JACCP JOURNAL OF THE AMERICAN COLLEGE OF CLINICAL PHARMACY,
Journal Year:
2025,
Volume and Issue:
unknown
Published: April 22, 2025
Abstract
Introduction
The
expanding
use
of
Chat
Generative
Pre‐Trained
Transformer
(ChatGPT,
OpenAI,
San
Francisco,
CA)
for
drug
information
may
enhance
access
to
information.
However,
it
is
crucial
assess
the
accuracy
and
reproducibility
ChatGPT
responses
questions,
examining
its
utility
limitations
in
clinical
decision‐making.
Objective
To
evaluate
ChatGPT‐3.5
ChatGPT‐4
responding
clinician
questions
compared
with
a
commonly
accepted
resource,
Lexicomp®(Wolters
Kluwer
Health,
Philadelphia,
PA).
Methods
A
serial
cross‐sectional
study
was
conducted
on
from
March
5
12,
2024
United
States.
free,
artificial
intelligence
(AI)
chatbot
trained
up
January
2022;
paid‐subscription
AI
internet
more
data.
For
trial
1
(day
0)
we
input
30
real‐world
(10
categories)
into
both
ChatGPT‐4.
2
1)
3
7),
10
randomly
selected
were
re‐input
ChatGPT.
primary
outcome
evaluated
versus
(vs.)
Lexicomp®
using
4‐point
Likert
scale.
Secondary
outcomes
included
assessing
vs.
Lexicomp,
comparing
versions'
responses,
over
time.
Cohen's
Kappa
Cochran's
Q
assessed
reproducibility.
Results
demonstrated
30%
(9/30),
while
had
40%
(12/30)
(
p
=
0.51).
Neither
versions
accurately
answered
all
any
category.
ChatGPT‐3.5's
agreement
between
trials
2,
3,
fair
k
0.21),
moderate
(k
0.41),
substantial
0.62),
respectively.
0.23),
0.80),
(0.40).
across
three
30%,
20%,
10%
0.78),
60%,
40%,
50%
0.82).
Conclusions
Both
limited
answering
suggesting
that
health
care
professionals
should
exercise
caution
when
Journal of Pharmaceutical Policy and Practice,
Journal Year:
2023,
Volume and Issue:
16(1)
Published: Oct. 3, 2023
The
purpose
of
this
study
is
to
find
out
how
much
pharmacists
know
and
have
used
ChatGPT
in
their
practice.
We
investigated
the
advantages
disadvantages
utilizing
a
pharmacy
context,
amount
training
necessary
use
it
proficiently,
influence
on
patient
care
using
survey.
Exploratory Research in Clinical and Social Pharmacy,
Journal Year:
2024,
Volume and Issue:
15, P. 100481 - 100481
Published: July 18, 2024
Generative
artificial
intelligence
(Gen-AI),
exemplified
by
the
widely
adopted
ChatGPT,
has
garnered
significant
attention
in
recent
years.
Its
application
spans
various
health
education
domains,
including
pharmacy,
where
its
potential
benefits
and
drawbacks
have
become
increasingly
apparent.
Despite
growing
adoption
of
Gen-AIsuch
as
ChatGPT
pharmacy
education,
there
remains
a
critical
need
to
assess
mitigate
associated
risks.
This
review
exploresthe
literature
strategies
for
mitigating
risks
with
integration
Gen-AI
education.
JMIR Public Health and Surveillance,
Journal Year:
2024,
Volume and Issue:
10, P. e53086 - e53086
Published: Jan. 4, 2024
The
online
pharmacy
market
is
growing,
with
legitimate
pharmacies
offering
advantages
such
as
convenience
and
accessibility.
However,
this
increased
demand
has
attracted
malicious
actors
into
space,
leading
to
the
proliferation
of
illegal
vendors
that
use
deceptive
techniques
rank
higher
in
search
results
pose
serious
public
health
risks
by
dispensing
substandard
or
falsified
medicines.
Search
engine
providers
have
started
integrating
generative
artificial
intelligence
(AI)
interfaces,
which
could
revolutionize
delivering
more
personalized
through
a
user-friendly
experience.
improper
integration
these
new
technologies
carries
potential
further
exacerbate
posed
illicit
inadvertently
directing
users
vendors.
