Aqueous re-dispersibility characterization of spray-dried hollow spherical silica nano-aggregates

Powder Technology 198 (2010) 354–363

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Aqueous re-dispersibility characterization of spray-dried hollow spherical silica nano-aggregates Katherine Kho, Kunn Hadinoto ⁎ School of Chemical and Biomedical Engineering, Nanyang Technological University, 637459 Singapore

a r t i c l e

i n f o

Article history: Received 14 October 2009 Received in revised form 17 November 2009 Accepted 30 November 2009 Available online 5 December 2009 Keywords: Spray drying Nano-aggregates Dry powder inhaler Agglomerate dispersion Silica nanoparticles

a b s t r a c t Hollow spherical aggregates of biocompatible silica nanoparticles are produced by the spray drying technique to facilitate the delivery of the nanoparticles to the lung for potential drug delivery applications. The large geometric size (dG N 5 µm) and the low density (ρeff ≈ 0.3 g/cm3) of the nano-aggregates are specifically formulated to achieve high aerosolization efficiency and an effective lung deposition. The nanoaggregates must readily re-disperse into the primary nanoparticles in an aqueous medium for the nanoparticles to perform their intended therapeutic functions. An aqueous re-dispersibility characterization technique based on the turbidity level measurement is developed for this purpose. A water-soluble excipient (i.e. mannitol), which forms “excipient bridges” interconnecting the nanoparticles, is included in the spraydrying formulation to produce readily re-dispersible nano-aggregates. The nano-aggregate aqueous redispersibility depends on (1) the silica: mannitol concentration ratio and (2) the degree of hollowness, where nano-aggregates with a higher shell thickness to particle radius ratio exhibit weaker re-dispersibility due to the poor particle wetting. The spray-drying condition and the silica: mannitol ratio, which lead to the production of highly re-dispersible nano-aggregates having the desired morphology, are determined. The promising results signify the potential application of hollow spherical silica nano-aggregates as an inhaled drug delivery vehicle. © 2009 Elsevier B.V. All rights reserved.

1. Introduction The use of silica nanoparticles in drug delivery applications has become increasingly popular as a result of their biocompatibility and attractive physico-chemical properties (e.g. high stability, hydrophilicity), which can be precisely controlled to manipulate the drug targeting ability and its release rate. In this regard, silica nanoparticles have been actively investigated as potential gene delivery vectors [1,2], and as carriers of anticancer drugs [3,4] and antimicrobial agents to treat severe lung infections [5]. In addition, silica nanoparticles have also been used to enhance the dissolution rate of nano-crystalline drugs [6], to enhance the chemical stability of emulsified drugs [7], to improve the aerosolization efficiency of inhaled drugs [8], and as a drying adjuvant in the solid-dosage form formulation of thermallysensitive drugs [9–12]. In particular, inhaled delivery of drug-bearing silica nanoparticles represents one promising avenue to improve the effectiveness of (1) antimicrobial therapy against cystic fibrosis and (2) photodynamic therapy against lung cancer [13–16]. The inhaled delivery route facilitates the targeted delivery to the lung infection or tumour sites, which improves the therapeutic efficacy and minimizes the negative

⁎ Corresponding author. Tel.: +65 6514 8381. E-mail address: [email protected] (K. Hadinoto). 0032-5910/$ – see front matter © 2009 Elsevier B.V. All rights reserved. doi:10.1016/j.powtec.2009.11.031

side effects from a high-level systemic drug exposure. Delivering the silica nanoparticles by inhalation, however, poses many challenges in practice as a result of (1) the strong tendency for particles in the submicron size range to agglomerate rendering their aerosolization extremely difficult, and (2) the poor delivery efficiency as aerosolized nanoparticles are predominantly exhaled from the lung due to their extremely low inertia. In inhaled drug delivery, the aerodynamic diameter (dA) defined in Eq. (1) is used to characterize the distance travelled by the inhaled particles in the human respiratory airways. Spherical particles with large dA (N10 µm) tend to deposit in the mouth and throat regions, whereas particles with small dA (b1 µm) remain suspended in the air flow and are consequently exhaled from the lung [17]. Particles for inhaled drug delivery are therefore designed with dA ≈ 2−4 µm to facilitate their deposition in the targeted lung regions.

dA = dG

sffiffiffiffiffiffiffiffiffiffiffiffi ρeff ρunity

ð1Þ

where dG is the particle geometric size, ρunity is equal to 1 g/cm3, and ρeff is the particle effective density defined as the particle mass divided by its total volume including the open and closed pores. Because of their small dG, nanoparticles possess dA bb 1 µm that requires them to be formulated into micron-scale structures with

K. Kho, K. Hadinoto / Powder Technology 198 (2010) 354–363

dA ≈ 2−4 µm to facilitate their delivery to the lung by inhalation. For this purpose, micron-size hollow spherical nano-aggregates acting as an aerosol delivery vehicle of drug-bearing nanoparticles have been engineered by means of the spray-drying technique [18,19]. The large geometric diameter of the nano-aggregates (dG N 5 µm) reduces their tendency to agglomerate hence improving their aerosolization efficiency, whereas the hollow morphology results in low-density nanoaggregates having dA between 2−4 µm that is suitable for an effective deposition in the lung. To produce the large hollow spherical nano-aggregates, the spraydrying condition (e.g. drying temperature, feed rate) and the formulation ingredients (i.e. excipient type and its concentration) must be meticulously determined. The physical mechanism behind the hollow nano-aggregate formation is described as follows. Liquid evaporation from the droplet surface exposes the nanoparticles at the receding liquid-vapor interface to the vapor phase. As the surface energy of a solid-vapor interface is greater than that of a liquid-vapor interface, the nanoparticles migrate toward the droplet centre to minimize their surface energy. A fast convective drying rate in which the liquid evaporation time is shorter than the time needed by the nanoparticles to diffuse back toward the droplet centre is required to produce the hollow morphology. A fast convective drying rate is obtained when the local Peclet number (Pe), which signifies the importance of the nanoparticle diffusion time scale (r2/DS) relative to that of the convective drying rate (τD), as defined in Eq. (2) is significantly larger than unity [20]. Pe =

