Journal of Microencapsulation, 2012; 29(5): 445–454� 2012 Informa UK Ltd.ISSN 0265-2048 print/ISSN 1464-5246 onlineDOI: 10.3109/02652048.2012.655428

Inhalation of alendronate nanoparticles as dry powder inhaler forthe treatment of osteoporosis

Shaheen Sultana1, Sushma Talegaonkar1, Rashid Ali2, Gaurav Mittal2, Farhan Jalees Ahmad1

and Aseem Bhatnagar2

1Department of Pharmaceutics, Faculty of Pharmacy, Jamia Hamdard, Delhi, India and2Institute of Nuclear Medicine and Allied Sciences, Department of Nuclear Medicine, DRDO, Delhi, India

AbstractThe precipitation technique was used to prepare non-polymeric alendronate nanoparticles. The influenceof various formulation parameters on the average particle size was investigated and the effect of variousstabilizers (PVA, tween, chitosan, alginate, PEG, HPMC, poloxomers) was evaluated. The selection ofsurfactant was a key factor to produce particles with desired properties. Poloxomer F68 was found bestin achieving the minimum particle size and providing physical stability to the drug. On basis of preliminarytrials, a central composite design was employed to study the effect of independent variables, drugconcentration (X1), antisolvent volume (X2), stirring speed (X3), and stabilizer concentration (X4) on the aver-age particle size. The drug and stabilizer concentrations exhibited a more significant effect on a dependentvariable. The particle size varied from 62 to 803.3 nm depending upon the significant terms. The validationof optimization study, performed using six confirmatory runs, indicated very high degree of prognosticability of response surface methodology, with mean percentage error (�SD) as �2.32� 2.47. The minimumparticle size (44.11 nm) was predicted at 10 mg/ml drug concentration, 20 ml antisolvent volume, 925 rpmstirring speed, and 8.5% stabilizer concentration with 98.16% experimental validity. Respirable fraction foroptimized nanosized alendronate (43.85%� 0.52%) was significantly higher when compared with commer-cial alendronate (17.6� 0.32). Mass median aerodynamic diameter of designed particles was 3.45 mm withgeometric standard deviation of 2.10.

Keywords: central composite design, lutrol, precipitation, stabilizers

Introduction

Osteoporosis is a condition characterized by the loss of

normal density of bone resulting in the fragile bone. This

disorder of the skeleton weakens the bone causing an

increase in the risk for bone fracture (Chesnut et al.,

2004). Bisphosphonates and their pharmaceutically

acceptable salts are useful in the treatment and prevention

of bone diseases such as osteoporosis (Conte and Guarneri,

2004). Bisphosphonates are especially useful for the treat-

ment of urolithiasis, lessening the risk of non-vertebral

fractures in osteoporotic women, as a therapeutic agent

for hypercalcemia and Paget’s disease (Russell, 2007),

and are capable of inhibiting bone reabsorption.

Current treatment of the above conditions comprises

administration of a bisphosphonic acid through oral

route such as tablets and intravenous route. The benefits

are observed by its effect on bone density and bone mass.

However, oral and intravenous dosage forms have very low

bioavailability (51%). In addition, oral dosage forms of

bisphosphonates may result in gastric irritability.

Therefore, it would be desirable to administer bisphospho-

nates by a route that avoids gastrointestinal problems and

increases its bioavailability (Palelu, 2004).

Nanomedicine is an emerging field for pulmonary

administration for systemic as well as the local action

(Sham et al., 2004). The pulmonary route of administration

has been used for many years for the local treatment of

Address for correspondence: Shaheen Sultana, Department of Pharmaceutics, Faculty of Pharmacy, Jamia Hamdard, Delhi, India. Tel: þ91-9968099082.Fax: þ91-01122191082. E-mail: shaheen634@yahoo.co.uk

