Computers & Industrial Engineering,
Год журнала:
2024,
Номер
191, С. 110078 - 110078
Опубликована: Март 24, 2024
Cancer
is
a
leading
cause
of
death
and
cost
burden
on
healthcare
systems
worldwide.
The
mainstay
treatment
chemotherapy
which
most
often
administered
empirically.
Optimizing
the
frequency
drug
administration
would
benefit
patients
by
avoiding
overtreatment
reducing
costs.
In
this
work,
optimization
regimens
using
mathematical
programming
techniques
demonstrated
developing
simple
model
for
fictitious
drug.
question
to
be
answered
solution
how
should
so
that
tumor
size
does
not
exceed
predefined
reaches
minimum
value.
proposed
computer-implemented
well-established
system,
thus
keeping
effort
obtaining
results
low.
An
example
used
demonstrate
superiority
approach
over
approach.
Proceedings of the Royal Society B Biological Sciences,
Год журнала:
2021,
Номер
288(1947)
Опубликована: Март 24, 2021
Chimeric
antigen
receptor
(CAR)
T
cell
therapy
is
a
remarkably
effective
immunotherapy
that
relies
on
in
vivo
expansion
of
engineered
CAR
cells,
after
lymphodepletion
(LD)
by
chemotherapy.
The
quantitative
laws
underlying
this
and
subsequent
tumour
eradication
remain
unknown.
We
develop
mathematical
model
cell–tumour
interactions
demonstrate
can
be
explained
immune
reconstitution
dynamics
LD
competition
among
cells.
cells
rapidly
grow
engage
but
experience
an
emerging
growth
rate
disadvantage
compared
to
normal
Since
deterministically
unstable
our
model,
we
define
cure
as
stochastic
event,
which,
even
when
likely,
occur
at
variable
times.
However,
show
variability
timing
largely
determined
patient
variability.
While
events
impacted
these
fluctuations
early
are
narrowly
distributed,
progression
late
more
widely
distributed
time.
parameterized
using
population-level
data
over
time
compare
predictions
with
progression-free
survival
rates.
find
could
improved
optimizing
the
tumour-killing
cells'
ability
adapt,
quantified
their
carrying
capacity.
Our
extinction
leveraged
examine
why
works
some
patients
not
others,
better
understand
interplay
deterministic
effects
outcomes.
For
example,
implies
before
second
injection
necessary.
Cancers,
Год журнала:
2021,
Номер
13(12), С. 3008 - 3008
Опубликована: Июнь 16, 2021
Tumor-associated
vasculature
is
responsible
for
the
delivery
of
nutrients,
removal
waste,
and
allowing
growth
beyond
2–3
mm3.
Additionally,
vascular
network,
which
changing
in
both
space
time,
fundamentally
influences
tumor
response
to
systemic
radiation
therapy.
Thus,
a
robust
understanding
dynamics
necessary
accurately
predict
growth,
as
well
establish
optimal
treatment
protocols
achieve
control.
Such
goal
requires
intimate
integration
theory
experiment.
Quantitative
time-resolved
imaging
methods
have
emerged
technologies
able
visualize
characterize
properties
before
during
therapy
at
tissue
cell
scale.
Parallel
to,
but
separate
from
those
developments,
mathematical
modeling
techniques
been
developed
enable
silico
investigations
into
theoretical
dynamics.
In
particular,
recent
efforts
sought
integrate
experiment
data-driven
modeling.
models
are
calibrated
by
data
obtained
individual
tumor-vascular
systems
future
agents,
radiotherapy.
this
review,
we
discuss
experimental
visualizing
quantifying
including
magnetic
resonance
imaging,
microfluidic
devices,
confocal
microscopy.
We
then
focus
on
these
measures
with
biologically
based
generate
testable
predictions.
Neoplasia,
Год журнала:
2022,
Номер
28, С. 100796 - 100796
Опубликована: Апрель 19, 2022
Radiotherapy
is
a
primary
therapeutic
modality
widely
utilized
with
curative
intent.
Traditionally
tumor
response
was
hypothesized
to
be
due
high
levels
of
cell
death
induced
by
irreparable
DNA
damage.
However,
the
immunomodulatory
aspect
radiation
now
accepted.