Deleted Journal,
Journal Year:
2024,
Volume and Issue:
2024, P. 14 - 19
Published: Feb. 15, 2024
The
objective
of
this
systematic
review
was
to
assess
the
adequacy
current
medication
management
in
Ghana
considering
risks
posed
by
increased
artificial
intelligence
(AI)
automation
pharmacies
worldwide
A
qualitative
comparative
approach
used
despite
reviewed
1994
Pharmacy
Act
against
recognition
AI
challenges
and
international
governance
guidelines
.
results
revealed
flaws
terms
quality
prerequisites,
transparency
checklists
liability
mechanisms
developed
for
systems
compared
existing
regulations
manual
process.
Outdated
approaches
patient
care
that
fail
ensure
safety
or
address
threats
accuracy
recommendations
from
data
collection
biases
technical
errors.
Proposed
changes
include
a
requirement
usability
testing
before
approving
pharmacy
deployments
creation
board
post-implementation
validity.
Updating
deal
with
modern
equipment
puts
innovation
responsible
regulation
fast-paced
healthcare
industry.
This
study
contributes
significantly
preliminary
research
on
policy
readiness
Ghanaian
legal
context,
suggests
feasible
methodology
exploring
differences
use
companies
countries
competing
technology
disturbing,
increasingly
beyond
date
code.
Early
government
reform
helps
keep
pace
realities
adoption.
Quantitative Biology,
Journal Year:
2024,
Volume and Issue:
12(4), P. 345 - 359
Published: June 27, 2024
Abstract
The
year
2023
marked
a
significant
surge
in
the
exploration
of
applying
large
language
model
chatbots,
notably
Chat
Generative
Pre‐trained
Transformer
(ChatGPT),
across
various
disciplines.
We
surveyed
application
ChatGPT
bioinformatics
and
biomedical
informatics
throughout
year,
covering
omics,
genetics,
text
mining,
drug
discovery,
image
understanding,
programming,
education.
Our
survey
delineates
current
strengths
limitations
this
chatbot
offers
insights
into
potential
avenues
for
future
developments.
Cureus,
Journal Year:
2024,
Volume and Issue:
unknown
Published: Jan. 16, 2024
Background:
ChatGPT
is
an
artificial
intelligence-powered
chatbot
that
has
demonstrated
capabilities
in
numerous
fields,
including
medical
and
healthcare
sciences.
This
study
evaluates
the
potential
for
application
telepharmacy,
delivering
of
pharmaceutical
care
via
means
telecommunications,
through
assessing
its
interactions,
adherence
to
instructions,
ability
role-play
as
a
pharmacist
while
handling
series
life-like
scenario
questions.
Methods:
Two
versions
(ChatGPT
3.5
4.0,
OpenAI)
were
assessed
using
two
independent
trials
each.
was
instructed
act
answer
patient
inquiries,
followed
by
set
20
assessment
Then,
stop
act,
provide
feedback
list
sources
drug
information.
The
responses
questions
evaluated
terms
accuracy,
precision
clarity
4-point
Likert-like
scale.
Results:
follow
detailed
pharmacist,
appropriately
handle
all
able
understand
case
details,
recognize
generic
brand
names,
identify
side
effects,
prescription
requirements
precautions,
proper
point-by-point
instructions
regarding
administration,
dosing,
storage
disposal.
overall
pooled
scores
3.425
(0.712)
3.7
(0.61)
respectively.
rank
distribution
not
significantly
different
(P>0.05).
None
answers
could
be
considered
directly
harmful
or
labeled
entirely
mostly
incorrect,
most
point
deductions
due
other
factors
such
indecisiveness,
adding
immaterial
information,
missing
certain
considerations,
partial
unclarity.
similar
length
across
concise.
4.0
showed
superior
performance,
higher
consistency,
better
character
report
various
reliable
information
sources.
However,
it
only
allowed
input
40
every
three
hours
provided
inaccurate
number
patients,
compared
which
unlimited
but
unable
feedback.
Conclusions:
Integrating
telepharmacy
holds
promising
potential;
however,
drawbacks
are
overcome
order
function
effectively.
The Journal of Clinical Pharmacology,
Journal Year:
2024,
Volume and Issue:
64(9), P. 1095 - 1100
Published: April 16, 2024
ChatGPT
is
a
language
model
that
was
trained
on
large
dataset
including
medical
literature.
Several
studies
have
described
the
performance
of
exams.