(Received 8 Sep 2011; accepted 19 Dec 2011)http://www.informahealthcare.com/mnc

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lung diseases. More recently, systemic drug absorption has

been investigated for the treatment of diabetes mellitus and

pain relief (Labiris and Dolovich, 2003), asthma (Hardy and

Chadawick, 2000), cystic fibrosis (Garcia-Contreras and

Hickey, 2002), lung cancer (Rao et al., 2003) and tubercu-

losis (Pandey and Khuller, 2005). Nanoparticles with mass

median aerodynamic diameter (MMAD) of 1–5 mm are

likely to achieve greater deposition in the lower respiratory

tract, while larger particles have impact on the throat and

oesophagus (Coates et al., 2007; Rogueda and Traini, 2007)

and avoid mucociliary and phagocytic clearance (Grenha

et al., 2005). The deep penetration of particles into smaller

airways correlates well with better clinical response (Chow

et al., 2007). Inhalation formulation for pulmonary drug

delivery includes nebulizers, metered dose inhaler (MDI)

and dry powder inhalers (DPI). Pulmonary drug delivery by

DPI is favoured due to its simplicity, high patient compli-

ance, high loading capacity and ease of use. DPI remains

challenging due to particle aggregation that leads to low

inhalation efficiency (5–15%) and inconsistent emitted

dose (Malcolmson and Embleton, 1998; Bosquillon et al.,

2001; Newman and Busse, 2002). Hence, a novel DPI

system is required for inhalation with excellent aerosoliza-

tion behaviour and higher respirable fraction that maxi-

mizes the drug delivery to lungs.

The DPI’s can be produced by various technologies such

as wet milling (Lee et al., 2005; Dai et al., 2007), microflui-

dization process (Verma et al., 2009b), homogenization

process (Biradar et al., 2006; Gao et al., 2008; Lou et al.,

2009; Sharma et al., 2009), spray drying (Hartwig and

Heike, 2004) and spray freeze drying (Mauludin et al.,

2009; Niwa et al., 2009). These processes required high

energy and produced unstable particles with broad particle

size distribution (Zhang et al., 2006). More recently, super-

critical fluid technologies involving rapid expansion of

supercritical solution (RESS), supercritical antisolvent

(SAS) and aerosol spray extraction system (ASES) to

create tremendous opportunities for nanoparticles forma-

tion (Dalvi et al., 2009; Hezave and Esmaeilzadeh, 2010;

Tozuka et al., 2010). The process is very sophisticated

and costly in generating particles with desired size and

morphology.

The precipitation method is most widely used for gen-

eration of nanosized particles (Dong et al., 2009; Fakes

et al., 2009; Verma et al., 2009a) in which precipitation

can be achieved by solvent, temperature, pH change or a

solvent evaporation process preferably in the presence of

crystal growth inhibitor. The process is simple and com-

mercially suitable for controlling particle size and

morphology.

Administration of bisphosphonates through inhalation

route to the respiratory tract directly produced much

higher bioavailability than oral or intravenous route

(Palelu, 2004). Previously published studies focused on

microparticles (Cruz et al., 2011) and PEG conjugated com-

plex (Katsumi et al., 2011) for pulmonary delivery of alen-

dronate. The current emphasis was to prepare novel

alendronate formulation for lung targeting that enhance

bioavailability and avoid gastrointestinal toxicity, thus

present commercial utility. The objectives of this study

relate to formulation development and evaluation of alen-

dronate nanoparticles as a dry powder inhaler for treat-

ment and prevention of osteoporosis in postmenopausal

women. The influence of some preparative variables such

as drug concentration, concentration of suitable stabilizer

(alone or in combination) and antisolvent volume have

been investigated in order to control and optimize the pro-

cess. A central composite design was employed to evaluate

the combined effects of the selected variables on the aver-

age particle size. The particles were characterized by scan-

ning electron microscopy (SEM), transmission electron

microscopy (TEM) and Malvern. We have tested the

in vitro performance of nanosized aerosol by Anderson

cascade impactor (ACI) and compared it with the

micron-sized drug.

This article is the first detailed description of formula-

tion development of alendronate nanoparticles as DPI

using antisolvent precipitation technique for osteoporosis.

Materials and methods

Chemicals

Micronised alendronate (commercial) was supplied by Dr

Reddy’s laboratory (Hyderabad, India). Lactose (pharma-

tose) was obtained from DMV international (Veghal, The

Netherlands). Cellulose derivatives (HPMC and HPC) were

generously gifted by Ranbaxy Pharmaceutical (India).

Different grades of poloxomer (F68, F108, F127) were pur-

chased from Sigma Aldrich (Bangalore, India). PEG (400,

6000), chitosan (medium viscosity), alginate and PVA

(molecular weight 125 000) were procured from SD Fine

Chem (India). Organic solvents were obtained from

Merck (India). Water used was purified by reverse osmosis

(Milli-Q, Millipore, USA). All others chemicals were of the

analytical grade.

