Accepted Manuscript Title: Formulation and process optimization of naproxen nanosuspensions stabilized by hydroxy propyl methyl cellulose Author: Bibaswan Mishra Jagannath Sahoo Prasanna Kumar Dixit PII: DOI: Reference:
S0144-8617(15)00290-8 http://dx.doi.org/doi:10.1016/j.carbpol.2015.03.077 CARP 9819
To appear in: Received date: Revised date: Accepted date:
4-2-2015 19-3-2015 25-3-2015
Please cite this article as: Mishra, B., Sahoo, J., and Dixit, P. K.,Formulation and process optimization of naproxen nanosuspensions stabilized by hydroxy propyl methyl cellulose, Carbohydrate Polymers (2015), http://dx.doi.org/10.1016/j.carbpol.2015.03.077 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
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TITLE PAGE
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Formulation and process optimization of naproxen nanosuspensions stabilized by hydroxy propyl methyl cellulose
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Gayatri College of pharmacy, Sambalpur, Odisha 768200, India
Shri Ram Murti Smarak College of Engg. and Technology (Pharmacy), Bareilly, U.P. 243202, India
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Department of Zoology, Berhampur University, Ganjam, Odisha 760007,India
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E-mail address of authors:
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Bibaswan Mishra – [email protected]
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Jagannath Sahoo - [email protected]
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Prasanna Kumar Dixit- [email protected]
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Bibaswan Mishraa*, Jagannath Sahoob, Prasanna Kumar Dixitc
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* Corresponding author.
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Bibaswan Mishra
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Gayatri College of pharmacy, Sambalpur, 768200, Odisha, India
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Ph no- +91 98613 38249
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E-mail address: [email protected]
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In present study precipitation-ultrasonication was used to obtain nanosuspensions of poorly
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water-soluble drug, Naproxen (NPX). We investigated the effects of HPMC concentration (X1)
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and time of ultrasonication (X2) on imperative attributes like mean particle size (Y1), % drug
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content (Y2), and time required to 90% drug release (Y3) via 32 factorial design. The morphology
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of nanosuspensions was found almost spherical by SEM observation. DSC and XRD studies
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suggested slight crystalline change in drug. FT-IR revealed lack of significant interactions
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between NPX and HPMC. Nanosuspensions of mean particle size 530.55 nm was achieved.
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Dissolution rate obtained from all nanosuspensions were markedly higher than pure NPX.
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Response surface methodology and optimized polynomial equations were used to select optimal
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formulation i.e. 1.36 % W/V of X1 and 13.9 mins of X2 to get desired response Y1; 727.97 nm,
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Y2; 95.59 % and Y3; 8.67 mins that were in reasonable agreement with observed value.
Formulation and process optimization of naproxen nanosuspensions stabilized by hydroxy propyl methyl cellulose
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Abstract
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Key words: Naproxen; HPMC; Nanosuspensions; Ultrasonication; Response surface
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methodology.
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Formulation and process optimization of naproxen nanosuspensions stabilized by hydroxy propyl methyl cellulose
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1. Introduction
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In the pharmaceutical drug delivery system poor solubility of drugs is a major challenge due to
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non optimal physicochemical and pharmaceutical properties. About 40% of active
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pharmaceutical ingredients (API) discovered through different drug discovery program have
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dissolution related bioavailability problem (Lipinski, 2002). Such drugs show variable
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bioavailability and very erratic absorption profile. Low dissolution velocity of such drugs in both
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water and organic media prevents to formulate intravascular preparations for getting sufficiently
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high blood level.
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Many approaches have been developed to overcome such issues like inclusion complexes with
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B-cyclodextrin (Yang et al., 2014), co crystal (Schultheiss & Newman, 2009), salt formation
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(Serajuddin, 2007), pH micro environment modifier (Stephenson, Aburub, & Woods, 2011), Self
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emulsified drug delivery system (SEDDS) (Neslihan & Benita 2004), solid lipid nanoparticles
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(Muchow, Maincent, & Müller, 2008), liposome (Fenske, Chonn, & Cullis, 2008),
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microemulsion (Stephenson, Aburub, & Woods, 2011), and so on. Because of various obstacles
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such as poor drug loading, poor stability, high economical cost, complex manufacturing
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approaches and high toxicity, none of these techniques can be applied to all categories of drug.
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Nanosuspension refers to the reduction in drug particle size down to submicron range suitably
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stabilized by polymer and/or surfactants (Müller, Peters, Becker, & Kruss, 1995a.; Müller,
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Becker, Kruss, & Peters, 1998). The contributing role of nanosized drugs to the dissolution
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velocity is described by Nernst Brunner equation and increase in solubility illustrated by
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Ostwald-Freundlich equation (Brough & Williams III 2013). Nanosuspensions are advantageous
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in achieving quick onset of action, reduce fed/fasted state variability, improved dose
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proportionality, and improve the saturation solubility and hence enhancing bioavailability. The
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methods of producing nanosuspension are of two types; ‘bottom up’ and ‘top down’. Top down
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approaches such as high pressure homogenization (Xiong et al., 2008) and media milling
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(Vander et al., 2007) based on disintegration approach from large particle, microparticles to
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nanoparticles and bottom up techniques include microprecipitation, microemulsion, melt
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emulsification and so on, based on assembling method from molecules to nano sized particle
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have been successfully developed to obtain stable nanosuspension (Grau, Kayser, & Müller,
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2000).
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Antisolvent precipitation has been successfully employed as an effective and simple technique to
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get stable nanosuspension of nitrendipine (Xia et al., 2010). In this method the drug was
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dissolved in a suitable solvent mixture which was then incorporated in to a precooled antisolvent
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solution containing stabilizer. The antisolvent solution must be maintained at low temperature to
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restrict the formation of larger particle due to Ostwald ripening which is a function of rapid
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disolvation technique. A number of stabilizers such as hydroxy propyl methyl cellulose & methyl
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cellulose (Douroumis & Fahr, 2007), Povidone (Lindfors, Forssén, Westergren, & Olsson, 2008),
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and poly vinyl alcohol (Xia et al., 2010) in aqueous solution showed a tremendous result in
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stabilizing the formulation as a result of hydrogen bonding to the hydrophobic core of drug.
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Naproxen (NPX), a propionic acid derivative, is used extensively in inflammatory diseases such
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as acute gout and rheumatoid arthritis. The absorption of drugs with poor aqueous solubility like
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NPX is dissolution rate limited and therefore, they exhibit poor bioavailability resulting in
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multiple dosing of drug as well as fluctuation in blood concentrations (Correa, Scarpa, Franzini,
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& Oliveira, 2005; Guo et al., 2010). The oral administration of the drug is the most common
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route of delivery due to convenience and patient compliance which make it more effective when
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compared with other routes of administration. But the important problem associated in obtaining
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a solid oral dosage forms for NPX has been its poor aqueous solubility and wettability.
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Pharmaceutical formulators often face the challenge of finding the appropriate combination of
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process variables to obtain a product with desired quality attributes. However, statistical design
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of experiment tools such as factorial designs can be used to analyze and understand these
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variables to get optimum properties. All factors are studied in all possible combinations with
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minimum experimentation and time to estimate the influence of individual process variables.
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This optimization technique encompasses the generation of model equations for the investigated
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responses over the experimental design to obtain the optimum formulation(s) (Acharya, Patra, &
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Pani, 2014).
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In the present study precipitation ultrasonication method has been employed to develop and
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fabricate nanosuspensions of naproxen. The effect of process variables i.e., stabilizer
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concentration and time length of sonication (two independent factors) on mean particle size, %
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drug content and time required to 90% of drug release (t90) (three dependent variables) were
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systematically investigated through response surface methodology (RSM) via 32 factorial design.
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The dependent variables are so chosen in order to get enhanced bioavailability with minimum
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dose. The in-vitro dissolution study was considered to access the solubility enhancement of drug
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in different formulations.
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2. Materials
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Naproxen (mean particle size; 67.32 µm) was obtained as a gift sample from Dr. Reddy’s
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Laboratories Ltd. (Hyderabad, Andhra Pradesh, India). Hydroxy Propyl Methyl Cellulose
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(Methocel K4M) was procured from Corolcon Asia Pvt. Ltd. and Polyethylene Glycol 200 (PEG
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200) and acetone were purchased from Ranbaxy fine chemicals Ltd., New Delhi, India. All the
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reagents were of analytical grade and used without further purification.
