Artificial Intelligence (AI) Applications in Drug Discovery and Drug Delivery: Revolutionizing Personalized Medicine
Pharmaceutics,
Год журнала:
2024,
Номер
16(10), С. 1328 - 1328
Опубликована: Окт. 14, 2024
Artificial
intelligence
(AI)
encompasses
a
broad
spectrum
of
techniques
that
have
been
utilized
by
pharmaceutical
companies
for
decades,
including
machine
learning,
deep
and
other
advanced
computational
methods.
These
innovations
unlocked
unprecedented
opportunities
the
acceleration
drug
discovery
delivery,
optimization
treatment
regimens,
improvement
patient
outcomes.
AI
is
swiftly
transforming
industry,
revolutionizing
everything
from
development
to
personalized
medicine,
target
identification
validation,
selection
excipients,
prediction
synthetic
route,
supply
chain
optimization,
monitoring
during
continuous
manufacturing
processes,
or
predictive
maintenance,
among
others.
While
integration
promises
enhance
efficiency,
reduce
costs,
improve
both
medicines
health,
it
also
raises
important
questions
regulatory
point
view.
In
this
review
article,
we
will
present
comprehensive
overview
AI's
applications
in
covering
areas
such
as
discovery,
safety,
more.
By
analyzing
current
research
trends
case
studies,
aim
shed
light
on
transformative
impact
industry
its
broader
implications
healthcare.
Язык: Английский
Next-Generation Microfluidics for Biomedical Research and Healthcare Applications
Biomedical Engineering and Computational Biology,
Год журнала:
2023,
Номер
14
Опубликована: Янв. 1, 2023
Microfluidic
systems
offer
versatile
biomedical
tools
and
methods
to
enhance
human
convenience
health.
Advances
in
these
enables
next-generation
microfluidics
that
integrates
automation,
manipulation,
smart
readout
systems,
as
well
design
three-dimensional
(3D)
printing
for
precise
production
of
microchannels
other
microstructures
rapidly
with
great
flexibility.
These
3D-printed
microfluidic
platforms
not
only
control
the
complex
fluid
behavior
various
applications,
but
also
serve
microconduits
building
3D
tissue
constructs—an
integral
component
advanced
drug
development,
toxicity
assessment,
accurate
disease
modeling.
Furthermore,
integration
emerging
technologies,
such
microscopy
robotics,
spatiotemporal
manipulation
high-throughput
screening
cell
physiology
within
precisely
controlled
microenvironments.
Notably,
portability
high
precision
automation
capabilities
integrated
facilitate
rapid
experimentation
data
acquisition
help
deepen
our
understanding
biological
their
behaviors.
While
certain
challenges,
including
material
compatibility,
scaling,
standardization
still
exist,
artificial
intelligence,
Internet
Things,
materials,
miniaturization
holds
tremendous
promise
reshaping
traditional
approaches.
This
transformative
potential,
when
has
potential
revolutionize
research
healthcare
ultimately
benefiting
review
highlights
advances
field
emphasizes
critical
role
next
generation
advancing
research,
point-of-care
diagnostics,
systems.
Язык: Английский
A novel approach for predicting the separation in column chromatography elution using microchannel countercurrent reverse extraction: Essential correlation of confined mass transfer kinetics
Process Safety and Environmental Protection,
Год журнала:
2025,
Номер
unknown
Опубликована: Фев. 1, 2025
Язык: Английский
Integration of Artificial Intelligence and Computational Thinking in Lab-on-a-chip Technology for Quality Improvement in Healthcare
Royal Society of Chemistry eBooks,
Год журнала:
2024,
Номер
unknown, С. 272 - 309
Опубликована: Авг. 14, 2024
The
biological
sciences
now
have
a
wealth
of
exciting
prospects
because
artificial
intelligence
(AI).
For
the
analysis
enormous
amounts
information
generated
by
biotechnology
platforms
for
as
well
biomedical
applications,
AI
approaches
can
be
very
helpful.
With
advancements
in
controllable
response
chambers,
high
throughput
arrays,
and
tracking
devices,
microfluidics
generates
huge
quantities
data
which
is
not
always
properly
processed.