Preparation of nano alendronate sodium

Nanosized alendronate sodium was produced by the anti-

solvent precipitation technique. The drug was dissolved in

HPLC grade water and passed through 0.22 mm pore size

filter to remove particulate impurities. The solution was

then dropwise added into different organic solvents con-

taining different stabilizers. The precipitated solution

was then spray dried using a Buchi mini drier

(SM Scientech SMST, Calcutta) with a standard 0.5-mm

nozzle. The suspension was fed to the nozzle with a peri-

staltic pump, atomized by the force of compressed air and

blown together with a hot air to the chamber where the

solvent in the droplets was evaporated. The dry product

was then collected in a collection bottle. The drying con-

ditions were as follows: spray flow rate/fed rate 90 ml/h

feed rate, inlet air temperature of 70�C and outlet air tem-

perature of 50�C.

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Characterization of particles

Particle size

The particle size was measured by using photon correlation

spectroscopy (HSA3000, Malvern Instruments, UK). Three

millilitres of fresh filtered (0.22 mm) ethanol was filled into a

disposable cuvette. A proper diluted (ten times) nanopar-

ticle suspensions was added to the cuvette. In order to

deaggregate particles, the samples were treated for a

short time in an ultrasonic bath before measurement.

Each sample was analyzed in triplicate. The average parti-

cle size was expressed as d90 (represent size of 90%

particles).

Transmission electron microscopy

To prepare sample for TEM analysis, alendronate particles

were suspended in ethanol and ultrasonicated for a min-

utes to deaggregate particles. A small drop of a suspension

was then placed on carbon-coated grid covered with nitro-

cellulose and then negatively stained with phosphotungstic

acid (PTA). They were dried at room temperature.

A Hitachi H 9000 NAR transmission electron microscope

was used for the nanoparticle analysis. The TEM has a

point resolution of 0.18 nm at 300 kV in the phase contrast

HRTEM imaging mode and is equipped with an energy

dispersive X-ray (EDX) spectrometer. Both low-magnifica-

tion TEM and HRTEM imaging modes were used.

Scanning electron microscopy

The formulated nanoparticles were examined by SEM for

determining the surface morphology and particle size. Gold

sputter coating was carried out under reduced pressure in

an inert argon gas atmosphere (Agar Sputter Coater P7340)

on the dried sample. After sputter coating the sample on

the carbon coated grid was examined under scanning elec-

tron microscope (Leo 435 VP) operated at 15–25 KV and

photographs were recorded.

In vitro lung deposition studies

In vitro deposition of nanosized medication was deter-

mined by using Anderson Cascade Impactor (Copley

Instruments (Nottingham) Ltd). The instrument complied

with specifications for apparatus A of the European

Pharmacopoeia and British Pharmacopoeia. A capsule

containing 1 mg nanosized and micronized (commercial

drug passed through 400 mesh sieve) alendronate mixed

with 10 mg lactose was placed in rotainhaler and vac-

uumed to produce air streams of 60 L min�1 for 5 s. Each

stage was washed and the amount of drug collected in each

stage analyzed by UV-Visible spectrophotometer at � max

569 nm after appropriate dilution. Respirable fraction was

calculated as the amount deposited in the lower stage as a

percentage of the emitted dose (amount emitted into upper

and lower stages excluding the amount remaining in the

device). Samples were analysed in triplicate. Statistical

analysis was carried out using Minitabe statistical software

(Version 13.1). To calculate the GSD, a nonlinear least

squares analysis with a log-normal function was used.

Geometric standard deviation is a measure of the

variability of the particle diameter within the aerosol

(Finlay, 2001). It is defined by the ratio of the diameters

of particles from aerosols corresponding to 84% and 50%

on the cumulative distribution curve of the weights of par-

ticles. The emitted dose was calculated as the amount of

loaded powder minus the amount collected in the

Andersen Cascade Impactor. MMAD was calculated from

‘‘mmad calculator’’ software.

