ndwarshuis
/
phd_thesis
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

ENH proofread introduction

This commit is contained in:
Nathan Dwarshuis 2021-09-08 00:53:51 -04:00
parent 088a8bf709
commit 130edc364e
1 changed files with 293 additions and 297 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

590
tex/thesis.tex
View File

@ -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