$\upzeta$ stimulatory domain along with the CD28, OX-40, or
-4-1BB domains for costimulation. Since these can all be expressed with one
-protein sequence, \gls{car} T cells are relatively simple to produce and require
-only a single genetic transduction step (usually a lentiviral vector) to
-reprogram a batch T cells \exvivo{} toward the desired antigen. \gls{car} T
-cells have primarily found success in against CD19- and CD20-expressing tumors
-such as \gls{all} and \gls{cll} (eg B-cell malignancies)\cite{Kalos2011,
-  Brentjens2011, Kochenderfer2010, Maude2014, Till2012, Till2008}.
+\gls{scfv} for antigen recognition, a CD3$\upzeta$ domain for the stimulatory
+signal, and a CD28, OX-40, or 4-1BB domains for the costimulatory signal. Since
+these can all be expressed with one protein sequence, \gls{car} T cells are
+relatively simple to produce and require only a single genetic transduction step
+(usually a lentiviral vector) to reprogram a batch T cells \exvivo{} toward the
+desired antigen. \gls{car} T cells have primarily found success in against CD19-
+and CD20-expressing tumors such as \gls{all} and \gls{cll} (eg B-cell
+malignancies)\cite{Kalos2011, Brentjens2011, Kochenderfer2010, Maude2014,
+  Till2012, Till2008}.
 
 Out of all the T cell therapies discussed thus far, \gls{car} T cells have
 experienced the most commercial success and excitement. In 2017, Novartis and
@@ -828,9 +831,8 @@ date, there are almost 1000 clinical trials using \gls{car} T cells.
 
 \subsection{Scaling T Cell Expansion}
 
-In order to scale T cell therapies to meet clinical demands, automation and
-bioreactors will be necessary. To this end, there are several choices that have
-found success in the clinic.
+In order to scale T cell therapies, automation and bioreactors will be
+necessary. To this end, several choices have found success in the clinic.
 
 The WAVE bioreactor (GE Healthcare) is the choice of expansion for many clinical
 applications\cite{Brentjens2011, Hollyman2009, Brentjens2013}. It is part of a
@@ -844,32 +846,30 @@ design, which could have negative impact on cross-talk, activation, and
 growth\cite{Somerville2012}.
 
 % BACKGROUND find clinical trials (if any) that use this
-Alternatively, the CliniMACS Prodigy (Miltenyi) is an all-in-one system that is
-a fully closed system that removes the need for expensive cleanrooms and
-associated personnel\cite{Kaiser2015, Bunos2015}. It contains modules to perform
-transduction, expansion, and washing. This setup also implies that fewer
-mistakes and handling errors will be made, since many of the steps are internal
-to the machine. Initial investigations have shown that it can yield T cells
-doses required for clinical use\cite{Zhu2018}. At the time of writing, several
-clinical trial are underway which use the CliniMACS, although mostly for
-stem-cell based cell treatments.
+Alternatively, the CliniMACS Prodigy (Miltenyi) is an all-in-one, fully-closed
+system that removes the need for expensive cleanrooms and associated
+personnel\cite{Kaiser2015, Bunos2015}. It contains modules to perform
+transduction, expansion, and washing. This setup is less prone to mistakes,
+since most steps are internal to the machine. Initial investigations have shown
+that it can yield T cells doses required for clinical use\cite{Zhu2018}. At the
+time of writing, several clinical trial are underway which use the CliniMACS,
+although mostly for stem-cell based cell treatments.
 
 Finally, another option that has been investigated for T cell expansion is the
 Grex bioreactor (Wilson Wolf). This is effectively a tall tissue-culture plate
-with a porous membrane at the bottom, which allows gas exchange to the active
-cell culture at the bottom of the plate while permitting large volumes of media
-to be loaded on top without suffocating the cells. While this is quite similar
-to plates and flasks normally used for small-scale research, the important
-difference is that its larger size requires fewer interactions and keeps the
-cells at a higher nutrient concentration for longer periods of time. However, it
-is still a an open system and requires manual (by default) interaction from an
-operator to load, feed, and harvest the cell product. Grex bioreactors have been
-using to grow \glspl{til}\cite{Jin2012} and virus-specific T
-cells\cite{Gerdemann2011}.
+with a porous membrane at the bottom. This allows large volumes of media to be
+loaded without suffocating the cells, which can exchange gas through the
+membrane. While this is quite similar to plates and flasks normally used for
+small-scale research, the important difference is that its larger size requires
+fewer interactions and keeps the cells at a higher nutrient concentration for
+longer periods of time. However, it is still a an open system and requires
+manual (by default) interaction from an operator to load, feed, and harvest the
+cell product. Grex bioreactors have been using to grow \glspl{til}\cite{Jin2012}
+and virus-specific T cells\cite{Gerdemann2011}.
 
 Much work is still required in the space of bioreactor design for T cell
 manufacturing, but novel T cell expansion technologies such as that described in
-this work need to consider how it may be used at scale in such a system.
+this work need to consider how they may be used at scale in such a system.
 
