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tex/references.bib
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@ -2475,6 +2475,75 @@ CONCLUSIONS: We developed a simplified, semi-closed system for the initial selec
publisher = {Springer Science and Business Media {LLC}},
}
@Article{Kamholz2001,
author = {Kamholz, A. E. and Schilling, E. A. and Yager, P.},
journal = {Biophysical journal},
title = {Optical measurement of transverse molecular diffusion in a microchannel.},
year = {2001},
issn = {0006-3495},
month = apr,
pages = {1967--1972},
volume = {80},
abstract = {Quantitative analysis of molecular diffusion is a necessity for the efficient design of most microfluidic devices as well as an important biophysical method in its own right. This study demonstrates the rapid measurement of diffusion coefficients of large and small molecules in a microfluidic device, the T-sensor, by means of conventional epifluorescence microscopy. Data were collected by monitoring the transverse flux of analyte from a sample stream into a second stream flowing alongside it. As indicated by the low Reynolds numbers of the system (< 1), flow is laminar, and molecular transport between streams occurs only by diffusion. Quantitative determinations were made by fitting data with predictions of a one-dimensional model. Analysis was made of the flow development and its effect on the distribution of diffusing analyte using a three-dimensional modeling software package. Diffusion coefficients were measured for four fluorescently labeled molecules: fluorescein-biotin, insulin, ovalbumin, and streptavidin. The resulting values differed from accepted results by an average of 2.4%. Microfluidic system parameters can be selected to achieve accurate diffusion coefficient measurements and to optimize other microfluidic devices that rely on precise transverse transport of molecules.},
chemicals = {Biotin},
citation-subset = {IM},
completed = {2001-06-21},
country = {United States},
doi = {10.1016/S0006-3495(01)76166-8},
issn-linking = {0006-3495},
issue = {4},
keywords = {Biochemistry, instrumentation; Biotin, pharmacology; Computer Simulation; Diffusion; Microscopy, Fluorescence, instrumentation, methods; Models, Theoretical},
nlm-id = {0370626},
owner = {NLM},
pii = {S0006-3495(01)76166-8},
pmc = {PMC1301385},
pmid = {11259309},
pubmodel = {Print},
pubstate = {ppublish},
revised = {2018-11-13},
}
@Article{Niether2020,
author = {Doreen Niether and Mona Sarter and Bernd W. Koenig and Jörg Fitter and Andreas M. Stadler and Simone Wiegand},
journal = {Polymers},
title = {Thermophoresis: The Case of Streptavidin and Biotin},
year = {2020},
month = {feb},
number = {2},
pages = {376},
volume = {12},
doi = {10.3390/polym12020376},
publisher = {{MDPI} {AG}},
}
@Article{Kerwin2008,
author = {Kerwin, Bruce A.},
journal = {Journal of pharmaceutical sciences},
title = {Polysorbates 20 and 80 used in the formulation of protein biotherapeutics: structure and degradation pathways.},
year = {2008},
issn = {1520-6017},
month = aug,
pages = {2924--2935},
volume = {97},
abstract = {Polysorbates 20 and 80 (Tween 20 and Tween 80) are used in the formulation of biotherapeutic products for both preventing surface adsorption and as stabilizers against protein aggregation. The polysorbates are amphipathic, nonionic surfactants composed of fatty acid esters of polyoxyethylene sorbitan being polyoxyethylene sorbitan monolaurate for polysorbate 20 and polyoxyethylene sorbitan monooleate for polysorbate 80. The polysorbates used in the formulation of biopharmaceuticals are mixtures of different fatty acid esters with the monolaurate fraction of polysorbate 20 making up only 40-60% of the mixture and the monooleate fraction of polysorbate 80 making up >58% of the mixture. The polysorbates undergo autooxidation, cleavage at the ethylene oxide subunits and hydrolysis of the fatty acid ester bond. Autooxidation results in hydroperoxide formation, side-chain cleavage and eventually formation of short chain acids such as formic acid all of which could influence the stability of a biopharmaceutical product. Oxidation of the fatty acid moiety while well described in the literature has not been specifically investigated for polysorbate. This review focuses on the chemical structure of the polysorbates, factors influencing micelle formation and factors and excipients influencing stability and degradation of the polyoxyethylene and fatty acid ester linkages.},
chemicals = {Polysorbates, Proteins, Surface-Active Agents},
citation-subset = {IM},
completed = {2008-11-04},
country = {United States},
doi = {10.1002/jps.21190},
issn-linking = {0022-3549},
issue = {8},
keywords = {Chemistry, Pharmaceutical; Molecular Structure; Oxidation-Reduction; Polysorbates, chemistry; Proteins, administration & dosage, chemical synthesis, therapeutic use; Surface Tension; Surface-Active Agents, chemistry},
nlm-id = {2985195R},
owner = {NLM},
pii = {S0022-3549(16)32657-0},
pmid = {17973307},
pubmodel = {Print},
pubstate = {ppublish},
references = {91},
revised = {2008-07-28},
}
@Comment{jabref-meta: databaseType:bibtex;}
@Comment{jabref-meta: grouping:

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tex/thesis.tex
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@ -485,8 +485,8 @@ such as bioreactors.