r2 τD DS

ð2Þ

where r, τD, and DS are the droplet radius, drying time, and nanoparticle diffusion coefficient, respectively. As the drying progresses, the nanoparticles, which are driven by the capillary force generated by the meniscus formed in the gap between the nanoparticles, self-assemble at the interface to form aggregates resulting in the shell formation. This attractive capillary force, however, is resisted by the repulsive electrostatic force acting as a stabilizer. The competing interaction between the two forces, which is dictated by the colloidal stability of the nanoparticulate suspension, leads to a shell buckling that corresponds to a rheology transformation of the shell from the viscous to the elastic regimes [21]. The extent of the shell buckling dictates the resulting morphology (i.e. size, shape, and degree of hollowness) of the nano-aggregates. In addition to their specific dG and dA requirements, for the nanoaggregates to be therapeutically effective, they must readily disassociate into the primary nanoparticles upon their deposition in the lung interstitial fluid. The reason is because the drug dissolution rate from nano-aggregates has been found to lag behind that of colloidally stable primary nanoparticles due to the reduced wetted surface area in the nano-aggregates [22]. Furthermore, the primary nanoparticles must remain colloidally stable after being re-dispersed in order to maintain the high dissolution rate. In addition, an effective re-dispersion of the nano-aggregates into the primary nanoparticles is also crucial in minimizing the lung phagocytic clearance mechanism, which effectively removes foreign particles in the size range of 1−2 µm, but greatly diminishes for foreign particles having either smaller (b300 nm) or larger sizes (N6 µm) [23]. The aqueous re-dispersibility of the nano-aggregates is governed by (1) the strength of the nano-aggregate binding force and (2) the degree of particle wetting in an aqueous medium. In this regard, inhaled drug delivery formulations typically employ a wide range of pharmaceutical excipients (e.g. polymers, surfactants) for various purposes mainly to enhance the drug absorption and to minimize the phagocytosis in the lung. As a result of the excipient inclusion, the strength of the nano-aggregate binding force is governed by the solubility of the “excipient bridges” interconnecting the nanoparticles

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and is less influenced by the inherent nanoparticle attractive forces as illustrated in Fig. 1. The degree of particle wetting depends on the nano-aggregate surface hydrophilicity, which is a function of the nanoparticles and the “excipient bridges” hydrophilicity and their surface compositions. The particle wetting is also influenced by the shell thickness (S) to the particle radius (R) ratio, where nano-aggregates with a thicker shell, which is constituted of several nano-aggregate layers, are anticipated to exhibit weaker re-dispersibility due to the reduced wetted surface area. In this regard, several studies have found that nonhollow nano-aggregates (S/R ≈ 1) of various nanoparticle types are not re-dispersible in water [24–26]. With regard to the characterization technique, the aqueous redispersibility of dry-powder aggregates is typically examined by applying a high-intensity dispersion force (e.g. homogenization, ultrasonication) to the aggregate suspension after which the aggregate size reduction is examined to determine the extent of the re-dispersion. For the nano-aggregates intended for inhaled drug delivery, however, this characterization technique is inadequate as it does not represent the actual re-dispersion mechanism in the lung interstitial fluid, which is due to the spontaneous particle wetting. Furthermore, previous investigations on the aqueous re-dispersibility of nano-aggregates mainly involved nanoparticles having diameters in the several hundrednanometer range [22,26]. Silica nanoparticles on the other hand are typically in the size range of less than 50 nm hence they likely require a more sensitive characterization technique due to the smaller particle size. The objectives of the present work are therefore (1) to develop experimental techniques to characterize the aqueous re-dispersibility of hollow spherical silica nano-aggregates, (2) to examine the effects of the nano-aggregate morphology and the hydrophilic excipient inclusion on the aqueous re-dispersibility, and (3) to determine the optimal spray drying condition and formulation ingredients to produce highly redispersible hollow spherical nano-aggregates with dG ≈ 5–10 µm and dA ≈ 2–4 µm. Mannitol is selected as the hydrophilic excipient constituting the “excipient bridges” because it is highly soluble in water (0.18 g/mL), and more importantly it has been shown to improve the lung function of cystic fibrosis patients [27]. With regard to the particle production technique, the conventional spray-drying method to produce hollow nano-aggregates typically uses a large amount of organic solvent (up to 70% v/v) to lower the boiling point of the spray-drying solution, so that a fast convective drying rate can be achieved [18–20]. A significant presence of organic solvent in the formulation can potentially lead to drug compatibility issues, but more importantly it requires the spray drying to be conducted under an inert condition, which is costly and less operationally stable, for the safety and environmental reasons. The present work therefore aims to minimize the amount of organic solvent used. The effects of the spray drying condition on the resulting nano-aggregate

Fig. 1. “Excipient bridges” governs the nano-aggregate aqueous re-dispersibility (NP = nanoparticles).