 \subsection{Cell Sources in T Cell Manufacturing}\label{sec:background_source}
 
@@ -887,35 +887,34 @@ cross-reactivity with the patient and thus \gls{gvhd} is not a
 concern\cite{Decker2012}. However, there are numerous disadvantages. Autologous
 therapies are over 20 times more costly as the process needs to be repeated for
 every patient\cite{Harrison2019}. Compounding this, many cell products are
-manufactured at a centralized location, so patient T cells need to be shipped
-twice on dry ice from the hospital and back. This adds days to the process,
-which is critical for patients with fast moving diseases. Manufacturing could be
-done on-site in a decentralized manner, but this requires more equipment and
-personnel overall. Using cells from a diseased patient has many drawbacks in
-itself. Cancer patients (especially those with chronic illnesses) often have
-exhausted T cells which expand far less readily and are consequently less
-potent\cite{Wherry2015, Ando2019, Zheng2017}. Additionally, they may have high
-frequencies of \glspl{treg} which inhibitory\cite{Decker2012}. Removing these
-cells as well as purifying \glspl{th1} may enhance the potency of the final
-product\cite{Goldstein2012, Drela2004, Rankin2003, Luheshi2013, Grotz2015};
-however, this would make the overall process more expensive as an additional
-separation step would be required.
+manufactured at a centralized location, so cells need to be shipped on dry ice
+from the hospital and back. This adds days to the process, which is critical for
+patients with fast moving diseases. Manufacturing could be done on-site in a
+decentralized manner, but this requires more equipment and personnel overall.
+Sourcing cells from a diseased patient has many drawbacks in itself. Cancer
+patients (especially those with chronic illnesses) often have exhausted T cells
+which expand far less readily and are consequently less potent\cite{Wherry2015,
+  Ando2019, Zheng2017}. Additionally, they may have high frequencies of
+\glspl{treg} which have an inhibitory effect on
+immunotherapies\cite{Decker2012}. Removing these cells as well as purifying
+\glspl{th1} may enhance the potency of the final product\cite{Goldstein2012,
+  Drela2004, Rankin2003, Luheshi2013, Grotz2015}; however, this makes the
+overall process more expensive as an additional separation step is required.
 
 Allogeneic T cell therapies overcome nearly all of these disadvantages. Donor
 \glspl{pbmc} are easy to obtain, they can be processed in centralized locations,
-they can be stored easily under liquid nitrogen, and donors could be screened to
-find those with optimal anti-tumor cells. The key is overcoming \gls{gvhd}.
-Obviously this could be done the same way as done for transplants where patients
-find a `match' for their \gls{hla} type, but this severally limits options. This
-can be overcome by using advanced gene-editing tools which can both add and
-delete genetic material (eg \glspl{zfn}, \glspl{talen}, or \gls{crispr}) to
-remove the native \gls{tcr} which would prevent the donor T cells from attacking
-host tissue\cite{Liu2019, Wiebking2020, Provasi2012, Berdien2014, Themeli2015}.
-This obviously complicates the process, as additional edits besides the
-insertion of the \gls{car} would be required, and these technologies are not yet
-very efficient. To date there are about 10 open clinical trials utilizing
-allogeneic T cell therapies edited with \gls{crispr} to reduce the likelihood of
-\gls{gvhd}.
+and they can be stored easily under liquid nitrogen. Donors can also be screened
+to find those with optimal anti-tumor cells. The key is overcoming \gls{gvhd}.
+Obviously this could be done analogously to transplants where patients find a
+``match'' for their \gls{hla} type, but this severally limits options. This can
+be overcome by using advanced gene-editing tools (eg \glspl{zfn}, \glspl{talen},
+or \gls{crispr}) to remove the native \gls{tcr} and thus prevent the donor T
+cells from attacking host tissue\cite{Liu2019, Wiebking2020, Provasi2012,
+  Berdien2014, Themeli2015}. This obviously complicates the process, as
+additional edits besides the insertion of the \gls{car} would be required, and
+these technologies are not yet very efficient. To date there are about 10 open
+clinical trials utilizing allogeneic T cell therapies edited with \gls{crispr}
+to reduce the likelihood of \gls{gvhd}.
 
 \subsection{Overview of T Cell Quality}\label{sec:background_quality}
 
@@ -927,13 +926,13 @@ criteria, and initial cell source screening.
 
 One of the most important dimensions of T cell quality is that of
 differentiation. T cells begin their life in circulation (eg after they exit the
-thymus) as \glspl{tn}. When they become activated in the secondary lymph node
+thymus) as \glspl{tn}. When they become activated in the secondary lymphoid
 organs, they differentiate from \gls{tn} to \glspl{tscm}, \glspl{tcm},
 \glspl{tem}, and finally \glspl{teff}\cite{Gattinoni2012}. Subtypes earlier in
-this process are generally called `memory' or `memory-like' cells (eg \gls{tscm}
-and \gls{tcm}), and have been shown to have increased potency toward a variety
-of tumors, presumably due to their higher capacity for self-renewal and
-replication, enhanced migratory capacity, and/or increased engraftment
+this process are generally called ``memory'' or ``memory-like'' cells (eg
+\gls{tscm} and \gls{tcm}), and have been shown to have increased potency toward
+a variety of tumors, presumably due to their higher capacity for self-renewal
+and replication, enhanced migratory capacity, and/or increased engraftment
 potential\cite{Xu2014, Gattinoni2012, Fraietta2018, Gattinoni2011, Turtle2009}.
 The capacity for self-renewal is especially important for T cells therapies, as
 evidenced by the fact that \gls{til} therapies with longer telomeres tend to
@@ -951,7 +950,7 @@ In addition to memory, the other major axis by which T cells may be classified
 is the CD4/CD8 ratio. \Glspl{th} are CD4+ are responsible for secreting
 cytokines which coordinate the immune response while CD8+ \glspl{tc} are
 responsible for killing tumors or infected cells using specialized lytic
-enzymes. Since \glspl{tc} actually perform the killing function, it seems
+enzymes. Since \glspl{tc} actually possess the killing function, it seems
 intuitive that \glspl{tc} would be most important for anti-tumor
 immunotherapies. However, in mouse models with glioblastoma, survival was
 negatively impacted when \glspl{th} were removed\cite{Wang2018}. Furthermore,
@@ -969,10 +968,10 @@ radioactive tracer, by measuring the degranulation of the T cells themselves, or
 by measuring a cytokine that is secreted upon T cell activation and killing such
 as \gls{ifng}. Furthermore, the viability of T cells may be assessed using a
 number of methods, including exclusion dyes such as \gls{aopi} or a functional
-assay to detect metabolism. Finally, for the purposes of safety, T cell products
-using retro- or lentiviral vectors as their means of gene-editing must be tested
-for replication competent vectors\cite{Wang2013} and for contamination via
-bacteria or other pathogens.
+assay to detect metabolism. Finally, for safety, retro- or lentivirally
+transduced T cell products must be tested for replication competent
+vectors\cite{Wang2013}, and all cell products in general should be tested for
+bacterial or fungal contamination.
 
