Sizing of powders in inhalers with an AerosizerJ according to.pdf

7/26/2019 Sizing of powders in inhalers with an AerosizerJ according to.pdf

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Aerosol Science 35 (2004) 509527

www.elsevier.com/locate/jaerosci

Sizing of powders in inhalers with an AerosizerJ according toa mixed experimental factorial design

P.J. Mendesa;b, A. Raposoa;b, J.M.M. Sousab, J.F. Pintoa ;

aDept. de Tecnologia Farmaceutica, Faculdade de Farm acia da Universidade de Lisboa,

Av. Prof. Gama Pinto 1649-003 Lisboa, PortugalbDept. de Engenharia Mecanica, Instituto Superior Tecnico, Universidade Tecnica de Lisboa,

Av. Rovisco Pais 1, 1049-001 Lisboa, Portugal

Received 18 March 2003; received in revised form 18 September 2003; accepted 3 October 2003

Abstract

In the present work, the AerosizerJ with the AerodisperserJ is used to assess the size and size distribution

of two common dry powder inhalers: Ventilan RotacapsTM (salbutamol sulfate) and Bricanyl TurbohalerTM

(terbutaline sulfate), according to a mixed factorial design. The dierent parameters of the equipment (voltage

applied to the detector, shear force, deagglomeration, feed rate and pin vibration) were the factors considered

in the design, set to dierent levels. Altogether, a full 41 31 23 factorial was considered and the results

of the experiments analyzed according to the Montgomery technique. Results have shown that samples with

a single population of particles were less aected by the changes in the parameters, whereas for mixtures

incorporating dierent populations results were aected upon change of the levels of the factors. The voltage

at the detector was the most important factor, followed by the shear force. By contrast, pin vibration and feed

rate were less signicant. The interactions between variables were also responsible for signicant changes in

the results and should not be neglected throughout the measurements.

? 2003 Elsevier Ltd. All rights reserved.

Keywords: Aerosizer; Factorial design; Montgomery technique; Dry-powder inhaler; Salbutamol sulfate; Terbutaline sulfate

1. Introduction

In recent years, a great development on aerosols and related technology has been observed and

the dispersion of ne powders or liquids found application in the administration of drugs to humans.

Corresponding author. Tel.: +351-217-946-434; fax: +351-217-937-703.

E-mail address: [email protected] (J.F. Pinto).

0021-8502/$ - see front matter? 2003 Elsevier Ltd. All rights reserved.doi:10.1016/j.jaerosci.2003.10.005
mailto:[email protected]:[email protected]


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510 P.J. Mendes et al. / Aerosol Science 35 (2004) 509 527

Aerosols have been used in the treatment of diseases, namely those aecting the respiratory tract.

The main advantages of the respiratory route, as compared to the oral one, are the lower dose of

drug required to achieve the same therapeutic eect, in turn leading to decreased side eects, and

an earlier onset of the drugs eect (Wierlik, Diepenmaat, & Damhuis, 2002).Dry powder inhalers (DPIs) play a major role in aerosol therapy because they are chlorouoro-

carbon (CFC) free (Wierlik et al., 2002; Dunbar, 2002), less dependent on patients coordination on

inhalation, easy to formulate and less aected by environmental changes (e.g. temperature) (Ramon

et al., 2000). Ramon et al., 2000 provided that their components have adequate properties (Hickey,

2002). However, the size of the particles and the way they interact are critical for a proper deposition

in the alveoli (Gonda, 1992), and sizing of the particles is, therefore, of paramount importance for

a good therapeutic eect.

There are many in vitro methods for sizing DPI particles. Examples of compendial methods are

the cascade impactor (e.g. Andersen multi-stage impactor), and the multistage liquid impinger (e.g.

twin impinger) (US Pharmacopoeia, 26). Unfortunately, these methods are time consuming (up to1 h per measurement) by contrast to other analyzers which give measurements in minutes (Peters,

Vanderpool, & Wiener, 2001). Examples of such equipment are the time-of-ight (TOF) based

aerodynamic particle size analyzers, such as the AerosizerJ, the Aerodynamic Particle SizerJ spec-

trophotometer or the E-SpartJ (Mitchell & Nagel, 1999). These analyzers are often used in the

assessment of medicinal aerosols, either dry powder or pressurized metered dose inhalers (pMDIs).