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morphology must therefore be re-examined. Pertaining to silica nanoparticles, previous investigations in the silica nano-aggregate production engaged in the production of meso-porous spherical nanoaggregates [28,29]. The porous nano-aggregates were produced by spray pyrolysis in a laminar-flow aerosol reactor using an ultrasonic atomizer, whereas the present work utilizes a spray dryer that operates in a turbulent-flow regime with a two-fluid flow atomizer hence the present work embodies a unique approach to the silica nano-aggregate production. 2. Methodology 2.1. Materials Colloidal silica Ludox AS-30 (Sigma-Aldrich, USA) in the size range of 25 ± 2 nm is used as the model silica nanoparticles. The Ludox nanoparticles have been studied as potential medical implant coatings [30], and they have been shown in-vivo to be naturally removed from the lung with a half-life of ≈ 50 days [31]. The silica nanoparticles are not loaded with any drugs as the current emphasis is on the nanoaggregate production and the aqueous re-dispersibility characterization. D-mannitol (C6H14O6) and ethanol (Sigma-Aldrich, USA) are used as the hydrophilic excipient and organic solvent, respectively. Nanoparticulate suspensions are prepared by adding the silica nanoparticles and dissolving the excipients into water or water-ethanol solution. Trizma base and hydrogen chloride (Sigma-Aldrich, USA) are used to adjust the nanoparticulate suspension pH, which dictates the colloidal stability of the silica nanoparticles [32]. 2.2. Spray-drying experiments In the present work, the minimal amount of flammable organic solvent (i.e. ethanol) used allows the Büchi B-290 mini spray dryer (Büchi, Switzerland) to be operated in an open-loop mode using compressed air as the drying gas. In contrast, previous nano-aggregate productions by spray drying [18–20] were operated in a close-loop mode using nitrogen as the drying gas because of the use of highlyconcentrated ethanol solutions. Importantly, the open or close-loop operation modes have been shown to significantly influence the spray-dried particle morphology [33]. The open-loop mode when feasible is preferred as it is simpler to operate, more stable, and less costly compared to the close-loop mode, which requires a condensing unit to recover the organic solvent in order to reduce its emission. The present approach using the open-loop mode therefore represents an attractive alternative to the currently available hollow nano-aggregate production technique by spray drying. The spray-drying condition is controlled by (1) the inlet drying temperature, (2) the gas atomizing flow rate, (3) the feed rate, and (4) the feed concentration. A two-fluid flow atomizer with a nozzle diameter of 1.5 mm is used. The spray-drying yield is defined as the ratio of the collected powder mass to the initial powder mass (i.e. nanoparticle and excipient) in the spray-drying solution. A back-ofthe-envelope calculation indicates that the drying time (τD) of a single 50-µm aqueous droplet at 100 °C is ≈ 0.15 s, whereas the diffusion coefficient of 100 nm silica nanoparticles (DS) is ≈10−12 m2/s resulting in Pe ≈ 1000. This simple analysis indicates that the fast convective drying rate required to form the hollow nano-aggregates can be satisfied at a drying temperature of ≈100 °C when water is used as the spray-drying solution. 2.3. Nano-aggregate morphology characterizations The morphology of the dry-powder nano-aggregates is characterized in terms of their geometric diameter (dG), aerodynamic diameter (dA), and effective density (ρeff). The spray-dried particles are stored in a dry humidity cabinet for a minimum of 48-hour-period prior

to the characterization. The geometric size, shape, and surface chemical composition of the nano-aggregates are characterized using a Scanning Electron Microscope (SEM) model JSM-6700F (JEOL, USA) equipped with Energy Dispersive X-ray Spectroscopy (EDXS) for chemical element detections. The geometric diameter is determined from the SEM images using image processing software Image J. The results reported are based on the average of three different particle samples with a minimum of 1000 particle total counts. The number-based size distribution from the image analysis is next converted to the volume-based distribution. The dG results from the image analysis are evaluated using laserdiffraction-based Particle Size Analyzer MS2000 (Malvern, UK). The particle size analyzer employs a high-intensity wet dispersion method using both mechanical agitation and ultrasonication prior to the laser diffraction measurement to break up agglomerated particles. The nano-aggregates containing the hydrophilic excipient, however, are designed to re-disperse into the primary nanoparticles in an aqueous medium. Consequently, the wet dispersion method would lead to inaccurate dG measurements of the dry-powder nano-aggregates as they are likely to be re-dispersed during the size measurement. Furthermore, the hollow nano-aggregates possess a low mechanical stability attributed to their low S/R ratio, such that the wet dispersion method can disintegrate the nano-aggregates into fragments, which are non-spherical and tend to form large-size agglomerates hence jeopardizing the dG measurement accuracy. The drawbacks of using the particle size analyzer are manifested in the appearance of size distribution peaks at large dG values (N50 µm) in its outputs that are not present in the SEM images. For this reason, the image analysis is deemed to be the more suitable method for characterizing the nanoaggregate size. The bulk density is determined by filling the powder into a 5-mL measuring cylinder. The effective particle density that characterizes the degree of hollowness, assuming a constant true particle density, is determined from the tap density using a tap densitometer (Quantachromme, USA). The tap density is measured after 2000 taps using three replicates of 4 mL each. The measured tap density is corrected by a factor of 0.79−1 to obtain ρeff after taking into account the imperfect particle packing [34]. The bulk and tap density values allow the determination of the Carr's compressibility index (CI in Eq. (3)), where Carr's index values below 25 indicate free-flowing particles and values above 40 indicate cohesive particles having poor flowability [35]. Lastly, the aerodynamic diameter (dA) is calculated using Eq. (1) from the measured values of dG and ρeff. CI =

  ρeff −ρbulk × 100% ρeff

ð3Þ

2.4. Aqueous re-dispersibility characterizations To quantify the mass percentage of the re-dispersed nanoaggregates, 10 mg of the powder are dispersed in 2 mL of deionized water and the suspension is let sit for 30 min under occasional stirrings. Afterwards, the size of the particles present in the suspension is analyzed to determine the extent of the re-dispersion. Next, the suspension is centrifuged at 6000rpm for 10 min after which 1.5 mL of the supernatant, which contains the dissolved mannitol and the redispersed nano-aggregates, is removed and is replaced with 1.5 mL of deionized water without stirring. The resulting suspension containing the sedimented pellets is again centrifuged. The size of the particles present in the supernatant after the first centrifugation is also analyzed. The dilution and centrifugation are repeated four times to ensure that all the nano-aggregates that have re-dispersed are removed and all the mannitol is dissolved. After the fourth centrifugation, 1.5 mL of the supernatant is discarded and the remaining sedimented pellets (0.5 mL) are freeze-dried for 12 h using Alpha 1–2 LDplus freeze dryer (Martin-