 \subsection{T Cell Activation Methods}\label{sec:background_activation}
 
@@ -983,24 +982,23 @@ present a peptide via \gls{mhc} that the T cell in question is able to
 recognize. Signal 2 is administered via CD80 and CD86 which are also present on
 \glspl{apc} and is necessary to prevent the T cell from becoming anergic. While
 these two signal are the bare minimum to trigger a T cell to expand, there are
-many other potential signals present. T cells have many other costimulatory
-receptors such as OX40, 4-1BB and ICOS which are costimulatory along with CD28,
-and \glspl{apc} have corresponding ligands for these depending on the nature of
-the pathogen they have detected\cite{Azuma2019}. Furthermore, T cells exist in
-high cell density within the secondary lymphoid organs, which allows efficient
-cytokine cross-talk in an autocrine and paracrine manner. These cytokines are
-responsible for triggering proliferation (in the case of \il{2}) and subset
-differentiation (in the case of many others)\cite{Luckheeram2012}. By tuning the
-signal strength and duration of Signal 1, Signal 2, the various costimulatory
-signals, and the cytokine milieu, a variety of T cell phenotypes can be
-actualized.
+many other potential signals present. T cells have other receptors such as OX40,
+4-1BB, and ICOS which are costimulatory along with CD28, and \glspl{apc} have
+corresponding ligands for these depending on the nature of the pathogen they
+have detected\cite{Azuma2019}. Furthermore, T cells exist in high cell density
+within the secondary lymphoid organs, which allows efficient cytokine cross-talk
+in an autocrine and paracrine manner. These cytokines are responsible for
+triggering proliferation (in the case of \il{2}) and subset differentiation (in
+the case of many others)\cite{Luckheeram2012}. By tuning the signal strength and
+duration of Signal 1, Signal 2, the various costimulatory signals, and the
+cytokine milieu, a variety of T cell phenotypes can be actualized.
 
-\Invitro{}, T cells can be activated in a number of ways but the simplest and
-most common is to use \glspl{mab} that cross-link the CD3 and CD28 receptors,
-which supply Signal 1 and Signal 2 without the need for antigen (which also
-means all T cells are activated and not just a few specific clones). Additional
-signals may be supplied in the form of cytokines (eg \il{2}, \il{7}, or \il{15})
-or feeder cells\cite{Forget2014}.
+There are many ways to activate T cells \invitro{}, but the simplest and most
+common is to use \glspl{mab} that cross-link CD3 and CD28, which supply Signal 1
+and Signal 2 without the need for antigen (which also means all T cells are
+activated and not just a few specific clones). Additional signals may be
+supplied in the form of cytokines (eg \il{2}, \il{7}, or \il{15}) or feeder
+cells\cite{Forget2014}.
 
 As this is a critical unit operation in the manufacturing of T cell therapies, a
 number of commercial technologies exist to activate T cells\cite{Wang2016,
@@ -1009,11 +1007,11 @@ number of commercial technologies exist to activate T cells\cite{Wang2016,
 accomplished in a \gls{gmp} manner (at least from a reagents perspective) as
 soluble \gls{gmp}-grade \glspl{mab} are commericially available. A similar but
 distinct method along these lines is to use multivalent activators such as
-ImmunoCult (StemCell Technologies) or Expamer (Juno Therapeutics) which may have
+ImmunoCult (StemCell Technologies) or Expamer (Juno Therapeutics) which have
 increased cross-linking capacity compared to traditional \glspl{mab}. Beyond
 soluble protein, \glspl{mab} against CD3 and CD28 can be mounted on magnetic
 microbeads (\SIrange{3}{5}{\um} in diameter) such as DynaBeads (Invitrogen) and
-MACSbeads (\miltenyi{}), which are easier to separate using magnetic washing
+MACSbeads (\miltenyi{}), which are easy to separate using magnetic washing
 plates. Magnetic nanobeads such as TransAct (\miltenyi{}) work by a similar
 principle except they can be removed via centrifugation rather than a magnetic
 washing plate. Cloudz (RnD Systems) are another bead-based T cell expansion
@@ -1026,18 +1024,17 @@ Signal 1 and Signal 2 and ignore the many other physiological cues present in
 the secondary lymphoid organs. A variety of novel T cell activation and
 expansion solutions have been proposed to overcome this. One strategy is to use
 modified feeder cell cultures to provide activation signals similar to those of
-\glspl{dc}\cite{Forget2014}. While this has the theoretical capacity to mimic
-several key components of the lymph node, it is hard to reproduce on a large
-scale due to the complexity and inherent variability of using cell lines in a
-fully \gls{gmp}-compliant manner. Others have proposed biomaterials-based
-solutions to circumvent this problem, including lipid-coated
-microrods\cite{Cheung2018}, 3D-scaffolds via either Matrigel\cite{Rio2018} or
-3d-printed lattices\cite{Delalat2017}, ellipsoid beads\cite{meyer15_immun}, and
-\gls{mab}-conjugated \gls{pdms} beads\cite{Lambert2017} that respectively
-recapitulate the cellular membrane, large interfacial contact area,
-3D-structure, or soft surfaces T cells normally experience \textit{in vivo}.
-None have been demonstrated to demonstrably expand high quality T cells as
-outlined in \cref{sec:background_quality}.
+\glspl{dc}\cite{Forget2014}. While this can theoretically mimic many components
+of the lymph node, it is hard to scale due to the complexity and inherent
+variability of using cell lines in a \gls{gmp}-compliant manner. Others have
+proposed biomaterials-based solutions to circumvent this problem, including
+lipid-coated microrods\cite{Cheung2018}, 3D-scaffolds via either
+Matrigel\cite{Rio2018} or 3d-printed lattices\cite{Delalat2017}, ellipsoid
+beads\cite{meyer15_immun}, and \gls{mab}-conjugated \gls{pdms}
+beads\cite{Lambert2017} that respectively recapitulate the cellular membrane,
+large interfacial contact area, 3D-structure, or soft surfaces T cells normally
+experience \textit{in vivo}. None of these have been shown to expand high
+quality T cells as outlined in \cref{sec:background_quality}.
 
