Meliha Ekinci1, Gizem Yeğen2, Buket Aksu2, Derya İlem-Özdemir1. 1. Faculty of Pharmacy, Department of Radiopharmacy, Ege University, Bornova, Izmir 35040, Turkey. 2. School of Pharmacy, Department of Pharmaceutical Technology, Altınbas University, Bakırköy, Istanbul 34217, Turkey.
Abstract
The aim of the study was to prepare and evaluate the potential use of poly(lactic acid)/poly(vinyl alcohol) (PLA/PVA) nanoparticle formulations as a drug delivery system. The nanoparticle formulations were successfully developed by the double emulsification/solvent evaporation method. The developed formulations were optimized using the quality by design approach of the ICH Q8 (Pharmaceutical Development) guideline. In the studies, the effects of emulsifying devices, evaporation technique, centrifugation effect, and polymer concentrations on the physicochemical parameters of the formulations were investigated to obtain the best results. Furthermore, the prepared formulations were evaluated for clarity, particle size, distribution, zeta potential, surface and morphological features, preparation efficiency, and long-term stability. Based on the obtained results, the nanoparticle formulation containing 12.5% PLA, 1% primer, and seconder PVA has a suitable particle size (181.7 ± 2.194 nm) and distribution (0.104 ± 0.049), zeta potential (-0.88 ± 0.45 mV), and high preparation efficiency (65.38%), and nanoparticles were spherical, had a smooth surface, and were stable up to 12 months. In conclusion, this novel formulation can be used as a potential drug delivery system.
The aim of the study was to prepare and evaluate the potential use of poly(lactic acid)/poly(vinyl alcohol) (PLA/PVA) nanoparticle formulations as a drug delivery system. The nanoparticle formulations were successfully developed by the double emulsification/solvent evaporation method. The developed formulations were optimized using the quality by design approach of the ICH Q8 (Pharmaceutical Development) guideline. In the studies, the effects of emulsifying devices, evaporation technique, centrifugation effect, and polymer concentrations on the physicochemical parameters of the formulations were investigated to obtain the best results. Furthermore, the prepared formulations were evaluated for clarity, particle size, distribution, zeta potential, surface and morphological features, preparation efficiency, and long-term stability. Based on the obtained results, the nanoparticle formulation containing 12.5% PLA, 1% primer, and seconder PVA has a suitable particle size (181.7 ± 2.194 nm) and distribution (0.104 ± 0.049), zeta potential (-0.88 ± 0.45 mV), and high preparation efficiency (65.38%), and nanoparticles were spherical, had a smooth surface, and were stable up to 12 months. In conclusion, this novel formulation can be used as a potential drug delivery system.
Nanomedicines, such as
polymeric nanoparticles, nanoemulsions,
and liposomes, have become increasingly popular in recent years.[1] Polymeric nanoparticles are frequently used as
drug and gene delivery systems due to their ability to protect drugs
and other molecules with biological activity against the environment,
their high bioavailability, safety, and biodegradability.[2] They have been proven to accumulate preferentially
at tumor sites, and their use as carriers improves efficacy while
reducing side effects.[3]In nanoparticle
preparation, polymers, such as poly(-caprolactone)
(PCL), poly(lactic acid) (PLA), poly(vinyl alcohol) (PVA), poly(glycolic
acid) (PGA), glycolic acid copolymer (PLGA), alginate, and others,
can all be employed.[4,5] Due to the advantages of nanoparticle
systems, intensive studies are carried out on the use of PLA/PVA nanoparticles
as a drug delivery system.[6] Herein, PLA/PVA
nanoparticle formulations were prepared as a drug delivery system
with an optimum amount and appropriate methods by selecting PLA, a
renewable, biocompatible, biodegradable, and widely used polymer with
good mechanical and optical properties, and PVA, a biodegradable and
widely used polymer, which is water-soluble and hydrophilic, has excellent
film-forming, emulsifying, and adhesive properties, and is harmless
and non-toxic for living tissues.[7,8]The International
Council for Harmonization (ICH) guidelines, Q8
Pharmaceutical Development, Q9 Quality Risk Management, and Q10 Pharmaceutical
Quality System, all explain the quality by design (QbD) strategy.
These systems serve as the cornerstones of drug development and research.
The basic goal of QbD is to develop a strategy for keeping critical
formulation or process variables within an acceptable range so that
product quality can be ensured while maintaining a stable and consistent
manufacturing process.[9,10]Any feature of formulation
components or process parameters that
has a significant impact on the desired product quality is referred
to as critical. For this purpose, experimental studies should be designed
in the light of risk assessment and previous scientific knowledge
to determine critical variables in process and formulation.[11]To investigate and understand the effects
of critical process parameters
(CPPs) and material attributes (CMAs) on product critical quality
attributes (CQAs), data analyses should be performed. The design space
(DS), which is a multidimensional combination and interaction of CMAs
and CPPs that have been demonstrated to provide assurance of quality,
should be formed to control well-understood variables.[12]Design of experiments and mathematical
models are used in the data
analysis and optimization process under a QbD approach. Many statistical
programs were created to help drug developers with an experimental
design capability for data required during the development stage of
a pharmaceutical product.[13]The aim
of this study was to prepare PLA/PVA polymeric nanoparticle
formulation as a drug delivery system. For this purpose, the impact
of formulation, such as primer/seconder PVA and PLA amounts, and various
process parameters have on particle size, distribution, and zeta potential
was enlightened, experimental results were evaluated, and then an
optimum formulation was chosen via MODDE Pro (Sartorius Stedim Data
Analytics) to establish DS.
Materials and Methods
Materials
PLA (40–100 kDa),
PVA (0.1% w/v, 85% hydrolyzed), and phosphate buffer (PBS) (pH: 7.4)
were purchased from Sigma-Aldrich, Germany. Dichloromethane (DCM)
was purchased from Merck, Germany. The saline solution (0.9% sodium
chloride solution) was obtained from Intermountain Life Sciences,
LLC.
Defining CQAs and CMAs
The parameters
that could potentially affect the process performance and product
were established using risk analysis.[12,14] A fishbone
diagram, as shown in Figure , can be used to visualize the connection between specific
quality parameters. To ensure that products of the desired quality
are developed, these parameters (CPP, CMA, and CQA) must be measured,
analyzed, and controlled throughout the entire process.
Figure 1
Ishikawa diagram
for determining CQAs for nanoparticles. *PVA:
polyvinyl alcohol, PLA: polylactic acid, and CQAs: critical quality
attributes.