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3. Methods
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3.1. Preparation of naproxen nanosuspensions
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Nanosuspensions of naproxen (NPXN) stabilized by HPMC were prepared by controlled
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precipitation-ultrasonication method. NPX (50 mg) was dissolved in 2mL of solvent mixture of
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acetone and PEG 200 (1:1, V/V). Antisolvents containing different percentage of HPMC (0.5%,
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1% and 1.5%, W/V) were prepared with water. Both solutions are filtered through 0.45 micron
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filter (Nylon 66 membrane filter). HPMC solution of 40mL was placed in a bath ultrasonicator
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(Sonica, Spincotech Pvt. Ltd. 2200 MH, 305 W, Soltech Sri Milano, Italy) and the water inside
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the ultrasonicator was precooled and maintained at temperature of 3°C. The organic drug
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solution was quickly incorporated to the later with the help of a 22 gauze syringe after the
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application of ultrasonic wave. Ultrasonication was applied for a time period of 5, 10 and 15
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mins for each combination of the antisolvent solutions. The obtained nanosuspension were
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subjected to cooling ultracentrifuge (C-24 BL, Remi, Mumbai, India) at 20 000 rpm for 40 mins.
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The supernatant was discarded and replaced by same quantity of fresh antisolvent. The solid
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residue is redispersed by the application of sonication. The study design is presented in Table-1.
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Table-1. 32 full factorial design with observed response values of Naproxen nanosuspensions.
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R.E (%)
Avg. drug content (%)
R.E (%)
Avg. time to 90% drug release (mins) Obs. Pred. value value
R.E (%)
Z.P. (mV)
Batch code
HPMC (%W/V)
U. Sonic time (Mins)
NPXN-1
0.5(-1)
5(-1)
2519.61
2527.99
0.33
95.98
95.58
-0.42
23.9
23.73
-0.71
-32.56
NPXN-2
1.0(0)
5(-1)
1372.12
1412.88
2.88
96.32
96.58
0.26
13.92
13.84
-0.55
-29.94
NPXN-3
1.5(1)
5(-1)
2178.78
2184.61
0.27
97.89
97.57
-0.33
19.5
19.71
1.08
-35.77
NPXN-4
0.5(-1)
10(0)
2311.35
2264.17
-2.08
93.11
93.63
0.56
21.68
22.17
2.20
-32.49
NPXN-5
1.0(0)
10(0)
ed
Mean Particle size(nm)
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982.42
961.69
-2.16
95.11
95.21
0.11
11.77
11.47
-2.58
-29.96
NPXN-6
1.5(1)
10(0)
1588.13
1546.05
-2.72
96.44
96.79
0.36
16.76
16.57
-1.16
-31.85
NPXN-7
0.5(-1)
15(1)
1961.58
2000.35
1.94
91.79
91.68
-0.12
17.18
16.82
-2.15
-34.56
NPXN-8
1.0(0)
15(1)
530.55
510.5
-3.93
94.17
93.85
-0.35
5.27
5.35
1.50
-33.09
NPXN-9
1.5(1)
15(1)
871.27
907.49
3.99
96.04
96.01
-0.03
9.68
9.67
-0.12
-31.1
NPXN-O
1.36
13.9
757.16
727.97
-4.01
94.91
95.59
0.71
8.89
8.67
-2.54
-34.73
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Obs. value
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Pred. value
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Obs. value
Pred. value
Note: NPXN, Naproxen Nanosuspensions; NPXN -O, Optimized batch; HPMC, Hydroxy Propyl Methyl Cellulose; U. Sonic Time, Ultasonication Time; Obs. Value, Observed Value; Pred. Value, Predicted Value; R.E, Relative Error; Z.P, Zeta Potential
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3.2. Isolation of dried nanosuspensions.
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The solidified state is preferred as compared with aqueous nanosuspensions because aggregation
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and other instability factors are significantly decreased. Nanosuspension of 20 mL was filled in
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flint colored vials with rubber stoppers and frozen using deep freezer at −75 °C for 24 hr. These
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frozen semisolids were freeze-dried using lyophilizer (Virtis benchtop, Bombay, India) at a
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vacuum degree of 200 Pascal for 36 hr to produce free flowing dry powder.
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3.3. Characterization of naproxen nanosuspensions
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3.3.1. Mean Particle size, zeta-potential and particle morphology
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The particle size and Zeta-potential of nanosuspensions were measured using dynamic light
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scattering zetasizer (Zetasizer Nano ZS 90, Malvern Ltd., UK). All formulations were adequately
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diluted to obtained final drug particle concentration of 1 mg/mL and introduced into the
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electrophoretic cell. In addition, nanosuspensions were also stored to assess the short term and
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accelerated stability and their particle size were analyzed. The surface topography was studied
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using scanning electron microscope (JEOL, JSM-6390, Tokyo, Japan). Morphological
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examination of surface was performed at 3000X and 10000X magnifications.
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3.3.2. Differential Scanning Calorimetry
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NPX pure drug and freeze dried NPXN were analyzed by differential scanning calorimetry
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(DSC-60, Shimadzu Co., Japan) at a heating rate of 10°C /min from 30 to 300°C to study the
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phase transition. This study was done under dry nitrogen atmosphere using Al2O3 as a reference.
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3.3.3. Fourier transform infrared spectroscopy (FT-IR)
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The molecular structures of the samples were recorded through obtaining FT-IR spectra using
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FT-IR spectrometer (Shimadzu Corporation, Japan). The IR spectra were obtained in a KBr disc.
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Pure drug, HPMC and nanosuspensions were mixed with potassium bromide separately. Scans
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were obtained at a resolution of 2 cm−1, from 4500 to 400 cm−1.
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3.3.4. X-ray diffraction analysis
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The pure NPX, HPMC and freeze dried NPXN were analyzed by X-ray diffractometer (DX-
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2700, China) in symmetrical reflection mode using Cu Kα radiation generated at 30mA and 40
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kV. The scanning speed was 10°/min from 0° to 55°of 2θ.
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3.4. Drug content study
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Drug equivalent to 10 mg of NPX was dissolved in 50 ml ethanol. The samples were stirred for
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4h and subsequently centrifuged at 6000 rpm for 10 min. The contents of NPX in sample were
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analyzed after suitable dilution by double beam UV spectrophotometer (model UV-1700,
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Shimadzu, Japan) at λmax272 nm. The procedure was performed in triplicate and the averages
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were calculated (Adibkia et al., 2013). Drug content was calculated by the following equation:
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Drug content (%) = (Observed drug content/Theoretical drug content) ×100
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3.5. Dissolution study
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In vitro release tests were performed for the prepared nanosuspension as well as pure NPX. The
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study was performed in 900 mL of hydrochloric acid solution (pH 3) using USP apparatus II
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(TDT-08 L, Electrolab, Mumbai, India) with constant temperature maintained at 37 ± 0.5°C and
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50 rpm. An aliquot of 5 mL was withdrawn at various time intervals and passed through a 0.1µm
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syringe filter (Whatman Ltd, Middlesex, UK). The prewarmed fresh dissolution medium was
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replaced immediately. The contents of NPX in sample were analyzed by double beam UV
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spectrophotometer (model UV-1700, Shimadzu, Japan) at λmax 272 nm (The United States
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Pharmacopeia, 2011). Then the corresponding concentrations were determined from the standard
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curve of NPX prepared in hydrochloric acid solution (pH 3) at λmax 272nm. The mean values
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were calculated from 3 replicates. The cumulative % of drug released as a function of time was
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plotted as a measure of dissolution velocity.
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3.6. Experimental design and optimization
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A 32 randomized full factorial design was used to optimize the variables in the present study. In
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this design, 2 factors: percentages of HPMC and time length of ultrasonication were evaluated,
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each at 3 levels: low, medium and high (Table-1) and experimental trials were performed at all 9
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possible combinations as depicted (Acharya et al., 2014). Various percentage of HPMC (X1)
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such as 0.5%, 1% and 1.5% W/V, and time length of ultrasonication (X2), such as 5, 10, and 15
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mins were selected as independent variables. Mean particle size (Y1), percentage drug content
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(Y2) and t90 (Y3) were selected as dependent variables. Data obtained from all formulations were
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analyzed using Design Expert software (Stat-Ease Inc., Minneapolis, Minnesota) and were used
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to generate the study design and the response surface plots. The matrix of the design including
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investigated factors and responses are shown in Table-1. Polynomial models, including linear,
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interaction and quadratic terms were generated for all the response variables using the software.
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Design Expert software provides the best fitting model was selected based on comparisons of
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several statistical parameters, including the regression coefficient (R2), coefficient of variation
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(CV), and adjusted regression coefficient (adj. R2). To identify significant effects of factors on
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response regression coefficients, analysis of variance (ANOVA) was used by calculating the F
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test and P values. For optimization, the mathematical model equation involving independent
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variables and their interactions for various measured responses generated by 32 factorial design
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is:
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Y = b0 + b1X1 + b2X2 + b12X1X2 + b11X12 + b22X22
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Where Y is the dependent variable, b0 is the arithmetic mean response of the 9 runs, and bi is the
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estimated coefficient for the factor Xi. The main effects (X1and X2), the interaction terms (X1X2),
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and the polynomial terms (X12and X22) represent the average result of changing one factor at a
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time from its low to high value, how the response changes when two factors are simultaneously
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changed and non-linearity respectively. Response surface plots are used to elucidate the
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relationship between the dependent and independent variables. Subsequently, a numerical
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optimization technique using the desirability approach and a graphical optimization technique
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using overlay plots were used to generate new formulations with the desired attributes.