 \subsection{Microcarriers in Bioprocessing}
 
@@ -1046,56 +1043,54 @@ methods described in \cref{sec:background_activation}.
 
 Microcarriers have historically been used to grow a number of adherent cell
 types for a variety of applications. They were introduced in 1967 as a means to
-grow adherent cells `in suspension', effectively turning a 2D flask system into
-a 3D culture system\cite{WEZEL1967}. Microcarriers are generally spherical and
-are several hundred \si{\um} in diameter, which means they collectively have a
-much higher surface area than a traditional flask when matched for volume.
+grow adherent cells ``in suspension,'' effectively turning a 2D flask into a 3D
+culture system\cite{WEZEL1967}. Microcarriers are generally spherical and are
+several hundred \si{\um} in diameter, which means they collectively have a much
+higher surface area than a traditional flask when matched for volume.
 Consequently, this means that microcarrier-based cultures can operate with much
-lower footprints than flask-like systems. Microcarriers also allow cell culture
-to operate more like a traditional chemical engineering process, wherein a
-\gls{cstr} may be employed to enhance oxygen transfer, maintain pH,
-and continuously supply nutrients\cite{Derakhti2019}.
+lower footprints than flask-like systems. Microcarriers also allow cell cultures
+to operate more like traditional chemical engineering processes, wherein a
+\gls{cstr} may be employed to enhance oxygen transfer, maintain pH, and
+continuously supply nutrients\cite{Derakhti2019}.
 
 A variety of microcarriers have been designed, primarily differing in their
-choice of material and macroporous structure. Key concerns driving these
-choiceshave been cell attachment at the beginning of culture and cell detachment
-at the harvesting step\cite{Derakhti2019}. Many microcarriers simply use
-polystyrene (the material used for tissue culture flasks and dishes in general)
-with no modification (SoloHill Plastic, Nunc Biosilon), with a cationic surface
-charge (SoloHill Hillex) or coated with an \gls{ecm} protein such as collagen
-(SoloHill Fact III). Other base materials have been used such as dextran (GE
-Healthcare Cytodex), cellulose (GE Healthcare Cytopore), and glass (\sigald{}
-G2767), all with none or similar surface modifications. Additionally, some
-microcarriers such as \gls{cus} and \gls{cug} are composed entirely out of
-protein (in these cases, porcine collagen) which also allows the microcarriers
-to be enzymatically degraded. In the case of non-protein materials, cells may
-still be detached using enzymes but these require similar methods to those
-currently used in flasks such as trypsin which target the cellular \gls{ecm}
-directly. Since trypsin and related enzymes tends to be harsh on cells, an
-advantage of using entirely protein-based microcarriers is that they can be
-degraded using a much safer enzyme such as collagenase, at the cost of being
-more expensive and also being harder to make
-\gls{gmp}-compliant\cite{Derakhti2019}. Going one step further, some
-microcarriers are composed of a naturally degrading scaffold such as alginate,
-which do not need an enzyme for degradation. Finally, microcarriers can differ
-in their overall structure. \gls{cug} and \gls{cus} microcarriers as well as the
-Cytopore microcarriers are macroporous, meaning they have a porous network in
-which cells can attach throughout their interior. This drastically increases the
-effective surface area and consequently the number of cells which may be grown
-per unit volume. Other microcarriers are microporous (eg only to small
-molecules) or not porous at all (eg polystyrene); in either case the cells can
-only grow on the surface.
+choice of material and macroporous structure. Key concerns driving these choices
+have been cell attachment at the beginning of culture and cell detachment at the
+harvesting step\cite{Derakhti2019}. Many microcarriers simply use polystyrene
+(the material used for tissue culture flasks and dishes in general) with no
+modification (SoloHill Plastic, Nunc Biosilon), with a cationic surface charge
+(SoloHill Hillex) or coated with an \gls{ecm} protein such as collagen (SoloHill
+Fact III). Other base materials have been used such as dextran (GE Healthcare
+Cytodex), cellulose (GE Healthcare Cytopore), and glass (\sigald{} G2767), all
+with similar surface modifications (if any). Additionally, some microcarriers
+such as \gls{cus} and \gls{cug} are composed entirely out of protein (in these
+cases, porcine collagen) which also allows the microcarriers to be enzymatically
+degraded. In the case of non-protein materials, cells may still be detached
+using enzymes but these require similar methods to those currently used in
+flasks such as trypsin which target the cellular \gls{ecm} directly. Since
+trypsin and related enzymes tends to be harsh on cells, an advantage of using
+entirely protein-based microcarriers is that they can be degraded using a much
+safer enzyme such as collagenase, at the cost of being more expensive and also
+being harder to make \gls{gmp}-compliant\cite{Derakhti2019}. Going one step
+further, some microcarriers are composed of a naturally degrading scaffold such
+as alginate, which do not need an enzyme for degradation. Finally, microcarriers
+can differ in their overall structure. \gls{cug} and \gls{cus} microcarriers as
+well as the Cytopore microcarriers are macroporous, meaning they have a porous
+network in which cells can attach throughout their interior. This drastically
+increases the effective surface area and consequently the number of cells which
+may be grown per unit volume. Other microcarriers are microporous (eg only
+permeable to small molecules) or not porous at all; in either case, cells can
+only grow on the outer surface.
 