Ishikawa diagram
for determining CQAs for nanoparticles. *PVA:
polyvinyl alcohol, PLA: polylactic acid, and CQAs: critical quality
attributes.
Preparation of PLA/PVA Nanoparticle Formulations
PLA/PVA nanoparticles were prepared using the double emulsification/solvent
evaporation method based on the method by Hernandez-Giottonini et
al.[15] The formulation was optimized by
changing various parameters in the preparation of PLA/PVA nanoparticles.In the literature reviews, it has been determined that the technique
used in formulation preparation has an important effect as much as
the content. For this reason, a series of controlled experiments were
planned within the scope of our study.[16] In this context, formulations with the same composition were prepared
using different emulsifiers (high-speed and high-pressure homogenizer).[17,18] Later, different volatilization techniques (rotavapor and magnetic
stirrers) were used to evaporate the organic solvent in the prepared
formulations.[19,20] After examining the effect of
centrifugation, which is one of the mechanical factors, the ideal
preparation technique was determined. Then, using the determined ideal
preparation technique, controlled experiments were carried out to
determine the formulation composition. In this context, the effect
of primary and secondary polymer concentrations on the physicochemical
properties of formulation was investigated.[21]
Effect of Emulsifying Devices
In
order to determine the preparation method in PLA/PVA nanoparticle
formulations, high-speed homogenizer and high-pressure homogenizer,
which were frequently used, were used to investigate the effect of
the emulsifying device.[17,18]
Use of a High-Speed Homogenizer Device
For the preparation of PLA/PVA nanoparticles; first, aqueous solution
of 0.6 mL of PVA (0.1% w/v, 85% hydrolyzed) was mixed with 0.6 mL
of physiological saline. This mixture was added to a solution of 50
mg PLA (40–100 kDa) in 4 mL of DCM and mixed in a high-speed
homogenizer (UltraTurrax T25, Ika, Germany) for different times (3,
5, and 10 min) to prepare a water/organic solvent (w/o) emulsion system.
This system was then dispersed in 10 mL of PVA (1% w/v) solution.
The organic solvent in the w/o/w emulsion system was obtained by mixing
in the high-speed homogenizer under the same conditions (3, 5, and
10 min) was removed by evaporation under vacuum at 60 rpm at 25 °C
for 1.5 h using rotavapor. Particles were recovered by centrifugation
at 20,000 rpm for 20 min at 20 °C to remove excess PVA and redispersed
in 2 mL of PBS (pH: 7.4).
Combined Use of High-speed Homogenizer
and High-pressure Homogenizer Devices
PLA/PVA nanoparticles
were prepared up to the w/o/w emulsion system as described in the
“Use of a High-Speed Homogenizer Device” section. Then, the w/o/w emulsion system was passed through
1 and/or 2 cycles of a high-pressure homogenizer device. Then, the
organic solvent in the system was removed by evaporation using a rotavapor
at 60 rpm at 25 °C for 1.5 h under vacuum. Particles were recovered
by centrifugation at 20,000 rpm for 20 min at 20 °C to remove
excess PVA and redispersed with 2 mL of PBS (pH: 7.4).
Effect of Evaporation Technique
Rotavapor and magnetic stirrers were both used as evaporation techniques
to investigate their impact on the preparation of PLA/PVA nanoparticle
formulations.[19,20]
Use of Rotavapor Device
PLA/PVA
nanoparticles were prepared up to the w/o/w emulsion system as described
in the “Combined Use of High-speed Homogenizer
and High-Pressure Homogenizer Devices” section. Then,
the organic solvent in the w/o/w emulsion system obtained by mixing
in the high-speed homogenizer under the same conditions was removed
by evaporation under vacuum at 60 rpm at 25 °C for 1.5 h using
a rotavapor. Particles were recovered by centrifugation at 20,000
rpm for 20 min at 20 °C to remove excess PVA and redispersed
in 2 mL of PBS (pH: 7.4).
Use of Magnetic Stirrer Device
PLA/PVA nanoparticles were prepared up to a w/o/w emulsion system,
as described in the “Combined Use of
High-speed Homogenizer and High-Pressure Homogenizer Devices” section. Then, the organic solvent in the w/o/w emulsion
system obtained by mixing in the high-speed homogenizer under the
same conditions was removed by evaporation using a magnetic stirrer
at 100 rpm at 25 °C for 1.5 h. Particles were recovered by centrifugation
at 20,000 rpm for 20 min at 20 °C to remove excess PVA and redispersed
in 2 mL of PBS (pH: 7.4).
Centrifugal Effect
The effect of
high-speed centrifuge on the particle size in the preparation of PLA/PVA
nanoparticle formulations was investigated. For this purpose, aqueous
solution of 0.6 mL of PVA (0.1% w/v, 85% hydrolyzed) was mixed with
0.6 mL of physiological saline. This mixture was added to a solution
of 50 mg PLA (40–100 kDa) in 4 mL of DCM and mixed in a high-speed
homogenizer for 5 min to prepare a w/o emulsion system. This system
was then dispersed in 10 mL of PVA (1% w/v) solution. The organic
solvent in the w/o/w emulsion system obtained by mixing in the high-speed
homogenizer for 5 min was removed by evaporation using a magnetic
stirrer for 1.5 h at 25 °C at 100 rpm. Then, while a group of
particles was redispersed in 2 mL of PBS (pH: 7.4), recovered by centrifugation
at 20,000 rpm for 20 min at 20 °C to remove excess PVA, the other
group of particles was not centrifuged.
Effect of Polymer Concentration
Because PLA and PVA concentrations are an important parameter affecting
the particle size of the formulations,[21] the physicochemical parameters (particle size, size distribution,
and zeta potential) of the formulations prepared using polymers at
different concentrations were examined based on the method of Hernandez-Giottonini
et al.[15]The decided formulations
by mixed full factorial design were numbered by the percentage of
PLA for ease of tracking. The contents of the formulations are given
in Table .