The particle size distribution spectrum obtained reects the dierences in the aerodynamic diameters

of particles present in the aerosol. For instance, a DPI containing lactose (larger particles), as the

drug (salbutamol sulfate, smaller particles) carrier, exhibits a spectrum with two peaks that could

be cautiously related to the individual symmetrical spectra produced for both lactose and salbutamol

sulfate particles (Srichana, Brain, Marriott, & Martin, 2000). However, care must be observed when

measurements are carried out, since when suspensions of pMDIs are considered, the measured valuesdier from those obtained by other techniques (Mitchell, Nagel, & Archer, 1999). This reects the

vulnerability of the method when disperse systems are considered, with some preferential removal

of larger mass median aerodynamic diameter (MMAD) particles, due to the evaporation of solvent

and/or inertial gravitational deposition (Nagel, Wiersema, Bates, & Mitchell, 2002), thus leading

to dierent results. Moreover, when DPIs are considered, the ability of the equipment to disperse

particles is highly dependent on the properties of the materials (Laitinen & Juppo, 2003). In a less

conventional application of this technique, the use of a third laser beam has been suggested in order

to avoid the particle density dependency of the method (Oskouie, Noll, & Wang, 2003). The use of

adequate mathematical models, that allow the calculation of the particles lumped density and shape

factors (Oskouie, Noll, & Wang, 2002) have also been suggested.The technique described above has several advantages as compared to others: (a) the large number

of particles counted per second, (b) the easy operating procedure and maintenance and (c) the small

sample size required. However, some limitations have been pointed out (Mitchell & Nagel, 1996)

such as: (a) the particles are detected on a one at a time basis, therefore some particles may not

be detected particularly at high feed rates; (b) the equipment assumes that all the particles are

spherical and (c) the equipment is unable to distinguish between particles belonging to dierent

populations (e.g. drug and excipients), so all the particles are detected and treated identically and

(d) the density of the sample must be known. The rst limitation aects seriously the counting

eciency and can create false peaks. Since the equipment determines the aerodynamic diameter and


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P.J. Mendes et al. / Aerosol Science 35 (2004) 509 527 511

then calculates the geometric diameter using the density of the material, an incorrect value for the

density of the material produces wrong values for the geometric diameters, without aecting the

aerodynamic diameter because the AerosizerJ measures the TOF of individual particles which is

dependent on their mass. Moreover, non-spherical particles present dierent velocities of ight fromspherical particles due to dierences on the drag coecients. For the above-mentioned limitations,

special care should be taken in the analysis of the results since a DPI can have more than two

dierent populations of particles with dierent drag forces, densities and shapes, leading to inaccurate

measurements, a drawback shared with other techniques. It follows that the AerosizerJ provides more

accurate results for single populations of particles rather than for mixtures of dierent populations of

particles, i.e., populations made of dierent chemical identities, and therefore showing multimodal

distributions. The equipment may also underestimate the aerodynamic sizes of airborne particles from

both powder and pressurized inhalers, often requiring a comparison with other measuring techniques

(Nagel et al., 2002).

The aim of the present work was the assessment of the performance of the AerodisperserJ

AerosizerJ on the characterization of two DPIs when all the operating parameters were considered

in a factorial experimental design. This design, selected on the ground of its robustness and because

the variables (equipment settings) can be considered simultaneously, allows for the evaluation of the

possible interactions between variables after establishing the relative importance of each parameter,

by the Montgomery method (Montgomery, 1996).

2. Material and methods

In this work, VentilanTM RotacapsTM (GlaxoWellcome) and BricanylJ TurbohalerJ (AstraZeneca)

were used as model DPIs, whose particle size aect their therapeutic ecacy. The rst is presentedto patients as a hard gelatin capsule containing 200 g of salbutamol sulfate (in 25 mg of powder),

whereas the second contains 500 g of terbutaline sulfate per blister. For calibration purposes, two

sets of spheres were considered: one of nylon (mean diameter standard deviation of 5 1:5 m,

Dantec Measurement Technology GmbH, Germany), and another of glass (mean diameterstandard

deviation of 10:0 1:0 m, Duke Corporation, Palo Alto, CA, USA).