% TODO probably need to address some of the modeling stuff here as well
This thesis describes a novel degradable microscaffold-based method derived from
porous microcarriers functionalized with \acd{3} and \acd{28} \glspl{mab}
for use in T cell expansion cultures. Microcarriers have historically been used
porous microcarriers functionalized with \acd{3} and \acd{28} \glspl{mab} for
use in T cell expansion cultures. Microcarriers have historically been used
throughout the bioprocess industry for adherent cultures such as stem cells and
\gls{cho} cells, but not with suspension cells such as T
cells\cite{Heathman2015, Sart2011}. The microcarriers chosen to make the DMSs in
@ -499,17 +499,17 @@ larger contact area for T cells to interact with the \glspl{mab} relative to
beads; this may better emulate the large contact surface area that occurs
between T cells and \glspl{dc}. These microcarriers are readily available in
over 30 countries and are used in an FDA fast-track-approved combination retinal
pigment epithelial cell product (Spheramine, Titan Pharmaceuticals) {\#}[Purcell
documentation]. This regulatory history will aid in clinical translation. We
show that compared to traditional microbeads, \gls{dms}-expanded T cells not
only provide superior expansion, but consistently provide a higher frequency of
naïve/memory and CD4 T cells (CCR7+CD62L+) across multiple donors. We also
demonstrate functional cytotoxicity using a CD19 \gls{car} and a superior
performance, even at a lower \gls{car} T cell dose, of \gls{dms}-expanded
\gls{car}-T cells \invivo{} in a mouse xenograft model of human B cell
\gls{all}. Our results indicate that \glspl{dms} provide a robust and scalable
platform for manufacturing therapeutic T cells with higher naïve/memory
phenotype and more balanced CD4+ T cell content.
pigment epithelial cell product (Spheramine, Titan
Pharmaceuticals)\cite{purcellmain}. This regulatory history will aid in clinical
translation. We show that compared to traditional microbeads, \gls{dms}-expanded
T cells not only provide superior expansion, but consistently provide a higher
frequency of naïve/memory and CD4 T cells (CCR7+CD62L+) across multiple donors.
We also demonstrate functional cytotoxicity using a CD19 \gls{car} and a
superior performance, even at a lower \gls{car} T cell dose, of
\gls{dms}-expanded \gls{car}-T cells \invivo{} in a mouse xenograft model of
human B cell \gls{all}. Our results indicate that \glspl{dms} provide a robust
and scalable platform for manufacturing therapeutic T cells with higher
naïve/memory phenotype and more balanced CD4+ T cell content.
\section*{hypothesis}
@ -1569,10 +1569,9 @@ diffusion coefficient of \gls{stp} in water. This model was given by
\item $n$ is the number of microcarriers in the reaction volume
\end{itemize}
% TODO cite the diffusion rate of stp
The diffusion rate of \gls{stp} was assumed to be
\SI{3.89e-7}{\cm\squared\per\second} {\#}{diffusion rate citation}. Since all
but $\beta$ was known, the experimental data was fit using these equations using
\SI{6.2e-7}{\cm\squared\per\second}\cite{Kamholz2001}. Since all but $\beta$ was
known, the experimental data was fit using these equations using
\inlinecode{ode45} in MATLAB and least squares as the fitting error.