Table 1
Content of Formulations
formulation
primer PVA (%)
PLA (%)
seconder PVA (%)
A1
0.1
5
0.1
A2
0.1
5
0.5
A3
0.1
5
1
A4
0.5
5
0.1
A5
0.5
5
0.5
A6
0.5
5
1
A7
1
5
0.1
A8
1
5
0.5
A9
1
5
1
B1
0.1
7.5
0.1
B2
0.1
7.5
0.5
B3
0.1
7.5
1
B4
0.5
7.5
0.1
B5
0.5
7.5
0.5
B6
0.5
7.5
1
B7
1
7.5
0.1
B8
1
7.5
0.5
B9
1
7.5
1
C1
0.1
10
0.1
C2
0.1
10
0.5
C3
0.1
10
1
C4
0.5
10
0.1
C5
0.5
10
0.5
C6
0.5
10
1
C7
1
10
0.1
C8
1
10
0.5
C9
1
10
1
D1
0.1
12.5
0.1
D2
0.1
12.5
0.5
D3
0.1
12.5
1
D4
0.5
12.5
0.1
D5
0.5
12.5
0.5
D6
0.5
12.5
1
D7
1
12.5
0.1
D8
1
12.5
0.5
D9
1
12.5
1
Characterization Studies of PLA/PVA Nanoparticles
Particle Size, Distribution, and Zeta Potential
Value
The prepared formulations were evaluated in terms of
aggregate formation, particle size, and distribution using a Malvern
Zeta Sizer in the particle size range of 3–1000 nm, at room
temperature, with an angle of 173°. Samples were diluted 1:400
with filtered and bidistilled water (pH = 7) before evaluation.The zeta potential of the formulations was evaluated using a Malvern
Zeta Sizer at a field strength of 40 V cm–1 using
a DTS 1060C zeta cuvette at 25 °C, dielectric constant of 78.5,
and conductivity of 5 mS cm–1. Samples were diluted
1:400 with bidistilled water (pH = 7) before measuring. The mean zeta
potential was determined.
Surface and Morphological Feature Analysis
Studies
Scanning Electron Microscopy
The size and surface properties of PLA/PVA nanoparticles were examined
under scanning electron microscopy (SEM). For this purpose, the nanoparticles
were mounted onto an aluminum grid, sputter-coated with gold palladium
(Au/Pd) using a vacuum evaporator, scanning of the coated nanoparticles
was carried out at ×12,000 magnification and 4 kV incremental
voltage conditions by a SEM device (Philips XL-30S FEG).
Atomic Force Microscopy
The morphology
and dimensions of PLA/PVA nanoparticles were analyzed by atomic force
microscopy (AFM) to acquire topographic and phase images to investigate
the diameter, height, and phase composition of the particles. For
this purpose, AFM topography of PLA/PVA nanoparticles surface was
taken using a Bruker Dimension Edge with ScanAsyst operating in the
peak force tapping mode. The scanning tip was a silicon tip on nitride
lever, 115 μm in length with a force constant of 0.4 N/m. A
10 μL of sample drop was spotted on freshly cleaved lamel. The
sample solution was left on the substrates for about 1 min, blown
off with air, and immediately observed by AFM.
Preparation Yield of PLA/PVA Nanoparticles
The preparation yield of the nanoparticles was calculated gravimetrically
as a percentage using eq .[22,23]MN: mass of produced nanoparticles and MP:
mass of initial polymer materials
Long-Term Stability Studies of Nanoparticles
Studies to examine the stability of the developed formulations
were carried out in accordance with the stability guide, at 5 ±
3 °C (in the refrigerator) and 25 ± 5 °C, 60 ±
5% relative humidity, and 40 ± 5 °C, 75 ± 5% relative
humidity. In the stability study, the samples were checked for their
physical appearance, particle size and distribution, and zeta potentials
for 12 months at initial, 1, 3, 6, and 12 months.[24]
Formulation Optimization and Evaluation of
DS
After characterization studies, the experimental data
were evaluated using Modde Pro 12.1 (Sartorius Stedim Data Analytics)
statistical computer program, which allows the optimization and establishment
of a DS that is the multidimensional combination and interaction of
input variables (e.g., material attributes) to provide quality assurance
with response surface methodology. As seen in Table , the amount of primer and seconder PVA and
the PLA was evaluated as a mixture/formulation factor. A mixture design
was generated with 36 runs; three measurements were included as responses
in the experimental design: particle size, distribution, and zeta
potential value.
Table 2
Input Factors and Their Levels used
for Specification in Modde 12.1 Pro Software
input factors
abbr.
level settings
primer PVA (%)
pri
0.1–1
seconder PVA (%)
sec
0.1–1
PLA (%)
PLA
5–12.5
The validity of the experimental design was checked
using a variance
test, and a mathematical model for all responses was fitted using
the partial least squares regression approach in the statistical module
of the Modde 12.1 Pro program (ANOVA). According to the model, an
optimization process was conducted, and DS were created. Verification
studies for DS were carried out with the edge point of the normal
operation range in DS.
Statistical Analysis
Statistical
analysis and variance analysis (Univariate Variance Analyze) of all
the obtained characterization results were done using SPSS software
version 25. The statistical significance level was accepted as p < 0.05 for all analyses performed. Results were obtained
in triplicate and presented as the mean ± SD.
Results
In Table , determined CQAs
and their limits according to the scientific literature knowledge
were given. Moreover, with risk assessment emulsifying devices, evaporation
technique, centrifugation effect, and polymer concentration on the
physicochemical parameters of the formulations were investigated.
Table 3
CQA’s for Nanoparticles
nanoparticle property
specifications
particle size
<200 nm
particle size distribution
<0.25
zeta potential
–30 mV to +30 mV
PLA/PVA nanoparticles were prepared successfully using a double
emulsification/solvent evaporation method to examine the effect of
the variables in process and formulation.The
particle size, distribution, and zeta potential values of the formulations
prepared by mixing at different times with the use of a high-speed
homogenizer and high-pressure homogenizer devices are given in Table .
Table 4
Results of Change in Characterization
Parameters of Formulations Prepared by Mixing at Different Times with
the Use of High-speed Homogenizer and High-pressure Homogenizer Devices
(Mean ± SD)
high-speed homogenizer
(time) (min)
high-pressure homogenizer (cycle)
particle size (nm ± ss)
PdI (±ss)
zeta potential (mV ± ss)
3
-
415.8 ± 3.743
0.153 ± 0.017
–2.10 ± 0.26
3
1 cycle
373.3 ± 4.002
0.160 ± 0.025
–0.42 ± 0.35
3
2 cycles
376.2 ± 2.121
0.132 ± 0.001
–2.56 ± 0.27
5
-
290.5 ± 0.351
0.107 ± 0.083
–3.25 ± 0.10
5
1 cycle
224.4 ± 3.439
0.119 ± 0.022
–7.25 ± 0.63
5
2 cycles
223.7 ± 1.852
0.122 ± 0.052
+0.01 ± 0.26
10
-
384.7 ± 2.892
0.129 ± 0.023
–1.59 ± 0.33
10
1 cycle
273.4 ± 1.273
0.127 ± 0.008
–0.08 ± 0.10
10
2 cycles
276.2 ± 4.022
0.130 ± 0.032
–6.56 ± 0.41
Use of a high-speed homogenizer device was determined
that all
formulations had a homogeneous particle size distribution, and the
lowest particle size was obtained after 5 min of mixing time. Furthermore,
the characterization results of the particles formed as a result of
only the use of high-speed homogenizer device and the combined use
of high-speed homogenizer and high-pressure homogenizer device were
evaluated. The particle size of the formulations prepared as a result
of the combined use of the devices decreased. When the number of rounds,
in which the formulations were passed through the high-pressure homogenizer
device, was examined, there was no significant change in the particle
size (p > 0.05).Considering these results,
it was decided to use high-speed homogenizer
and high-pressure homogenizer devices in combination in the next studies
(high-speed homogenizer device: 5 and 10 min and high-pressure homogenizer
device: 1 cycle).