In these experiments, the two types of DPIs were analyzed by using an AerodisperserJAerosizerJ

(TSI, GmbH, Aachen, Germany). Briey, this equipment operates by suspending the particles in the

air, using a disperser, a uidizer and a deagglomerating device (AerodisperserJ), before this air

ow is expanded into a vacuum. This vacuum draws the particles through a ow nozzle, produc-

ing a precisely controlled acceleration to a high-speed (subsonic) aerosol jet (Allen, 1990) in theAerosizerJ. Fig. 1 presents the assembly considered in the present study. The velocity of the air

remains constant in the measurement region but the particles accelerate at dierent rates, inversely

related to their aerodynamic size (Barber, 1993). Two laser beams (at a known distance between

them) placed in the nozzles exit allow the measurement of the time required for the particles to

travel between them and, thus, the velocity. The scattering of the beams by the particles induces the

emission of an electrical signal by the detector, made of photomultiplier diodes, starting/stopping a

clock. The particles aerodynamic diameter is calculated from the time elapsed between the two sig-

nals (Laitinen & Juppo, 2003). Traveling times are in the order of hundreds of nanoseconds for small

particles and thousands of nanoseconds for larger particles. The measurement of the aerodynamic


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Fig. 1. Schematic representation of the AerodisperserJ connected to the AerosizerJ.

diameter of particles is automatically compensated for changes in shape, surface irregularities, mass

and refractive index. Visual inspection of the samples was made by scanning electron microscopy(Phillips Analytical, UK).

Prior to the analysis of the DPIs, according to a factorial experimental design, the equipment was

calibrated with both types of spheres and validated for reproducibility and eectiveness of counting.

These characteristics were assessed by the run time and presentation of the data according to size

distribution by number and by volume, as a function of the aerodynamic diameter. To check the

counting eciency of the AerosizerJ, lactose monohydrate (Granulac 200, Meggle, Germany) and

microcrystalline cellulose (Avicel PH-101, FMC Corp., USA) were used as received, in the same

quantity (6 mg) as that collected from the DPIs. The distribution of the populations was characterized

by the mode, or, if otherwise referred in the text, by another measure of central tendency.

2.1. Experimental design

Experiments were carried out according to a mixed factorial design and the results were analyzed

by the method described by Montgomery (1996). Briey, this statistical technique allows the trans-

formation of an n-level factor (with n 2) into a k2 factorial design (kfactors at two levels each),

and the assessment of the eect of each factor and their interactions on the results. In the present

investigation, a 413123 mixed factorial design was considered, where the exponents represent the

equipment variables and the bases stand for the levels of each variable in the experiments (Table 1).

According to this method, the variables with three or four levels can be converted into two variables


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Table 1

Equipment variables and levels considered in the experiments

Variables Levels

Photomultiplier voltage (PMV) (V) 850 1100

Shear force (SF) (Psi) 0.5 1.5 3.0 4.0

Deagglomeration (D) 0 1

Feed rate 103 (FR) (counts/s) 15 10

Pin vibration (PV) 0 1

with two levels each (22) (Myers & Montgomery, 1995). Therefore, for a variable with two levels,

this technique indicates the eect of that variable on the results when it changes from the lowest to

the highest level. For a variable with three levels, it indicates the average eect of that variable foreach level (levels 1 to 2 or levels 2 to 3). Thus, when the variable changes from the lowest to the

highest level, the magnitude of the eect doubles the value found for the intermediate variations.

With factors at four levels, Montgomerys technique produces three results: the rst corresponds to

the average eect when the factor changes from levels 1 to 2 or 3 to 4, the second corresponds to

the average eect of the change from levels 1 to 3 or 2 to 4 and the third reects the tendency of

the change. Consequently, the total eect is the sum of the rst and second results.

The dierent magnitudes of the eects observed were compared by an analysis of variance

(ANOVA) of the factorial design with more than two levels (Armstrong & James, 1996), and

the levels of signicance assessed by an F-test. The smallest values of the mean squares were aver-

aged and considered as the experimental error in experiments. Appendix A presents a more detailed

explanation of the method.

