International Journal of Molecular Sciences,
Год журнала:
2025,
Номер
26(7), С. 2969 - 2969
Опубликована: Март 25, 2025
Photodynamic
therapy
(PDT)
is
an
innovative
treatment
that
has
recently
been
approved
for
clinical
use
and
holds
promise
cancer
patients.
It
offers
several
benefits,
such
as
low
systemic
toxicity,
minimal
invasiveness,
the
ability
to
stimulate
antitumor
immune
responses.
For
certain
types
of
cancer,
it
shown
positive
results
with
few
side
effects.
However,
PDT
still
faces
some
challenges,
including
limited
light
penetration
into
deeper
tumor
tissues,
uneven
distribution
photosensitizer
(PS)
can
also
affect
healthy
cells,
difficulties
posed
by
hypoxic
microenvironment
(TME).
In
conditions,
PDT's
effectiveness
reduced
due
insufficient
production
reactive
oxygen
species,
which
limits
destruction
lead
relapse.
This
review
highlights
recent
advances
in
photosensitizers
nanotechnologies
are
being
developed
improve
PDT.
focuses
on
multifunctional
nanoplatforms
nanoshuttles
have
preclinical
studies,
especially
treating
solid
tumors.
One
key
areas
focus
development
PSs
specifically
target
mitochondria
treat
deep-seated
malignant
New
mitochondria-targeting
nano-PSs
designed
better
water
solubility
extended
wavelength
ranges,
allowing
them
tumors
more
effectively,
even
challenging,
environments.
These
advancements
opening
new
doors
treatment,
when
combined
other
therapeutic
strategies.
Moving
forward,
research
should
optimizing
PDT,
creating
efficient
drug
delivery
systems,
developing
smarter
platforms.
Ultimately,
these
efforts
aim
make
a
first-choice
option
International Journal of Pharmaceutics,
Год журнала:
2025,
Номер
671, С. 125202 - 125202
Опубликована: Янв. 10, 2025
Over
the
past
two
decades,
extensive
research
has
focused
on
both
fundamental
and
applied
aspects
of
nanomedicine,
driven
by
compelling
advantages
that
nanoparticles
offer
over
their
bulk
counterparts.
Despite
this
intensive
effort,
fewer
than
100
nanomedicines
have
been
approved
U.S.
Food
Drug
Administration
European
Medicines
Agency
since
1989.
This
disparity
highlights
a
substantial
gap
in
translational
research,
reflecting
disconnect
between
prolific
nanomedicine
limited
number
products
successfully
reach
sustain
themselves
market.
For
instance,
DepoCyt,
which
received
FDA
approval
1999
for
treatment
lymphomatous
meningitis,
was
discontinued
2017
due
to
persistent
manufacturing
issues.
To
address
similar
challenges,
review
aims
identify
analyse
issues
related
formulation
design
nanomedicines.
It
provides
an
overview
most
prevalent
technologies
excipients
used
production,
followed
critical
evaluation
clinical
translatability.
Furthermore,
presents
strategies
rational
optimization
manufacturing,
adhering
principles
quality-by-design
quality
risk
management.
Heliyon,
Год журнала:
2025,
Номер
11(4), С. e42739 - e42739
Опубликована: Фев. 1, 2025
This
review
explores
the
synergistic
potential
of
natural
products
and
nanotechnology
for
viral
infections,
highlighting
key
antiviral,
immunomodulatory,
antioxidant
properties
to
combat
pandemics
caused
by
highly
infectious
viruses.
These
often
result
in
severe
public
health
crises,
particularly
affecting
vulnerable
populations
due
respiratory
complications
increased
mortality
rates.
A
cytokine
storm
is
initiated
when
an
overload
pro-inflammatory
cytokines
chemokines
released,
leading
a
systemic
inflammatory
response.
Viral
mutations
limited
availability
effective
drugs,
vaccines,
therapies
contribute
continuous
transmission
virus.
The
coronavirus
disease-19
(COVID-19)
pandemic
has
sparked
renewed
interest
product-derived
antivirals.
efficacy
traditional
medicines
against
infections
examined.
Their
anti-inflammatory,
are
highlighted.
discusses
how
enhances
herbal
combating
infections.
MEDICINUS,
Год журнала:
2025,
Номер
38(1), С. 27 - 36
Опубликована: Янв. 1, 2025
Proses
penemuan
obat
telah
memasuki
era
baru
dengan
munculnya
kecerdasan
buatan
(artificial
intelligence/AI)
dan
big
data.
Pendekatan
tradisional,
panjang,
mahal
kini
dilengkapi
alternatif
yang
efisien
berkat
kemampuan
AI
untuk
menganalisis
pola
kompleks
data
mengintegrasikan
kumpulan
berskala
besar.
Artikel
ini
membahas
peran
teknologi
tersebut
dalam
mempercepat
inovasi
farmasi,
mengulas
aplikasi
praktis,
menyoroti
tantangan
serta
prospek
masa
depan.