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3.7. Validation of the experimental design
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To validate the chosen experimental design, the experimental observed values of the responses
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were quantitatively compared with predicted values and the relative error (%) was calculated
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using the following equation:
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Relative error (%) = {(Predicted value − Experiment value) / Predicted value} × 100
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3.8. Stability testing
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Stability is the first requisite for nanosuspension based product to be a commercial drug product.
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Both short term and long term stress testing were investigated to ensure the stability of the
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prepared formulation during storage.
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3.8.1. Short-term physical stability test
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NPXN-8 was stored at 25°C for up to 3 weeks. The nanosuspensions were kept in a 10 mL
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closed glass vial. At the predetermined times, aliquots were taken and subjected to particle size
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analysis as described before (Yao et al., 2014).
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3.8.2. Long term accelerated stability test
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To ensure the long term stability, NPXN-8 was tested during storage (40°C, RH 75%). Samples
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were sealed tightly in 10 mL closed glass vial and the stability was evaluated for the increase in
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particle size after 1, 3 and 6 months of storage (Yao et al., 2014).
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4. Result and discussion
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4.1. Particle morphology
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To characterize the surface morphology of nanosuspension formulations, optical microscopy
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(Olympus, CH2 model) of pure drug was compared with SEM images, taken directly after
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preparation, as depicted in Figure-1. The micrographs clearly showed the great differences
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between NPX raw crystal and nanosuspensions. The former were very large and irregular
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(Figure-1.a), while in nanosuspension, the particle size reduced significantly and found to be
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spherical in shape perhaps because the particles were coated with a HPMC polymeric layer
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(Figure-1.b and c.).
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Figure-1. Optical microscopic photograph of NPX crystal (a); SEM of NPX
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nanosuspensions (b and c). 13 Page 13 of 33
4.2. Differential scanning calorimetry
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In order to determine, whether amorphization had occurred at particle surfaces and to explore
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potential transformations of the structure, DSC analysis was performed on the freeze dried
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nanosuspension formulations (Figure-2.a). DSC of pure naproxen displayed single sharp
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endothermic fusion peak at 152.7°C, which is corresponding to the melting point of drug. In
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order to further confirm the physical state, DSC of NPXN-8 and NPXN-9 were also performed to
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analyze nanosuspensions. The DSC spectra of nanosuspensions also exhibited endothermic
263
melting peak at 151.9°C and 152.3°C respectively but with lower intensity which could be
264
explained by lower amount of NPX in nanosuspensions comparing to pure NPX. In formulations
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with high ratio of polymers, lower intensity is as a result of dilution effect of the polymers
266
(Cafaggi et al., 2008). The study inferred that there was no interaction between drug and
267
excipients (Oguchi, Sasaki, Hara, Tozuka, &Yamamoto, 2003).
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4.3. X-ray diffraction
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X-ray diffraction has been used to analyze potential changes in the inner structure of NPX
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crystals. XRD findings, as shown in Figure-2.b, were in good agreement with the DSC results.
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Nanosuspension showed distinctive patterns of peaks that were consistent with the peak pattern
272
of the NPX raw crystal. The height of the peaks in the nanosuspension demonstrated the
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reduction in magnitude of peaks due to the dilution of drug in the inner core of stabilizer and a
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decrease of NPX crystallinity in nanosuspension (Adibkia et al., 2013). During the addition of
275
the anti-solvent, the newly formed crystal nuclei are most likely amorphous (Lindfors et al.,
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2006a) but it increases the bulk drug concentration and facilitates particle growth by Ostwald
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ripening (Lindfors et al., 2006b).
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4.4. Fourier transform infrared spectroscopy (FT-IR)
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FT-IR studies were done to find out the possible intermolecular interactions between the NPX
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and HPMC. The characteristic peaks of NPX, HPMC and nanosuspensions are depicted in
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Figure-2.c. Absorption peaks of 1155 cm−1and 1174 cm−1 are correlated to etheric bonds and
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peaks of 1724 cm−1 and 1681 cm−1 are related to the carboxylic acid bond and benzene ring,
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respectively. Absence of any other new peaks and also no differences in the positions of the
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absorption bands in the nanosuspensions, indicate the lack of significant interactions between
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NPX and HPMC.
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Figure-2. DSC thermograms of the original NPX powder and NPX nanosuspensions (a); X-
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ray diffractograms of the original NPX powder, HPMC, and NPX nanosuspensions (b)
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and FTIR of original NPX powder, HPMC, and NPX nanosuspensions (c). 16 Page 16 of 33
4.5. Analysis of data and optimization of design
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As ‘stabilizer concentration’ and ‘time length of ultrasonication’ are independent to each other
292
and controlled in experiments, both were considered as independent variable in this study. Mean
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particle size, % drug content, and time required to 90% drug release (t90) obtained were
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considered as dependent variables due to their significant contribution in formulation
295
development. The software provided suitable polynomial model equations involving individual
296
main factors and interaction factors after fitting these data. The co-efficients in the optimized
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model equations relating Y1, Y2 and Y3 as responses are given in (Table-2). The results of
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ANOVA, as shown in table-2, indicated that all models were significant (p < 0.05) for all
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response parameters investigated. Model simplification was carried out by eliminating non-
300
significant terms (p > 0.05) in polynomial equations (Nayak & Pal, 2011).
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Co-efficient value
df
Sum square
Mean square
F-Value
p-value Prob > F
961.70 -359.06 -451.19 -187.37 943.42
4 1 1 1 1
3915477.17 773544.50 1221407.43 140430.07 1780095.17
978869.29 773544.50 1221407.43 140430.07 1780095.17
416.14 328.85 519.25 59.70 756.76
< 0.0001 0.0001 < 0.0001 0.0015 0.0001
3
27.56
9.19
54.12
0.0003
1 1 1
15.01 11.18 1.37
15.01 11.18 1.37
88.42 65.86 8.06
0.0002 0.0005 0.0363
5 1 1 1 1 1
283.57 47.15 105.76 2.40 121.58 6.69
56.71 47.15 105.76 2.40 121.58 6.69
325.98 271.02 607.86 13.81 698.79 38.43
0.0003 0.0005 0.0001 0.0339 0.0001 0.0085
For Mean Particle Size Model X1 X2 X1X2 X12
95.21
X1 X2 X1X2
1.58 -1.37 0.59
ce pt
Model
ed
For Percent drug Content
us
Source
cr
Table-2. Analysis of variance table for dependent variables from full factorial design.
M an
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For time to 90% drug release
11.54 -2.80 -4.20 -0.78 7.80 -1.83
Ac
Model X1 X2 X1X2 X12 X22 312 313
18 Page 18 of 33
4.5.1 Effect of independent factors on Mean particle size and Zeta potential
315
Mean Particle sizes and Zeta potentials of all the formulations were depicted in Table-1. The
316
relationship between the formulation ingredients (independent variables) and dependent
317
variables) was elucidated using response surface plots presented in Figure-3.a for Y1. The effect
318
of X1 and X2 and their interaction on Y1 by fixing one factor at constant level was determined.
319
As seen in figure, at fixed levels of X2, Y1 was decreased when the amount of HPMC
320
concentration added was increased from 0.5 to 1.0 % W/V and was increased when the HPMC
321
concentration was increased from 1.0 to 1.5 % W/V. The decrease in particle size may be
322
attributed to the following reasons. As HPMC is a nonionic polymer, potential agglomeration
323
was less liable to occurred. Due to the presence of a hydrodynamic boundary layer surrounding
324
the nanosuspensions as well as adsorption of the polymer molecules on the growing crystal
325
faces, HPMC provides a steric hindrance to agglomeration and growth of nanosuspensions
326
(Raghavan, Trividic, Davis, & Hadgraft, 2001; Zimmermann et al., 2009). The drug-stabilizer
327
system can be explained on the basis of hydrogen bonding between the drug molecules and the
328
stabilizer with abundance of hydroxyl groups (Figure-4). Amongst all formulation NPXN-8
329
showed the least mean particle size i.e. 530.55 nm.
331 332
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330
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333 334 335 19 Page 19 of 33
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Figure-3. Three-dimensional response curve of mean particle size (a); % drug content (b);
338
and t90 (c).