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Christ, Germany). The freeze-dried pellets, which consist of the nanoaggregates that have not re-dispersed after 30 min, are weighted. The mass percentage of the re-dispersible nano-aggregates (i.e. % redispersed) is determined from the ratio of the freeze-dried pellet mass to the initial silica nanoparticle mass after taking into account the silica: mannitol ratio. Note: the re-dispersible nano-aggregates are not necessarily fully recovered as primary nanoparticles. The silica nanoparticle diameters before spray-drying (Si = 25 ± 2 nm) and the size after being re-dispersed from the nano-aggregates (Sf) are characterized using 90PLUS Particle Size Analyzer (Brookhaven Instrument Corporation, USA) based on photon correlation spectroscopy. The Sf/Si ratio ≈ 1 suggests that the nano-aggregates are fully re-dispersible into the primary nanoparticles. The experimental uncertainties in the Sf/Si measurements are approximately 3%. Two values of the Sf/Si ratio before and after the first centrifugation are reported based on two replicates of three size measurements each to characterize the extent of re-dispersibility. The former, (Sf/Si) Bef, includes contributions from the primary nanoparticles and the not yet re-dispersed nano-aggregates hence they tend to be larger than the latter, (Sf/Si) Aft, which includes contributions mainly from the primary nanoparticles and the small aggregate fragments that cannot be recovered by centrifugation at 6000 rpm. The (Sf/Si) Bef value is useful to examine whether the nanoaggregates can readily re-disperse and to what extent, whereas the (Sf/Si) Aft value is useful to determine whether the nanoparticles after spray drying can be recovered at the same size as the original nanoparticles. To complement the % re-dispersed and the Sf/Si ratio measurements, the aqueous re-dispersibility is next characterized using the turbidity level measurement of the nanoparticulate suspension. The intensity of a light source passing through a particulate suspension is attenuated proportional to the suspension's turbidity level, which is a function of the particle size. Upon addition of the micron-size nano-aggregates into an aqueous medium, the turbidity level rapidly increases resulting in a rise in the light-attenuation level that is reflected in a decrease in the light-transmittance level (%T) measured by the UV–VIS spectrophotometer mini-1240 (Shimadzu, Japan). As the particle wetting takes place and the wetted “excipient bridges” dissolve, the primary nanoparticles begin to disassociate themselves from the aggregate network reducing the aggregate size, which leads to a lower turbidity level and consequently a gradual increase in %T. The %T value of a nanoparticulate suspension can reach up to ≈90% depending on the nanoparticle concentration. Consequently, nanoaggregates that readily re-disperse into the primary nanoparticles exhibit a steady-state %T value that is similar in magnitude to that of the nanoparticulate suspension having a similar concentration. On the other hand, nano-aggregates with poor re-dispersibility and whose re-dispersed constituents form agglomerates, exhibit a steadystate %T value that remains low at the level obtained upon addition of the nano-aggregates. In practice, the powder is dispersed in a quartz cuvette filled with 3.5 mL of deionized water at 0.5% (w/v) concentration to simulate the typical drug concentration present in the lung interstitial fluid [36]. Next, %T is measured at different time intervals for up to 30 min. The measurements are done in three replicates. The suspension is gently stirred prior to the %T measurement to prevent sedimentation. %T is measured at wavelength = 350 nm, where the silica and the mannitol exhibit zero absorbance, and where %T is found to be most sensitive to the turbidity level of the nanoparticulate suspension. 3. Results and discussion 3.1. Effect of spray-drying operating condition in the open-loop mode The effects of (1) drying temperature, (2) ratio of the gas atomizing flow rate to the feed rate, (3) feed concentration, and (4) suspension

357

pH on the nano-aggregate morphology are examined under the openloop mode in the absence of the organic solvent and mannitol. The spray-drying condition, at which nano-aggregates having the desired dG and dA values are produced, is determined using a factorial design approach. The optimal condition is found to be at 105 °C inlet temperature, 320 L/h drying gas, 0.17 L/h feed rate, 1.0% (w/w) feed concentration, and at pH = 3. At the optimal condition, hollow spherical nano-aggregates with dG ≈ 5 µm and ρeff ≈ 0.7 g/cm3 resulting in dA ≈ 4.2 µm are produced (Run A1 in Table 1). The factorial design results indicate that the effect of varying the drying temperature between 100 °C and 120 °C on the nano-aggregate morphology is insignificant in the open-loop mode. Similarly, varying the gas flow to the feed rate ratio does not significantly influence the morphology. The ratio, however, influences the spray-drying yield, where a lower ratio leads to wetting of the drying chamber by the sprayed droplets resulting in a lower yield. The effect of varying the pH between 3–9 is found to be minimal at 1.0% (w/w) feed concentration though a strong interaction exists between the effects of the feed concentration and the pH. In contrast, the effect of varying the feed concentration is significant independent of the pH. At lower feed concentrations (0.2−0.4% w/w), fine particles with dG ≈ dA ≈ 2 µm are produced, whereas toroidal shape particles with dG ≈ dA N 5 µm are produced at concentrations higher than 1.2% (w/w) due to an excessive shell buckling. Despite the hollow spherical morphology, the SEM image of the nano-aggregates from Run A1 in Fig. 2A reveals a relatively high S/R ratio signifying a low degree of hollowness that results in their dA to be slightly larger than 4 µm. The spray drying condition therefore must be further modified to increase the degree of hollowness (i.e. reduce ρeff). For this purpose, the effect of adding a small volume of ethanol to increase the drying rate is investigated. Spray drying using 10% (v/v) ethanol solution is conducted at pH of 3 and 9, respectively, in Runs A2 and A3 as silica nanoparticles are highly stable at both pH [32]. The other spray-drying parameters are kept identical to those in Run A1. Using 10% (v/v) ethanol solution, nano-aggregates, which have relatively similar dG (≈5–6 µm) as Run A1's, but considerably lower ρeff (≈0.3 g/cm3), are produced at both pH= 3 and 9. The lower ρeff obtained in Runs A2 and A3, which signifies a higher degree of hollowness, is validated by the SEM image in Fig. 2B, where nanoaggregates having a lower S/R ratio compared to that of Run A1 are apparent. Importantly, the resulting nano-aggregates possess dA b 4 µm as a result of the lower ρeff. The geometric particle size distribution of the nano-aggregates from Runs A2 and A3 is shown in Fig. 3 to be bimodal with dG modes around 8 and 18 µm. Therefore, these nano-aggregates possess the ideal dG and dA for an effective inhaled delivery. In an attempt to further reduce ρeff, the ethanol concentration is increased to 30% (v/v) at pH = 3 and 9 in Runs A4 and A5, respectively. The results at both pH, however, suggest that increasing the ethanol concentration does not significantly affect both dG and ρeff. The geometric particle size distribution of the nano-aggregates from Run A5 in Fig. 3 is also comparable to that of Run A3. In summary, spray drying using 90:10 (v/v) water–ethanol solutions at the current operating condition is sufficient in the open-loop mode to produce nano-aggregates having the desired dG and dA values. As the nano-

