AAPS PharmSciTech,
Journal Year:
2025,
Volume and Issue:
26(5)
Published: April 17, 2025
Abstract
BCS
class
II
candidates
pose
challenges
in
drug
development
due
to
their
low
solubility
and
permeability.
Researchers
have
explored
various
techniques;
co-amorphous
solid
dispersion
are
major
approaches
enhance
in-vitro
dissolution.
However,
in-vivo
oral
bioavailability
remains
challenging.
Physiologically
based
pharmacokinetic
(PBPK)
modeling
with
a
detailed
understanding
of
absorption,
distribution,
metabolism,
excretion
(ADME)
using
mechanistic
approach
is
emerging.
This
review
summarizes
the
fundamentals
PBPK,
dissolution—absorption
models,
parameterization
absorption
for
drugs,
provides
information
about
newly
emerging
artificial
intelligence/machine
learning
(AI/ML)
linked
PBPK
advantages,
disadvantages,
areas
further
exploration.
Additionally,
fully
integrated
workflow
formulation
design
investigational
new
drugs
(INDs)
virtual
bioequivalence
generic
molecules
falling
under
BCS-II
discussed.
Graphical
Pharmaceutics,
Journal Year:
2024,
Volume and Issue:
16(10), P. 1328 - 1328
Published: Oct. 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.
Modern Pathology,
Journal Year:
2025,
Volume and Issue:
38(4), P. 100705 - 100705
Published: Jan. 5, 2025
Artificial
intelligence
(AI)
and
machine
learning
(ML)
are
transforming
the
field
of
medicine.
Health
care
organizations
now
starting
to
establish
management
strategies
for
integrating
such
platforms
(AI-ML
toolsets)
that
leverage
computational
power
advanced
algorithms
analyze
data
provide
better
insights
ultimately
translate
enhanced
clinical
decision-making
improved
patient
outcomes.
Emerging
AI-ML
trends
in
pathology
medicine
reshaping
by
offering
innovative
solutions
enhance
diagnostic
accuracy,
operational
workflows,
decision
support,
These
tools
also
increasingly
valuable
research
which
they
contribute
automated
image
analysis,
biomarker
discovery,
drug
development,
trials,
productive
analytics.
Other
related
include
adoption
ML
operations
managing
models
settings,
application
multimodal
multiagent
AI
utilize
diverse
sources,
expedited
translational
research,
virtualized
education
training
simulation.
As
final
chapter
our
educational
series,
this
review
article
delves
into
current
adoption,
future
directions,
transformative
potential
medicine,
discussing
their
applications,
benefits,
challenges,
perspectives.
Health Science Reports,
Journal Year:
2025,
Volume and Issue:
8(1)
Published: Jan. 1, 2025
Artificial
Intelligence
(AI)
beginning
to
integrate
in
healthcare,
is
ushering
a
transformative
era,
impacting
diagnostics,
altering
personalized
treatment,
and
significantly
improving
operational
efficiency.
The
study
aims
describe
AI
including
important
technologies
like
robotics,
machine
learning
(ML),
deep
(DL),
natural
language
processing
(NLP),
investigate
how
these
are
used
patient
interaction,
predictive
analytics,
remote
monitoring.
goal
of
this
review
present
thorough
analysis
AI's
effects
on
healthcare
while
providing
stakeholders
with
road
map
for
navigating
changing
environment.
This
analyzes
the
impact
using
data
from
Web
Science
(2014-2024),
focusing
keywords
AI,
ML,
applications.
It
examines
uses
by
synthesizing
recent
literature
real-world
case
studies,
such
as
Google
Health
IBM
Watson
Health,
highlighting
technologies,
their
useful
applications,
difficulties
putting
them
into
practice,
problems
security
resource
limitations.
also
discusses
new
developments
they
can
affect
society.
findings
demonstrate
enhancing
skills
medical
professionals,
diagnosis,
opening
door
more
individualized
treatment
plans,
reflected
steady
rise
AI-related
publications
158
articles
(3.54%)
2014
731
(16.33%)
2024.