Experimental design

The central composite design was used to optimize the

formulation parameters and systemically to investigate

the effect of wide range of independent and dependent

variables. Drug concentration (X1), antisolvent volume

(X2), stirring speed (X3) and stabilizer concentration (X4)

were four independent variables (factors) considered in the

preparation of alendronate nanoparticles, while the aver-

age particle size was dependent variables (response). The

details of the design are shown in Table 1. For each factor,

the experimental range based on the result of preliminary

experiment was selected and process parameters were

studied by conducting the runs at different levels of all

factors. Data collected for responses in each run were ana-

lyzed using the software DESIGN EXPERT 7.1 (Statease,

USA) and fitted into a multiple linear regression model.

Results

Preliminary trials

Effect of antisolvent

Different antisolvents were tried and optimized on the

basis of particle size. As shown in Figure 1(a), it can be

depicted that selection of antisolvent had a noticeable

effect on the particle size. Large-sized and aggregated par-

ticles were formed when ethanol, acetone and IPA were

used as a precipitation medium. Minimum particle size

of 313 nm was attained when precipitation was carried

out in acetonitrile. However, no precipitation took place

when methanol was selected as antisolvent.

Effect of stabilizer

Formulations were prepared using different stabilizers in

different concentration and their effects on average particle

size were evaluated (Figure 1(b)). Figure 2 shows the effect

Table 1. Level of process parameters used in experiment.

Code Process parameters Levels

�2 �1 0 þ1 þ2

X1 Drug concentration (%) 10 20 30 40 50

X2 Antisolvent volume (ml) 5 10 15 20 25

X3 Stirring speed (rpm) 300 600 900 1200 1500

X4 Stabilizer concentration (%) 2.5 5 7.5 10 12.5

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of stabilizer on the particle size and stability of the

formulated particles. The particles were of very large

size (41mm), cubical in shape, and highly aggregated

when prepared without stabilizer (Figure 2(a.1) and

(a.2)). Therefore, the resultant particles required to be sta-

bilized by surfactants as stabilizer in the formulation

process.

TEM photomicrograph (Figure 2(b)) depicted that the

particles were nicely round shape with narrow-size distri-

bution when PVA was selected as a crystal growth inhibitor.

Further attempt was done to improve that particle size by

incorporating pluronics in the precipitation medium.

Figure 3(a) shows effect of different poloxomer grades on

the particle size. The best size was achieved with poloxo-

mer F68 as compared to F108 and F127.

Effect of pluronic concentration

Preliminary studies were carried out in order to select a

narrow concentration range to achieve desired size. The

results showed that minimum 1% concentration of polox-

omer F68 was required to produce stable alendronate

nanoparticles (Figure 3(b)). Large aggregates were

obtained when concentration was increased to 20%.

Above 20% concentration, sticky mass was obtained that

showed poor flow properties. Hence, 5% to 12.5% was

selected and optimized on the basis of design expert trial.

Central composite design

The individual and interactive effects of different process

variables were studied by conducting the process at differ-

ent levels of all factors. All the responses observed in

30 runs were simultaneously fitted to first order-, second-

order and quadratic models using DESIGN EXPERT. It was

observed that the best-fitted model was the quadratic

model. The results of experimental data and simulated

values are listed in Table 2. The analysis of variance of

the model for response is represented in Table 3. This qua-

dratic model resulted in response surface graphs for the

average particle size and two significant ones are shown

in Figure 4.

The model proposes the following polynomial equation

for absorbance:

Y ¼ þ459þ 174:11X1 � 25:38X2 � 15:36X3

� 61:57X4 � 1:48X1X2 � 6:08X1X3

þ 15:69X1X4 � 19:19X2X3 � 0:86X2X4

þ 5:50X3X4 � 5:89X 21 þ 3:69X 2

2

þ 32:39X 23 � 4:99X 2

4

The model F-value of 193.96 implied that the model was

significant. Values of ‘‘Prob4 F’’ less than 0.0500 indicated

that model terms were significant. In our model X1, X2, X3,

X4, X1X4, X2X3, X 23 were significant model terms. The ‘‘Lack

of Fit F-value’’ of 1.63 implied the lack of fit was not

Figure 1. Effect of (a) antisolvent, (b) stabilizer on particle size of alen-

dronate particles.

Figure 2. TEM photomicrographs of alendronate nanoparticles prepared

(a) without stabilizer, (a.1) particles showing aggregation, (a.2) zoomed

out individual particle; (b) with PVA as stabilizer.

Figure 3. Effect of different polymer (a) grade, (b) concentration on aver-

age particle size of alendronate particles.