Table 1 Summary of Runs A1–A5: effect of ethanol inclusion. Run

Ethanol (% v/v)

pH

dG (µm)

ρeff (g/cm3)

dA (µm)

A1 A2 A3 A4 A5

0 10 10 30 30

3 3 9 3 9

5.0 4.6 6.2 6.1 5.8

0.73 0.27 0.32 0.27 0.34

4.2 2.4 3.5 3.2 3.4

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Fig. 2. SEM images of nano-aggregates obtained in (A) Run A1 using 100% water, and (B) Run A3 using 90:10 % (v/v) water–ethanol solution.

aggregate morphology has been shown to be not affected by the pH, the subsequent runs are conducted at pH = 9 unless noted otherwise. 3.2. Effect of silica: mannitol concentration ratio Despite having a high degree of hollowness (S/R ratio ≈ 10% from the SEM images), the nano-aggregates produced in Runs A2–A5 exhibit low steady-state %T values (b3%) even after sonication, which suggest extremely poor re-dispersibility. The low %T denotes a strong

nano-aggregate binding force of the silica nanoparticles, such that an inclusion of a water-soluble excipient (i.e. mannitol) to form the “excipient bridges” is mandatory for the nano-aggregate re-dispersion. As the mannitol inclusion not only alters the nano-aggregate redispersibility, but also the morphology, the optimal silica: mannitol concentration ratio must be systematically determined. For this reason, the effects of the silica: mannitol ratio on the nanoaggregate morphology and re-dispersibility are examined at a constant nanoparticle concentration. The results are presented as Runs B1–B4 in Table 2. A t-test analysis of variance has indicated that the variations in dG and ρeff at different silica: mannitol ratios in Runs B1–B4 are statistically significant. A sample calculation of the t-test analysis is provided in Appendix A. The silica nanoparticle concentration is fixed at 1.0% (w/w) and the silica: mannitol concentration ratio is varied between 10:1 and 2:3 by increasing the mannitol concentration. At the highest silica: mannitol ratio (Run B1), nano-aggregates having dG ≈ 8 µm and ρeff = 0.2 g/cm3 are produced signifying a higher degree of hollowness compared to that in Runs A2–A5. Furthermore, a high spray-drying yield (N70%) and a low Carr's index value (b25) denoting high flowability are obtained. Nonetheless, the nanoaggregates from Run B1 are not re-dispersible (%T b 3%) suggesting an inadequate amount of the mannitol. Spray drying at lower silica: mannitol ratios in Runs B2–B4, however, results in nano-aggregates of higher ρeff and the spray-drying yields become considerable lower. Importantly, their dA becomes larger than 4 µm hence they are unsuitable for inhaled delivery. Despite the higher ρeff (i.e. higher S/R ratio), the steady-state %T value of Run B4 is considerably higher (≈12%) than that of Run B1, thought it is not high enough to be considered effectively re-dispersible. Taking a closer look at the re-dispersion process, the SEM image of the re-dispersed nano-aggregates from Run B2 in Fig. 4A indicates that the nano-aggregates sustain their micron-size structure upon re-dispersion resulting in the low %T (≈5%). Similar observations are made for Runs B1 and B3. In contrast, the re-dispersed nano-aggregates from Run B4 are shown in Fig. 4B to disintegrate into irregularly-shaped smaller size fragments as the mannitol dissolves resulting in the higher %T. Importantly, the results of Runs B1–B4 suggest that the aqueous re-dispersibility can be improved by decreasing the silica: mannitol ratio. Nevertheless, the improved re-dispersibility is achieved at the expense of having less than ideal nano-aggregate morphology (i.e. higher ρeff). In this regard, the silica: mannitol ratio can be decreased by either (1) decreasing the silica nanoparticle concentration to be below than 1.0% (w/w), or (2) increasing the mannitol concentration above 1.5%(w/w) while keeping the other concentration constant. Importantly, the two approaches likely have different impacts on the nano-aggregate morphology. The effect of decreasing the silica nanoparticle concentration at a relatively constant mannitol concentration (≈ 0.9–1.0% w/w) to obtain the lower silica: mannitol ratio is examined first in Runs B5–B7. The results in Table 3 indicate that spray drying at a low nanoparticle concentration (b0.4% w/w) in the presence of a significant amount of mannitol leads to the production of irregularly shaped particles,

Table 2 Summary of Runs B1–B4: effect of silica: mannitol ratio at 1.0% (w/w) silica concentration. Run

Fig. 3. Geometric particle size distributions of Runs A1, A3, and A5.