-Microcarriers in general have seen the most use in growing \gls{cho} cells and
-hybridomas in the case of protein manufacturing (eg \gls{igg}
-production)\cite{Xiao1999, Kim2011} as well as \glspl{esc} and \glspl{msc} more
-recently in the case of cell manufacturing\cite{Heathman2015, Sart2011,
-  Chen2013, Schop2010, Rafiq2016}. Interestingly, some groups have even explored
-using biodegradable microcarriers \invivo{} as a delivery vehicle for stem cell
-therapies in the context of regenerative medicine\cite{Zhang2016, Saltz2016,
-  Park2013, Malda2006}. However, the characteristic shared by all the cell types
-in this application is the fact that they are adherent. In this work, we explore
-the use of microcarrier for T cells, which are naturally non-adherent.
+Microcarriers have been mainly used for growing \gls{cho} cells and hybridomas
+in the case of protein manufacturing (eg \gls{igg} production)\cite{Xiao1999,
+  Kim2011} as well as \glspl{esc} and \glspl{msc} more recently in the case of
+cell manufacturing\cite{Heathman2015, Sart2011, Chen2013, Schop2010, Rafiq2016}.
+Interestingly, some groups have even explored using biodegradable microcarriers
+\invivo{} as a delivery vehicle for stem cell therapies in the context of
+regenerative medicine\cite{Zhang2016, Saltz2016, Park2013, Malda2006}. However,
+all these cell types are adherent. In this work, we explore the use of
+microcarrier for T cells, which are naturally non-adherent.
 
 The microcarriers used in this work were \gls{cus} and \gls{cug} (mostly the
 former) which are both composed of cross-linked gelatin and have a macroporous
@@ -1119,7 +1114,7 @@ T cells naturally expand in the lymph nodes which have an \gls{ecm} composed of
 collagen\cite{Dustin2001, Ebnet1996, Ohtani2008}. Despite this, T cells don't
 interact with collagen fibers in the lymph node as the collagen fibers are
 sheathed with stromal fibroblasts\cite{Dustin2001, Ebnet1996}. However, the
-\gls{ecm} of peripheral tissues is dense with exposed collagen fibers are
+\gls{ecm} of peripheral tissues is dense where exposed collagen fibers are
 available to interact with T cells. Furthermore, T cells have been shown
 \invitro{} to crawl along collagen fibers in the presence of \glspl{apc},
 facilitating short encounters with \glspl{apc}\cite{Gunzer2000}. While this may
@@ -1129,16 +1124,15 @@ not be ideal \invivo{} due to the lack of cumulative signal received by
 
 The major surface receptors for collagen are \gls{a2b1} and
 \gls{a2b2}\cite{Dustin2001, Hemler1990}. These receptors are not expressed on
-naive T cells and thus presence and stimulation of collagen alone is not
-sufficient to cause activation or expansion of T cells\cite{Hemler1990}. These
-receptors have been shown to lead to a number of functions that may be useful in
-the context of T cell expansion. First, they have been shown to act in a
-costimulatory manner which leads to increased proliferation\cite{Rao2000}.
-Furthermore, \gls{a2b1} and \gls{a2b2} have been shown to protect Jurkat cells
-against Fas-mediated apoptosis in the presence of collagen I\cite{Aoudjit2000,
-  Gendron2003}. Finally, these receptors have been shown to increase \gls{ifng}
-production \invitro{} when T cells derived from human \glspl{pbmc} are
-stimulated in the presence of collagen I\cite{Boisvert2007}.
+naive \gls{tn} cells and thus presence and stimulation of collagen alone is not
+sufficient for activation or expansion\cite{Hemler1990}; however, they have been
+shown to possess many functions that may be useful for T cell expansion. First,
+they can act in a costimulatory manner which leads to increased
+proliferation\cite{Rao2000}. Furthermore, \gls{a2b1} and \gls{a2b2} seem to
+protect Jurkat cells against Fas-mediated apoptosis in the presence of collagen
+I\cite{Aoudjit2000, Gendron2003}. Finally, these receptors can increase
+\gls{ifng} production \invitro{} when T cells derived from human \glspl{pbmc}
+are stimulated in the presence of collagen I\cite{Boisvert2007}.
 
 \subsection{The Role of IL15 in Memory T Cell Proliferation}
 
@@ -1148,8 +1142,8 @@ further exploration in \cref{aim2b}.
 