20 Page 20 of 33
ip t cr us an
339
Figure-4. Molecular structures of Naproxen (a) and HPMC (b).
341
The increase in the particle size with increase in HPMC concentration can be explained as
342
follows. Enhance viscosity of the solution hinder the transmission of ultrasonic energy and
343
thereby obstruct the diffusion between the solvent and antisolvent during precipitation formation.
344
This resulted in the formation of larger particle due to Ostwald ripening. Moreover the
345
deposition of concentric layers of HPMC on the drug surface resulted in larger particle size.
346
However in formulations with 1.0 % W/V of HPMC concentration found to be the optimal value
347
that sufficiently cover the crystal surface and provide steric repulsion between crystals.
348
At low levels of X1, the Y1 was decreased from 2519.61 nm to 1961.58 nm as X2 was increasing
349
from 5 to 15 minutes. Similarly, at high levels of X1, Y1 was decreasing from 2178.78 nm to
350
871.27 nm when X2 was increasing from 5 to 15 minutes. The decrease in the particle size with
351
decrease in X2 can be attributed to (a) the increase time length of the erosion effect on the surface
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21 Page 21 of 33
of large crystal and crystal agglomerates, (b) the HPMC molecule get completely adsorbed onto
353
the crystal surface to provide steric hindrance.
354
If particles possess sufficient zeta potential to provide enough electric repulsion or steric
355
hindrance, particle aggregation is less likely to occur. It has to be noted that adsorption of a steric
356
stabilizer such as the HPMC in all the formulations in our study, leads to a reduction of the
357
measured zeta potential. This is because the adsorption layer of the HPMC on the drug surface
358
increases its distance to the plane of shear, at which the zeta potential is measured.
359
4.5.2. Effect of independent factors on % Drug content
360
Similar trend was observed for the effect of X1 and X2 and their interaction on Y2. As seen from
361
Figure-3.b, at fixed levels of X2, Y2 was increased when the amount of HPMC concentration
362
added (X1) was increasing from 0.5 to 1.0 % W/V. The increase in the percentage drug content
363
with increase in HPMC concentration can be ascribed to the formation of more concentric layers
364
of HPMC molecule on the drug surface that restricts the drug to diffuse back in to the bulk. At
365
fixed levels of X1, Y2 was decreased as X2 was increasing from 5 to 15 minutes. The decrease in
366
the particle size with decrease in X2 may be as follows. The insufficient time of ultrasonic energy
367
at lower value of X2 resulted in the incomplete adsorption of HPMC molecule on the newly
368
formed crystal nuclei as a result of agglomeration that occurred rapidly (Xia et al., 2010).
369
4.5.3. Effect of independent factors on t90
370
Dissolution profiles of NPX pure drug and nanosuspensions are presented in Figure-5. The slow
371
dissolution rate of NPX may be due to its large crystal size while the nanosuspensions exhibited
372
considerably faster dissolution rates which may be ascribed to the following reasons (a) high
373
hydrophilicity of the polymers bring about aggregation reduction, wettability improvement and
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22 Page 22 of 33
local solubilization by the carrier in the diffusion layer and thereby increasing in the dissolution
375
rate (Jalali et al., 2012; Tiong & Elkordy, 2009), (b) the crystallinity reduction in the NPX loaded
376
nanosuspensions prepared by HPMC as the amorphous form of a drug has a higher
377
thermodynamic activity than its crystalline form, leading to rapid dissolution of the drug (Paudel,
378
Worku, Meeus, Guns, & Van den, 2013; Mohammadi et al., 2010), (c) the reduced particle size
379
and accordingly elevated surface area could enhance the dissolution rate of NPX in the
380
formulation (Adibkia et al., 2013).
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Figure-5. Comparison of dissolution profiles of Nanosuspensions formulation with pure
384
Naproxen
385
As seen in figure-3.c, at fixed levels of X2, Y1 was decreased when the amount of HPMC
386
concentration added was increased from 0.5 to 1.0 % W/V and was increased when the HPMC
387
concentration was increased from 1.0 to 1.5 % W/V. The variation in the dissolution rate in
388
different formulations is attributed to variation in diffusion layer thickness due to gel formation 23 Page 23 of 33
effect of HPMC since the drug molecules were entrapped completely within the gel structure.
390
This effect was probably affected by hydrophilicity of HPMC in the higher drug-HPMC ratios.
391
Although, a direct relationship between the amount of stabilizer and NPX dissolution rate could
392
not be established from the dissolution profiles of the different nanosuspensions, but dissolution
393
rate obtained from all nanosuspension were much higher than the pure NPX.
394
To optimize all the responses with different targets, a multi-criteria decision approach, a
395
numerical optimization technique by the desirability and a graphical optimization technique by
396
the overlay plot was used (Figure- 6.a and 6.b). The optimized formulation was obtained by
397
applying constraints on independent variables and dependent responses. These constrains for
398
independent variable were X1; 0.5%, 1% and 1.5% W/V, and X2; 5, 10, and 15 mins and that of
399
dependant variable were: Y1; 530.55-1000 nm, Y2; 95- 97.89 % and Y3; 5.27-10 mins. The
400
recommended values of the independent variables were calculated by the Design Expert software
401
from the above plots which has the highest desirability near to 1.0. The optimum values of
402
selected variables obtained using Design Expert software were 1.36 % W/V of X1 and 13.9 min
403
of X2 to get the desired response Y1; 727.97 nm, Y2; 95.59 % and Y3; 8.67 mins in the final
404
composition of NPXN-O.
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24 Page 24 of 33
ip t cr us an M d te Ac ce p
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Figure-6. Optimization of nanosuspensions through desirability plot (a); and overlay plot
407
(b).
408
4.6. Evaluation and validation of the optimized formulation
25 Page 25 of 33
The statistically optimized formulation (NPXN-O) was prepared, evaluated and Y1, Y2, and Y3
410
were calculated to verify with the theoretical prediction. It was found that the observed value of
411
Y1 (757.16), Y2 (94.91) and Y3 (8.89) were in close agreement with the model predictions Y1
412
(727.97), Y2 (95.59) and Y3 (8.67) of in NPXN-O. The relative errors (%) between the predicted
413
and experimental values for each response were calculated and the values found to be within ±
414
5% (Table-1). The experimental values were in agreement with the predicted values confirming
415
the predictability and validity of the model.
416
4.7. Stability study
417
The representative diameters of the nanosuspensions were plotted as a function of the storage
418
time. It was found that the particle size of the NPXN-8 increased from 530.55 nm to 553.14 nm
419
after three week, and then they changed insignificantly over the subsequent period. The shift in
420
the particle size distribution to a higher range could be attributed to Oswald ripening. So it can be
421
concluded nanosuspensions were able to maintain the particle size during storage. In long term
422
stability testing, though the mean particle size of nanoparticles had a slight increasing trend from
423
530.55 to 562.69 during the test, it is still reasonable to believe the nanosuspension revealed high
424
stability within accelerated testing. It is well documented that HPMC have sufficient affinity for
425
the particle surface and possess an adequately high diffusion rate to cover the generated surface
426
rapidly with the application of ultrasonic energy. In addition, the amount of stabilizer was found
427
to be sufficient for full coverage of the particle surface in order to provide enough steric
428
repulsion between the particles (Gao, Zhang, & Chen, 2008).
429
5. Conclusion
430
This study discussed a positive application of statistical optimization techniques to predict the
431
compositions of a set of formulations that gives optimum quality attributes for the development
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26 Page 26 of 33
of naproxen nanosuspension of formulated by controlled diffusion-ultrasonication technique. The
433
optimized formulation fulfilled all the requirements of the target set and exhibited suitable values
434
of HPMC concentration and time length of ultrasonication. With the optimized process
435
parameters, nanosuspensions with diameter of about 757.16 nm could be obtained. There is
436
slight crystalline change found during nanosuspension preparation. Marked enhancement of
437
dissolution velocity with excellent % drug content was achieved by the nanoprecipitation
438
method. Hence the successful results of the present research establish the significant role of
439
HPMC as a stabilizer capable of maintain the particle size even after long term stability. It may
440
contribute in the development of an ideal pharmaceutical formulation with high drug content and
441
superior dissolution velocity to overcome the poor bioavailability of naproxen.
442
6. Acknowledgement
443
Authors are acknowledged the Director and Principal of Gayatri College of Pharmacy,
444
Sambalpur, Odisha for providing the research facilities.
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European Journal
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Highlights HPMC stabilized nanosuspensions have optimized to improve dissolution of Naproxen.
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Controlled precipitation-ultrasonication technique adopted.
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Mean particle size, % drug content, and dissolution time correlated with HPMC.
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Response surface methodology have adopted for formulation optimization.