As
such,
interest
into
combination
radiotherapy
and
immunotherapy
increasing,
synergy
which
has
potential
improve
regression
beyond
that
observed
after
either
treatment
alone.
questions
regarding
timing
(sequential
vs
concurrent)
dose
fractionation
(hyper-,
standard-,
or
hypo-fractionation)
result
in
improved
anti-tumor
immune
responses,
thus
potentially
enhanced
inhibition,
remain.
Here
we
discuss
biological
its
properties
before
giving
an
overview
pre-clinical
data
clinical
trials
concerned
answering
these
questions.
Finally,
review
published
mathematical
models
impact
on
tumor-immune
interactions.
Ranging
from
considering
microenvironment
induction
choice
site
setting
metastatic
disease,
all
have
underlying
feature
common:
push
towards
personalized
therapy.
Fractal and Fractional,
Год журнала:
2023,
Номер
7(8), С. 595 - 595
Опубликована: Авг. 1, 2023
Cancer
is
a
complex
disease,
responsible
for
significant
portion
of
global
deaths.
The
increasing
prioritisation
know-why
over
know-how
approaches
in
biological
research
has
favoured
the
rising
use
both
white-
and
black-box
mathematical
techniques
cancer
modelling,
seeking
to
better
grasp
multi-scale
mechanistic
workings
its
phenomena
(such
as
tumour-immune
interactions,
drug
resistance,
tumour
growth
diffusion,
etc.).
In
light
this
wide-ranging
mathematics
unique
memory
non-local
properties
Fractional
Calculus
(FC)
have
been
sought
after
last
decade
replace
ordinary
differentiation
hypothesising
FC’s
superior
modelling
oncological
phenomena,
which
shown
possess
an
accumulated
knowledge
past
states.
As
such,
review
aims
present
thorough
structured
survey
about
main
guiding
trends
categories
research,
emphasising
field
oncology
employment
whole.
most
pivotal
questions,
challenges
future
perspectives
are
also
outlined.
Bulletin of Mathematical Biology,
Год журнала:
2024,
Номер
86(2)
Опубликована: Янв. 18, 2024
Abstract
Longitudinal
tumour
volume
data
from
head-and-neck
cancer
patients
show
that
tumours
of
comparable
pre-treatment
size
and
stage
may
respond
very
differently
to
the
same
radiotherapy
fractionation
protocol.
Mathematical
models
are
often
proposed
predict
treatment
outcome
in
this
context,
have
potential
guide
clinical
decision-making
inform
personalised
protocols.
Hindering
effective
use
context
is
sparsity
measurements
juxtaposed
with
model
complexity
required
produce
full
range
possible
patient
responses.
In
work,
we
present
a
compartment
composition,
which,
despite
relative
simplicity,
capable
producing
wide
We
then
develop
novel
statistical
methodology
leverage
cohort
existing
predictive
both
progression
associated
level
uncertainty
evolves
throughout
patient’s
course
treatment.
To
capture
inter-patient
variability,
all
parameters
specific,
bootstrap
particle
filter-like
Bayesian
approach
developed
set
training
as
prior
knowledge.
validate
our
against
subset
unseen
data,
demonstrate
ability
trained
its
limitations.
PLoS ONE,
Год журнала:
2025,
Номер
20(1), С. e0310844 - e0310844
Опубликована: Янв. 9, 2025
Mathematical
modeling
plays
an
important
role
in
our
understanding
and
targeting
therapy
resistance
mechanisms
cancer.
The
polymorphic
Gompertzian
model,
analyzed
theoretically
numerically
by
Viossat
Noble
to
demonstrate
the
benefits
of
adaptive
metastatic
cancer,
describes
a
heterogeneous
cancer
population
consisting
therapy-sensitive
therapy-resistant
cells.
In
this
study,
we
that
model
successfully
captures
trends
both
vitro
vivo
data
on
non-small
cell
lung
(NSCLC)
dynamics
under
treatment.
Additionally,
for
tumor
patients
undergoing
treatment,
compare
goodness
fit
classical
oncologic
models,
which
were
previously
identified
as
models
best.
We
show
can
capture
U-shape
trend
size
during
relapse,
not
be
fitted
with
models.
general,
corresponds
well
real-world
data,
suggesting
it
candidate
improving
efficacy
therapy,
example,
through
evolutionary/adaptive
therapies.