3. Results and discussion

3.1. Preliminary experiments

At rst, the good performance of the measuring equipment was ascertained with the calibration

spheres. The mean geometric diameters by number measured with the AerodisperserJAerosizerJ

conguration were 4.97 and 10:45 m for the spheres of nylon and glass, respectively. The dierences

to the nominal values of 5.00 and 10:00 m were, therefore, 0:03 m (i.e., 0.6%) and 0:45 m (i.e.,4.5%), respectively. These dierences were deemed acceptable and indicative of the ability of the

AerosizerJ to measure the diameter of the particles accurately. Moreover, as shown in Fig. 2,

the narrow distribution of the geometric diameters by number is identical to that reported by the

manufacturers for the calibration spheres.

In a separate set of experiments, it was observed that the run time of the equipment was pro-

portional to the number of particles counted and dependent on the feed rate: the higher the feed

rate, the shorter the run time (Fig. 3). A change from the largest to the lower feed rate decreased

the number of counts per second from 1950 (higher) to 1460 (medium) and 590 (lower). The

eect of the number of particles counted on the diameter measured has been studied by using the


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Fig. 2. Distribution by number of counts for the calibration spheres: () spheres of nylon, (- - - - - -) spheres of glass.

Fig. 3. Relationship between the run time and the number of particles counted as a function of feed rate: ( ) low, ( )

med, () high.

Fig. 4. Relationship between the aerodynamic diameters (mode) of particles and the number of particles counted: ()

distribution by number, ( ) distribution by volume.

pharmaceutical VentilanTM RotacapsTM (salbutamol sulfate). Once the parameters of the equipment

have been set, it was realized that for a number of counted particles larger than 120,000, the geo-

metric aerodynamic diameter (modes shown) was more uniformly distributed (Fig. 4). This gure

takes 54 runs into consideration and shows the results for the aerodynamic diameters obtained in


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Fig. 5. Size distributions for microcrystalline cellulose samples detected at 850 V (a) and 1100 V (b): () 1 mg,

( ) 4 mg, () 8 mg, () 16 mg, () 24 mg.

distributions by number and by volume, and the number of counted particles in each run. As an-

ticipated, as the sample size increases (reected by the number of counts), the precision of the

measurement also increases (reected by a decrease of the standard deviation). Above 120,000 par-

ticles, the dispersion of the mode values was small enough for the measurement to be considered

acceptable. For samples of other materials, a dierent number of counts was required (results not

shown) for the readings to become reproducible. For instance, when microcrystalline cellulose was

used, a minimum sample quantity of 8 and 4 mg were required when results were detected at 850

and 1100 V, respectively (Fig. 5).

As previously discussed, when DPIs are considered, one should be aware that more than one

population of particles may be present in the sample. There is, usually, one population of drugparticles (small in size) and another of the carrier (larger particles). The proportion between the two

populations has an impact on the therapeutic eect of the drug and, consequently, it is important

to characterize them adequately. In this part of the study, carried out using VentilanTM RotacapsTM

(containing particles of both salbutamol sulfate and lactose), the evaluation of both populations was

possible by considering the particle size distribution both by number and by volume. It was possible

to estimate the approximate geometric diameters (modes) of both components in the formulation,

due to the large dierence in size between the two populations of particles. In short, the averages of

the modes found in 54 runs were calculated and the values of 1:48 m (by number) and 68:9 m

(by volume) were estimated for the drug and carrier particles, respectively. The validity of the


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Fig. 6. Relationship between the diameter (mode) expressed by volume and by number of counts.

procedure is supported on the ground that dierent measurements have shown that the diameters by

number and by volume are not related (Fig. 6). In fact, in this gure, a scattered distribution of

the readings is observed, with no relationship between the geometric diameters by number and by

volume, as expected.

Thornburg, Cooper, and Leith (1998) observed that the counting eciency (ratio of the number

of particles detected to the number of particles passing through the detector) of the AerosizerJ is

variable. The same authors (Thornburg et al., 1998) stated that counting eciencies below 100%

or, variations dependent upon particle size, would give inaccurate size distributions. Furthermore,

factors, such as the concentration of the sample, the model of the equipment, the voltage at thedetector, the measurement of particles with diameters below 7 m or acceptance of counting rates

above 20,000 particles per second, were also described as aecting the counting eciency of the

equipment. These observations were conrmed in the present work, when particles of lactose were

considered. In fact, for samples with the same mass and equivalent number of counts, the size

distribution of the particles varied at small number of counts.