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significant. A correlation plot between actual and predicted

values are shown in Figure 5(a). The ‘‘Pred R-Squared’’ of

0.9737 is in reasonable agreement with the ‘‘Adj R-

Squared’’ of 0.9893. The high R2 value for the response

(0.99) suggested that the final model could satisfactorily

account for the variation in process response. ‘‘Adeq

Precision’’ measured the signal to noise ratio. A ratio

greater than 4 was desirable. Our ratio 54.571 indicated

an adequate signal. Therefore, this model could be used

to navigate the design space. A positive value of X1 repre-

sented a favorable optimization process while negative

value of X2 indicated an inverse relationship. As drug con-

centration increased from 10 to 50 mg/ml, particle size also

increased proportionally. Formulation C18 prepared with

10 mg/ml concentration showed an average particle size

of 62 nm when compared to formulation C6 and C20 that

indicated a marked increase in a average particle size at a

constant volume of antisolvent. As antisolvent volume

increased from 5 to 25 ml particle size also decreased

from 530.2 to 411.7 nm (C11 and C5). Similarly, an increase

in stirring speed from 300 to 900 rpm decreased the particle

size. Formulation C1 prepared at 300 rpm stirring speed

exhibited 610.2 nm when compared with C25 prepered at

900 rpm stirring speed that showed an average particle size

487.6 nm. Further increased in stirring speed to 1500 rpm

provided large-size particles (C24). The inflence of stabilizer

concentration was also studied. A decrease in particle size

was observed with increase in stabilizer concentration.

Formulation prepared with 2.5% poloxomer (C7) showed

an average size of 561.3 nm when compared with C28.

RSM and Contour plots: Figure 4 represents three-

dimensional RSM plot and two-dimensional contour-plot

that show interactive effect of X1 and X4 on response, that

is, the average particle size at one time, while rest of the

factors kept at the constant level. The graph shows the

interactive effect ofdrug concentration versus stabilizer

with factor X2 and X3 constant at its �1 and þ1 coded

level. As clearly shown, all the factors were exhibited

nearly linear relationship at all levels. The interactive

effect was found to be favorable for the response. As drug

concentration increased from 20 to 35 mg/ml at a constant

concentration of poloxomer (7.5%), particle size also

increased from 353 to 589 nm. This interactive effect

more clearly depicted from surface response plots that

showed the linear result with the particle size. A significant

negative interactive effect was observed between stirring

speed and volume of antisolvent. A quadratic path was

favored that showed nonlinear relationship at all levels

(Figure 4(b)). The effect was found to be significant from

10 to 15 ml of antisolvent. The result was converted to

almost parallel effect (less significant) when antisolvent

volume was further increased.

Validation of RSM results

Point prediction of the design expert software was used to

determine the optimum values of the factors for the mini-

mum particle size. For all the six checkpoint formulations,

the result of average particle size was found to be 5200 nm.

Table 4 lists the composition of the checkpoints, their pre-

dicted and experimental values of the response variables

and the percentage error in prognosis. Upon comparison of

Table 2. Central composite design with results.

Code Process parameters Average particle size

X1 X2 X3 X4 Actual Predicted

C1 0 0 �2 0 610.2 620

C2 þ1 �1 þ1 þ1 623.0 643

C3 �1 þ1 þ1 þ1 194.3 185

C4 þ1 �1 �1 þ1 652.8 636

C5 0 þ2 0 0 411.7 423

C6 þ2 0 0 0 803.3 783

C7 0 0 0 �2 561.3 558

C8 þ1 þ1 þ1 þ1 550.7 549

C9 �1 þ1 �1 �1 420.4 398

C10 �1 �1 þ1 �1 426.3 415

C11 0 �2 0 0 530.2 524

C12 þ1 þ1 þ1 �1 641.6 631

C13 þ1 �1 þ1 �1 710.8 722

C14 �1 �1 þ1 þ1 286.1 273

C15 �1 þ1 �1 þ1 248.3 231

C16 �1 þ1 þ1 �1 320.1 330

C17 þ1 þ1 �1 þ1 610.1 620

C18 �2 0 0 0 62.0 87

C19 þ1 þ1 �1 �1 716.8 724

C20 0 0 0 þ2 311.0 316

C21 �1 �1 �1 �1 410.5 406

C22 �1 �1 �1 þ1 234.4 242

C23 þ1 �1 �1 �1 730.4 737

C24 0 0 þ2 0 561.3 562

C25 0 0 0 0 487.6 459

C26 0 0 0 0 460.1 459

C27 0 0 0 0 461.4 459

C28 0 0 0 0 450.0 459

C29 0 0 0 0 452.6 459

C30 0 0 0 0 444.0 459

Table 3. Analysis of variance of calculated model for response.

