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Binderless granulation of pharmaceutical lactose powders
Powder Technology 122 Ž2002. 212–221 www.elsevier.comrlocaterpowtec
Binderless granulation of pharmaceutical lactose powders Katsura Takano a , Kazuo Nishii a , Akiko Mukoyama b, Yuki Iwadate b, Hidehiro Kamiya b, Masayuki Horio b,) a
b
Fuji Paudal Co. Ltd., Osaka 536-0005, Japan Department of Chemical Engineering, Tokyo UniÕersity of Agriculture and Technology, 2-24-16 Nakamachi, Koganei, Tokyo 184-8588, Japan Received 26 September 2000; received in revised form 30 December 2000; accepted 11 January 2001
Abstract With a binderless fluidized bed granulation method ŽPressure Swing Granulation, PSG., jet-milled lactose particles were successfully agglomerated into narrow and spherical granules. This should be the first achievement of binderless granulation from an organic powder indicating the high potential of PSG application to pharmaceutical processes. With a decrease in the mean diameter of primary particles, the granules’ mean diameter decreased, and the compression strength of a single granule increased. The size of product lactose granules predicted by the Iwadate–Horio wPowder Technol. 100 Ž1998. 223x model was in good agreement with the experimental results obtained by sieve analysis. q 2002 Elsevier Science B.V. All rights reserved. Keywords: Fluidized bed; Pressure Swing Granulation; Binderless; Lactose; Dry powder inhalation
1. Introduction In many powder process industries, including pharmaceutical, ceramics and powder metallurgy, granulation is an important method for the improvement of powder handling. Especially for fine powders, which are difficult to handle due to their fliability and cohesiveness, granulation is effective to reduce the difficulties. To obtain granules from fine powders, most granulation systems use binders in wet conditions. However, binders often cause troubles such as contamination in products, unwanted solubility reduction or too much strength to disintegrate. Concerning the strength, those granules applicable to dry powder inhalation have to be sufficiently weak to be easily decomposed and dispersed to form aerosols. Accordingly, Pressure Swing Granulation ŽPSG. granules have a potential for dry powder inhalation, for which wet granulation would never provide any possibilities. To solve the above problems, the PSG, a binderless fluidized bed granulation method, has been proposed by Nishii et al. w2x. It utilizes the spontaneously agglomerating nature of group C powders of the Geldart classification w3x, which was quantitatively investigated by Sugihara w4x and
Jimbo w5x early in 1966. In PSG, their agglomerating nature is accelerated and controlled by the cyclic fluidization and compaction by the alternative upward and downward gas flow. The down blow also returns the fines captured by the filter. Thus, agglomerates are subject to the controlled growth by adjusting their sizes, strength and shapes effectively. PSG granules have rather spherical shape, uniform diameter and strength sufficient to keep them as granules during storage, weighing and feeding but sufficiently weak to shape or dissolve into a solvent in downstream processes. The PSG technology has already been successfully applied to hardmetal cutting tool manufacturing process w6x and will be further applied to other industries. This work aims at examining the possibility of PSG in pharmaceutical granulation processes. Since lactose is generally used for excipients, it was chosen for the test material. In this paper, the maximum allowable lactose diameter to obtain good PSG granules, the product granule properties and the theoretical prediction of granule sizes are investigated. 2. Experimental procedures
)
Corresponding author. Tel.: q81-42-388-7067; fax: q81-42-3863303. E-mail addresses: [email protected] ŽK. Takano., [email protected] ŽM. Horio..
2.1. Primary particle preparation Seven samples were prepared from DMV Pharmatose 200 M by hammer-mill ŽFuji Paudal, K II G-1S. or jet-mill
0032-5910r02r$ - see front matter q 2002 Elsevier Science B.V. All rights reserved. PII: S 0 0 3 2 - 5 9 1 0 Ž 0 1 . 0 0 4 1 8 - 1
K. Takano et al.r Powder Technology 122 (2002) 212–221 Table 1 Milling condition
213
Table 2 Granulation conditions
Jet mill
No. 4
Sample no.
Milling cycles Ža.
Jet pressure ŽMPa.
Feed pressure ŽMPa.