Dengan
data,
industri
farmasi
dapat
memajukan
pengobatan
presisi
memperdalam
pemahaman
kita
tentang
biologi
penyakit.
This
technical
article
examines
the
transformative
impact
of
artificial
intelligence
on
pharmaceutical
manufacturing
operations,
focusing
predictive
maintenance
and
cybersecurity
frameworks.
The
investigates
how
AI-driven
systems
areSreeharsha
Amarnath
Rongala
https://iaeme.com/Home/
FASEB BioAdvances,
Год журнала:
2025,
Номер
unknown
Опубликована: Март 3, 2025
Abstract
A
“quiet
revolution”
in
medicine
has
been
taking
place
over
the
past
two
decades.
There
are
converging
dynamic
forces
that
have
propelled
precision
to
limelight,
garnering
wide
public
attention.
The
first
driver
is
realization
populations
within
a
disease
area
can
be
stratified,
thus
developing
therapies
tailored
their
specific
needs,
and
capability
identify
these
by
analyzing
large,
diverse
datasets.
second
technology
advances
multi‐omics
approaches
applications
(i.e.,
molecularly
informed
medicine)
enabling
more
comprehensive
portrait
of
biology.
This
promises
not
only
accelerate
development
processes
but
also
presents
challenges
for
healthcare
professionals
health
systems
struggling
interconnect
integrate
disparate
data
sources
into
cohesive
clinical
strategy
benefit
patients.
We
coin
here
term
next‐generation
(ngPM),
which
bound
become
conventional
clinics
sooner
or
later.
Artificial
intelligence
(AI)
machine
learning
(ML)
transformative
potential
strategic
response
today's
tomorrow's
opportunities.
chief
how
well
(PM)
permeates
primary
care
standard
drive
toward
wellness
lifestyle
while
ensuring
access
feasible,
streamlined,
routine.
present
perspective
would
harness
power
ngPM
wellness.
MEDICINUS,
Год журнала:
2025,
Номер
38(2), С. 28 - 35
Опубликована: Фев. 1, 2025
Integrasi
kecerdasan
buatan
(artificial
intelligence/AI)
dan
pembelajaran
mesin
(machine
learning/ML)
telah
merevolusi
industri
farmasi,
mengubah
cara
obat
ditemukan,
dikembangkan,
diuji,
diproduksi.
Teknologi
ini
memungkinkan
efisiensi
akurasi
yang
belum
pernah
terjadi
sebelumnya
dengan
memanfaatkan
sejumlah
besar
data
algoritmakomputasi
canggih.
Dalam
penemuan
obat,
AI
mempercepat
identifikasi
target
terapeutik
desain
molekul
baru,
secara
drastis
mengurangi
waktu
menuju
pemasaran.
Selama
pengembangan,
ML
membantu
mengoptimalkan
uji
klinik
stratifikasi
populasi
pasien
untuk
meningkatkan
presisi
efektivitas.
klinik,
alat
berbasis
rekrutmen,
pemantauan,
adaptif,
menghasilkan
studi
lebih
andal
hemat
biaya.
Terakhir,
memastikan
pengendalian
kualitas
real-time
pemeliharaan
prediktif
dalam
manufaktur,
konsistensi
produk
biaya
operasional.
Makalah
mengeksplorasi
aplikasi
AI/ML
komprehensif
di
berbagai
domain,
didukung
oleh
kasus
analisis
mendalam
tentang
dampaknya.
Selain
itu,
makalah
membahas
tantangan
seperti
data,
hambatan
regulasi,
transparansi
algoritma
menghambat
adopsinya
luas.
Pertimbangan
etis,
termasuk
masalah
privasi
risiko
bias
sistem
juga
dievaluasi.
Akhirnya,
menguraikan
peluang
kemajuan
masa
depan,
menekankan
perlunya
upaya
kolaboratif
antara
akademisi,
industri,
badan
regulasi
potensi
penuh
membentuk
kembali
lanskap
farmasi.
International Journal of Scientific Research in Computer Science Engineering and Information Technology,
Год журнала:
2025,
Номер
11(1), С. 2772 - 2780
Опубликована: Фев. 10, 2025
This
comprehensive
article
examines
the
transformative
impact
of
artificial
intelligence
on
drug
discovery
and
development
processes.
The
explores
traditional
challenges
in
pharmaceutical
development,
including
extended
timelines,
high
costs,
low
success
rates,
which
have
prompted
industry's
shift
toward
AI-driven
solutions.
investigates
how
AI
applications
revolutionized
early
research
stages,
clinical
trial
management,
validation
Through
a
detailed
examination
recent
implementations,
demonstrates
AI's
significant
improvements
target
identification,
molecular
screening,
optimization.
also
addresses
technical
considerations,
data
quality
requirements,
algorithm
challenges,
resource
implications
for
successful
integration
research.
provides
insights
into
emerging
trends
future
directions
while
highlighting
achievements
limitations
discovery.