Results of the analysis of variance Average particle size

Regression

Sum of squares 0.00088

Df 14

Mean squares 63101

F-ratio 194

P 50.0001

Residual

Sum of squares 4880

Df 15

Mean squares 325.33

SD 18.14

Lack of fit test

Sum of squares 3736

Df 10

Mean squares 374

F value 1.63

Correlation coeffecient (R2) 0.9945

Correlation of varaition (CV %) 3.78

Notes: Analysis of variance from DESIGN EXPERT 7.0.

Df, degree of freedom.

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the observed responses with that of the anticipated

responses, the prediction error varied between þ1.72%

and �5.63%. Figure 5(b) shows linear correlation plots

between observed and predicted response variables. The

linear correlation plots drawn between the predicted and

observed responses demonstrated high values of r2 (0.9825)

indicating excellent goodness of fit (p5 0.001). All check-

points formulation exhibited 490% experimental validity.

Upon validation the optimized formulation (FS3) exhibited

percentage error of �1.87% with the minimum particle size

of 44.11 nm.

The TEM and SEM photomicrographs are shown in

Figure 6. TEM revealed the presence of spherical particles

from 5.86 to 150 nm (Figure 6(a)). While SEM photomicro-

graphs clearly demonstrate the nanosization of particles.

Micron size drug was large sized and crystalline in nature

(Figure 6(b.1)). On the other hand, nanosized particles

were small in size (�100 nm). The crystalline particle

with round ages are present together with spherical parti-

cles (Figure 6(b.2)).

In vitro lung deposition

Anderson Cascade Impactor (ACI) details for nano and

micronized alendronate are shown in Table 5. The emitted

dose was more than 90%. The deposition pattern as shown

in Figure 7 clearly demonstrated that the commercial alen-

dronate deposited mainly on the upper regions of the

impactor (indicating throat, mouth, and oropharynx).

Nanosized particles showed more deposition in deeper

alveolar regions. The respirable fraction for alendronate

nanoparticles was 48.85%� 0.52% that was significantly

higher (p5 0.05) than micron form underlying small size

particles and better deaggregation behaviour. MMAD

of designed particles was found to be 3.45 mm with GSD

of 2.10� 0.3 and were suitable for better lung retention.

Figure 4. (a) Response surface plot, (b) contour plots showing the effect of different process parameters on the average particle size.

Figure 5. (a) Regression curve, (b) linear correlation plot between actual

and predicted value.

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In contrast micronized particles presented aerodynamic

diameter of 6.62 mm with 2.32� 0.1 GSD.

Discussion

The nanosized particles were prepared by antisolvent pre-

cipitation in the presence of stabilizer. A known concentra-

tion of drug solution when added to organic solution

(antisolvent), the drug precipitated out immediately and

precipitation was usually in the nanometer size range.

Stabilizers were often added to stabilize the solution and

to prevent the crystal growth during drying and storing.

Different antisolvents and stabilizer were tested and opti-

mized on the basis of the particle size. The minimum size

was obtained when acetonitrile was employed as antisol-

vent. The key for preparation of stable nanoparticles was

based on a selection of proper stabilizer. For similar charge

particles, the particle deposition on surfaces increased with

electrostatic interaction or decreased particle size and sur-

face charge density. In a similar way, the particle–particle

interactions could be controlled by coating either the par-

ticles or the surface or both with stabilizer. It was observed

that the particle size of nanoparticles was significantly

influenced by the type of stabilizer. Small sized, nicely

rounded particles were prepared with polyvinyl alcohol,

while the other surfactant produced large size particles.

