INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT,
Journal Year:
2023,
Volume and Issue:
07(11), P. 1 - 11
Published: Nov. 1, 2023
Comprehending
the
aspects
that
impact
song
popularity
has
become
crucial
in
always
changing
music
industry.
This
study
explores
field
of
predictive
modeling
using
cutting-edge
algorithms
XGBoost
and
LightGBM.
Predictive
models
developed
by
a
large
dataset
includes
variety
musical
variables,
such
as
duration,
tempo,
lyrical
content,
release
year.
To
improve
models'
capacity,
approach
extensive
work.
provide
thorough
assessment
algorithms'
performance,
is
divided
into
training
testing
sets.
Additionally,
effectiveness
LightGBM
forecasting
evaluated
comparison
analysis.
increase
prediction
accuracy,
hyperparameter
optimization
methods—specifically,
Optuna—are
used
to
fine-tune
them.
In
addition,
looks
at
feature
importance,
illuminating
elements
that,
eyes
each
algorithm,
greatly
add
its
appeal.
Using
rigorous
cross-validation
approach,
are
validated,
their
generalization
capabilities
shown.
The
performance
metrics,
which
comprehensive
picture
predicted
include
mean
absolute
error,
squared
median
R-squared.
By
providing
comparative
analysis
two
well-known
machine
learning
methods
for
popularity,
this
paper
advances
rapidly
developing
analytics.
results
offer
significant
perspectives
professionals
data
scientists
who
looking
efficient
approaches
forecast
across
various
genres.
Keywords
—
Music
Popularity
Prediction;
Machine
Learning;
XGBoost;
LightGBM;
Modeling;
Feature
Engineering;
Hyperparameter
Optimization;
Data
Analytics;
Comparative
Analysis;
Song
Characteristics;
Genre
Classification;
Ensemble
Models;
Cross-Validation;
Optuna;
Preprocessing;
Importance;
Regression;
Analytics.
Journal of Chemical Information and Modeling,
Journal Year:
2022,
Volume and Issue:
62(5), P. 1160 - 1171
Published: Feb. 28, 2022
Computational
chemistry
applications
have
become
an
integral
part
of
the
drug
discovery
workflow
over
past
35
years.
However,
computational
modeling
in
support
development
has
remained
a
relatively
uncharted
territory
for
significant
both
academic
and
industrial
communities.
This
review
considers
workflows
three
key
components
preclinical
clinical
development,
namely,
process
chemistry,
analytical
research
as
well
product
formulation
development.
An
overview
each
step
respective
is
presented.
Additionally,
context
solid
form
design,
special
consideration
given
to
modern
physics-based
virtual
screening
methods.
covers
rational
approaches
polymorph,
coformer,
counterion,
solvent
selection
design.
Crystal Growth & Design,
Journal Year:
2022,
Volume and Issue:
22(7), P. 4513 - 4527
Published: June 15, 2022
Controlling
the
physical
properties
of
solid
forms
for
active
pharmaceutical
ingredients
(APIs)
through
cocrystallization
is
an
important
part
drug
product
development.
However,
it
difficult
to
know
a
priori
which
coformers
will
form
cocrystals
with
given
API,
and
current
state-of-the-art
cocrystal
discovery
involves
expensive,
time-consuming,
and,
at
early
stages
development,
API
material-limited
experimental
screen.
We
propose
systematic,
high-throughput
computational
approach
primarily
aimed
identifying
API/coformer
pairs
that
are
unlikely
lead
experimentally
observable
can
therefore
be
eliminated
only
brief
check,
from
any
investigation.
On
basis
well-established
crystal
structure
prediction
(CSP)
methodology,
proposed
derives
its
efficiency
by
not
requiring
expensive
quantum
mechanical
calculations
beyond
those
already
performed
CSP
investigation
neat
itself.
The
assumptions
tested
on
30
potential
1:1
multicomponent
systems
(cocrystals
solvate)
involving
3
9
one
solvent.
This
complemented
detailed
all
pairs,
led
five
new
(three
API-coformer
combinations,
polymorphic
example,
different
stoichiometries)
cis-aconitic
acid
polymorph.
indicates
that,
some
APIs,
significant
proportion
could
investigated
thereby
saving
considerable
effort.
Pharmaceutics,
Journal Year:
2023,
Volume and Issue:
15(3), P. 836 - 836
Published: March 3, 2023
In
this
study,
the
existing
set
of
carbamazepine
(CBZ)
cocrystals
was
extended
through
successful
combination
drug
with
positional
isomers
acetamidobenzoic
acid.
The
structural
and
energetic
features
CBZ
3-
4-acetamidobenzoic
acids
were
elucidated
via
single-crystal
X-ray
diffraction
followed
by
QTAIMC
analysis.
ability
three
fundamentally
different
virtual
screening
methods
to
predict
correct
cocrystallization
outcome
for
assessed
based
on
new
experimental
results
obtained
in
study
data
available
literature.
It
found
that
hydrogen
bond
propensity
model
performed
worst
distinguishing
positive
negative
experiments
87
coformers,
attaining
an
accuracy
value
lower
than
random
guessing.
method
utilizes
molecular
electrostatic
potential
maps
machine
learning
approach
named
CCGNet
exhibited
comparable
terms
prediction
metrics,
albeit
latter
resulted
superior
specificity
overall
while
requiring
no
time-consuming
DFT
computations.
addition,
formation
thermodynamic
parameters
newly
evaluated
using
temperature
dependences
Gibbs
energy.
reactions
between
selected
coformers
be
enthalpy-driven,
entropy
being
statistically
from
zero.
observed
difference
dissolution
behavior
aqueous
media
thought
caused
variations
their
stability.