Biotechnology
research
benefit
from
increased
clinical
analytical
throughputs
integration
with
microfluidics.
While
improves
experimental
techniques
lowers
costs
scales,
technologies
dramatically
increase
processing
large
datasets
produced
multiplexed,
high-throughput
Future
such
drug
discovery,
quick
point-of-care
diagnostics,
customized
medicine,
may
all
gain
use
smart
A
summary
key
advances
integrated
presented
here
we
discuss
possibilities
combining
Язык: Английский
Integrating Artificial Intelligence and Microfluidics Technology for Psoriasis Therapy: A Comprehensive Review for Research and Clinical Applications
Advanced Intelligent Systems,
Год журнала:
2024,
Номер
unknown
Опубликована: Ноя. 26, 2024
Microfluidics
has
evolved
into
a
transformative
technology
with
far‐reaching
applications
in
biomedical
research.
However,
designing
and
optimizing
custom
microfluidic
systems
remains
challenging
because
of
their
inherent
complexities.
Integrating
artificial
intelligence
(AI)
microfluidics
promises
to
overcome
these
barriers
by
leveraging
AI
algorithms
automate
device
design,
streamline
experimentation,
enhance
diagnostic
therapeutic
outcomes.
Psoriasis
is
an
incurable
dermatological
condition
that
difficult
diagnose
treat
owing
its
complex
pathogenesis.
Traditional
approaches
are
often
ineffective
fail
address
individual
variabilities
disease
progression
treatment
responses.
AI‐coupled
platforms
have
the
potential
revolutionize
psoriasis
research
clinical
expansive
applications.
AI‐driven
chips
embedded
biosensors
precisely
detect
biomarkers
(BMs),
manipulate
biological
samples,
mimic
psoriasis‐like
vivo
vitro
models,
thereby
allowing
real‐time
monitoring
optimized
testing.
This
review
examines
AI‐powered
for
advancing
It
design
mechanisms
cell
screening,
diagnosis,
drug
delivery.
highlights
recent
advances,
applications,
challenges,
future
perspectives,
ethical
considerations
personalized
care
patient
Язык: Английский
A concise overview of advancements in ultrasensitive biosensor development
Frontiers in Bioengineering and Biotechnology,
Год журнала:
2023,
Номер
11
Опубликована: Ноя. 28, 2023
Electrochemical
biosensing
has
evolved
as
a
diverse
and
potent
method
for
detecting
analyzing
biological
entities
ranging
from
tiny
molecules
to
large
macromolecules.
biosensors
are
desirable
option
in
variety
of
industries,
including
healthcare,
environmental
monitoring,
food
safety,
due
significant
advancements
sensitivity,
selectivity,
portability
brought
about
by
the
integration
electrochemical
techniques
with
nanomaterials,
bio-recognition
components,
microfluidics.
In
this
review,
we
discussed
realm
sensors,
investigating
contrasting
strategies
that
have
been
harnessed
push
boundaries
limit
detection
achieve
miniaturization.
Furthermore,
assessed
distinct
sensing
methods
employed
such
potentiometers,
amperometers,
conductometers,
colorimeters,
transistors,
electrical
impedance
spectroscopy
gauge
their
performance
various
contexts.
This
article
offers
panoramic
view
aimed
at
augmenting
(LOD)
sensors.
The
role
nanomaterials
shaping
capabilities
these
sensors
is
examined
detail,
accompanied
insights
into
chemical
modifications
enhance
functionality.
our
work
not
only
comprehensive
strategic
framework
but
also
delineates
advanced
methodologies
development
biosensors.
equips
researchers
knowledge
required
develop
more
accurate
efficient
technologies.
Язык: Английский
Is AI essential? Examining the need for deep learning in image-activated sorting of Saccharomyces cerevisiae
Lab on a Chip,
Год журнала:
2023,
Номер
23(19), С. 4232 - 4244
Опубликована: Янв. 1, 2023
Artificial
intelligence
(AI)
has
become
a
focal
point
across
multitude
of
societal
sectors,
with
science
not
being
an
exception.
Particularly
in
the
life
sciences,
imaging
flow
cytometry
increasingly
integrated
AI
for
automated
management
and
categorization
extensive
cell
image
data.