B1 B2 B3 B4

Concentration Silica (% w/w)

Mannitol (% w/w)

1.0 1.0 1.0 1.0

0.1 0.5 1.0 1.5

Ratio

dG (µm)

ρeff (g/cm3)

dA (µm)

CI

Yield (%)

10:1 2:1 1:1 2:3

7.8 7.1 5.7 8.1

0.20 0.60 0.41 0.46

3.4 5.6 3.7 5.4

24 56 23 31

73 60 42 48

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Table 4 Summary of Runs C1–C6: effect of silica: mannitol ratio at 0.8% (w/w) silica concentration. Run

C1 C2 C3 C4 C5 C6 a

Fig. 4. SEM images of re-suspended nano-aggregates for (A) Run B2 and (B) Run B4.

which are undesirable due to their unpredicted aerosolization properties. These results suggest that the nano-aggregate morphology depends not only on the silica: mannitol ratio, but also on the silica nanoparticle concentration, which must be kept sufficiently high to produce the desired morphology. Therefore, the effect of lowering the silica: mannitol ratio by increasing the mannitol concentration at a constant nanoparticle concentration is investigated next. 3.3. Identifying the optimal silica: mannitol ratio in terms of the nanoaggregate morphology The silica nanoparticle concentration in the subsequent runs (Runs C1–C6 in Table 4) is set to a slightly lower value of 0.8% (w/w) to reduce the amount of mannitol required at lower silica: mannitol ratios. The lower total solute concentration is aimed to improve the likelihood of obtaining low density nano-aggregates at lower silica: mannitol ratios. The silica: mannitol ratio is varied between 2:3 and 1:6 by increasing the mannitol concentration. Similar to the result of Run B4, the nano-aggregates produced in Run C1 at silica: mannitol ratio = 2:3 possess dA N 4 µm as a result of the high ρeff. Furthermore,

Concentration Silica (% w/w)

Mannitol (% w/w)

0.8 0.8 0.8 0.8 0.8 0.8

1.2 2.0 2.0a 2.4 3.2 4.8

Ratio

dG (µm)

ρeff (g/cm3)

dA (µm)

CI

Yield (%)

2:3 2:5 2:5 1:3 1:4 1:6

8.5 7.3 7.4 6.4 7.4 8.0

0.75 0.27 0.58 0.29 0.36 0.41

7.3 3.8 5.6 3.4 4.4 5.1

48 31 33 21 19 19

31 29 50 74 70 64

pH = 3.

the nano-aggregates are rather cohesive resulting in poor flowability as reflected in the high Carr's index value. The spray-drying yield is also low around 30% as a considerable amount of the particles are not recovered from the cyclone separator due to their cohesiveness. Importantly, the steady-state %T value of Run C1 does not increase beyond 12% indicating poor re-dispersibility similar to Run B4. The optimal silica: mannitol ratio must therefore be lower than 2:3. Decreasing the silica: mannitol ratio to 2:5 and 1:3 in Runs C2 and C4, respectively, significantly improves the particle morphology, where hollow spherical nano-aggregates with dG ≈ 7 µm and dA b 4 µm are produced. The nano-aggregates in both runs exhibit relatively low Carr's index values denoting reasonable flowability. The spray-drying yield of Run C2, however, is slightly less than 30% compared to 74% for Run C4. In an attempt to improve the spray-drying yield of Run C2, the run is repeated at pH = 3 in Run C3 while keeping the other parameters constant. The lower pH does improve the yield to 50% but at the expense of the morphology, where nano-aggregates of high ρeff are produced. The geometric particle size distributions of Runs C2 and C4 in Fig. 5 are comparable to each other, where both exhibit bimodal distributions with dG modes around 10 and 24 µm similar to those obtained from Runs A2–A5. The high mannitol concentration is therefore found to not significantly alter the geometric particle size distribution. The SEM image of the nano-aggregates produced in Run C4 in Fig. 6A denotes the large hollow spherical morphology. A closer look at one particle with a broken shell in Fig. 6B reveals the low S/R ratio (≈10%) signifying a high degree of hollowness manifested by the low ρeff of 0.29 g/cm3. Importantly, the surface chemical composition map of the nanoaggregates obtained from the EDX analysis (Fig. 7) indicates a homogeneous distribution of the silica nanoparticles and the mannitol throughout the surface. The chemical composition of the spray-dried particles is found to be comparable in magnitude (±10% w/w) to the solute composition in the spray-drying feed solution. Hence, the

Table 3 Summary of Runs B5 – B7: effect of silica: mannitol ratio at low silica concentrations. Run

B5 B6 B7

Concentration Silica (% w/w)

Mannitol (% w/w)

0.40 0.30 0.24

1.00 0.90 0.96

Ratio

Shape

2:5 1:3 1:4

Irregular Irregular Irregular

Fig. 5. Geometric particle size distributions of Runs C2 and C4.