Core
applications
monitoring
analytics
improve
effectiveness
involvement.
However,
there
major
obstacles
mainstream
implementation
issues
budget
constraints.
Healthcare
may
be
transformed
but
its
successful
use
requires
ethical
responsible
use.
To
meet
demands
sector
guarantee
application
evaluation
highlights
necessity
ongoing
research,
instruction,
multidisciplinary
cooperation.
In
future,
integrating
responsibly
will
essential
optimizing
advantages
reducing
related
dangers.
Pharmaceutics,
Journal Year:
2025,
Volume and Issue:
17(3), P. 375 - 375
Published: March 15, 2025
Recent
progress
in
material
science
has
led
to
the
development
of
new
drug
delivery
systems
that
go
beyond
conventional
approaches
and
offer
greater
accuracy
convenience
application
therapeutic
agents.
This
review
discusses
evolutionary
role
nanocarriers,
hydrogels,
bioresponsive
polymers
enhanced
release,
target
accuracy,
bioavailability.
Oncology,
chronic
disease
management,
vaccine
are
some
applications
explored
this
paper
show
how
these
materials
improve
results,
counteract
multidrug
resistance,
allow
for
sustained
localized
treatments.
The
also
translational
barriers
bringing
advanced
into
clinical
setting,
which
include
issues
biocompatibility,
scalability,
regulatory
approval.
Methods
overcome
challenges
surface
modifications
reduce
immunogenicity,
scalable
production
methods
such
as
microfluidics,
harmonization
systems.
In
addition,
convergence
artificial
intelligence
(AI)
machine
learning
(ML)
is
opening
frontiers
personalized
medicine.
These
technologies
predictive
modeling
real-time
adjustments
optimize
needs
individual
patients.
use
can
be
applied
rare
underserved
diseases;
thus,
strategies
gene
therapy,
orphan
drugs
development,
global
distribution
may
hopes
millions
Advanced Therapeutics,
Journal Year:
2024,
Volume and Issue:
unknown
Published: Sept. 18, 2024
Abstract
Host‐directed
therapies
(HDTs)
have
emerged
as
a
promising
strategy
to
combat
viral
infections
by
modifying
host
factors
and
immune
responses
restrict
replication
improve
patient
outcomes.
This
review
summarizes
the
latest
advances
future
potential
of
HDTs
in
antiviral
therapy.
With
developments
genomics
proteomics,
new
targets
essential
for
been
identified.
Gene‐editing
tools,
such
CRISPR‐Cas9,
enable
precise
manipulation
genes
linked
processes,
paving
way
innovative
HDTs.
Emerging
approaches,
including
RNA
interference
interference,
further
demonstrate
specifically
modify
inhibit
replication.
Additionally,
probiotics
are
being
explored
their
capacity
enhance
modulate
gut
microbiota,
offering
natural
safe
method
boosting
defenses.
Despite
these
advancements,
significant
challenges
remain,
particularly
deciphering
complex
host–virus
interactions
ensuring
safety
efficacy
therapies.
Continued
research
clinical
evaluation
realize
full
provides
comprehensive
overview
current
HDT
strategies,
emphasizing
promise
shaping
interventions.
Pharmaceutical Development and Technology,
Journal Year:
2025,
Volume and Issue:
30(1), P. 126 - 136
Published: Jan. 2, 2025
Machine
learning
(ML)
has
emerged
as
a
transformative
tool
in
drug
delivery,
particularly
the
design
and
optimization
of
liposomal
formulations.
This
review
focuses
on
intersection
ML
technology,
highlighting
how
advanced
algorithms
are
accelerating
formulation
processes,
predicting
key
parameters,
enabling
personalized
therapies.
ML-driven
approaches
restructuring
development
by
optimizing
liposome
size,
stability,
encapsulation
efficiency
while
refining
release
profiles.
Additionally,
integration
enhances
therapeutic
outcomes
precision-targeted
delivery
minimizing
side
effects.
presents
current
breakthroughs,
challenges,
future
opportunities
applying
to
systems,
aiming
improve
efficacy
patient
various
disease
treatments.