Optimization of Evaporation Technique
The particle size, distribution, and zeta potential values of the
formulations, in which the organic solvent was removed using the rotavapor
and magnetic stirrer devices, are given in Table .
Table 5
Results of Change in Characterization
Parameters of Formulations Prepared at Different Times, in which the
Organic Solvent was Removed Using the Rotavapor and Magnetic Stirrer
Devices (Mean ± SD)
high-speed homogenizer
(time) (min)
high-pressure homogenizer (cycle)
evaporation technique
particle size (nm ± ss)
PdI (±ss)
zeta potential (mV ± ss)
5
1 cycle
rotavapor
199.7 ± 4.126
0.123 ± 0.026
–9.13 ± 1.19
5
1 cycle
magnetic stirrer
197.0 ± 4.980
0.095 ± 0.052
–0.83 ± 0.02
10
1 cycle
rotavapor
264.3 ± 6.152
0.587 ± 0.011
–1.38 ± 0.15
10
1 cycle
magnetic stirrer
230.5 ± 8.520
0.491 ± 0.039
–1.38 ± 0.34
There was no significant change in the physicochemical
parameters
of the formulations, in which the organic solvent was removed by using
both evaporation techniques (p > 0.05). The use
of
a magnetic stirrer device was appropriate for evaporation in terms
of ease of use and time method. After the evaporation process using
a magnetic stirrer device, 5 min mixing time was the most suitable
time because the lowest particle size was obtained after 5 min mixing
time and because of the increase in PdI values of the formulations
after 10 min of mixing time.Considering these results, it was
decided to use a magnetic stirrer
in the next studies (high-speed homogenizer device: 5 min and evaporation
technique: magnetic stirrer).The effect of
centrifugation, which is carried out to ensure the recovery of the
particles in the formulations, on the physicochemical parameters of
the formulations was investigated. The particle size, distribution,
and zeta potential values of the formulations with and without the
centrifugation are given in Table .
Table 6
Results of Change in Characterization
Parameters of Formulations with and without the Centrifugation (Mean
± SD)
high-speed homogenizer
(time) (min)
high-pressure homogenizer (cycle)
evaporation technique
centrifugation
particle size (nm ± ss)
PdI (±ss)
zeta potential (mV ± ss)
5
1 cycle
magnetic stirrer
-
197.0 ± 4.980
0.095 ± 0.052
–0.83 ± 0.02
5
1 cycle
magnetic stirrer
20,000 rpm 20 min at 20 °C
199.6 ± 5.086
0.035 ± 0.014
–0.43 ± 0.32
The centrifugation process did not cause a significant
change (p > 0.05) in the physicochemical parameters
of the formulations,
so the centrifugation process was appropriate for the recovery of
particles.Considering these results, it was decided to use
the centrifugation
process in the next studies.The particle size, distribution, and zeta potential values of the
formulations prepared using 5, 7.5, 10, and 12.5% PLA and different
ratios of primer/seconder PVA are given in Figures –5.
Figure 2
Graph of the (A) particle size, (B) PdI, and
(C) ζ potential
of formulations prepared using 5% PLA and different ratios of primer/seconder
PVA.
Figure 5
Graph of the (A) particle size, (B) PdI, and (C) ζ
potential
of formulations prepared using 12.5% PLA and different ratios of primer/seconder
PVA.
Graph of the (A) particle size, (B) PdI, and
(C) ζ potential
of formulations prepared using 5% PLA and different ratios of primer/seconder
PVA.Graph of the (A) particle size, (B) PdI, and (C) ζ
potential
of formulations prepared using 7.5% PLA and different ratios of primer/seconder
PVA.Graph of the (A) particle size, (B) PdI, and (C) ζ
potential
of formulations prepared using 10% PLA and different ratios of primer/seconder
PVA.Graph of the (A) particle size, (B) PdI, and (C) ζ
potential
of formulations prepared using 12.5% PLA and different ratios of primer/seconder
PVA.As a result of all these studies, it was decided
to perform surface
and morphological analyses with formulations containing 1% seconder
PVA, which were determined to have the lowest particle size.
Particle Size and Zeta Potential Analyses
The results of the particle size, distribution, and zeta potential
analyses of PLA/PVA nanoparticle formulations are given in Figures –5 and Tables –6.
SEM Analysis
SEM images of PLA/PVA
nanoparticle formulations with ideal properties (particle size, distribution,
zeta potential, and redispersibility) are given in Figure . The size of the particles
was found to be consistent with the Malvern Zeta Sizer analysis results.
Figure 6
SEM images
of the formulations containing 1% seconder PVA. “A”,
“B”, “C”, and “D” coded
formulations were prepared by using 5, 7.5, 10, and 12.5% PLA. In
addition, “3”, “6”, and “9”
coded formulations were prepared by using 0.1, 0.5, and 1% primer
PVA, respectively.
SEM images
of the formulations containing 1% seconder PVA. “A”,
“B”, “C”, and “D” coded
formulations were prepared by using 5, 7.5, 10, and 12.5% PLA. In
addition, “3”, “6”, and “9”
coded formulations were prepared by using 0.1, 0.5, and 1% primer
PVA, respectively.Considering these results, it was decided to use
D9 formulation,
which was found to have ideal properties, in the next studies.
AFM Analysis
The AFM images of
the D9 formulation with ideal properties are shown in Figure . As seen in Figure , the images of the particles
were found to be compatible with the SEM results. Accordingly, the
particles are spherical in shape and have a smooth surface.
Figure 7
AFM image of
D9 formulation.
AFM image of
D9 formulation.Advanced imaging techniques, such as SEM and AFM,
can be used to
determine the microscopic properties of submicron materials such as
shape, size, surface morphology, crystal structure, and distribution.