% TODO this diffusion rate isn't actually reflected in the code
@ -1582,6 +1581,9 @@ These equations were then used analogously to describe the reaction profile of
% METHOD add the equation governing the washing steps
The diffusion coefficient used for biotin was
\SI{5e-6}{\cm\squared\per\second}\cite{Niether2020}
\subsection{Luminex Analysis}\label{sec:luminex_analysis}
Luminex was performed using a \product{ProcartaPlex kit}{\thermo}{custom} for
@ -1685,25 +1687,25 @@ context of pure error). Statistical significance was evaluated at $\upalpha$ =
Two types of gelatin-based microcariers, \gls{cus} and \gls{cug}, were
covalently conjugated with varying concentration of \gls{snb} and then coated
with \gls{stp} and \glspl{mab} to make \glspl{dms}. Aside from slight
differences in swelling ratio and crosslinking chemistry {\#}[Purcell
documentation], the properties of \gls{cus} and \gls{cug} were the same
(\cref{tab:carrier_props}). We chose to continue with the \gls{cus}-based
\glspl{dms}, which showed higher overall \gls{stp} binding compared to
\gls{cug}-based \glspl{dms} (\cref{fig:cug_vs_cus}). We showed that by varying
the concentration of \gls{snb}, we were able to precisely control the amount of
attached biotin (\cref{fig:biotin_coating}), mass of attached \gls{stp}
differences in swelling ratio and crosslinking chemistry\cite{purcellmain} the
properties of \gls{cus} and \gls{cug} were the same (\cref{tab:carrier_props}).
We chose to continue with the \gls{cus}-based \glspl{dms}, which showed higher
overall \gls{stp} binding compared to \gls{cug}-based \glspl{dms}
(\cref{fig:cug_vs_cus}). We showed that by varying the concentration of
\gls{snb}, we were able to precisely control the amount of attached biotin
(\cref{fig:biotin_coating}), mass of attached \gls{stp}
(\cref{fig:stp_coating}), and mass of attached \glspl{mab}
(\cref{fig:mab_coating}). Furthermore, we showed that the microcarriers were
evenly coated with \gls{stp} on the surface and throughout the interior as
evidenced by the presence of biotin-binding sites occupied with \gls{stp}-\gls{fitc}
on the microcarrier surfaces after the \gls{stp}-coating step
(\cref{fig:stp_carrier_fitc}). Finally, we confirmed that biotinylated
evidenced by the presence of biotin-binding sites occupied with
\gls{stp}-\gls{fitc} on the microcarrier surfaces after the \gls{stp}-coating
step (\cref{fig:stp_carrier_fitc}). Finally, we confirmed that biotinylated
\glspl{mab} were bound to the \glspl{dms} by staining either \gls{stp} or
\gls{stp} and \gls{mab}-coated carriers with \antim{\gls{igg}-\gls{fitc}} and imaging
on a confocal microscope (\cref{fig:mab_carrier_fitc}). Taking this together, we
noted that the maximal \gls{mab} binding capacity occurred near \SI{50}{\nmol}
biotin input (which corresponded to \SI{2.5}{\nmol\per\mg\of{\dms}}) thus we
used this in subsequent processes.
\gls{stp} and \gls{mab}-coated carriers with \antim{\gls{igg}-\gls{fitc}} and
imaging on a confocal microscope (\cref{fig:mab_carrier_fitc}). Taking this
together, we noted that the maximal \gls{mab} binding capacity occurred near
\SI{50}{\nmol} biotin input (which corresponded to
\SI{2.5}{\nmol\per\mg\of{\dms}}) thus we used this in subsequent processes.
% TODO flip the rows of this figure (right now the text is backward)
\begin{figure*}[ht!]
@ -1872,7 +1874,7 @@ using the \gls{bca} assay to indirectly quantify the amount of attached
(\cref{fig:dms_stp_per_time}). Assuming a quasi-steady-state paradigm, we used
this experimental binding data to fit a continuous model for the \gls{stp}
binding reaction. Using the diffusion rate of the \gls{stp}, we then calculated
the effective diffusivity of the microcarriers to be {\#}.
the effective diffusivity of the microcarriers to be 0.2.