 Functionally, mice lacking the gene for either \il{15}\cite{Kennedy2000} or its
 high affinity receptor \il{15R$\upalpha$}\cite{Lodolce1998} are generally
-healthy but show a deficit in memory CD8 T cells, thus underscoring its
-importance in manufacturing high-quality memory T cells for immunotherapies. T
+healthy but show a deficit in memory CD8 T cells, thus underscoring this
+cytokine's importance in producing memory T cells for immunotherapies. T
 cells themselves express \il{15} and all of its receptor
 components\cite{MirandaCarus2005}. Additionally, blocking \il{15} itself or
 \il{15R$\upalpha$} \invitro{} has been shown to inhibit homeostatic
@@ -1158,20 +1152,20 @@ proliferation of resting human T cells\cite{MirandaCarus2005}.
 % ACRO fix the il2R and IL15R stuff
 \il{15} has been puzzling historically because it shares almost the same pathway
 as \il{2} yet has different functions\cite{Stonier2010, Osinalde2014, Giri1994,
-  Giri1995}. In particular, both cytokines share the common $\upgamma$ subchain
-(CD132) as well as the \il{2} $\upbeta$ receptor (CD122). The main difference in
-the heterodimeric receptors for \il{2} and \il{15} is the \il{2} $\upalpha$
-receptor (CD25) and the \il{15} $\upalpha$ chain respectively, both of which
-have high affinity for their respective ligands. The \il{2R$\upalpha$} chain
-itself does not have any signaling capacity, and therefore all the signaling
-resulting from \il{2} is mediated thought the $\upbeta$ and $\upgamma$ chains,
-namely via JAK1 and JAK3 leading to STAT5 activation consequently T cell
-activation. \il{15R$\upalpha$} itself has some innate signaling capacity, but
-this is poorly characterized in lymphocytes\cite{Stonier2010}. Thus there is a
-significant overlap between the functions of \il{2} and \il{15} due to their
-receptors sharing the $\upbeta$ and $\upgamma$ chains in their heterodimeric
-receptors, and perhaps the main driver of their differential functions it the
-half life of each respective receptor\cite{Osinalde2014}.
+  Giri1995}. In particular, both cytokines bond with heterotrimeric receptors
+which share the common $\upgamma$ subchain (CD132) as well as the \il{2}
+$\upbeta$ receptor (CD122). The difference is the third subchain which is either
+the \il{2} $\upalpha$ receptor (CD25) or the \il{15} $\upalpha$ chain
+respectively, both of which have high affinity for their respective ligands. The
+\il{2R$\upalpha$} chain itself does not have any signaling capacity, and
+therefore all the signaling resulting from \il{2} is mediated thought the
+$\upbeta$ and $\upgamma$ chains (namely via JAK1 and JAK3, which leads to STAT5
+activation, which leads to T cell activation). \il{15R$\upalpha$} itself has
+some innate signaling capacity, but this is poorly characterized in
+lymphocytes\cite{Stonier2010}. Thus there is a significant overlap between the
+functions of \il{2} and \il{15} due to their receptors sharing the $\upbeta$ and
+$\upgamma$ chains, and perhaps the main driver of their differential functions
+it the half life of each respective receptor\cite{Osinalde2014}.
 
 Where \il{15} is unique is that many (or possibly most) of its functions derive
 from being membrane-bound to its receptor\cite{Stonier2010}. Particularly,
@@ -1186,18 +1180,18 @@ mechanism is that cells expression \il{15R$\upalpha$} either need to express
 proximity require the $\upbeta$ and $\upgamma$ chains to receive the signal. In
 addition to \textit{trans} presentation, \il{15} may also work in a \textit{cis}
 manner, where \il{15R$\upalpha$}/\il{15} complexes may bind to the $\upbeta$ and
-$\upgamma$ chains on the same cell, assuming all receptors are expressed and
-soluble \il{15} is available\cite{Olsen2007}. Finally, \il{15R$\upalpha$} itself can exist in
-a soluble form, which can bind to \il{15} and signal to cells which are not
-adjacent to the source independent of the \textit{cis/trans} mechanisms already
-described\cite{Budagian2004}.
+$\upgamma$ chains on the same cell, assuming each subchain is expressed and
+soluble \il{15} is available\cite{Olsen2007}. Finally, \il{15R$\upalpha$} itself
+can exist in soluble form, which can bind to \il{15} and signal to cells which
+are not adjacent to the source independent of the \textit{cis/trans} mechanisms
+already described\cite{Budagian2004}.
 
 \subsection{Overview of Design of Experiments}\label{sec:background_doe}
 
-The \gls{dms} system described in this dissertation has a number of parameters
-that can be optimized and controlled (eg \glspl{cpp}). A \gls{doe} is an ideal
-framework to test multiple parameters simultaneously and determine which are
-relevant \glspl{cpp}.
+The \gls{dms} system described in this dissertation has many parameters that can
+be optimized and controlled (eg \glspl{cpp}). A \gls{doe} is an ideal framework
+to test multiple parameters simultaneously and determine which are relevant
+\glspl{cpp}.
 
 The goal of \gls{doe} is to answer a data-driven question with the least number
 of resources\cite{Wu2009}. It was developed in many non-biological industries
@@ -1206,30 +1200,33 @@ industries where engineers needed to minimize downtime and resource consumption
 on full-scale production lines.
 
 At its core, a \gls{doe} is simply a matrix of conditions to test where each row
-(usually called a `run') corresponds to one experimental unit for which the
-conditions are applied, and each column represents a parameter of concern to be
-tested. The values in each cell represent the level at which each parameter is
-to be tested. When the experiment is performed using this matrix of conditions,
-the results are be summarized into one or more `responses' that correspond to
-each run. These responses are then be modeled (usually using linear regression)
-to determine the statistic relationship (also called an `effect') between each
-parameter and the response(s).
+(usually called a ``run,'' which is the term used throughout this work)
+corresponds to one experimental unit for which the conditions are applied, and
+each column represents a parameter of concern to be tested. The values in each
+cell represent the level of each parameter. When the experiment is performed
+using this matrix of conditions, the results are be summarized into one or more
+``responses'' that correspond to each run. These responses are then be modeled
+(usually using linear regression) to determine the statistical relationship
+(also called an ``effect'') between each parameter and the response(s).
 