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the nano-aggregate morphology is equal to 1:3. Next, a similar study is conducted at nanoparticle concentrations of 0.72, 0.90, and 1.10% (w/w) to examine whether the optimal silica: mannitol ratio is also found at 1:3. The results at 0.90 and 1.10% (w/w) in Runs D1 and D3 in Table 5, respectively, indicate that the optimal silica: mannitol ratios are also at 1:3, where a further increase or decrease in the silica: mannitol ratio would lead to the production of nano-aggregates having inferior morphologies. On the other hand, at 0.72% (w/w) in Run D4, the optimal silica: mannitol ratio is found to be slightly lower at 1:4. The effect of spray drying at pH = 3 is re-examined in Run D2, whose result indicates that higher ρeff nano-aggregates are produced similar to that observed in Run C3.The result signifies the important role of the pH in the resulting nano-aggregate morphology in the presence of mannitol. Importantly, the nano-aggregates produced in Runs D1, D3, and D4 exhibit relatively low Carr's index values (≤31) and reasonably high spray-drying yields (N65%). Therefore, they together with Runs C2 and C4 represent the five promising formulations in terms of their morphology, whose aqueous re-dispersibility needs to be evaluated next. 3.4. Identifying the optimal silica: mannitol ratio in terms of the aqueous re-dispersibility

Fig. 6. SEM images of Run C4 (A) large hollow spherical nano-aggregates and (B) their close-up view.

presence of nanoparticle clusters, which are difficult to re-disperse as observed Runs A2–A5, can be minimized with the mannitol inclusion provided that the correct silica: mannitol ratio is selected. Decreasing the silica: mannitol ratio further to 1:4 and 1:6 in Runs C5 and C6, respectively, leads to the production of nano-aggregates having both slightly larger dG and higher ρeff resulting in dA N 4 µm. In short, the results of Runs C1–C6 at 0.8% (w/w) nanoparticle concentration indicate that the optimal silica: mannitol ratio in terms of

The steady-state %T, Sf/Si ratios, and % re-dispersed of the five promising formulations (i.e. Runs C2, C4, D1, D3, and D4) are summarized in Table 6. In addition, the aqueous re-dispersibility of Runs C5, C6, and D2, which exhibit less than ideal morphologies, are also characterized to examine the impact of the nano-aggregate morphology on their re-dispersibility. A t-test analysis of variance in Appendix A has indicated that the variations in the %T and Sf/Si values obtained between Runs C5, C6, D2 and Runs C2, C4, D1, D3, D4 are statistically significant. For the five promising formulations, the % redispersed and (Sf/Si) Aft values of Runs C2, C4, D1, D3, and D4 are found to be relatively constant at ≈80% and 1.5–2.0, respectively. On the other hand, their %T and (Sf/Si) Bef values are more sensitive to the differences in their formulations. Theoretically, nano-aggregates that are poorly re-dispersible are to exhibit low %T, high (Sf/Si) Bef, and low % re-dispersed. For the proposed aqueous re-dispersibility characterization techniques to be proven reliable, the %T values obtained from different experimental runs must first be shown to (1) increase with decreasing (Sf/Si) Bef values and (2) increase with increasing % re-dispersed values. In this regard, the %T values reported in Table 6 have been found to be correlated with the values of (Sf/Si) Bef and % re-dispersed in manners that follow the theoretical predictions after taking into account the experimental uncertainties. The aqueous re-dispersibility can therefore be reliably characterized using the techniques proposed in the present work. Comparing the results of Runs C2 and C4 with those of Runs C5and C6 suggests that the aqueous re-dispersibility is not necessarily improved by decreasing the silica: mannitol ratio below the optimal point. The %T values of Run C4 as a function of time are shown in Fig. 8

Table 5 Summary of Runs D1–D4: optimal silica: mannitol ratio at different silica concentrations. Run

D1 D2a D3 D4 Fig. 7. EDX surface analysis (nanoparticles = green, mannitol = red) of Run C4.

a

Concentration Silica (% w/w)

Mannitol (% w/w)

0.90 0.90 1.10 0.72

2.70 2.70 3.30 2.88

pH = 3.

Ratio

dG (µm)

ρeff (g/cm3)

dA (µm)

CI

Yield (%)

1:3 1:3 1:3 1:4

6.9 7.6 5.8 7.0

0.35 0.50 0.40 0.30

4.0 5.4 3.7 3.8

19 32 31 23

67 58 81 81

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361

Table 6 Aqueous re-dispersibility parameters from different formulations. Run

%T

(Sf/Si)

C2 C4 C5 C6 D1 D2 D3 D4

44 ± 1 41 ± 6 28 ± 8 26 ± 1 39 ± 9 12 ± 1 31 ± 2 57 ± 7

12 20 39 47 29 87 27 6

Bef

(Sf/Si) 1.4 1.4 1.2 5.8 1.4 1.5 1.3 2.1

Aft

% re-dispersed (w/w) 75 ± 0.8 76 ± 1.4 60 ± 2.4 44 ± 1.9 76 ± 2.3 32 ± 3.0 84 ± 0.2 80 ± 2.2

to be higher at all times than those of Run C6. Not unexpectedly, the (Sf/Si) Bef value of Run C4 is also found to be lower than that of Run C6, whereas an opposite trend is observed for % re-dispersed. The nanoparticle size distributions of the re-dispersed nano-aggregates before the first centrifugation in Fig. 9A clearly indicate that a significant fraction of the nano-aggregates from Run C4 can be re-dispersed into nanoparticles in the ≈20 nm range. In contrast, a majority of the nano-aggregates from Run C6 only re-disperse down to the ≈1 µm range. Similar trends are observed when Run C2 is compared with Run C5 but not presented here for brevity. The weaker re-dispersibility of Runs C5 and C6 relative to that of Runs C2 and C4 is postulated to be caused by their higher S/R ratios that lead to poorer particle wetting. The significance of the S/R ratio role in the resulting aqueous re-dispersibility is also evident when the results of %T and (Sf/Si) Bef of Run D2 are compared with those of Run D4 in Figs. 8 and 9B, respectively. The results again suggest that Run D2, which possesses a higher S/R ratio, exhibits lower %T and higher (Sf/Si) Bef compared to Run D4. Significantly, these comparisons indicate that the silica: mannitol ratio that produces nano-aggregates having the optimal morphology also results in nano-aggregates having the high aqueous re-dispersibility. Among the five promising runs, Run D4 is found to re-disperse most readily as it exhibits the highest %T (≈60%) and the lowest (Sf/Si) Bef (≈6). The size distribution peaks of the re-dispersed nano-aggregates from Run D4 in Fig. 9B indicate that a majority of the nano-aggregates readily re-disperse into nanoparticles with size that is similar in magnitude as the nanoparticle size before the spray drying (Si ≈ 25± 2 nm). A smaller fraction of the re-dispersed nano-aggregates represented by the lower peak are recovered either as (1) aggregate fragments in the size