After performing a few tests with VentilanTM RotacapsTM, it was noticed that the size distribution

of the particles was not constant between runs performed under the same conditions, even for sam-

ples taken from the same capsule, although the modes of the distributions (peaks) remained constant.

This fact shows that the counting eciency changes with the size of the particles in dierent runs

and samples. Furthermore, we noticed that the values read in the equipment were discontinuous,i.e., identical values were registered several times, whereas in between values were never found.

This happens because the AerosizerJ collects the TOF of the particles in 2048 linearly spaced time

channels, which are converted by the software into 500 logarithmically spaced sized bins (Amherst

Process Instruments). Consequently, the equipment presents the rounded value in the bin instead

of showing the true measurement. This eect of rounding the results is dicult to assess be-

cause the software of the equipment shows the results already in bins and, therefore, that some

lack of consistency in the measurements is expected. Results are presented in a more discrete way

than the measurements, and consequently, some lack of accuracy, reproducibility or sensitivity can

be anticipated.


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Fig. 7. Eect of the voltage in the detector over the size of the particles. Insets show scanning electron photomicrographs

of BricanylJ TurbohalerJ and VentilanTM RotocapsTM, () BricanylJ TurbohalerJ (1100 V), (- - -- - -) BricanylJ

TurbohalerJ (850 V), ( ) VentilanTM RotacapsTM (1100 V), (- - - - - -) VentilanTM RotacapsTM (850 V).

Results present in both Figs. 4 and 6 stress these observations since the results are organizedaccording to horizontal and vertical lines, rather than a scattered distribution. This problem may aect

the analysis of the samples, especially of those populations with large particles. When the results

are represented as percentages this dierence is less signicant, but dierences in the aerodynamic

and geometric diameters can still be observed, even though the samples have been prepared under

the same conditions.

3.2. Factorial design

The performance of the AerosizerJ changed with the voltage applied to the detector, as observed

when the voltage was changed between measurements, both for the calibration spheres and theaerosols. A narrower distribution curve was obtained when the voltage was increased (Fig. 7), and

in all cases, the number of counted particles was higher for the highest voltage, as observed already

byThornburg et al. (1998).In close agreement with the work ofMitchell and Nagel (1996),dierent

sensitivities of the detector did not aect the mean geometric diameter for the calibration spheres

(nylon) with a very narrow size distribution as opposed to the results observed for the inhalers (large

sizes distributions).

In the case of BricanylJ TurbohalerJ, the distributions had identical shapes for the two recom-

mended values of the photo-multiplier voltage (850 and 1100 V), although dierent geometric mean

diameters and smaller base lines of the peaks were observed for the highest voltage (Fig. 7, open


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circles). Like the calibration spheres, this DPI presents only one population of particles (Fig. 7 and

micrograph associated with curves), but a wider particle size distribution. In both cases, only one

peak was observed. When the sensitivity of the equipment was increased, smaller particles were

detected more easily, and, thus, a shift of the distribution of the curve to smaller sizes was observed(mean diameters diered by 34%, whereas the mode remained constant). However, when the shear

force was changed from peak to low, the aerodynamic diameters (modes) increased from 0.76

to 0:79 m (0.3% increase). As this product does not contain any excipient, it can be assumed that

the shear force only promotes a minor separation of the particles of terbutaline, the only component

in the formulation (Fig. 7, open circles and micrograph).

When VentilanTM RotacapsTM was considered, the aerodynamic diameters expressed by the number

of counts originated three peaks within the distribution. This type of distribution is due to the presence

of several groups of particles present in the product (Fig. 7, open squares and micrograph). For this

product, a higher voltage led to a shift of the peaks towards smaller sizes (Fig. 7). On the other

hand, when the results (aerodynamic diameter) were expressed by volume, only a slight shift of theresults towards smaller sizes was observed, suggesting a higher sensitivity of the detector to smaller

particles, as mentioned previously. For VentilanTM RotacapsTM, the dierences between the means

(aerodynamic diameter) of the particles observed for high and low voltages on the detector were

0:52 m (33%) and 23:02 m (33%) for number and volume distributions, respectively (Table 2).