Preparation Efficiency of Nanoparticles
The preparation efficiency of D9 formulation was found to be 65.38%.Stability studies of formulations stored at 5 ± 3 °C
(in the refrigerator) and 25 ± 5 °C and 60 ± 5% relative
humidity and 40 ± 5 °C and 75 ± 5% relative humidity
for 12 months at the beginning, at 1, 3, 6, and 12 months, and the
results are given in Tables –9.
Table 7
Initial, 1st, 3rd, 6th, and 12th Month
Particle Size (nm ± ss), PdI, and Zeta Potential (mV ± ss)
Results of PLA/PVA Nanoparticles Placed in a 5 ± 3 °C Stability
Cabinet (Mean ± SD)
for.
Tinitial
T1month
T3month
T6month
T12month
A3
171.6 ± 2.290 nm
170.0 ± 1.607 nm
171.6 ± 6.576 nm
180.7 ± 5.147 nm
190.2 ± 3.045 nm
0.136 ± 0.028
0.110 ± 0.058
0.162 ± 0.020
0.041 ± 0.039
0.126 ± 0.016
–11.2 ± 1.05 mV
–0.42 ± 0.12 mV
–0.16 ± 0.15 mV
–10.6 ± 4.60 mV
–5.12 ± 0.97 mV
A6
196.9 ± 1.202 nm
211.9 ± 0.000 nm
213.3 ± 3.607 nm
226.1 ± 1.485 nm
232.2 ± 2.418 nm
0.239 ± 0.076
0.245 ± 0.074
0.174 ± 0.103
0.148 ± 0.018
0.170 ± 0.026
–3.06 ± 0.63 mV
–1.17 ± 0.15 mV
–1.57 ± 0.17 mV
–7.93 ± 0.71 mV
–4.38 ± 0.59 mV
A9
199.9 ± 0.353 nm
201.3 ± 5.020 nm
235.7 ± 3.404 nm
221.2 ± 1.273 nm
219.4 ± 2.109 nm
0.174 ± 0.076
0.176 ± 0.054
0.199 ± 0.043
0.101 ± 0.094
0.156 ± 0.032
–3.08 ± 0.46 mV
–1.37 ± 0.21 mV
–1.15 ± 0.09 mV
–6.24 ± 1.23 mV
–2.65 ± 0.75 mV
B3
199.9 ± 0.116 nm
207.1 ± 0.000 nm
219.9 ± 3.748 nm
222.1 ± 1.344 nm
222.3 ± 1.478 nm
0.192 ± 0.038
0.182 ± 0.037
0.151 ± 0.024
0.054 ± 0.057
0.102 ± 0.041
–9.14 ± 1.21 mV
–1.88 ± 1.15 mV
–1.69 ± 0.59 mV
–8.62 ± 1.01 mV
–5.36 ± 0.97 mV
B6
202.7 ± 3.118 nm
189.4 ± 0.778 nm
192.2 ± 2.828 nm
210.5 ± 3.260 nm
216.7 ± 3.216 nm
0.156 ± 0.059
0.160 ± 0.066
0.073 ± 0.090
0.028 ± 0.017
0.105 ± 0.032
–4.24 ± 0.84 mV
–1.18 ± 0.12 mV
–0.43 ± 0.16 mV
–9.03 ± 1.51 mV
–3.15 ± 0.64 mV
B9
183.6 ± 5.467 nm
176.6 ± 2.800 nm
180.8 ± 4.423 nm
197.3 ± 3.748 nm
200.6 ± 3.458 nm
0.193 ± 0.049
0.133 ± 0.089
0.123 ± 0.074
0.051 ± 0.062
0.096 ± 0.034
–6.71 ± 1.71 mV
–12.1 ± 2.76 mV
–2.75 ± 0.64 mV
–8.86 ± 0.71 mV
–5.36 ± 0.75 mV
C3
176.4 ± 4.172 nm
169.9 ± 0.495 nm
169.5 ± 0.473 nm
186.9 ± 2.051 nm
190.5 ± 1.432 nm
0.171 ± 0.022
0.056 ± 0.070
0.143 ± 0.071
0.102 ± 0.047
0.112 ± 0.056
–1.52 ± 0.40 mV
–0.25 ± 0.19 mV
–4.16 ± 0.11 mV
–7.13 ± 0.93 mV
–3.25 ± 0.41 mV
C6
189.6 ± 2.859 nm
185.9 ± 0.071 nm
187.3 ± 2.730 nm
205.1 ± 1.131 nm
198.4 ± 2.165 nm
0.184 ± 0.012
0.126 ± 0.034
0.160 ± 0.067
0.049 ± 0.032
0.096 ± 0.018
–0.45 ± 0.63 mV
–1.23 ± 0.10 mV
–1.23 ± 1.07 mV
–7.04 ± 1.23 mV
–3.05 ± 0.95 mV
C9
163.9 ± 2.051 nm
168.2 ± 2.121 nm
176.2 ± 1.556 nm
189.7 ± 1.697 nm
197.1 ± 1.238 nm
0.145 ± 0.002
0.077 ± 0.028
0.175 ± 0.025
0.119 ± 0.050
0.124 ± 0.031
–1.32 ± 0.09 mV
–1.41 ± 0.28 mV
–1.83 ± 0.11 mV
–5.11 ± 0.69 mV
–3.28 ± 0.49 mV
D3
188.6 ± 6.576 nm
192.8 ± 4.950 nm
190.1 ± 1.556 nm
198.1 ± 0.566 nm
205.4 ± 1.637 nm
0.115 ± 0.076
0.094 ± 0.016
0.112 ± 0.052
0.243 ± 0.013
0.165 ± 0.038
–1.88 ± 0.18 mV
+0.46 ± 0.27 mV
+0.16 ± 0.18 mV
–4.51 ± 0.34 mV
+0.87 ± 0.24 mV
D6
191.8 ± 3.111 nm
183.7 ± 3.020 nm
187.6 ± 1.273 nm
198.7 ± 1.401 nm
206.4 ± 2.665 nm
0.191 ± 0.011
0.081 ± 0.024
0.100 ± 0.005
0.065 ± 0.047
0.054 ± 0.017
–3.94 ± 0.28 mV
–2.19 ± 0.21 mV
–0.75 ± 0.30 mV
–6.85 ± 1.20 mV
–5.47 ± 1.39 mV
D9
181.7 ± 2.194 nm
180.0 ± 4.026 nm
197.3 ± 1.992 nm
194.5 ± 2.639 nm
195.2 ± 1.435 nm
0.104 ± 0.049
0.158 ± 0.005
0.210 ± 0.027
0.031 ± 0.030
0.089 ± 0.036
–0.88 ± 0.45 mV
–1.57 ± 0.65 mV
–0.31 ± 0.22 mV
–0.69 ± 0.05 mV
–1.54 ± 0.18 mV
Table 9
Initial, 1st, 3rd, 6th, and 12th Month
Particle Size (nm ± ss), PdI, and Zeta Potential (mV ± ss)
Results of PLA/PVA Nanoparticles Placed in a 40 ± 5 °C Stability
Cabinet (Mean ± SD)
for.