When HPMC was used as stabilizer, large aggregated par-

ticles were formed, independently of concentration and

process parameters. Even the suspensions were highly

unstable and easily favour the crystal growth. Similar

results were observed for alginate and chitosan. These

results indicated that stabilizer played an important role

in controlling the surface morphology as well as size of

alendronate nanoparticles. A slight decrease in the particle

size from several microns to nanometer was achieved when

PEG was used as stabilizer (irrespective of the molecular

weight). Formulations were prepared by different grades of

poloxomer and their effect on the particle size was investi-

gated. Poloxamers are non-ionic poly (ethylene oxide)

(PEO)–poly (propylene oxide) (PPO) copolymers that

widely used as surfactant, emulsifying agent, dispersing

agent and in vivo absorption enhancer (Lin and

Kawashima et al., 1985). All poloxamers have similar chem-

ical structures but with different molecular weights and

composition of the hydrophilic PEO block (a) and hydro-

phobic PPO block (b). It was observed that the best size was

achieved with poloxomer F68 when compared with other

grades. The fact can be supported by the hypothesis that

F68 because of its low molecular weight preferentially

adsorbed on the particle surface reducing interparticular

interaction. Therefore, poloxomer F68 was selected for fur-

ther studies. Moreover, poloxomer in the emulsion resulted

in particles with improved dispersibility (Hartwig and

Heike, 2004).

Response surface methodology (RSM) was used to

systemically investigate the effect of a wide range of

Table 4. Composition of the checkpoint formulations, predicted and experimental values of response variables and

percentage prediction error.

S. no. Composition

(X1:X2:X3:X4)

Experimental

value

Predicted Percentage

error

Experimental

validity

1 10:20:900:7.5 68.80 71.56 �4.01 96.14

2 10:20:924:7.0 84.60 83.14 þ1.72 101.76

3 10:18.11:1200:8.85 43.30 44.11 �1.87 98.16

4 10:20:925:7.03 84.58 86.32 �2.06 97.98

5 7.5:5:600:8.5 51.26 54.15 �5.63 94.66

6 20:16.76:762:10 171.94 175.6 �2.12 97.91

Figure 6. (a) TEM photomicrograph of optimized formulation; (b) SEM

photomicrograph of (b.1) micron size (b.2) optmized formulation.

Table 5. ACI data for micronized and nanosized alendronate sodium

using 60 L/min flow rate.

Particle size attributes ACI (inhalation data)

Nanosized Micronized

alendronate

Emitted dose (%) 90.66� 0.8 91.8� 0.5

Respiratory fractiona (%) 43.85� 0.52 17.6� 0.32

Mean median aerodynamic

diameter (mm)

3.45 6.62

GSD 2.10� 0.3 2.32� 0.1

Note: Respiratory fraction calculated as ratio of total drug deposited in the

lower stages of the ACI (stages 2–8) to total theoretical dose.

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independent and dependent variables. Central-composite

designs (CCDs) are popular designs for use in response-

surface exploration. They are blocked designs consisting of

at least one ‘cube’ block (two-level factorial or fractional

factorial, plus centre points), and at least one ‘star’ block

(points along each axis at positions �alpha and þalpha),

plus centre points. Everything is assumed to be on a coded

scale, where the cube portion of the design has values of�1

and 1 for each variable, and the center points are 0 (Meyers

and Montgomery, 2002; Lenth, 2009). Drug concentration,

antisolvent volume, stabilizer concentration and stirring

speed were four independent variables considered in the

preparation of nanosized alendronate while the particle

size was the dependent variable (response). To identify

the optimum levels of different process parameters

influencing the particle size, an experimental design of

30 runs containing central points was made according to

the central composite design for these selected parameters.

The model F-value provides a statistic that can be com-

pared to a probability distribution table for a given confi-

dence level (e.g., 95% confidence level that means

experimenters are 95% confident about the results and con-

sidering �5% error for the experiment) to determine

whether the treatment means are significantly different.

This value was found to be significant for the experiment.

The results showed that an increase in drug concentration

resulted in an increase in response, that is, an average par-

ticle size. The expected fact might be due to more tendency

of particles to aggregates in a more concentrated solution

during precipitation. Two factors could be considered to

describe this phenomenon, first was formation of number

of nuclei formed at the interface of two phases and second

one was the viscosity of the solution. As concentration of

drug solution increased, number of nuclei formed at the

interface also increased proportionally that reduced the dif-

fusion of particles from solvent to antisolvent. The result

ultimately was particle aggregation. As drug concentration

increased, viscosity of solution increased that hindered the

diffusion process between solvent and antisolvent.

During this phenomenon the crystal growth took place

very rapidly that increased the particle size from sev-

eral nanometers to micrometers (Zhang et al., 2006).