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S0144-8617(15)00290-8 http://dx.doi.org/doi:10.1016/j.carbpol.2015.03.077 CARP 9819
To appear in: Received date: Revised date: Accepted date:
4-2-2015 19-3-2015 25-3-2015
Please cite this article as: Mishra, B., Sahoo, J., and Dixit, P. K.,Formulation and process optimization of naproxen nanosuspensions stabilized by hydroxy propyl methyl cellulose, Carbohydrate Polymers (2015), http://dx.doi.org/10.1016/j.carbpol.2015.03.077 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
1
TITLE PAGE
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Formulation and process optimization of naproxen nanosuspensions stabilized by hydroxy propyl methyl cellulose
a
6 b
Gayatri College of pharmacy, Sambalpur, Odisha 768200, India
Shri Ram Murti Smarak College of Engg. and Technology (Pharmacy), Bareilly, U.P. 243202, India
8 c
Department of Zoology, Berhampur University, Ganjam, Odisha 760007,India
us
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an
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E-mail address of authors:
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Bibaswan Mishra – [email protected]
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Jagannath Sahoo - [email protected]
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Prasanna Kumar Dixit- [email protected]
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Bibaswan Mishraa*, Jagannath Sahoob, Prasanna Kumar Dixitc
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* Corresponding author.
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Bibaswan Mishra
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Gayatri College of pharmacy, Sambalpur, 768200, Odisha, India
23
Ph no- +91 98613 38249
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E-mail address: [email protected]
1 Page 1 of 33
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In present study precipitation-ultrasonication was used to obtain nanosuspensions of poorly
31
water-soluble drug, Naproxen (NPX). We investigated the effects of HPMC concentration (X1)
32
and time of ultrasonication (X2) on imperative attributes like mean particle size (Y1), % drug
33
content (Y2), and time required to 90% drug release (Y3) via 32 factorial design. The morphology
34
of nanosuspensions was found almost spherical by SEM observation. DSC and XRD studies
35
suggested slight crystalline change in drug. FT-IR revealed lack of significant interactions
36
between NPX and HPMC. Nanosuspensions of mean particle size 530.55 nm was achieved.
37
Dissolution rate obtained from all nanosuspensions were markedly higher than pure NPX.
38
Response surface methodology and optimized polynomial equations were used to select optimal
39
formulation i.e. 1.36 % W/V of X1 and 13.9 mins of X2 to get desired response Y1; 727.97 nm,
40
Y2; 95.59 % and Y3; 8.67 mins that were in reasonable agreement with observed value.
Formulation and process optimization of naproxen nanosuspensions stabilized by hydroxy propyl methyl cellulose
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Abstract
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Key words: Naproxen; HPMC; Nanosuspensions; Ultrasonication; Response surface
43
methodology.
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Formulation and process optimization of naproxen nanosuspensions stabilized by hydroxy propyl methyl cellulose
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1. Introduction
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In the pharmaceutical drug delivery system poor solubility of drugs is a major challenge due to
59
non optimal physicochemical and pharmaceutical properties. About 40% of active
60
pharmaceutical ingredients (API) discovered through different drug discovery program have
61
dissolution related bioavailability problem (Lipinski, 2002). Such drugs show variable
62
bioavailability and very erratic absorption profile. Low dissolution velocity of such drugs in both
63
water and organic media prevents to formulate intravascular preparations for getting sufficiently
64
high blood level.
65
Many approaches have been developed to overcome such issues like inclusion complexes with
66
B-cyclodextrin (Yang et al., 2014), co crystal (Schultheiss & Newman, 2009), salt formation
67
(Serajuddin, 2007), pH micro environment modifier (Stephenson, Aburub, & Woods, 2011), Self
68
emulsified drug delivery system (SEDDS) (Neslihan & Benita 2004), solid lipid nanoparticles
69
(Muchow, Maincent, & Müller, 2008), liposome (Fenske, Chonn, & Cullis, 2008),
70
microemulsion (Stephenson, Aburub, & Woods, 2011), and so on. Because of various obstacles
71
such as poor drug loading, poor stability, high economical cost, complex manufacturing
72
approaches and high toxicity, none of these techniques can be applied to all categories of drug.
73
Nanosuspension refers to the reduction in drug particle size down to submicron range suitably
74
stabilized by polymer and/or surfactants (Müller, Peters, Becker, & Kruss, 1995a.; Müller,
75
Becker, Kruss, & Peters, 1998). The contributing role of nanosized drugs to the dissolution
76
velocity is described by Nernst Brunner equation and increase in solubility illustrated by
77
Ostwald-Freundlich equation (Brough & Williams III 2013). Nanosuspensions are advantageous
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3 Page 3 of 33
in achieving quick onset of action, reduce fed/fasted state variability, improved dose
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proportionality, and improve the saturation solubility and hence enhancing bioavailability. The
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methods of producing nanosuspension are of two types; ‘bottom up’ and ‘top down’. Top down
81
approaches such as high pressure homogenization (Xiong et al., 2008) and media milling
82
(Vander et al., 2007) based on disintegration approach from large particle, microparticles to
83
nanoparticles and bottom up techniques include microprecipitation, microemulsion, melt
84
emulsification and so on, based on assembling method from molecules to nano sized particle
85
have been successfully developed to obtain stable nanosuspension (Grau, Kayser, & Müller,
86
2000).
87
Antisolvent precipitation has been successfully employed as an effective and simple technique to
88
get stable nanosuspension of nitrendipine (Xia et al., 2010). In this method the drug was
89
dissolved in a suitable solvent mixture which was then incorporated in to a precooled antisolvent
90
solution containing stabilizer. The antisolvent solution must be maintained at low temperature to
91
restrict the formation of larger particle due to Ostwald ripening which is a function of rapid
92
disolvation technique. A number of stabilizers such as hydroxy propyl methyl cellulose & methyl
93
cellulose (Douroumis & Fahr, 2007), Povidone (Lindfors, Forssén, Westergren, & Olsson, 2008),
94
and poly vinyl alcohol (Xia et al., 2010) in aqueous solution showed a tremendous result in
95
stabilizing the formulation as a result of hydrogen bonding to the hydrophobic core of drug.
96
Naproxen (NPX), a propionic acid derivative, is used extensively in inflammatory diseases such
97
as acute gout and rheumatoid arthritis. The absorption of drugs with poor aqueous solubility like
98
NPX is dissolution rate limited and therefore, they exhibit poor bioavailability resulting in
99
multiple dosing of drug as well as fluctuation in blood concentrations (Correa, Scarpa, Franzini,
100
& Oliveira, 2005; Guo et al., 2010). The oral administration of the drug is the most common
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route of delivery due to convenience and patient compliance which make it more effective when
102
compared with other routes of administration. But the important problem associated in obtaining
103
a solid oral dosage forms for NPX has been its poor aqueous solubility and wettability.
104
Pharmaceutical formulators often face the challenge of finding the appropriate combination of
105
process variables to obtain a product with desired quality attributes. However, statistical design
106
of experiment tools such as factorial designs can be used to analyze and understand these
107
variables to get optimum properties. All factors are studied in all possible combinations with
108
minimum experimentation and time to estimate the influence of individual process variables.
109
This optimization technique encompasses the generation of model equations for the investigated
110
responses over the experimental design to obtain the optimum formulation(s) (Acharya, Patra, &
111
Pani, 2014).
112
In the present study precipitation ultrasonication method has been employed to develop and
113
fabricate nanosuspensions of naproxen. The effect of process variables i.e., stabilizer
114
concentration and time length of sonication (two independent factors) on mean particle size, %
115
drug content and time required to 90% of drug release (t90) (three dependent variables) were
116
systematically investigated through response surface methodology (RSM) via 32 factorial design.
117
The dependent variables are so chosen in order to get enhanced bioavailability with minimum
118
dose. The in-vitro dissolution study was considered to access the solubility enhancement of drug
119
in different formulations.
120
2. Materials
121
Naproxen (mean particle size; 67.32 µm) was obtained as a gift sample from Dr. Reddy’s
122
Laboratories Ltd. (Hyderabad, Andhra Pradesh, India). Hydroxy Propyl Methyl Cellulose
123
(Methocel K4M) was procured from Corolcon Asia Pvt. Ltd. and Polyethylene Glycol 200 (PEG
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200) and acetone were purchased from Ranbaxy fine chemicals Ltd., New Delhi, India. All the
125
reagents were of analytical grade and used without further purification.
