International Journal of Pharmaceutics X,
Journal Year:
2023,
Volume and Issue:
5, P. 100181 - 100181
Published: April 18, 2023
Inkjet
printing
has
been
extensively
explored
in
recent
years
to
produce
personalised
medicines
due
its
low
cost
and
versatility.
Pharmaceutical
applications
have
ranged
from
orodispersible
films
complex
polydrug
implants.
However,
the
multi-factorial
nature
of
inkjet
process
makes
formulation
(e.g.,
composition,
surface
tension,
viscosity)
parameter
optimization
nozzle
diameter,
peak
voltage,
drop
spacing)
an
empirical
time-consuming
endeavour.
Instead,
given
wealth
publicly
available
data
on
pharmaceutical
printing,
there
is
potential
for
a
predictive
model
outcomes
be
developed.
In
this
study,
machine
learning
(ML)
models
(random
forest,
multilayer
perceptron,
support
vector
machine)
predict
printability
drug
dose
were
developed
using
dataset
687
formulations,
consolidated
in-house
literature-mined
inkjet-printed
formulations.
The
optimized
ML
predicted
formulations
with
accuracy
97.22%,
quality
prints
97.14%.
This
study
demonstrates
that
can
feasibly
provide
insights
prior
preparation,
affording
resource-
time-savings.
Pharmaceutics,
Journal Year:
2022,
Volume and Issue:
14(1), P. 183 - 183
Published: Jan. 13, 2022
During
the
development
of
a
pharmaceutical
formulation,
powerful
tool
is
needed
to
extract
key
points
from
complicated
process
parameters
and
material
attributes.
Artificial
neural
networks
(ANNs),
promising
more
flexible
modeling
technique,
can
address
real
intricate
questions
in
high
parallelism
distributed
pattern
manner
biological
networks.
The
data
mined
analyzing
based
on
ANNs
have
ability
replace
hundreds
trial
error
experiments.
been
used
for
analysis
by
pharmaceutics
researchers
since
1990s
it
has
now
become
research
method
science.
This
review
focuses
latest
application
progress
prediction,
characterization
optimization
formulation
provide
reference
further
interdisciplinary
study
ANNs.
Journal of Manufacturing Science and Engineering,
Journal Year:
2022,
Volume and Issue:
145(1)
Published: Nov. 8, 2022
Abstract
Precision
medicine
is
an
emerging
healthcare
delivery
approach
that
considers
variability
between
patients,
such
as
genetic
makeups,
in
contrast
to
the
current
one-size-fits-all
designed
treat
average
patient.
The
White
House
launched
Medicine
Initiative
2015,
starting
endeavor
reshape
delivery.
To
translate
concept
of
precision
from
bench
practice,
advanced
manufacturing
will
play
integral
part,
including
fabrication
personalized
drugs
and
drug
devices
screening
platforms.
These
products
are
highly
customized
require
robust
yet
flexible
systems.
field
has
rapidly
evolved
past
five
years.
In
this
state-of-the-art
review,
manufactured
for
be
introduced,
followed
by
a
brief
review
processing
materials
their
characteristics.
A
on
different
processes
applicable
those
aforementioned
provided.
status
development
regulatory
submission
quality
control
considerations
also
discussed.
Finally,
paper
presents
future
outlook
used
medicine.
International Journal of Pharmaceutics,
Journal Year:
2023,
Volume and Issue:
639, P. 122926 - 122926
Published: April 7, 2023
Achieving
carbon
neutrality
is
seen
as
an
important
goal
in
order
to
mitigate
the
effects
of
climate
change,
dioxide
a
major
greenhouse
gas
that
contributes
global
warming.
Many
countries,
cities
and
organizations
have
set
targets
become
neutral.
The
pharmaceutical
sector
no
exception,
being
contributor
emissions
(emitting
approximately
55%
more
than
automotive
for
instance)
hence
need
strategies
reduce
its
environmental
impact.
Three-dimensional
(3D)
printing
advanced
fabrication
technology
has
potential
replace
traditional
manufacturing
tools.
Being
new
technology,
impact
3D
printed
medicines
not
been
investigated,
which
barrier
uptake
by
industry.
Here,
energy
consumption
(and
emission)
printers
considered,
focusing
on
technologies
successfully
demonstrated
produce
solid
dosage
forms.
6
benchtop
was
measured
during
standby
mode
printing.
On
standby,
ranged
from
0.03
0.17
kWh.
required
producing
10
printlets
0.06
3.08
kWh,
with
using
high
temperatures
consuming
energy.
Carbon
between
11.60
112.16
g
CO2
(eq)
per
printlets,
comparable
tableting.
Further
analyses
revealed
decreasing
temperature
found
demand
considerably,
suggesting
developing
formulations
are
printable
at
lower
can
emissions.
study
delivers
key
initial
insights
into
potentially
transformative
provides
encouraging
results
demonstrating
deliver
quality
without
environmentally
detrimental.
International Journal of Pharmaceutics X,
Journal Year:
2023,
Volume and Issue:
5, P. 100181 - 100181
Published: April 18, 2023
Inkjet
printing
has
been
extensively
explored
in
recent
years
to
produce
personalised
medicines
due
its
low
cost
and
versatility.
Pharmaceutical
applications
have
ranged
from
orodispersible
films
complex
polydrug
implants.
However,
the
multi-factorial
nature
of
inkjet
process
makes
formulation
(e.g.,
composition,
surface
tension,
viscosity)
parameter
optimization
nozzle
diameter,
peak
voltage,
drop
spacing)
an
empirical
time-consuming
endeavour.
Instead,
given
wealth
publicly
available
data
on
pharmaceutical
printing,
there
is
potential
for
a
predictive
model
outcomes
be
developed.
In
this
study,
machine
learning
(ML)
models
(random
forest,
multilayer
perceptron,
support
vector
machine)
predict
printability
drug
dose
were
developed
using
dataset
687
formulations,
consolidated
in-house
literature-mined
inkjet-printed
formulations.
The
optimized
ML
predicted
formulations
with
accuracy
97.22%,
quality
prints
97.14%.
This
study
demonstrates
that
can
feasibly
provide
insights
prior
preparation,
affording
resource-
time-savings.