Pharmaceutics,
Journal Year:
2021,
Volume and Issue:
13(12), P. 2160 - 2160
Published: Dec. 15, 2021
Active
pharmaceutical
ingredients
(APIs)
extracted
and
isolated
from
traditional
Chinese
medicines
(TCMs)
are
of
interest
for
drug
development
due
to
their
wide
range
biological
activities.
However,
the
overwhelming
majority
APIs
in
TCMs
(T-APIs),
including
flavonoids,
terpenoids,
alkaloids
phenolic
acids,
limited
by
poor
physicochemical
biopharmaceutical
properties,
such
as
solubility,
dissolution
performance,
stability
tabletability
development.
Cocrystallization
these
T-APIs
with
coformers
offers
unique
advantages
modulate
properties
drugs
without
compromising
therapeutic
benefits
non-covalent
interactions.
This
review
provides
a
comprehensive
overview
current
challenges,
applications,
future
directions
T-API
cocrystals,
cocrystal
designs,
preparation
methods,
modifications
corresponding
mechanisms
properties.
Moreover,
variety
studies
presented
elucidate
relationship
between
crystal
structures
cocrystals
resulting
along
underlying
mechanism
changes.
It
is
believed
that
understanding
engineering
could
contribute
more
bioactive
natural
compounds
into
new
drugs.
Crystal Growth & Design,
Journal Year:
2022,
Volume and Issue:
22(2), P. 1390 - 1397
Published: Jan. 10, 2022
Drug
development
may
include
extensive
screening
for
crystalline
forms
of
active
pharmaceutical
ingredients.
Crystal
engineering
aims
to
apply
supramolecular
knowledge
simplify
such
a
task.
The
failure
strategy
result
in
overlooking
potentially
interesting
compounds.
Here,
the
advantages
knowledge-based
approach
is
compared
systematic
crystallization
cocrystals.
This
work
indicates
that
simply
based
on
known
synthons
and
their
relative
frequency
as
reported
database
effective
random
exercise,
missing
25%
successful
cocrystallization.
Readily
available
computational
methods
perform
better,
enabling
identification
all
observed
cocrystals
with
reduction
24%
experimental
attempts.
Molecular Pharmaceutics,
Journal Year:
2023,
Volume and Issue:
20(7), P. 3380 - 3392
Published: June 6, 2023
Crystal
structure
prediction
(CSP)
is
an
invaluable
tool
in
the
pharmaceutical
industry
because
it
allows
to
predict
all
possible
crystalline
solid
forms
of
small-molecule
active
ingredients.
We
have
used
a
CSP-based
cocrystal
method
rank
ten
potential
coformers
by
energy
cocrystallization
reaction
with
antiviral
drug
candidate,
MK-8876,
and
triol
process
intermediate,
2-ethynylglyclerol.
For
was
performed
retrospectively
successfully
predicted
maleic
acid
as
most
likely
be
observed.
The
known
form
two
different
cocrystals
1,4-diazabicyclo[2.2.2]octane
(DABCO),
but
larger
landscape
desired.
screening
triol-DABCO
one,
while
triol-l-proline
two.
Computational
finite-temperature
corrections
enabled
determination
relative
crystallization
propensities
stoichiometries
polymorphs
free-energy
landscape.
obtained
during
subsequent
targeted
experiments
found
exhibit
improved
melting
point
deliquescence
behavior
over
triol-free
acid,
which
could
considered
alternative
synthesis
islatravir.
Crystal Growth & Design,
Journal Year:
2022,
Volume and Issue:
23(2), P. 842 - 852
Published: Dec. 23, 2022
The
development
of
multicomponent
crystal
forms,
such
as
cocrystals,
represents
a
means
to
enhance
the
dissolution
and
absorption
properties
poorly
water-soluble
drug
compounds.
However,
successful
discovery
new
pharmaceutical
cocrystals
remains
time-
resource-consuming
process.
This
study
proposes
use
combined
computational-experimental
high-throughput
approach
tool
accelerate
improve
efficiency
cocrystal
screening
exemplified
by
posaconazole.
First,
we
employed
COSMOquick
software
preselect
rank
candidates
(coformers).
Second,
crystallization
experiments
(HTCS)
were
conducted
on
selected
coformers.
HTCS
results
successfully
reproduced
liquid-assisted
grinding
reaction
crystallization,
ultimately
leading
synthesis
thirteen
posaconazole
(7
anhydrous,
5
hydrates,
1
solvate).
characterized
PXRD,
1H
NMR,
Fourier
transform-Raman,
thermogravimetry-Fourier
transform
infrared
spectroscopy,
differential
scanning
calorimetry.
In
addition,
prediction
performance
was
compared
that
two
alternative
knowledge-based
methods:
molecular
complementarity
(MC)
hydrogen
bond
propensity
(HBP).
Although
HBP
does
not
perform
better
than
random
guessing
for
this
case
study,
both
MC
show
good
discriminatory
ability,
suggesting
their
potential
virtual
screening.