126
3. Methods
127
3.1. Preparation of naproxen nanosuspensions
128
Nanosuspensions of naproxen (NPXN) stabilized by HPMC were prepared by controlled
129
precipitation-ultrasonication method. NPX (50 mg) was dissolved in 2mL of solvent mixture of
130
acetone and PEG 200 (1:1, V/V). Antisolvents containing different percentage of HPMC (0.5%,
131
1% and 1.5%, W/V) were prepared with water. Both solutions are filtered through 0.45 micron
132
filter (Nylon 66 membrane filter). HPMC solution of 40mL was placed in a bath ultrasonicator
133
(Sonica, Spincotech Pvt. Ltd. 2200 MH, 305 W, Soltech Sri Milano, Italy) and the water inside
134
the ultrasonicator was precooled and maintained at temperature of 3°C. The organic drug
135
solution was quickly incorporated to the later with the help of a 22 gauze syringe after the
136
application of ultrasonic wave. Ultrasonication was applied for a time period of 5, 10 and 15
137
mins for each combination of the antisolvent solutions. The obtained nanosuspension were
138
subjected to cooling ultracentrifuge (C-24 BL, Remi, Mumbai, India) at 20 000 rpm for 40 mins.
139
The supernatant was discarded and replaced by same quantity of fresh antisolvent. The solid
140
residue is redispersed by the application of sonication. The study design is presented in Table-1.
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Table-1. 32 full factorial design with observed response values of Naproxen nanosuspensions.
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148 149 150
R.E (%)
Avg. drug content (%)
R.E (%)
Avg. time to 90% drug release (mins) Obs. Pred. value value
R.E (%)
Z.P. (mV)
Batch code
HPMC (%W/V)
U. Sonic time (Mins)
NPXN-1
0.5(-1)
5(-1)
2519.61
2527.99
0.33
95.98
95.58
-0.42
23.9
23.73
-0.71
-32.56
NPXN-2
1.0(0)
5(-1)
1372.12
1412.88
2.88
96.32
96.58
0.26
13.92
13.84
-0.55
-29.94
NPXN-3
1.5(1)
5(-1)
2178.78
2184.61
0.27
97.89
97.57
-0.33
19.5
19.71
1.08
-35.77
NPXN-4
0.5(-1)
10(0)
2311.35
2264.17
-2.08
93.11
93.63
0.56
21.68
22.17
2.20
-32.49
NPXN-5
1.0(0)
10(0)
ed
Mean Particle size(nm)
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982.42
961.69
-2.16
95.11
95.21
0.11
11.77
11.47
-2.58
-29.96
NPXN-6
1.5(1)
10(0)
1588.13
1546.05
-2.72
96.44
96.79
0.36
16.76
16.57
-1.16
-31.85
NPXN-7
0.5(-1)
15(1)
1961.58
2000.35
1.94
91.79
91.68
-0.12
17.18
16.82
-2.15
-34.56
NPXN-8
1.0(0)
15(1)
530.55
510.5
-3.93
94.17
93.85
-0.35
5.27
5.35
1.50
-33.09
NPXN-9
1.5(1)
15(1)
871.27
907.49
3.99
96.04
96.01
-0.03
9.68
9.67
-0.12
-31.1
NPXN-O
1.36
13.9
757.16
727.97
-4.01
94.91
95.59
0.71
8.89
8.67
-2.54
-34.73
Ac
Obs. value
M an
Pred. value
ce pt
Obs. value
Pred. value
Note: NPXN, Naproxen Nanosuspensions; NPXN -O, Optimized batch; HPMC, Hydroxy Propyl Methyl Cellulose; U. Sonic Time, Ultasonication Time; Obs. Value, Observed Value; Pred. Value, Predicted Value; R.E, Relative Error; Z.P, Zeta Potential
151 7 Page 7 of 33
3.2. Isolation of dried nanosuspensions.
153
The solidified state is preferred as compared with aqueous nanosuspensions because aggregation
154
and other instability factors are significantly decreased. Nanosuspension of 20 mL was filled in
155
flint colored vials with rubber stoppers and frozen using deep freezer at −75 °C for 24 hr. These
156
frozen semisolids were freeze-dried using lyophilizer (Virtis benchtop, Bombay, India) at a
157
vacuum degree of 200 Pascal for 36 hr to produce free flowing dry powder.
158
3.3. Characterization of naproxen nanosuspensions
159
3.3.1. Mean Particle size, zeta-potential and particle morphology
160
The particle size and Zeta-potential of nanosuspensions were measured using dynamic light
161
scattering zetasizer (Zetasizer Nano ZS 90, Malvern Ltd., UK). All formulations were adequately
162
diluted to obtained final drug particle concentration of 1 mg/mL and introduced into the
163
electrophoretic cell. In addition, nanosuspensions were also stored to assess the short term and
164
accelerated stability and their particle size were analyzed. The surface topography was studied
165
using scanning electron microscope (JEOL, JSM-6390, Tokyo, Japan). Morphological
166
examination of surface was performed at 3000X and 10000X magnifications.
167
3.3.2. Differential Scanning Calorimetry
168
NPX pure drug and freeze dried NPXN were analyzed by differential scanning calorimetry
169
(DSC-60, Shimadzu Co., Japan) at a heating rate of 10°C /min from 30 to 300°C to study the
170
phase transition. This study was done under dry nitrogen atmosphere using Al2O3 as a reference.
171
3.3.3. Fourier transform infrared spectroscopy (FT-IR)
172
The molecular structures of the samples were recorded through obtaining FT-IR spectra using
173
FT-IR spectrometer (Shimadzu Corporation, Japan). The IR spectra were obtained in a KBr disc.
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Pure drug, HPMC and nanosuspensions were mixed with potassium bromide separately. Scans
175
were obtained at a resolution of 2 cm−1, from 4500 to 400 cm−1.
176
3.3.4. X-ray diffraction analysis
177
The pure NPX, HPMC and freeze dried NPXN were analyzed by X-ray diffractometer (DX-
178
2700, China) in symmetrical reflection mode using Cu Kα radiation generated at 30mA and 40
179
kV. The scanning speed was 10°/min from 0° to 55°of 2θ.
180
3.4. Drug content study
181
Drug equivalent to 10 mg of NPX was dissolved in 50 ml ethanol. The samples were stirred for
182
4h and subsequently centrifuged at 6000 rpm for 10 min. The contents of NPX in sample were
183
analyzed after suitable dilution by double beam UV spectrophotometer (model UV-1700,
184
Shimadzu, Japan) at λmax272 nm. The procedure was performed in triplicate and the averages
185
were calculated (Adibkia et al., 2013). Drug content was calculated by the following equation:
186
Drug content (%) = (Observed drug content/Theoretical drug content) ×100
187
3.5. Dissolution study
188
In vitro release tests were performed for the prepared nanosuspension as well as pure NPX. The
189
study was performed in 900 mL of hydrochloric acid solution (pH 3) using USP apparatus II
190
(TDT-08 L, Electrolab, Mumbai, India) with constant temperature maintained at 37 ± 0.5°C and
191
50 rpm. An aliquot of 5 mL was withdrawn at various time intervals and passed through a 0.1µm
192
syringe filter (Whatman Ltd, Middlesex, UK). The prewarmed fresh dissolution medium was
193
replaced immediately. The contents of NPX in sample were analyzed by double beam UV
194
spectrophotometer (model UV-1700, Shimadzu, Japan) at λmax 272 nm (The United States
195
Pharmacopeia, 2011). Then the corresponding concentrations were determined from the standard
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curve of NPX prepared in hydrochloric acid solution (pH 3) at λmax 272nm. The mean values
197
were calculated from 3 replicates. The cumulative % of drug released as a function of time was
198
plotted as a measure of dissolution velocity.
199
3.6. Experimental design and optimization
200
A 32 randomized full factorial design was used to optimize the variables in the present study. In
201
this design, 2 factors: percentages of HPMC and time length of ultrasonication were evaluated,
202
each at 3 levels: low, medium and high (Table-1) and experimental trials were performed at all 9
203
possible combinations as depicted (Acharya et al., 2014). Various percentage of HPMC (X1)
204
such as 0.5%, 1% and 1.5% W/V, and time length of ultrasonication (X2), such as 5, 10, and 15
205
mins were selected as independent variables. Mean particle size (Y1), percentage drug content
206
(Y2) and t90 (Y3) were selected as dependent variables. Data obtained from all formulations were
207
analyzed using Design Expert software (Stat-Ease Inc., Minneapolis, Minnesota) and were used
208
to generate the study design and the response surface plots. The matrix of the design including
209
investigated factors and responses are shown in Table-1. Polynomial models, including linear,
210
interaction and quadratic terms were generated for all the response variables using the software.
