Future prospective of AI in drug discovery
Advances in pharmacology,
Год журнала:
2025,
Номер
unknown
Опубликована: Янв. 1, 2025
Язык: Английский
Recommended approaches for integration of population pharmacokinetic modelling with precision dosing in clinical practice
British Journal of Clinical Pharmacology,
Год журнала:
2024,
Номер
unknown
Опубликована: Ноя. 21, 2024
Current
methods
of
dose
determination
have
contributed
to
suboptimal
and
inequitable
health
outcomes
in
underrepresented
patient
populations.
The
persistent
demand
individualise
treatment,
alongside
increasing
technological
feasibility,
is
leading
a
growing
adoption
model‐informed
precision
dosing
(MIPD)
at
point
care.
Population
pharmacokinetic
(popPK)
modelling
technique
that
supports
treatment
personalisation
by
characterising
drug
exposure
diverse
groups.
This
publication
addresses
this
important
shift
clinical
approach,
collating
summarising
recommendations
from
literature.
It
seeks
provide
standardised
guidelines
on
best
practices
for
the
development
popPK
models
their
use
MIPD
software
tools,
ensuring
safeguarding
optimisation
outcomes.
Moreover,
it
consolidates
guidance
key
regulatory
advisory
bodies
deployment,
as
well
technical
requirements
electronic
record
integration.
also
considers
future
application
impact
machine
learning
algorithms
MIPD.
Ultimately,
aims
facilitate
incorporation
high‐quality
precision‐dosing
solutions
into
standard
workflows,
thereby
enhancing
effectiveness
individualised
selection
Язык: Английский
Evolving Artificial Intelligence (AI) at the Crossroads: Potentiating Productive vs. Declining Disruptive Cancer Research
Cancers,
Год журнала:
2024,
Номер
16(21), С. 3646 - 3646
Опубликована: Окт. 29, 2024
Artificial
intelligence
(AI),
encompassing
several
tools
and
platforms
such
as
artificial
“general”
(AGI)
generative
(GenAI),
has
facilitated
cancer
research,
enhancing
productivity
in
terms
of
research
publications
translational
value
for
patients.
AGI
tools,
ChatGPT,
assist
preclinical
clinical
scientists
identifying
tumor
heterogeneity,
predicting
therapy
outcomes,
streamlining
publications.
However,
this
perspective
review
also
explores
the
potential
AI’s
influence
on
with
regard
to
its
impact
disruptive
sciences
discoveries
by
scientists.
The
increasing
reliance
AI
may
compromise
biological
intelligence,
disrupting
abstraction,
creativity,
critical
thinking.
This
could
contribute
declining
trend
sciences,
hindering
landmark
innovations.
narrates
role
different
forms
potentiation
productive
disruption
due
influence.
Язык: Английский