When all the results of the factorial design were considered, it was possible to express them in

terms of modes of the aerodynamic diameters, either by number or by volume. Results of the eects

are shown both in Tables2and3. Table2 presents the variations on the distribution by number and

by volume of the aerodynamic diameters observed for the dierent samples of the pharmaceuticals

considered. The upper part refers to the main eects or individual eects when a single variable

was changed at a time. Therefore, it is possible to assess the impact of each operational parameter

(variable) over the size distribution of samples. Table3 presents the results of the ANOVA performedon the experimental data emphasizing their degree of signicance as reected by the F-values. An

increase on the voltage of the photomultiplier promoted a decrease on the aerodynamic diameter

(mode) of 0.52 and 23:02 m, respectively by number and by volume (Table 2). This variable is

the most signicant one with a value ofp 0:001 (Table 3). The sensitivity of the detector aects

the number of counts, and, thus, the size of the sample. In order to obtain consistent and reproducible

results, the magnitude of this parameter must be carefully chosen and, thus, special care should be

taken on the selection of the photo-multiplier voltage.

When the shear force applied (Fig. 8a and b) was increased from low to peak, an increase on

the measured diameter (by number) was observed. In fact, when two levels were considered (low

to high and medium to peak), the eect was signicant (SF2, Table 2 and p 0:01, Table 3).This increasing tendency is aected only in a few cases by an increase on the shear force from

high (3 Psi) to peak (4 Psi), resulting in measured diameters that were equal or smaller (Fig. 9a

and b). Results in Table 2 do not show this linear tendency, but it should be borne in mind that

the dierence between levels low and medium and high and peak is only 1 Psi, whereas the

dierence between medium and high is 1:5 Psi. On the other hand, an increase on the shear force

(Fig. 8a and b) often leads to a decrease on the measured diameter for larger particles (upper parts

of the graphs in Figs. 8 and 9). Although the observation is not signicant (Table 3, distribution by

volume) and the results do not show a particular tendency (Fig. 9a and b), it is possible to suggest

that by increasing the shear force, the separation between the particles was promoted, as mentioned


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Table 2

Results of the main eects and interactions from the calculations, carried out according to the Montgomery technique

Variables and interactions Distribution by number (m) Distribution by volume (m)

Main eects

Photomultiplier voltage (PMV) 0.52 23.0

Shear force

Total (SFtotal) 0.17 1.15

1 level (SF1) 0.05 0.49

2 levels (SF2) 0.12 0.66

Shape of tendency line 0.01 0.52

Deagglomeration (D) 0.00 1.65

Feed rateTotal (FRtotal) 0.02 1.92

1 level (FR1) 0.01 0.96

Shape of tendency line 0.00 3.51

Pin vibration (PV) 0.02 0.23

Binary interactions

PMVSFtotal 0.12 0.26

PMVD 0.03 0.19

PMVFRtotal 0.01 0.06

PMVPV 0.01 0.05

SFtotalD 0.03 0.58

SFtotalFRtotal 0.03 0.90

SFtotalPV 0.02 0.20

DFRtotal 0.02 1.06

DPV 0.01 0.66

FRtotalPV 0.01 1.06

elsewhere (Houzego, 2002). Because larger particles present higher contact areas, the adhesion and

cohesion between them are larger too. Consequently, the eect of the shear force is observed mainly

on the smaller particles of the drug with a shift of the peak observed in the distribution by number to

larger sizes. This variable is particularly important for samples containing more than one populationbut, even for a single population, the shear force changes the values measured, as a consequence of

the additional deagglomeration produced.

Regarding the deagglomeration, when this parameter is set to high, the particles are transported

from the sample cup to the dispersion pin at a higher velocity. Hence, a stronger impact on the pin

occurs generating a larger force to separate the particles (Houzego, 2002). It can be assumed that

the same sort of explanation given for the eect of the shear force applies to the deagglomeration

variable. For smaller particles, a change from normal to high in deagglomeration failed to produce

a major dierence between the results (Table 2), whereas for larger particles a reduction on the

measured sizes was observed (Fig. 8a and b), although not statistically signicant (Table 3).