On the other hand, Zhang et al. (2009) reported a decrease

in the particle size with increase in drug concentration

from 20 to 60 mg/ml. Futher increase in the particle size

was observed at 80 mg/ml drug concentration. An inverse

relationship between antisolvent volume and particle size

was observed. The result could be attributed to the fact that

increment in antisolvent volume increased the diffusion of

the precipitated nuclei from solvent to antisolvent

which would lead to decrease in the particle size.

Furthermore, diffused nuclei had less tendency to agglom-

erate due to increase in interparticular distance. It could be

observed from the negative value of response that as stirring

speed increased, the particle size also decreased. An

increased in the stirring rate from 300 to 900 resulted in

decrease in the average particle size. The obvious explana-

tion for this phenomenon was high micromixing effeciency

with increase in the stirring rate between the two phases

that induced the rate of diffusion of nuclei into antisolvent.

Rapid nucleation produced the smaller size particles with

narrow size distribution (Zhang et al., 2006). The result was

reversed after 900 rpm stirring speed. This could be

explained on the basis of crytal growth at high shear

forces. At high stirring speed, the nanoparticles formed

would colloide and aggregated to form larger ones. From

the above equation, it could be depicted that the particle

size decreased with increased in surfactant concentration

that could be due to stabilizing effect of poloxomer on par-

ticles. During nanosizing, surfactant was adsorbed on the

surface of the particles that avoided coalescence of the par-

ticle droplets during the diffusion process between two

phases.

Ultimately, the goal of the pharmaceutical experi-

menters in this case was to minimize particle size. Results

above 200 nm were unacceptable. Ideally, this size reduc-

tion goal could be exceeded by optimizing interactive

processes parameters. RSM and Contour plots are imple-

mented that describe the mutual interaction between the

test variables and their subsequent effect on response

Figure 7. ACI study comparison for (%) deposition in each stage for nano and micronized alendronate DPI using rotahaler at 60 L min�1 (n¼ 6).

452 S. Sultana et al.

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where each curve represents a region of constant response.

These plots showed quadratic response between antisol-

vent volume and stirring speed at all levels. On the

other hand, a linear response was observed between

drug and stabilizer concentration. Checkpoint formulation

were prepared using the point prediction tool. The

experimental valdity was more than 90% for all checkpoint

formulations. Thus, the low magnitudes of error and

the significant values of r2 in the current study indicated

a high prognostic ability of RSM. Finally the optimized

formulation was selected on the basis of the minimum

particle size. The optimized formulation showed spherical

and small-sized particles suitable for deep alveolar

targeting.

The lung deposition characteristics and efficacy of an

aerosol depend largely on the particle or droplet size.

Generally, the smaller the particle greater its chance of

peripheral penetration and retention. The particle size for

an aerosol refers to aerodynamic of unit density meaning

the size of a spherical, unit density particle that settles with

the same velocity as the particle in question. The propor-

tion of an aerosol particle with an MMAD of 1–5 mm is

considered suitable for lung targeting. The nanosized par-

ticle has good aerosolization behaviour and deposits

mainly on lower stages. While more than 60% particles

deposited on PS and stage zero in case of micron-sized

alendronate. The MMAD and deposition pattern of nano-

sized formulation as determined by the cascade result was

well suited for lung delivery. The considerable higher respi-

rable fraction of nano alendronate may contribute to high

bioavailability due to biotransfer across the lung

membranes.

Conclusion

The alendronate nanoparticles were successfully

developed by antisolvent precipitation technique.

Preliminary studies revealed that choice and concentration

of stabilizer had a marked influence on the particle size.

Lutrol F68 was found best in attaining the minimum size.

The central composite design revelaed that the drug

and stabilizer concentration significantly affected the

response. Drug concentration had a positive impact

while stabilizer concentration had a negative influence

on the particle size. Particles of best batch based on

point prediction tool of design software exhibited

44.11 nm size with 98.16% experimental validity. In vitro

deposition studies of alendronate nanoparticles conducted

by Anderson cascade impactor demonstrated 43.5% respi-

rable fraction and 3.45 mm MMAD suitable for lung

targeting.

Acknowlegements

This work was financial supported by the University Grant

Commission (UGC), New Delhi, India.

Declaration of interest

The authors report no conflict of interest. The authors

alone are responsible for the content and writing of the

article.

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