211
Design Expert software provides the best fitting model was selected based on comparisons of
212
several statistical parameters, including the regression coefficient (R2), coefficient of variation
213
(CV), and adjusted regression coefficient (adj. R2). To identify significant effects of factors on
214
response regression coefficients, analysis of variance (ANOVA) was used by calculating the F
215
test and P values. For optimization, the mathematical model equation involving independent
216
variables and their interactions for various measured responses generated by 32 factorial design
217
is:
218
Y = b0 + b1X1 + b2X2 + b12X1X2 + b11X12 + b22X22
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Where Y is the dependent variable, b0 is the arithmetic mean response of the 9 runs, and bi is the
220
estimated coefficient for the factor Xi. The main effects (X1and X2), the interaction terms (X1X2),
221
and the polynomial terms (X12and X22) represent the average result of changing one factor at a
222
time from its low to high value, how the response changes when two factors are simultaneously
223
changed and non-linearity respectively. Response surface plots are used to elucidate the
224
relationship between the dependent and independent variables. Subsequently, a numerical
225
optimization technique using the desirability approach and a graphical optimization technique
226
using overlay plots were used to generate new formulations with the desired attributes.
227
3.7. Validation of the experimental design
228
To validate the chosen experimental design, the experimental observed values of the responses
229
were quantitatively compared with predicted values and the relative error (%) was calculated
230
using the following equation:
231
Relative error (%) = {(Predicted value − Experiment value) / Predicted value} × 100
232
3.8. Stability testing
233
Stability is the first requisite for nanosuspension based product to be a commercial drug product.
234
Both short term and long term stress testing were investigated to ensure the stability of the
235
prepared formulation during storage.
236
3.8.1. Short-term physical stability test
237
NPXN-8 was stored at 25°C for up to 3 weeks. The nanosuspensions were kept in a 10 mL
238
closed glass vial. At the predetermined times, aliquots were taken and subjected to particle size
239
analysis as described before (Yao et al., 2014).
240
3.8.2. Long term accelerated stability test
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To ensure the long term stability, NPXN-8 was tested during storage (40°C, RH 75%). Samples
242
were sealed tightly in 10 mL closed glass vial and the stability was evaluated for the increase in
243
particle size after 1, 3 and 6 months of storage (Yao et al., 2014).
244
4. Result and discussion
245
4.1. Particle morphology
246
To characterize the surface morphology of nanosuspension formulations, optical microscopy
247
(Olympus, CH2 model) of pure drug was compared with SEM images, taken directly after
248
preparation, as depicted in Figure-1. The micrographs clearly showed the great differences
249
between NPX raw crystal and nanosuspensions. The former were very large and irregular
250
(Figure-1.a), while in nanosuspension, the particle size reduced significantly and found to be
251
spherical in shape perhaps because the particles were coated with a HPMC polymeric layer
252
(Figure-1.b and c.).
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Figure-1. Optical microscopic photograph of NPX crystal (a); SEM of NPX
255
nanosuspensions (b and c). 13 Page 13 of 33
4.2. Differential scanning calorimetry
257
In order to determine, whether amorphization had occurred at particle surfaces and to explore
258
potential transformations of the structure, DSC analysis was performed on the freeze dried
259
nanosuspension formulations (Figure-2.a). DSC of pure naproxen displayed single sharp
260
endothermic fusion peak at 152.7°C, which is corresponding to the melting point of drug. In
261
order to further confirm the physical state, DSC of NPXN-8 and NPXN-9 were also performed to
262
analyze nanosuspensions. The DSC spectra of nanosuspensions also exhibited endothermic
263
melting peak at 151.9°C and 152.3°C respectively but with lower intensity which could be
264
explained by lower amount of NPX in nanosuspensions comparing to pure NPX. In formulations
265
with high ratio of polymers, lower intensity is as a result of dilution effect of the polymers
266
(Cafaggi et al., 2008). The study inferred that there was no interaction between drug and
267
excipients (Oguchi, Sasaki, Hara, Tozuka, &Yamamoto, 2003).
268
4.3. X-ray diffraction
269
X-ray diffraction has been used to analyze potential changes in the inner structure of NPX
270
crystals. XRD findings, as shown in Figure-2.b, were in good agreement with the DSC results.
271
Nanosuspension showed distinctive patterns of peaks that were consistent with the peak pattern
272
of the NPX raw crystal. The height of the peaks in the nanosuspension demonstrated the
273
reduction in magnitude of peaks due to the dilution of drug in the inner core of stabilizer and a
274
decrease of NPX crystallinity in nanosuspension (Adibkia et al., 2013). During the addition of
275
the anti-solvent, the newly formed crystal nuclei are most likely amorphous (Lindfors et al.,
276
2006a) but it increases the bulk drug concentration and facilitates particle growth by Ostwald
277
ripening (Lindfors et al., 2006b).
278
4.4. Fourier transform infrared spectroscopy (FT-IR)
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FT-IR studies were done to find out the possible intermolecular interactions between the NPX
280
and HPMC. The characteristic peaks of NPX, HPMC and nanosuspensions are depicted in
281
Figure-2.c. Absorption peaks of 1155 cm−1and 1174 cm−1 are correlated to etheric bonds and
282
peaks of 1724 cm−1 and 1681 cm−1 are related to the carboxylic acid bond and benzene ring,
283
respectively. Absence of any other new peaks and also no differences in the positions of the
284
absorption bands in the nanosuspensions, indicate the lack of significant interactions between
285
NPX and HPMC.
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Figure-2. DSC thermograms of the original NPX powder and NPX nanosuspensions (a); X-
288
ray diffractograms of the original NPX powder, HPMC, and NPX nanosuspensions (b)
289
and FTIR of original NPX powder, HPMC, and NPX nanosuspensions (c). 16 Page 16 of 33
4.5. Analysis of data and optimization of design
291
As ‘stabilizer concentration’ and ‘time length of ultrasonication’ are independent to each other
292
and controlled in experiments, both were considered as independent variable in this study. Mean
293
particle size, % drug content, and time required to 90% drug release (t90) obtained were
294
considered as dependent variables due to their significant contribution in formulation
295
development. The software provided suitable polynomial model equations involving individual
296
main factors and interaction factors after fitting these data. The co-efficients in the optimized
297
model equations relating Y1, Y2 and Y3 as responses are given in (Table-2). The results of
298
ANOVA, as shown in table-2, indicated that all models were significant (p < 0.05) for all
299
response parameters investigated. Model simplification was carried out by eliminating non-
300
significant terms (p > 0.05) in polynomial equations (Nayak & Pal, 2011).
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304 305 306 307
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303
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Co-efficient value
df
Sum square
Mean square
F-Value
p-value Prob > F
961.70 -359.06 -451.19 -187.37 943.42
4 1 1 1 1
3915477.17 773544.50 1221407.43 140430.07 1780095.17
978869.29 773544.50 1221407.43 140430.07 1780095.17
416.14 328.85 519.25 59.70 756.76
< 0.0001 0.0001 < 0.0001 0.0015 0.0001
3
27.56
9.19
54.12
0.0003
1 1 1
15.01 11.18 1.37
15.01 11.18 1.37
88.42 65.86 8.06
0.0002 0.0005 0.0363
5 1 1 1 1 1
283.57 47.15 105.76 2.40 121.58 6.69
56.71 47.15 105.76 2.40 121.58 6.69
325.98 271.02 607.86 13.81 698.79 38.43
0.0003 0.0005 0.0001 0.0339 0.0001 0.0085
For Mean Particle Size Model X1 X2 X1X2 X12
95.21
X1 X2 X1X2
1.58 -1.37 0.59
ce pt
Model
ed
For Percent drug Content
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Source
cr
Table-2. Analysis of variance table for dependent variables from full factorial design.
M an
311
For time to 90% drug release
11.54 -2.80 -4.20 -0.78 7.80 -1.83
Ac
Model X1 X2 X1X2 X12 X22 312 313
18 Page 18 of 33
4.5.1 Effect of independent factors on Mean particle size and Zeta potential
315
Mean Particle sizes and Zeta potentials of all the formulations were depicted in Table-1. The
316
relationship between the formulation ingredients (independent variables) and dependent
317
variables) was elucidated using response surface plots presented in Figure-3.a for Y1. The effect
318
of X1 and X2 and their interaction on Y1 by fixing one factor at constant level was determined.
319
As seen in figure, at fixed levels of X2, Y1 was decreased when the amount of HPMC
320
concentration added was increased from 0.5 to 1.0 % W/V and was increased when the HPMC
321
concentration was increased from 1.0 to 1.5 % W/V. The decrease in particle size may be
322
attributed to the following reasons. As HPMC is a nonionic polymer, potential agglomeration
323
was less liable to occurred. Due to the presence of a hydrodynamic boundary layer surrounding
324
the nanosuspensions as well as adsorption of the polymer molecules on the growing crystal
325
faces, HPMC provides a steric hindrance to agglomeration and growth of nanosuspensions
326
(Raghavan, Trividic, Davis, & Hadgraft, 2001; Zimmermann et al., 2009). The drug-stabilizer
327
system can be explained on the basis of hydrogen bonding between the drug molecules and the
328
stabilizer with abundance of hydroxyl groups (Figure-4). Amongst all formulation NPXN-8
329
showed the least mean particle size i.e. 530.55 nm.