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Table 3

Results of the ANOVA for the dierent experiments, according to the Montgomery technique

Degrees of Distribution by number Distribution by volume

freedom

Sum of Mean F Sum of Mean F

squares squares squares squares

Variables

Photomultiplier voltage (PMV) 1 6.82 6.82 9443.0 11806.4 11806.4 1793.5

Shear force (SF) 3 0.53 0.17 245.0 41.21 13.73 2.09

Deagglomeration (D) 1 0.00 0.00 0.00 26.15 26.14 3.97

Feed rate (FR) 2 0.01 0.00 4.85 323.0 161.5 24.54

Pin vibration (PV) 1 0.01 0.01 11.08 24.63 24.63 3.74

Binary interactions

PMVSF 3 0.13 0.04 59.08

52.15 17.38 2.64PMVD 1 0.03 0.03 42.92 13.39 13.39 2.04

PMVFR 2 0.02 0.01 15.23 136.1 68.08 10.34

PMVPV 1 0.00 0.00 5.54 3.95 3.94

SFD 3 0.07 0.02 31.85 119.8 39.92 6.07

SFFR 6 0.05 0.01 12.00 242.8 40.47 6.15

SFPV 3 0.09 0.03 39.23 9.87 3.28

DFR 2 0.01 0.00 3.46 88.41 44.20 6.72

DPV 1 0.00 0.00 18.62 18.61 2.83

FRPV 2 0.03 0.01 20.08 80.80 40.39 6.14

Blank spaces represent results associated with the experimental error.p 0:05,p 0:01,p 0:001.

The feed rate directly inuences the number of particles counted by unit of time. The

AerodisperserJ adjusts automatically the air jet to satisfy the value selected for the aforementioned

parameter. Table 2and Fig. 8(a and b) show a general decrease on the size of both small and large

particles when the feed rate was increased. However, the dierences in the particles characterized

by smaller diameters are not very signicant, although this variable promoted a signicant decrease

(p 0:01, Table 3) on the aerodynamic diameter by volume, i.e., over particles with larger sizes.

Eventually, a synergistic eect occurred at high feed rates due to the presence of more particles,

promoting cluster formation and the detection of apparently larger particles. Fig. 10(ad) shows thediameter of the particles as a function of feed rate for the dierent values of the voltage applied to

the detector when the pin vibration was on and o. Pin vibration aects the deposition of particles

on their way to the detector. Data clearly show that a more consistent pattern was observed when a

distribution by number of counts was considered, as compared to the distribution by volume (see,

respectively, lower and upper parts of Fig. 10). Pin vibration did not produce a major eect on the

size distribution (Fig. 8a and b, Table 2) and distribution by number was barely aected (Table 3)

by a change on the pin vibration status. Even though, if a distribution by volume is considered, two

remarks have to be made: (a) some of the observed dierences were not due to the AerosizerJ but

to variations in the content of the capsules and (b) the most important component in the capsules


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Fig. 8. Aerodynamic diameter of the particles as a function of parameters level: low (a) and high (b) voltage in the

detector. () shear force, () deagglomeration, () feed rate, ( ) pin vibration.

(salbutamol sulfate) was assumed to show the smallest particles, while the excipient (lactose) was

associated with the largest particles and less uniform size distribution.

The interactions of the variables at two levels (binary interactions) were more relevant for the

results presented by number of counts (smaller particles) than for the results presented by volume,

suggesting that the distribution by number is more sensitive to changes of these variables than the

distribution by volume. These interactions can occur between 2, 3, 4, or 5 parameters (results not

shown). However, as the number of interactions increases, the interpretation of the eect becomesmore dicult because the variables contribute dierently to the nal result. Results not presented

have shown that as the level of the interaction increases, the module of the result tends to decrease

even if the result is highly signicant. Thus, interactions with higher number of levels (more than

3) have proved to be more dicult to discuss based solely on the data available.

Interesting to point out are the results for the interaction between PMV and SF (p 0:001,

Table 3). A positive value for the distribution by number (Table 2) suggests an interaction between

the two variables, whereby the overall decrease on the value of the mode (balance between the

eect of PMV and SF) is about half of the value expected. For the interaction between PMV and

D and PMV and FR although an interaction was expected this time, the value is smaller for the

rst interaction and larger for the second when the balance between the main eects of the variablesare considered. These interactions are signicant at p 0:001 and 0:01, respectively (Table 3).