Fig. 9. Nanoparticle size distributions of (A) Runs C4 and C6; (B) Runs D2 and D4 before 1st centrifugation.

range of several hundred nanometers, or (2) agglomerates of the primary nanoparticles that are recently formed in the suspension. Not coincidentally, Run D4 also exhibits one of the lowest ρeff (≈0.3 g/cm3) among the five runs hence reaffirming the significant influence of the degree of hollowness on the resulting aqueous redispersibility. In summary, the optimal formulation in terms of both the nano-aggregate morphology and aqueous re-dispersibility is obtained at 0.72% (w/w) nanoparticle concentration with silica: mannitol ratio of 1:4. The result from the optimal formulation signifies the potential of employing the hollow spherical nano-aggregates as an inhaled delivery vehicle of drug-bearing silica nanoparticles. 4. Conclusion

Fig. 8. % Transmittance as a function of time for Runs C4, C6, D2, and D4.

Micron-size dry-powder aggregates of biocompatible silica nanoparticles are manufactured by the spray drying technique to be potentially developed as an inhaled delivery vehicle of drug-bearing silica nanoparticles. The nanoparticles are transformed into hollow spherical nano-aggregates having dG N 5 µm and dA ≈ 2–4 µm ideal for an effective delivery to the lung. The spray-drying condition (i.e. inlet temperature, feed concentration, pH, feed and gas flow rates) to obtain the large hollow spherical morphology has been determined. To be therapeutically effective, the dry-powder nano-aggregates must readily re-disperse into the primary nanoparticles in an aqueous medium to not compromise the drug targeting ability and the release rate. In this regard, the presence of a water-soluble excipient (i.e. mannitol) that forms “excipient bridges” interconnecting the nanoparticles has been found to be mandatory in enabling the nanoaggregate re-dispersion. An aqueous re-dispersibility characterization technique, which utilizes the variations in the turbidity level of the nano-aggregate suspension upon re-dispersion, has been developed to complement the results from the nanoparticle size measurement.

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The nano-aggregate morphology in the presence of mannitol has been found to be governed by both the nanoparticle concentration and the silica: mannitol concentration ratio. The nano-aggregate aqueous re-dispersibility has been found to depend on (1) the silica: mannitol concentration ratio, where an increased mannitol presence above the optimal value does not necessarily lead to higher aqueous re-dispersibility, and (2) their degree of hollowness, where nano-aggregates with higher S/R ratios are less readily to re-disperse due to the poor particle wetting. The optimal silica: mannitol ratio, which leads to the production of highly redispersible nano-aggregates having the desired morphology, has been identified. Hollow nano-aggregates with the highest re-dispersibility are obtained from spray drying at 0.72% (w/w) nanoparticle concentration and silica: mannitol ratio = 1:4. At this condition, approximately 80% of the nano-aggregates are re-dispersed into primary nanoparticles having the same size as the original nanoparticles. Nomenclatures CI dA dG DS Pe r R S Sf Si %T % re-dispersed T ρeff ρbulk ρunity τD

Carr's index particle mean aerodynamic diameter (µm) particle mean geometric diameter (µm) nanoparticle diffusion coefficient (m2/s) Peclet number droplet radius (µm) particle radius (µm) shell thickness (µm) nanoparticle diameter after spray drying (nm) nanoparticle diameter before spray drying (nm) % transmittance % of the nano-aggregate mass that have re-dispersed temperature (°C) particle effective density (g/cm3) particle bulk density (g/cm3) particle unit density (g/cm3) convective drying time (s)

t-test parameters x1, x2 mean of samples 1 and 2, respectively s1, s2 standard deviation of samples 1 and 2, respectively n1, n2 number of independent replicates of samples 1 and 2, respectively D.O.F degree of freedom α probability of error at the prescribed confidence interval (α = 0.05) tcalc calculated t-test parameter tα/2, DOF standard t-test parameter at the given α and D.O.F

Subscript Bef Aft

before the first centrifugation after the first centrifugation

Acknowledgement A financial support from Nanyang Technological University's StartUp Grant (Grant No. SUG 8/07) is gratefully acknowledged. Appendix A. t-test analysis The t-test of statistical significance is conducted for dG, ρeff, %T, and (Sf/Si) Bef for runs at different silica: mannitol ratios. A sample t-test calculation for Runs C4 and C6 is provided in Table A.1. At 95% confidence interval, the difference in the sample means is statistically

significant and not due to the random occurrence when tcalc N tα/2, DOF or when t calc b −tα/2, DOF. In this regard, the t-test results in Table A.1 clearly indicate the variations in dG, ρeff, %T, and (Sf/Si) Bef between Runs C4 and C6 are statistically significant. Table A.1 Parameter

x1

s1

x2

s2

n1 = s2

DOF

tα/2,DOF

tcalc

dG ρeff %T (Sf/Si)

6.4 0.29 41 1.4

0.384 0.0203 5.74 0.042

8.0 0.41 26 5.8

0.522 0.0287 1.04 0.174

4 3 3 6

10 8 7 8

2.228 2.306 2.365 2.306

− 5.206 − 5.913 4.454 − 60.212

Bef

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