331 332
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314
333 334 335 19 Page 19 of 33
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Figure-3. Three-dimensional response curve of mean particle size (a); % drug content (b);
338
and t90 (c).
20 Page 20 of 33
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Figure-4. Molecular structures of Naproxen (a) and HPMC (b).
341
The increase in the particle size with increase in HPMC concentration can be explained as
342
follows. Enhance viscosity of the solution hinder the transmission of ultrasonic energy and
343
thereby obstruct the diffusion between the solvent and antisolvent during precipitation formation.
344
This resulted in the formation of larger particle due to Ostwald ripening. Moreover the
345
deposition of concentric layers of HPMC on the drug surface resulted in larger particle size.
346
However in formulations with 1.0 % W/V of HPMC concentration found to be the optimal value
347
that sufficiently cover the crystal surface and provide steric repulsion between crystals.
348
At low levels of X1, the Y1 was decreased from 2519.61 nm to 1961.58 nm as X2 was increasing
349
from 5 to 15 minutes. Similarly, at high levels of X1, Y1 was decreasing from 2178.78 nm to
350
871.27 nm when X2 was increasing from 5 to 15 minutes. The decrease in the particle size with
351
decrease in X2 can be attributed to (a) the increase time length of the erosion effect on the surface
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of large crystal and crystal agglomerates, (b) the HPMC molecule get completely adsorbed onto
353
the crystal surface to provide steric hindrance.
354
If particles possess sufficient zeta potential to provide enough electric repulsion or steric
355
hindrance, particle aggregation is less likely to occur. It has to be noted that adsorption of a steric
356
stabilizer such as the HPMC in all the formulations in our study, leads to a reduction of the
357
measured zeta potential. This is because the adsorption layer of the HPMC on the drug surface
358
increases its distance to the plane of shear, at which the zeta potential is measured.
359
4.5.2. Effect of independent factors on % Drug content
360
Similar trend was observed for the effect of X1 and X2 and their interaction on Y2. As seen from
361
Figure-3.b, at fixed levels of X2, Y2 was increased when the amount of HPMC concentration
362
added (X1) was increasing from 0.5 to 1.0 % W/V. The increase in the percentage drug content
363
with increase in HPMC concentration can be ascribed to the formation of more concentric layers
364
of HPMC molecule on the drug surface that restricts the drug to diffuse back in to the bulk. At
365
fixed levels of X1, Y2 was decreased as X2 was increasing from 5 to 15 minutes. The decrease in
366
the particle size with decrease in X2 may be as follows. The insufficient time of ultrasonic energy
367
at lower value of X2 resulted in the incomplete adsorption of HPMC molecule on the newly
368
formed crystal nuclei as a result of agglomeration that occurred rapidly (Xia et al., 2010).
369
4.5.3. Effect of independent factors on t90
370
Dissolution profiles of NPX pure drug and nanosuspensions are presented in Figure-5. The slow
371
dissolution rate of NPX may be due to its large crystal size while the nanosuspensions exhibited
372
considerably faster dissolution rates which may be ascribed to the following reasons (a) high
373
hydrophilicity of the polymers bring about aggregation reduction, wettability improvement and
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local solubilization by the carrier in the diffusion layer and thereby increasing in the dissolution
375
rate (Jalali et al., 2012; Tiong & Elkordy, 2009), (b) the crystallinity reduction in the NPX loaded
376
nanosuspensions prepared by HPMC as the amorphous form of a drug has a higher
377
thermodynamic activity than its crystalline form, leading to rapid dissolution of the drug (Paudel,
378
Worku, Meeus, Guns, & Van den, 2013; Mohammadi et al., 2010), (c) the reduced particle size
379
and accordingly elevated surface area could enhance the dissolution rate of NPX in the
380
formulation (Adibkia et al., 2013).
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Figure-5. Comparison of dissolution profiles of Nanosuspensions formulation with pure
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Naproxen
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As seen in figure-3.c, at fixed levels of X2, Y1 was decreased when the amount of HPMC
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concentration added was increased from 0.5 to 1.0 % W/V and was increased when the HPMC
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concentration was increased from 1.0 to 1.5 % W/V. The variation in the dissolution rate in
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different formulations is attributed to variation in diffusion layer thickness due to gel formation 23 Page 23 of 33
effect of HPMC since the drug molecules were entrapped completely within the gel structure.
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This effect was probably affected by hydrophilicity of HPMC in the higher drug-HPMC ratios.
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Although, a direct relationship between the amount of stabilizer and NPX dissolution rate could
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not be established from the dissolution profiles of the different nanosuspensions, but dissolution
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rate obtained from all nanosuspension were much higher than the pure NPX.
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To optimize all the responses with different targets, a multi-criteria decision approach, a
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numerical optimization technique by the desirability and a graphical optimization technique by
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the overlay plot was used (Figure- 6.a and 6.b). The optimized formulation was obtained by
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applying constraints on independent variables and dependent responses. These constrains for
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independent variable were X1; 0.5%, 1% and 1.5% W/V, and X2; 5, 10, and 15 mins and that of
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dependant variable were: Y1; 530.55-1000 nm, Y2; 95- 97.89 % and Y3; 5.27-10 mins. The
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recommended values of the independent variables were calculated by the Design Expert software
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from the above plots which has the highest desirability near to 1.0. The optimum values of
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selected variables obtained using Design Expert software were 1.36 % W/V of X1 and 13.9 min
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of X2 to get the desired response Y1; 727.97 nm, Y2; 95.59 % and Y3; 8.67 mins in the final
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composition of NPXN-O.
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Figure-6. Optimization of nanosuspensions through desirability plot (a); and overlay plot
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(b).
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4.6. Evaluation and validation of the optimized formulation
25 Page 25 of 33
The statistically optimized formulation (NPXN-O) was prepared, evaluated and Y1, Y2, and Y3
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were calculated to verify with the theoretical prediction. It was found that the observed value of
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Y1 (757.16), Y2 (94.91) and Y3 (8.89) were in close agreement with the model predictions Y1
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(727.97), Y2 (95.59) and Y3 (8.67) of in NPXN-O. The relative errors (%) between the predicted
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and experimental values for each response were calculated and the values found to be within ±
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5% (Table-1). The experimental values were in agreement with the predicted values confirming
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the predictability and validity of the model.
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4.7. Stability study
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The representative diameters of the nanosuspensions were plotted as a function of the storage
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time. It was found that the particle size of the NPXN-8 increased from 530.55 nm to 553.14 nm
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after three week, and then they changed insignificantly over the subsequent period. The shift in
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the particle size distribution to a higher range could be attributed to Oswald ripening. So it can be
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concluded nanosuspensions were able to maintain the particle size during storage. In long term
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stability testing, though the mean particle size of nanoparticles had a slight increasing trend from
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530.55 to 562.69 during the test, it is still reasonable to believe the nanosuspension revealed high
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stability within accelerated testing. It is well documented that HPMC have sufficient affinity for
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the particle surface and possess an adequately high diffusion rate to cover the generated surface
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rapidly with the application of ultrasonic energy. In addition, the amount of stabilizer was found
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to be sufficient for full coverage of the particle surface in order to provide enough steric
428
repulsion between the particles (Gao, Zhang, & Chen, 2008).
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5. Conclusion
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This study discussed a positive application of statistical optimization techniques to predict the
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compositions of a set of formulations that gives optimum quality attributes for the development
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26 Page 26 of 33
of naproxen nanosuspension of formulated by controlled diffusion-ultrasonication technique. The
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optimized formulation fulfilled all the requirements of the target set and exhibited suitable values
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of HPMC concentration and time length of ultrasonication. With the optimized process
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parameters, nanosuspensions with diameter of about 757.16 nm could be obtained. There is
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slight crystalline change found during nanosuspension preparation. Marked enhancement of
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dissolution velocity with excellent % drug content was achieved by the nanoprecipitation
438
method. Hence the successful results of the present research establish the significant role of
439
HPMC as a stabilizer capable of maintain the particle size even after long term stability. It may
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contribute in the development of an ideal pharmaceutical formulation with high drug content and
441
superior dissolution velocity to overcome the poor bioavailability of naproxen.
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6. Acknowledgement
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Authors are acknowledged the Director and Principal of Gayatri College of Pharmacy,
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Sambalpur, Odisha for providing the research facilities.
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Highlights HPMC stabilized nanosuspensions have optimized to improve dissolution of Naproxen.
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Controlled precipitation-ultrasonication technique adopted.
563
Mean particle size, % drug content, and dissolution time correlated with HPMC.
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Response surface methodology have adopted for formulation optimization.
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