It can be assumed that these variables change the sample in the way it is presented to the detector.

Also signicant are the interactions between the shear force and other variables (SF and D, FR and

PV). On the contrary, interactions such as PMVPV, DFR orDPV are not signicant. A possible

explanation for these observations is that the shear force transforms agglomerates in individual

particles that are measured by the detector. Since neither the pin vibrator nor the deagglomeration

directly aect the process of counting, their interactions are not signicant.

Due to the fact that the signicant interactions were observed for the measurements by number,

the results presented by volume were not discussed in detail.


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Fig. 9. Eect of the shear force on the measured diameter of the particles with pin vibrationOn (a) and O (b).

( - - -- - -) deagglomeration: normal; feed rate: low; () deagglomeration: high; feed rate: low; (- - -- - - )deagglomeration: normal; feed rate: med; () deagglomeration: high; feed rate: med; (- - - - - -) deagglomeration:

normal; feed rate: high; () deagglomeration: high; feed rate: high.

4. Conclusions

The study has proved the ability of the AerosizerJ to determine the aerodynamic and geometric

diameters both by number and by volume of counts. Although the equipment performs in a fairly

constant way, its calibration is convenient prior to measurements. As anticipated, the measurements

made by the equipment are more accurate for powders containing single populations of particles,

rather than with samples made up of two or more populations, which are more sensitive to changesin the parameterization of the equipment. However, if two populations of particles with distinct size

distribution are present, it is still possible to characterize each population in the mixture, provided

adequate analysis of the results is made.

It was observed that the larger the number of particles counted, or the lower the feed rate, the

larger the required run time of the equipment. The counting eciency and reproducibility were

aected by the number of counts performed. For the two pharmaceuticals considered in the study,

for example, a minimum of 120,000 counts were necessary. Since a dierent number of counts

is required when other materials are considered, a preliminary evaluation of these parameters is

recommended before starting the analysis.


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Fig. 10. Measured diameter of the particles as a function of feed rate at dierent voltages applied to the detector: (a)

850 V and pin vibrationOn; (b) 850 V and pin vibrationO; (c) 1100 V and pin vibrationOn; (d) 1100 V and pin

vibrationO. (- - - - - -) Shear force: low; deagglomeration: normal; (- - - - - -) shear force: med; deagglomeration:

normal; (- - - - - -) shear force: high; deagglomeration: normal; (- - - - - -) shear force: peak; deagglomeration: normal;

() shear force: low; deagglomeration: high; () shear force: med; deagglomeration: high; ( ) shear force:

high; deagglomeration: high; () shear force: peak; deagglomeration: high.


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Table 4

Layout of a table for a 23 factorial design

A B C AB AC BC ABC

(1) + + +

A + + +

B + + +

C + + +

AB + + +

AC + + +

BC + + +

ABC + + + + + + +

Table 5

Conversion of a three level factor into factors A and B

Three level Two level

X A B

x1

x2 +

x2 +

x3 + +

eects. Eects for the factors and interactions are found by application of the signs to the set of

experimental results.

To nd the main eect or the interaction eect, the signs in the corresponding column are

multiplied by the corresponding combination, added and the sum divided by 2k1.

For example, the eect of A is

A = 1

231[(a + ab + ac+ abc) ((1) + b + c+ bc)]

and the interaction ABC is

ABC= 1

231[(abc+ a + b + c) ((1) + ab + ac+ bc)]:

A.2. More than two levels for each factor

The method just described cannot be used with three or four levels for each factor. To overcome

the problem, Montgomery has developed a technique that allows the analysis of these factorials.

Let X be a three level factor (x1; x2; x3), it can be decomposed into two factors with two levels

each, factors A and B (Table 6):

Let Y be a four level factor (y1; y2; y3; y4), it can be decomposed into the factors C and D,

(Table 5):


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Table 6

Conversion of a four level factor into factors C and D

Three level Two level

Y C D

y1

y2 +

y3 +

y4 + +

In practice, these new factors substitute the three or four levels of individual factors and can be

used as mentioned previously, including the calculation of the eects and interactions.

In the analysis of the results the eect of A has to be added to the eect of B to nd the eect

of X, and the eect of C to the eect of D to show the eect of Y.

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