Tinitial
T1month
T3month
T6month
T12month
A3
171.6 ± 2.290 nm
165.6 ± 1.556 nm
181.5 ± 3.683 nm
182.3 ± 3.790 nm
195.4 ± 2.347 nm
0.136 ± 0.028
0.030 ± 0.003
0.135 ± 0.055
0.122 ± 0.067
0.134 ± 0.031
–11.2 ± 1.05 mV
–3.80 ± 0.02 mV
–7.58 ± 1.45 mV
–1.39 ± 0.53 mV
–5.21 ± 1.11 mV
A6
196.9 ± 1.202 nm
228.4 ± 0.424 nm
230.1 ± 6.718 nm
272.4 ± 15.18 nm
254.6 ± 7.230 nm
0.239 ± 0.076
0.139 ± 0.031
0.198 ± 0.037
0.068 ± 0.058
0.154 ± 0.067
–3.06 ± 0.63mV
–7.38 ± 0.52 mV
–0.31 ± 0.58 mV
+0.26 ± 0.51 mV
–1.37 ± 0.75 mV
A9
199.9 ± 0.353 nm
203.3 ± 2.899 nm
211.0 ± 5.398 nm
224.9 ± 0.781 nm
235.1 ± 2.430 nm
0.174 ± 0.076
0.138 ± 0.006
0.121 ± 0.030
0.081 ± 0.015
0.134 ± 0.048
–3.08 ± 0.46 mV
–7.94 ± 1.86 mV
–1.73 ± 0.46 mV
–4.19 ± 1.85 mV
–1.36 ± 0.39 mV
B3
199.9 ± 0.116 nm
207.7 ± 1.692 nm
217.3 ± 3.859 nm
223.1 ± 0.424 nm
215.3 ± 1.530 nm
0.192 ± 0.038
0.124 ± 0.067
0.223 ± 0.040
0.087 ± 0.038
0.175 ± 0.023
–9.14 ± 1.21 mV
–0.05 ± 0.06 mV
–3.04 ± 0.42 mV
–0.34 ± 0.18 mV
–1.58 ± 0.32 mV
B6
202.7 ± 3.118 nm
188.5 ± 1.706 nm
205.1 ± 0.778 nm
223.7 ± 6.788 nm
215.3 ± 4.637 nm
0.156 ± 0.059
0.121 ± 0.032
0.138 ± 0.073
0.079 ± 0.052
0.109 ± 0.067
–4.24 ± 0.84 mV
–3.94 ± 0.14 mV
–10.7 ± 1.77 mV
+0.31 ± 0.28 mV
–5.47 ± 1.38 mV
B9
183.6 ± 5.467 nm
174.8 ± 2.051 nm
188.4 ± 2.676 nm
201.4 ± 0.283 nm
194.3 ± 2.207 nm
0.193 ± 0.049
0.091 ± 0.013
0.087 ± 0.047
0.038 ± 0.037
0.106 ± 0.038
–6.71 ± 1.71 mV
–3.71 ± 0.58 mV
–6.07 ± 0.72 mV
+0.36 ± 0.13 mV
–3.27 ± 0.40 mV
C3
176.4 ± 4.172 nm
160.5 ± 0.971 nm
184.5 ± 5.706 nm
183.7 ± 4.243 nm
197.3 ± 3.210 nm
0.171 ± 0.022
0.138 ± 0.055
0.229 ± 0.058
0.058 ± 0.021
0.145 ± 0.067
–1.52 ± 0.40 mV
–6.05 ± 0.63 mV
–3.45 ± 0.19 mV
–1.38 ± 0.21 mV
–3.21 ± 0.27 mV
C6
189.6 ± 2.859 nm
187.4 ± 4.738 nm
200.2 ± 3.828 nm
203.9 ± 0.354 nm
217.3 ± 1.058 nm
0.184 ± 0.012
0.139 ± 0.007
0.167 ± 0.033
0.095 ± 0.008
0.124 ± 0.052
–0.45 ± 0.63 mV
+0.54 ± 0.32 mV
–5.87 ± 0.58 mV
+0.22 ± 0.05 mV
–1.03 ± 0.25 mV
C9
163.9 ± 2.051 nm
170.3 ± 1.345 nm
182.6 ± 3.099 nm
191.3 ± 1.061 nm
198.7 ± 2.046 nm
0.145 ± 0.002
0.067 ± 0.048
0.093 ± 0.065
0.114 ± 0.037
0.098 ± 0.056
–1.32 ± 0.09 mV
–6.72 ± 0.95 mV
–0.75 ± 0.36 mV
–2.35 ± 1.02 mV
–1.35 ± 0.72 mV
D3
188.6 ± 6.576 nm
182.1 ± 0.919 nm
178.9 ± 6.435 nm
198.3 ± 4.230 nm
200.3 ± 3.241 nm
0.115 ± 0.076
0.128 ± 0.091
0.170 ± 0.016
0.088 ± 0.012
0.105 ± 0.034
–1.88 ± 0.18 mV
–0.76 ± 0.31 mV
–1.00 ± 0.32 mV
–0.33 ± 0.10 mV
–1.07 ± 0.54 mV
D6
191.8 ± 3.111 nm
179.7 ± 4.525 nm
193.3 ± 3.126 nm
196.6 ± 2.488 nm
205.2 ± 2.685 nm
0.191 ± 0.011
0.009 ± 0.008
0.160 ± 0.034
0.117 ± 0.095
0.087 ± 0.052
–3.94 ± 0.28 mV
–3.26 ± 0.38 mV
–1.33 ± 0.24 mV
–0.31 ± 0.07 mV
–1.69 ± 0.32 mV
D9
181.7 ± 2.194 nm
183.9 ± 4.879 nm
193.4 ± 1.528 nm
196.3 ± 4.243 nm
198.3 ± 3.470 nm
0.104 ± 0.049
0.150 ± 0.018
0.113 ± 0.045
0.071 ± 0.018
0.106 ± 0.024
–0.88 ± 0.45 mV
–7.10 ± 0.73 mV
–0.80 ± 0.11 mV
–0.57 ± 0.22 mV
–1.34 ± 0.19 mV
Formulation Optimization and DS Evaluation
The validity of the experimental design was evaluated, mainly R2 and Q2 values
given in Modde Pro 12.1. A model with an R2 (coefficient of determination) of 0.5 has a relatively low significance. Q2 (an estimation of precision of predictions)
should be greater than 0.1 for a significant model and greater than
0.5 for a good model. The difference between R2 and Q2 should also be smaller
than 0.3 for a good model. Q2 is the best
and most sensitive indicator.As seen in Figure , a significant model was created for only
particle size (R2 is 0.74 and Q2 is 0.58). Because the main factor is the particle
size in the study to search the effect of formulation parameters,
optimization study was conducted according to the particle size. The
revised values of the regression coefficients of the model equation
are presented as a histogram for the particle size.