 Collectively, the space spanned by all parameters at their feasible ranges is
-commonly referred to as the `design space', and generally the goal of a
+commonly referred to as the ``design space'', and generally the goal of a
 \gls{doe} is to explore this design space using using the least number of runs
 possible. While there are many types of \glspl{doe} depending on the nature
 of the parameters and the goal of the experimenter, they all share common
 principles:
 
 \begin{description}
-\item [randomization --] The order in which the runs are performed should
-  ideally be as random as possible. This is to mitigate against any confounding
-  factors that may be present which depend on the order or position of the runs.
-  For an example in context, the evaporation rate of media in a tissue culture
-  plate will be much faster at the perimeter of the plate vs the center. While
-  randomization does not eliminate this error, it will ensure the error is
-  `spread' evenly across all runs in an unbiased manner.
+\item [randomization --] The order in which the runs are performed should be
+  randomized. This is to guarantee that the tested parameters are independent of
+  any unobserved influences to the response, and thus allows the causal effect
+  of each parameter to be isolated completely\footnote{this is why \glspl{doe}
+    are sometimes called ``black box models;'' one can can safely say ``this
+    parameter causes that'' without paying attention to the causal structure of
+    the experiment}. For an example in context, the evaporation rate of media in
+  a tissue culture plate will be much faster at the perimeter of the plate vs
+  the center. While randomization does not eliminate this error, it will ensure
+  the error is ``spread'' across all runs in an unbiased manner.
 \item [replication --] Since the analysis of a \gls{doe} is inherently
   statistical, replicates should be used to ensure that the underlying
   distribution of errors can be estimated. While this is not strictly necessary
@@ -1237,7 +1234,7 @@ principles:
   strong assumptions about the model structure (particularly in the case of
   high-complexity models which could easily fit the data perfectly) and also
   precludes the use of statistical tests such as the lack-of-fit test which can
-  be useful in rejecting or accepting a particular analysis. Note that the
+  be useful in rejecting or accepting a particular model. Note that the
   subject of replication is within but not the same as power analysis, which
   concerns the number of runs required to estimate a certain effect size.
 \item [orthogonality --] Orthogonality refers to the independence of each
@@ -1249,14 +1246,15 @@ principles:
   experiments with many categorical variables) strategies exist to maximize
   orthogonality.
 \item [blocking --] In the case where the experiment must be non-randomly spread
-  over multiple groups, runs are assigned to `blocks' which are not necessarily
-  relevant to the goals of the experiment but nonetheless could affect the
-  response. A key assumption that is (usually) made in the case of blocking is
-  that there is no interaction between the blocking variable and any of the
-  experimental parameters. For example, in T cell expansion, if media lot were a
-  blocking variable and expansion method were a parameter, we would by default
-  assume that the effect of the expansion method does not depend on the media
-  lot (even if the media lot itself might change the mean of the response).
+  over multiple groups, runs are assigned to ``blocks'' which are not
+  necessarily relevant to the goals of the experiment but nonetheless could
+  affect the response. A key assumption that is (usually) made in the case of
+  blocking is that there is no interaction between the blocking variable and any
+  of the experimental parameters. For example, in T cell expansion, if media lot
+  were a blocking variable and expansion method were a parameter, we would by
+  default assume that the effect of the expansion method does not depend on the
+  media lot (even if the media lot itself might change the mean of the
+  response).
 \end{description}
 
 \Glspl{doe} served three purposes in this dissertation. First, we used them as
@@ -1279,28 +1277,26 @@ investigated. However, it could be the case that one already has data on many of
 the factors of concern. If one only cares about main effects, performing a
 \gls{doe} (particularly a lower-powered screening experiment such as a
 resolution III design) with these factors and a few others may not be
-productive, and one is better off performed a few extra pilot experiments before
-doing a more complex design such as a central composite if desired. Furthermore,
-it should be noted that while the goal of a \gls{doe} is to minimize resources,
-the size necessary to justify a \gls{doe} may not be worth the experimental
-return. For biological work (or any domain with little automation), performing a
-randomized experiment with 20 to 30 runs is not trivial from a logistical
-perspective, especially when considering the number of manual manipulations and
-the chance of human error.
+productive, and one is better off performing a few extra pilot experiments
+before doing a more complex design such as a central composite if desired.
+Furthermore, it should be noted that while the goal of a \gls{doe} is to
+minimize resources, the size necessary to justify a \gls{doe} may not be worth
+the experimental return. For biological work (or any domain with little
+automation), performing a randomized experiment with 20 to 30 runs is not
+trivial from a logistical perspective, especially when considering the number of
+manual manipulations and the chance of human error.
 