Using this effective diffusivity and the known diffusion coefficient of a
\gls{mab} protein in water, we calculated predict the binding of \glspl{mab} per
@ -2002,9 +2004,9 @@ membrane. When staining for these two markers and assessing via flow cytometry,
we observe that the \gls{dms}-expanded T cells have lower frequencies of
apoptotic and necrotic cells (\cref{fig:apoptosis_annV}). Furthermore, we
stained our cultures with CellEvent dye, which is an indicator of \gls{cas37},
which is activated in apoptotic cells {\#}{cas37 activation}. In line with the
\gls{pi}/\gls{anv} results, we observed that the \gls{dms} T cells had lower
frequency of \gls{cas37} expression, indicating less apoptosis for our method
which is activated in apoptotic cells. In line with the \gls{pi}/\gls{anv}
results, we observed that the \gls{dms} T cells had lower frequency of
\gls{cas37} expression, indicating less apoptosis for our method
(\cref{fig:apoptosis_cas}). Finally, we lysed our cells and stained for
\gls{bcl2}, which is also upregulated in apoptosis. In this case, some (but not
all) of the bead-expanded cultures showed higher \gls{bcl2} expression, which
@ -3642,8 +3644,8 @@ them to grow better in the \gls{dms} system.
We tested this hypothesis by adding blocking \glspl{mab} against \gls{a2b1}
and/or \gls{a2b2} to running T cell cultures activated using the \glspl{dms}.
These block \glspl{mab} were added at day 6 of culture when \gls{a2b1} and
\gls{a2b2} were known to be expressed {\#}. We found that the fold expansion was
identical in all the blocked groups vs the unblocked control group
\gls{a2b2} were known to be expressed\cite{Hemler1990}. We found that the fold
expansion was identical in all the blocked groups vs the unblocked control group
(\cref{fig:inegrin_1_fc}). Furthermore, we observed that the \ptmemp{} (total
and across the CD4/CD8 compartments) was not significantly different between any
of the groups (\cref{fig:inegrin_1_mem,tab:integrin_1_reg}). We also noted that
@ -3808,13 +3810,13 @@ receptors may simply be irrelevant for our system.
On the first point, we did not verify that these \glspl{mab} indeed blocked the
receptor we were targeting. There has been evidence from other groups that these
particular clones work at the concentrations we used {\#}. This does not
necessarily mean that the \glspl{mab} we obtained were functional in blocking
their intended targets (although they were from a reputable manufacturer, \bl).
Furthermore, we can safely rule out the possibility that the \glspl{mab} never
reached their targets, as they were added immediately after the T cells were
resuspended as required for cell counting, hence their resting clustered state
was disrupted.
particular clones work at the concentrations we used\cite{MirandaCarus2005}.
This does not necessarily mean that the \glspl{mab} we obtained were functional
in blocking their intended targets (although they were from a reputable
manufacturer, \bl). Furthermore, we can safely rule out the possibility that the
\glspl{mab} never reached their targets, as they were added immediately after
the T cells were resuspended as required for cell counting, hence their resting
clustered state was disrupted.
% TODO define Bite
On the second point, the collagen domains may not even be relevant to our system
@ -4046,15 +4048,15 @@ case of beads (\cref{fig:mouse_dosing_qc_mem}).
\subsection{Beads and DMSs perform similarly at earlier timepoints}
We then asked how T cells harvested using either beads or \gls{dms} performed
when harvested at earlier timepoints {\#}{levine paper with early timepoints}.
We performed the same experiments as described in
\cref{fig:mouse_dosing_overview} with the modification that T cells were only
grown and harvested after \SI{6}{\day}, \SI{10}{\day}, or \SI{14}{\day} of
expansion (\cref{fig:mouse_timecourse_overview}). T cells were frozen after
harvest, and all timepoints were thawed at the same time prior to injection. The
dose of T cells injected was \num{1.25e6} cells per mouse (the same as the high
dose in the first experiment). All other characteristics of the experiment were
the same.
when harvested at earlier timepoints\cite{Ghassemi2018}. We performed the same
experiments as described in \cref{fig:mouse_dosing_overview} with the
modification that T cells were only grown and harvested after \SI{6}{\day},
\SI{10}{\day}, or \SI{14}{\day} of expansion
(\cref{fig:mouse_timecourse_overview}). T cells were frozen after harvest, and
all timepoints were thawed at the same time prior to injection. The dose of T
cells injected was \num{1.25e6} cells per mouse (the same as the high dose in
the first experiment). All other characteristics of the experiment were the
same.
\begin{figure*}[ht!]
\begingroup
@ -4083,7 +4085,7 @@ untransduced cells. The \pthp{} of the harvested T cells was higher overall in
(\cref{fig:mouse_timecourse_qc_cd4}). The \ptmemp{} was similar at day 6
between bead and \gls{dms} groups but the \gls{dms} group had higher \ptmemp{}
at day 14 despite the overall \ptmemp{} decreasing with time as shown elsewhere
(\cref{fig:mouse_timecourse_qc_mem}) {\#}{levine paper mem over time}.