Figure 8
Summary of fit plot.
Summary of fit plot.Figure , the coefficient
plot, shows a graphical depiction of the model terms to help identify
their significance and degree of variable impacts on responses. The
sign of the model terms indicates whether they have a positive or
negative influence on the answer. A substantial term has a large distance
from y = 0 as well as an uncertainty level that does
not cross y = 0.[12]
Figure 9
Coefficient
graph demonstrates the influence of formulation variables
on the particle size.
Coefficient
graph demonstrates the influence of formulation variables
on the particle size.The optimizer set points with factor settings and
predicted response
values, and from the initial set point chosen based on the log(D) (normalized distance to the target), the DS for optimal
factors was generated using the robust set point function predicted
by Monte Carlo simulation (resolution 64, 50,000 simulations per point,
95% confidence level), as given in Table .[25]Figure demonstrates the
DS, the green areas are part of the DS, with a less than 1% risk of
failure. The regions with a higher probability of failure are depicted
from yellow to red.[12]
Table 10
Optimizer Set Points with Factor
Settings and Predicted Response Values, and the Robust Set Point of
Factors
response
response objectives
optimizer initial set point
robust set point
log(D)
Cpk
particle size
minimize
170.97
154.96
–0.671328
0.139524
PDI
predicted
0.139783
0.140309
zeta potential
predicted
–0.642953
–0.695698
Factor
primer PVA (%)
1
1
seconder
PVA (%)
1
1
PLA (%)
12.5
12.4
Figure 10
DS for the formulation
variables meets the specification of the
particle size.
DS for the formulation
variables meets the specification of the
particle size.The alternative representation of the DS given in Table , in the case of
multidimensional
DS, is to describe a hypercube that defines the edges of the DS.
Table 11
Hypercube Edges of the DS
factors
low
high
hypercube
low edge (NOP)a
hypercube high edge (NOP)a
primer PVA (%)
0.053
1.92
0.1
1
seconder PVA (%)
0.94
1.03
0.96
1
PLA (%)
11.1623
13.59
11.67
12.5
Responses
particle size
186.3 ± 2.301 nm
181.7 ± 2.194 nm
PDI
0.212 ± 0.049
0.104 ± 0.049
zeta potential
–1.58 ± 0.21 mV
–0.88 ± 0.45 mV
Normal operation range.
Normal operation range.DS verification was performed by preparing the formulation
edge
points of normal operating range and particle size was measured, and
the results are given in Table . All results were found to be satisfied for response
requirements.
Discussion
Nanoparticles are drug delivery
systems with sizes ranging from
1 to 1000 nm, which overcome biological barriers and facilitate diagnosis,
treatment, follow-up of the disease and treatment responses.[26−28] For these reasons, polymeric nanoparticle formulations consisting
of PLA and PVA were prepared that can be used as drug delivery systems
in this study.In order to determine the ideal formulation,
PLA/PVA nanoparticles
were prepared using the double emulsification/solvent evaporation
method.[15] Some various parameters in the
preparation of PLA/PVA nanoparticles have a significant effect on
the physicochemical parameters of the formulation. In this context,
during the formulation development studies, various parameters, such
as emulsifying devices,[17,18] evaporation technique,[19,20] centrifugation effect, and PLA concentration,[15,21] were changed, and ideal formulation conditions were determined.High-speed and high-pressure homogenizer devices are frequently
used in the preparation of PLA/PVA nanoparticle formulations.[17,18] Therefore, we first carried out a series of studies to determine
the ideal mixing method. The mixing time of the high-speed homogenizer
device used during the formulation preparation has important effects
on the physicochemical properties of the particles. All of the formulations
prepared by mixing with a high-speed homogenizer at different times
had a homogeneous particle size distribution, and the lowest particle
size was obtained after 5 min of mixing.The mixing time and
the number of cycles that the sample is passed
through the device have significant effects on the physicochemical
properties of the particles, where the high-speed and high-pressure
homogenizer devices used during the formulation preparation are combined.