In
this
study,
we
examine
its
in
answering
factual
knowledge
questions
regarding
clinical
pharmacy.
Questions
were
obtained
from
Dutch
application
features
multiple-choice
to
maintain
basic
level
for
pharmacists.
total,
264
pharmacy-related
presented
and
responses
evaluated
accuracy,
concordance,
quality
substantiation,
reproducibility.
Accuracy
defined
as
correctness
answer,
results
compared
overall
score
by
pharmacists
over
2022.
Responses
marked
concordant
if
no
contradictions
present.
The
substantiation
graded
two
independent
using
4-point
scale.
Reproducibility
established
presenting
multiple
times
various
days.
yielded
accurate
79%
questions,
surpassing
pharmacists'
accuracy
66%.
Concordance
95%,
deemed
good
or
excellent
73%
questions.
consistently
high,
both
within
day
between
days
(>92%),
well
across
different
users.
demonstrated
higher
reproducibility
related
pharmacy
practice
than
Consequently,
posit
could
serve
valuable
resource
We
hope
technology
will
further
improve,
which
may
lead
enhanced
future
performance.
Informatics,
Journal Year:
2025,
Volume and Issue:
12(1), P. 9 - 9
Published: Jan. 17, 2025
The
rapid
advancement
of
large
language
models
like
ChatGPT
has
significantly
impacted
natural
processing,
expanding
its
applications
across
various
fields,
including
healthcare.
However,
there
remains
a
significant
gap
in
understanding
the
consistency
and
reliability
ChatGPT’s
performance
different
medical
domains.
We
conducted
this
systematic
review
according
to
an
LLM-assisted
PRISMA
setup.
high-recall
search
term
“ChatGPT”
yielded
1101
articles
from
2023
onwards.
Through
dual-phase
screening
process,
initially
automated
via
subsequently
manually
by
human
reviewers,
128
studies
were
included.
covered
range
specialties,
focusing
on
diagnosis,
disease
management,
patient
education.
assessment
metrics
varied,
but
most
compared
accuracy
against
evaluations
clinicians
or
reliable
references.
In
several
areas,
demonstrated
high
accuracy,
underscoring
effectiveness.
some
contexts
revealed
lower
accuracy.
mixed
outcomes
domains
emphasize
challenges
opportunities
integrating
AI
into
certain
areas
suggests
that
substantial
utility,
yet
inconsistent
all
indicates
need
for
ongoing
evaluation
refinement.
This
highlights
potential
improve
healthcare
delivery
alongside
necessity
continued
research
ensure
reliability.
Journal of Multidisciplinary Healthcare,
Journal Year:
2023,
Volume and Issue:
Volume 16, P. 4099 - 4110
Published: Dec. 1, 2023
Background:
The
emergence
of
Chat-Generative
Pre-trained
Transformer
(ChatGPT)
by
OpenAI
has
revolutionized
AI
technology,
demonstrating
significant
potential
in
healthcare
and
pharmaceutical
education,
yet
its
real-world
applicability
clinical
training
warrants
further
investigation.
Methods:
A
cross-sectional
study
was
conducted
between
April
May
2023
to
assess
PharmD
students'
perceptions,
concerns,
experiences
regarding
the
integration
ChatGPT
into
pharmacy
education.
utilized
a
convenient
sampling
method
through
online
platforms
involved
questionnaire
with
sections
on
demographics,
perceived
benefits,
experience
ChatGPT.
Statistical
analysis
performed
using
SPSS,
including
descriptive
inferential
analyses.
Results:
findings
involving
211
students
revealed
that
majority
participants
were
male
(77.3%),
had
prior
artificial
intelligence
(68.2%).
Over
two-thirds
aware
Most
(n=
139,
65.9%)
benefits
for
various
tasks,
concerns
over-reliance,
accuracy,
ethical
considerations.
Adoption
varied,
some
not
it
at
all,
while
others
tasks
like
evaluating
drug-drug
interactions
developing
care
plans.
Previous
users
tended
have
higher
lower
but
differences
statistically
significant.
Conclusion:
Utilizing
offers
opportunities,
lack
trust
decisions
highlights
need
collaborative
human-ChatGPT
decision-making.
It
should
complement
professionals'
expertise
be
used
strategically
compensate
human
limitations.
Further
research
is
essential
optimize
ChatGPT's
effective
integration.
Keywords:
ChatGPT,
perception,
training,
Pharm-D