However,
necessity
over
traditional
classification
methods
when
extending
to
include
sorting
remains
uncertain,
primarily
due
time
constraints
between
acquisition
actuation.
AI-enabled
image-activated
(IACS)
remain
substantially
limited,
even
as
recent
advancements
IACS
have
found
success
while
largely
relying
on
feature
gating
strategies.
Here
we
assess
by
contrasting
performance
gating,
classical
machine
learning
(ML),
deep
(DL)
convolutional
neural
networks
(CNNs)
differentiation
Saccharomyces
cerevisiae
mutant
images.
We
show
that
ML
could
only
yield
2.8-fold
enhancement
target
enrichment
capability,
albeit
at
cost
13.7-fold
increase
processing
time.
Conversely,
CNN
offer
11.0-fold
improvement
capability
11.5-fold
further
executed
mixed
populations
quantified
strain
via
downstream
DNA
sequencing
substantiate
applicability
DL
proposed
study.
Our
findings
validate
feasibility
value
employing
morphology-based
genetic
screening
S.
cerevisiae,
encouraging
its
incorporation
future
similar
technologies.
Язык: Английский
Deep learning and defocus imaging for determination of three-dimensional position and orientation of microscopic objects
Physics of Fluids,
Год журнала:
2024,
Номер
36(8)
Опубликована: Авг. 1, 2024
We
present
a
method
to
determine
the
three-dimensional
position
and
orientation
of
microscopic,
non-spherical
objects
in
microfluidic
laboratory-on-a-chip
systems
observed
through
conventional
optical
microscopes.
The
is
based
on
combination
General
Defocusing
Particle
Tracking
technique
[Barnkob
et
al.,
“General
defocusing
particle
tracking,”
Lab
Chip
15,
3556–3560
(2015)]
deep
learning.
It
requires
minimal
input
from
user,
suitable
for
real-time
applications,
can
be
applied
any
microscopic
object
with
an
approximately
ellipsoidal
shape,
such
as
unicellular
swimming
organisms,
red
blood
cells,
or
spheroidal
colloids.
main
challenge
linked
construction
training
datasets
neural
network.
provide
procedure
generally
valid
active
microswimmers
discuss
possible
strategies
other
types
objects.
An
implementation
using
Visual
Geometry
Group
convolutional
network
(VGG-16)
presented
tested
synthetic
images
different
backgrounds
noise
levels.
same
used
track
specimens
heterotrophic
ciliate
Euplotes
Vannus
free-swimming
motion.
measurements
were
performed
10
×
objective
over
depth
800
μm
average
estimated
uncertainty
angles
9.0%.
Язык: Английский
Microfluidics in the diagnosis, treatment, and drug delivery of chronic respiratory disorders: Advancements and potential applications
Elsevier eBooks,
Год журнала:
2024,
Номер
unknown, С. 209 - 265
Опубликована: Ноя. 1, 2024
Язык: Английский
Advancing healthcare through laboratory on a chip technology: Transforming microorganism identification and diagnostics
World Journal of Clinical Cases,
Год журнала:
2024,
Номер
13(3)
Опубликована: Ноя. 8, 2024
In
a
recent
case
report
in
the
World
Journal
of
Clinical
Cases,
emphasized
crucial
role
rapidly
and
accurately
identifying
pathogens
to
optimize
patient
treatment
outcomes.
Laboratory-on-a-chip
(LOC)
technology
has
emerged
as
transformative
tool
health
care,
offering
rapid,
sensitive,
specific
identification
microorganisms.
This
editorial
provides
comprehensive
overview
LOC
technology,
highlighting
its
principles,
advantages,
applications,
challenges,
future
directions.
Success
studies
from
field
have
demonstrated
practical
benefits
devices
clinical
diagnostics,
epidemiology,
food
safety.
Comparative
underscored
superiority
over
traditional
methods,
showcasing
improvements
speed,
accuracy,
portability.
The
integration
with
biosensors,
artificial
intelligence,
data
analytics
promises
further
innovation
expansion.
call
action
emphasizes
importance
continued
research,
investment,
adoption
realize
full
potential
improving
healthcare
outcomes
worldwide.
Язык: Английский