Machine Learning‐Enabled Drug‐Induced Toxicity Prediction
Advanced Science,
Journal Year:
2025,
Volume and Issue:
unknown
Published: Feb. 3, 2025
Abstract
Unexpected
toxicity
has
become
a
significant
obstacle
to
drug
candidate
development,
accounting
for
30%
of
discovery
failures.
Traditional
assessment
through
animal
testing
is
costly
and
time‐consuming.
Big
data
artificial
intelligence
(AI),
especially
machine
learning
(ML),
are
robustly
contributing
innovation
progress
in
toxicology
research.
However,
the
optimal
AI
model
different
types
usually
varies,
making
it
essential
conduct
comparative
analyses
methods
across
domains.
The
diverse
sources
also
pose
challenges
researchers
focusing
on
specific
studies.
In
this
review,
10
categories
drug‐induced
examined,
summarizing
characteristics
applicable
ML
models,
including
both
predictive
interpretable
algorithms,
striking
balance
between
breadth
depth.
Key
databases
tools
used
prediction
highlighted,
toxicology,
chemical,
multi‐omics,
benchmark
databases,
organized
by
their
focus
function
clarify
roles
prediction.
Finally,
strategies
turn
into
opportunities
analyzed
discussed.
This
review
may
provide
with
valuable
reference
understanding
utilizing
available
resources
bridge
mechanistic
insights,
further
advance
application
drugs‐induced
Language: Английский
Artificial Intelligence in Experimental Surgery: Ethical Breakthroughs and Technological Innovations within In Silico Models
Published: Feb. 10, 2025
Integrating
artificial
intelligence
(AI)
into
experimental
surgery
represents
a
transformative
shift
in
biomedical
research,
offering
innovative
alternatives
to
traditional
animal-based
preclinical
models.
AI-driven
methodologies,
including
computerized
models
and
surgical
simulations,
enhance
precision,
reproducibility,
ethical
compliance
while
reducing
reliance
on
_in
vivo_
experimentation.
This
review
systematically
explores
the
role
of
AI
optimizing
procedures,
operative
techniques,
technology,
analyzing
its
impact
decision-making,
predictive
modeling,
training
simulations.
A
comprehensive
search
was
conducted
across
PubMed,
Embase,
Scopus,
Web
Science,
SciELO,
identifying
studies
AI-enhanced
strategies,
silico
models,
validation
techniques.
The
findings
highlight
AI's
potential
replace
animal
testing,
refine
training,
improve
research
accuracy.
However,
challenges
remain,
data
standardization,
regulatory
adaptation,
considerations
related
methodologies.
Addressing
these
requires
interdisciplinary
collaboration
development
validated
frameworks
support
widespread
implementation
surgery.
Future
should
focus
standardizing
applications,
ensuring
methodological
transparency,
integrating
clinical
translation
pathways.
underscores
revolutionary
shaping
future
path
more
ethical,
precise,
Language: Английский
Thalidomide: Following Tragedy, a Repurposed Molecule With Continuing Opportunities for Clinical Benefit
Clinical Therapeutics,
Journal Year:
2025,
Volume and Issue:
unknown
Published: Feb. 1, 2025
Language: Английский
An Immune-Liver Microphysiological System Method for Evaluation and Quality Control of Hepatotoxicity Induced by Polygonum multiflorum Thunb. Extract
Quanfeng Deng,
No information about this author
Yueyang Qu,
No information about this author
Yong Luo
No information about this author
et al.
Journal of Ethnopharmacology,
Journal Year:
2025,
Volume and Issue:
unknown, P. 119633 - 119633
Published: March 1, 2025
Language: Английский
Comprehensive Characterization of Oxidative Stress-Modulating Chemicals Using GPT-Based Text Mining
Environmental Science & Technology,
Journal Year:
2024,
Volume and Issue:
58(46), P. 20540 - 20552
Published: Nov. 8, 2024
The
screening
of
hazardous
environmental
pollutants
is
hindered
by
the
limited
availability
toxicological
databases.
Large
language
model
(LLM)-based
text
mining
holds
potential
to
automatically
extract
complex
information
from
literature.
Due
its
relevance
diseases
and
challenge
comprehensive
characterization,
oxidative
stress
serves
as
a
suitable
case
for
research
texting
mining.
In
this
study,
robust
workflow
utilizing
LLM
(i.e.,
GPT-4)
was
developed
on
tests,
including
data
collection,
preprocessing,
prompt
engineering,
performance
evaluation
procedures.
A
total
17,780
relevant
records
were
extracted
7166
articles,
covering
2558
unique
compounds.
rising
interest
in
observed
over
past
two
decades.
list
known
prooxidants
(
Language: Английский