(\cref{fig:mouse_timecourse_qc_mem})\cite{Ghassemi2018}.
\begin{figure*}[ht!]
\begingroup
@ -4265,17 +4267,17 @@ for the patient, while also minimizing cost for the manufacturer. Second,
\glspl{cqa} can be used to define process control schemes as well as release
criteria. Process control, and with it the ability to predict future outcomes
based on data obtained at the present, is highly important for cell therapies
given that batch failures are extremely expensive {\#}, and predicting a batch
failure would allow manufacturers to restart the batch in a timely manner
without wasting resources. Furthermore, \glspl{cqa} can be used to define what a
`good' vs `bad' product is, which will important help anticipate dosing and
followup procedures in the clinic if the T cells are administered. In the aim,
we cannot claim to have found the ultimate set of \glspl{cqa} and \glspl{cpp},
as we used tissue culture plates instead of a bioreactor and we only used one
donor. However, we have indeed outlined a process that others may use to find
these for their process. In particular, the 2-phase modeling process we used
(starting with a \gls{doe} and collecting data longitudinally) is a strategy
that manufacturers can easily implement. Also, collecting secretome and
given that batch failures are extremely expensive\cite{Harrison2019}, and
predicting a batch failure would allow manufacturers to restart the batch in a
timely manner without wasting resources. Furthermore, \glspl{cqa} can be used to
define what a `good' vs `bad' product is, which will important help anticipate
dosing and followup procedures in the clinic if the T cells are administered. In
the aim, we cannot claim to have found the ultimate set of \glspl{cqa} and
\glspl{cpp}, as we used tissue culture plates instead of a bioreactor and we
only used one donor. However, we have indeed outlined a process that others may
use to find these for their process. In particular, the 2-phase modeling process
we used (starting with a \gls{doe} and collecting data longitudinally) is a
strategy that manufacturers can easily implement. Also, collecting secretome and
metabolome is easily generalized to any setting and to most bioreactors and
expansion systems, as they can be obtained with relatively inexpensive equipment
(Luminex assay, benchtop \gls{nmr}, etc) without disturbing the cell culture.
@ -4285,12 +4287,13 @@ to control and optimize the \gls{dms} system. We determined that altering the
\gls{dms} concentration temporally has profound effects on the phenotype and
expansion rate. This agrees with other data we obtained in \cref{aim2a} and with
what others have generally reported about signal strength and T cell
differentiation {\#}. We did not find any mechanistic relationship between
either integrin signaling or \gls{il15} signaling. In the case of the former, it
may be more likely that the \glspl{dms} surfaces are saturated to the point of
sterically hindering any integrin interactions with the collagen surface. In the
case of \gls{il15} more experiments likely need to be done in order to plausibly
rule out this mechanism and/or determine if it is involved at all.
differentiation\cite{Gattinoni2012}. We did not find any mechanistic
relationship between either integrin signaling or \gls{il15} signaling. In the
case of the former, it may be more likely that the \glspl{dms} surfaces are
saturated to the point of sterically hindering any integrin interactions with
the collagen surface. In the case of \gls{il15} more experiments likely need to
be done in order to plausibly rule out this mechanism and/or determine if it is
involved at all.
% TODO make this tighter and cite paper showing that this makes at least some
% sense
@ -4327,11 +4330,11 @@ tubes. A human carrier protein such as \gls{hsa} could be used in its place to
eliminate the non-human animal origin material, but this could be much more
expensive. Alternatively, the use of protein could be replaced altogether by a
non-ionic detergent such as Tween-20 or Tween-80, which are already used for
commercial \gls{mab} formulations for precisely this purpose {\#}. Validating
the process with Tween would be the best next step to eliminate \gls{bsa} from
the process. The \gls{stp} and \glspl{mab} in this process were not
\gls{gmp}-grade; however, they are commonly used in clinical technology such as
dynabeads and thus the research-grade proteins used here could be easily
commercial \gls{mab} formulations for precisely this purpose\cite{Kerwin2008}.
Validating the process with Tween would be the best next step to eliminate
\gls{bsa} from the process. The \gls{stp} and \glspl{mab} in this process were
not \gls{gmp}-grade; however, they are commonly used in clinical technology such
as dynabeads and thus the research-grade proteins used here could be easily
replaced. The \gls{snb} is a synthetic small molecule and thus does not have any
animal-origin concerns.