When the characterization results of the particles formed as a result
of using only the high-speed homogenizer device and the combined use
of both devices are evaluated comparatively; as a result of the combined
use of the devices, the particle size decreased significantly (p < 0.05). In addition, the number of cycles of formulation
passing through the high-pressure homogenizer device did not cause
any significant change in the particle size (p >
0.05). Considering the results of the controlled experiment series,
it was decided to use high-speed and high-pressure homogenizer devices
in combination in formulation preparation studies (high speed homogenizer
device: 5 and 10 min, high pressure homogenizer device: 1 cycle).Because rotavapor and magnetic stirrer devices were used as evaporation
techniques in the preparation of PLA/PVA nanoparticle formulations,[19,20] the physicochemical parameters of the formulations prepared using
both devices were evaluated. There was no significant change (p > 0.05) in the physicochemical parameters of the formulations
removed by using the organic solvent rotavapor and magnetic stirrer
device. Therefore, the use of a magnetic stirrer device was appropriate
for evaporation in terms of ease of use and time method. In addition,
because the lowest particle size was obtained after 5 min of mixing
time after evaporation using the magnetic stirrer device, and there
was an increase in the PdI values of the formulations after 10 min
of mixing, a mixing time of 5 min was appropriate in the formulation
preparation process.The centrifugation process carried out
to ensure the recovery of
the particles in the formulations did not cause a significant change
(p > 0.05) in the physicochemical parameters of
the
formulations, so a centrifugation process would be appropriate for
the recovery of the particles.PLA and PVA concentrations are
important parameters affecting the
particle size of the formulations,[15,21] characterization
studies of the formulations prepared using polymers at different concentrations
were carried out. As a result of particle size and zeta potential
analysis studies of PLA/PVA nanoparticle formulations, it was decided
to perform surface and morphological analyses with all formulations
containing 1% seconder PVA, as a decrease in the particle size was
detected with an increase in seconder PVA (%), provided that the primer
PVA and PLA concentrations were kept constant (A3, A6, A9, B3, B6,
B9, C3, C6, C9, D3, D6, and D9).The images obtained as a result
of scanning of the PLA/PVA nanoparticle
formulations coated with gold palladium on the aluminum grid are shown
in Figure . In the
images obtained, the dimensions of the particles were compatible with
the Malvern Zeta Sizer results, the majority of them were spherical
in shape and had a smooth surface.The majority of the formulations
had properties close to ideal
in terms of stability and physicochemical properties. The QbD technique
provides a lot of advantages in terms of improved scientific understanding
of product and process, which allows for more regulatory flexibility
and control over the manufacturing process. In terms of complex design
and severe requirements for CQAs, using the QbD aspect for nanopharmaceutical
products has various advantages for maximizing product performance,
including particle size, zeta potential, drug loading capacity, in
vitro drug release profile, surface morphology characteristics, pharmacokinetic
performance, drug stability, and so forth. Therefore, QbD is increasingly
becoming a valuable, widely used technique in pharmaceutical product
development and manufacturing, and there are a number of studies in
QbD-based nanostructured drug delivery system research.[29,30]Therefore, in this study, the principles of QbD have been
applied
and experimental data were also evaluated within Modde Pro 12.1 to
enlighten the multivariate relationship between critical formulation
parameters and CQAs. Modde Pro 12.1 also processed optimization and
created a DS throughout the data.According to the model fitting
results demonstrated with the coefficient
plots,[12,31] increasing the seconder PVA amount shows
a significant effect on particle size reduction in accordance with
previous knowledge of studies, while other variables and their interactions
seem less effective (also with uncertainty), as seen in Figure .An optimized formulation
adjusted to reach the lowest particle
size was suggested as 1% primer PVA and 1% seconder PVA with 12.5%
PLA, which is the same as the D9 coded formulation. Within the study,
DS were also observed as representing the sum of the variable combinations
that lead to the desired CQA. As validation studies for DS show a
robust range for ingredients that formulation meets the requirement
for particle size were appointed. Considering the features, such as
the program used, redispersibility after centrifugation, preparation
efficiency, it was decided to continue with the D9 coded formulation.AFM or SEM based on imaging nanoparticles is considered a reference
technique for measuring the size of nanoparticles. In contrast to
microscopy-based techniques, sizing techniques such as dynamic light
scattering (DLS) are classified as indirect because they are the result
of a computation or modeling process in size measurement.[32] Furthermore, the AFM and SEM analyses corroborated
the DLS results, confirming the quality and homogeneity of the particles.The preparation efficiency of PLA/PVA nanoparticle formulation
(D9) was calculated as 65.38%.According to the stability studies,
all PLA/PVA nanoparticle formulations
were tested. It was stable and did not show a significant change in
particle size, distribution, and zeta potential under all three conditions
(p > 0.05).The zeta potential is an extremely
important concept for the stability
of nanoparticle suspensions due to electrostatic repulsion between
charged particles. As the zeta potential value increases in nanoparticle
formulations, the stability of colloidal dispersions is ensured. Nanoparticulate
formulations with a low zeta potential cannot maintain their stable
state. In such cases, these nanoparticulate formulations should be
stored in lyophilized form rather than liquid suspension and reconstituted
just before use.[33] The zeta potential value
can influence the nanosystems to undergo phagocytosis. Nanoparticles
with near-zero zeta potential undergo lower phagocytic uptake compared
to nanoparticles with a positive zeta potential. As the pH of PLA/PVA
nanoparticle formulations increases, carbonyl groups in PLA and hydroxyl
groups in PVA settle close to the nanoparticle surface, and negative
and high zeta potential values are measured.[34] However, when the pH of PLA/PVA nanoparticles is around 7, the zeta
potential value decreases and approaches zero. In our studies, the
zeta potential value of almost all nanoparticle formulations was determined
to be close to zero. Accordingly, it was determined that the preparation
method was not effective on the zeta potential (p > 0.05).
Conclusions
In preformulation studies,
it is known that the preparation method
as well as the composition is effective on the physicochemical parameters
of the formulation. In this context, we examined the effects of emulsifying
devices, evaporation technique, and mechanical preparation methods,
such as centrifugation on the formulation with our controlled experiments.
After determining the ideal mechanical preparation method, we examined
the effect of the amount of primary and secondary emulsifiers, which
are the most effective factors in the double emulsification method.
PLA/PVA nanoparticles were successfully developed by double emulsification/solvent
evaporation method using a high-speed homogenizer device. To evaluate
the effect of formulation parameters on CQAs and to optimize formulation
variables by creating a DS, Modde 12.1 software was usefully applied
to build a mathematical model within the framework of the QbD approach.Adopting Qbd approach and using mathematical modeling programs
in the study, to develop a nanoparticle formulation and determining
the acceptable range for formulation variables to assure the required
quality attributes, has improved the efficiency of the developing
stage through increased product knowledge. This aspect within the
QbD framework has enabled us to make decisions based on scientific
and risk-based information while encouraging operational excellence.In conclusion, the developed formulation (12.5% PLA, 1% primer
and seconder PVA) has ideal properties to be used as a drug carrier
system, such as particle size (181.7 ± 2.194 nm, polydispersity
index (0.104 ± 0.049), zeta potential (−0.88 ± 0.45
mV), high preparation efficiency (65.38%), and long-term stability
up to 12 months.
Table 8
Initial, 1st, 3rd, 6th, and 12th Month
Particle Size (nm ± ss), PdI, and Zeta Potential (mV ± ss)
Results PLA/PVA Nanoparticles Placed in a 25 ± 5 °C Stability
Cabinet (Mean ± SD)
Authors: J Carolina Visser; Willem M C Dohmen; Wouter L J Hinrichs; Jörg Breitkreutz; Henderik W Frijlink; Herman J Woerdenbag Journal: Int J Pharm Date: 2015-03-05 Impact factor: 5.875
Authors: Sara Rhaissa Rezende do Reis; Edward Helal-Neto; Aline Oliveira da Silva de Barros; Suyene Rocha Pinto; Filipe Leal Portilho; Luciana Betzler de Oliveira Siqueira; Luciana Magalhães Rebelo Alencar; Si Amar Dahoumane; Frank Alexis; Eduardo Ricci-Junior; Ralph Santos-Oliveira Journal: Pharm Res Date: 2021-02-18 Impact factor: 4.200
Figure 1
Figure 2
Figure 5
Figure 6
Figure 7
Figure 8
Figure 9
Figure 10