 Despite these caveats, many of the principles used for a \gls{doe} are important
 in general for experimentation. The most obvious is randomization, which is
-often not employed (and also not explicitly mentioned in papers) even though it
-is empirically obvious that well plates have different evaporation rates
-depending on well position. Assuming the experiment is manual, the largest
-reason to avoid randomization is that the experimentalist has no pattern to
-follow when administering treatment (such as ``add X to row 1 in well plate''),
-thus cognitive burden and the likelihood of mistakes increases. While
-\glspl{doe} are usually bigger with more parameters, the one-factor-at-a-time
-experiment usually performed in biological disciplines is much smaller and only
-has a few parameters, thus these concerns are minimal. There is no reason to
-avoid randomization in these cases, as the added cognitive cost is far offset by
-the guarantee of eliminated bias due to run position.
+often not employed (and also not explicitly mentioned in papers). Assuming the
+experiment is manual, the largest reason to avoid randomization is that the
+experimentalist has no pattern to follow when administering treatment (such as
+``add X to row 1 in well plate''), thus cognitive burden and the likelihood of
+mistakes increases. While \glspl{doe} are usually bigger with more parameters,
+the one-factor-at-a-time experiment usually performed in biological disciplines
+is much smaller and only has a few parameters, thus these concerns are minimal.
+There is no reason to avoid randomization in these cases, as the added cognitive
+cost is far offset by the guarantee of eliminated bias due to run position.
 
 \subsection{Identification and Standardization of CPPs and
   CQAs}\label{sec:background_cqa}
@@ -1315,15 +1311,15 @@ secrete numerous cytokines and metabolites in the media, which may reflect the
 internal state accurately and thus serve as a potential set of \glspl{cqa}.
 
 The complexity of these pathways dictates that we take a big-data approach to
-this problem. To this end, there are several pertinent multi-omic (or simply
-`omic') techniques that can be used to collect such datasets, which can then be
-mined, modeled, and correlated to relevent responses (such as an endpoint
-quantification of memory T cells) to identify pertinent \glspl{cqa}.
+this problem. To this end, there are several multi-omic (or simply ``omic'')
+techniques that can be used to collect such datasets, which can then be fit to
+relevent responses (such as an endpoint quantification of memory T cells) to
+identify pertinent \glspl{cqa}.
 
 An overview of the techniques used in this work are:
 
 \begin{description}
-\item[Luminex --] This is a multiplexed bead-based assay similar to \gls{elisa} that can measure
+\item[luminex --] This is a multiplexed bead-based assay similar to \gls{elisa} that can measure
   many bulk (not single cell) cytokine concentrations simultaneously
   in a media sample. This is a destructive assay but does not require cells to
   obtain a measurement.
@@ -1333,7 +1329,7 @@ An overview of the techniques used in this work are:
   oxidation\cite{Buck2016, van_der_Windt_2012}. \gls{nmr} is a technique that
   can non-destructively quantify small molecules in a media sample, and thus is
   an attractive method that could be used for inline, real-time monitoring.
-\item[Flow and Mass Cytometry --] Flow cytometry using fluorophores has been
+\item[flow and mass cytometry --] Flow cytometry using fluorophores has been
   used extensively for immune cell analysis, but has a practical limit of
   approximately 18 colors\cite{Spitzer2016}. Mass cytometry is analogous to
   traditional flow cytometry except that it uses heavy-metal \gls{mab}
@@ -1359,11 +1355,11 @@ interesting cell types and the markers that define them.
 
 Ultimately, identifying \glspl{cqa} will likely be an iterative process, wherein
 putative \glspl{cqa} will be identified, the corresponding \glspl{cpp} will be
-set and optimized to maximize products with these \glspl{cpp}, and then
-additional data will be collected in the clinic as the product is tested on
-various patients with different indications. Additional \glspl{cqa} may be
-identified which better predict specific clinical outcomes, which can be fed
-back into the process model and optimized again.
+set to maximize high-quality products, and then additional data will be
+collected in the clinic as the product is tested on various patients with
+different indications. Additional \glspl{cqa} may be identified which better
+predict specific clinical outcomes, which can be fed back into the process model
+and optimized again.
 
 \section{Innovation}
 
@@ -1373,7 +1369,7 @@ novel considering the state-of-the-art technology for T cell manufacturing:
 \begin{itemize}
 \item \Glspl{dms} offers a compelling alternative to state-of-the-art magnetic
   bead technologies (e.g. DynaBeads, MACS-Beads), which is noteworthy because
-  the licenses for these techniques is controlled by only a few companies
+  the licenses for these techniques are controlled by only a few companies
   (Invitrogen and Miltenyi respectively). Because of this, bead-based expansion
   is more expensive to implement and therefore hinders companies from entering
   the rapidly growing T cell manufacturing arena. Providing an alternative will
@@ -1381,7 +1377,7 @@ novel considering the state-of-the-art technology for T cell manufacturing:
   lower costs, and higher innovation in the T cell manufacturing space.
 \item This is the first technology for T cell immunotherapies that selectively
   expands memory T cell populations with greater efficiency relative to
-  bead-based expansion Others have demonstrated methods that can achieve greater
+  bead-based expansion. Others have demonstrated methods that can achieve greater
   expansion of T cells, but not necessarily specific populations that are known
   to be potent.
 \item We used \glspl{doe} to discover and validate novel \glspl{cpp}, which is a
@@ -1389,9 +1385,9 @@ novel considering the state-of-the-art technology for T cell manufacturing:
   usage in the development of cell therapies where research often employs a
   one-factor-at-a-time approach. We believe this method is highly relevant to
   the development of cell therapies, not only for process optimization but also
-  hypotheses generation. Furthermore, it is a perfectly natural strategy to use
-  even at small scale, where the cost of reagents, cells, and materials often
-  precludes large sample sizes.
+  hypotheses generation. Furthermore, it is a natural strategy to use even at
+  small scale, where the cost of reagents, cells, and materials often precludes
+  large sample sizes.
 \item The \gls{dms} system is be compatible with static bioreactors such as the
   G-Rex which has been adopted throughout the cell therapy industry. Thus this
   technology can be easily incorporated into existing cell therapy process that