3 4 5 6 7
1 2 1 1 2
0.05 0.10 0.60 0.45 0.30
0.10 0.10 0.35 0.45 0.40
ŽFuji Paudal, JM-1.. Table 1 shows the milling condition. The primary particle diameter was determined by a laser diffraction particle size analyzer ŽShimadzu, SALD-1100 Ver.2.10., and the specific surface area was by BET ŽYuasa Ionics, QUANTASORB Jr... Bulk density was determined by weighing a 50 = 10y6 m3 cup full powder. 2.2. Granulation Fig. 1 shows a schematic of the PSG granulator. The fluidized bed column was made of PMMA resin. Its internal surface was covered with a cellophane tape ŽNichiban, CT-18. so that the electrostatic adhesion of particles can be reduced. The internal diameter of the column was 0.108 m in lower part and 0.151 m in its upper part, where a bag-filter of 0.07 m in diameter and 0.157 m long was hung from the top flange. Table 2 shows the experimental conditions. In each granulation run, lactose powder was charged into the col-
Powder batch mass Gas velocity and fluidization time Compaction pressure and time Distributor vibration frequency Granulation time
120 g 0.263 mrs: 15 s 0.351 mrs: 15 s 0.03 MPa: 1 s 40 Hz 120 min
umn through a 16 mesh Ž1.0 mm. sieve to adjust initial agglomerate sizes by disintegrating large agglomerates. The distributor plate was vibrated at 40 Hz to assist fluidization. 2.3. Characterization of product granules The size distribution of product granules was determined by standard sieves, and the surface-to-volume mean diameter d a,sv was determined. Bulk density r bulk was determined by weighing a 50 = 10y6 m3 cup full granules of the size y12 mesh Ž1.41 mm.. The external surface of granules of the size y32 q 42 mesh Ž0.5–0.35 mm. was observed by an optical microscope as well as by a SEM. The porosity was measured by mercury porosimetry ŽShimadzu, Pore Sizer 9310. for granules of size y24 q 32 mesh Ž0.71–0.5 mm.. The compression strength of granules was measured by a micro compression testing machine ŽShimadzu, MCTE-200, the indenter rod diameters 0.5 mm. for granules of size y32 q 42 mesh Ž0.5–0.35 mm..
Fig. 1. Experimental apparatus and condition.
K. Takano et al.r Powder Technology 122 (2002) 212–221
214
plastic deformation, Type B is elastic brittle fracture and Type C is plastic deformation. For each case, Ff was determined as illustrated. The cohesive force of a primary particle Fpp was calculated with the following Rumpf w8x equation from the tensile strength s and the porosity of a granule ´a : Fpp s
ps d p2
Ž 2.
Ž 1 y ´a . n pk ,a
where n pk,a is the coordination number of primary particles in agglomerates. According to Nakagaki and Sunada w9x, n pk,a is correlated by .48 n pk ,a s 1.61 ´y1 a
Ž ´a O 0.82 . .
Ž 3.
3. Preparation and characterization of primary powders
Fig. 2. Classification of fracture tensile strength measurements by a micro compression testing machine.
Fig. 2Ža. shows a conceptual compression force vs. displacement relationship. When breakage of a granule takes place, there appears a nearly horizontal part in the force-displacement curve. From the fracture force Ff , the tensile strength s can be calculated by the following Hiramatsu and Oka w7x equation:
ss
2.8 Ff
p d a2
Fig. 3 shows the SEM images of lactose powders before and after milling. For Nos. 2 and 3 powders, we can observe many large particles of 10–100 mm, having crystal facets. As particle sizes became smaller, their edges were rounded off and more spherical particles were obtained. Table 3 shows properties of milled lactose powders. Fig. 4 shows size distributions of lactose powders before and after milling, from which surface-to-volume mean diameter d p,sv was calculated. Specific surface area S w,calc was calculated by d p,sv on the assumption that particles were spherical. Then, Carman’s shape factor fs,BET is equal to S w,calcrS w,BET . If fs,BET is close to 1, particles are of smooth surface and spherical. Fig. 5 shows the relationship between the mean diameter and the specific surface area S w,BET of primary particles. Except for Powder No. 4, specific surface area S w,BET was larger for smaller mean diameter. Powder No. 4 had a surface area larger than No. 5. However, the mean diameter of Powder No. 5 was smaller than No. 4. The reason of this contradictory phenomenon is thought to be because Powder No. 5 was milled only once. Instead, Powder No. 4 was obtained by milling two times and had more damage on particle surface, as can be seen from the cracks on the surface in the SEM image.
4. Granulation results 4.1. Limiting factors to produce PSG granules
.
Ž 1.
In reality, there were several types in force–displacement curves as shown in Fig. 2Žb.. Type A is the elastic
Fig. 6 shows microphotographs of PSG granules obtained from Nos. 2–7 powders. From Nos. 1–3 powders no good agglomerates were obtained.
K. Takano et al.r Powder Technology 122 (2002) 212–221
215
Fig. 3. SEM images of primary particles of lactose before and after milling.
When Powder No. 1 was fluidized, the bed was in slugging condition in the beginning then uniformly fluidized. This was in contrast with other powders, all of which showed channeling in the beginning. Powder No. 1 is classified into group C but very close to group A in Geldart classification. The poor agglomeration tendency of Powder No. 1 was also confirmed by the fact that Powder No. 1 particles passed through both the bag-filter and the distributor. The bed of Powder No. 2 was partly channeled and partly fluidized. Agglomerates were visually observed both on its bed surface and on the wall side, but they were easily broken during compression cycles. However, Powder No. 2 did not pass through the bag-filter nor the distributor. Powder No. 3 was fluidized in a manner similar to No. 2. When gas flow rate was 0.263 mrs, agglomerates were observed only on the bed surface. When gas flow rate was increased to 0.351 mrs, fluidization and formation of small agglomerates in the bed were confirmed by visual observation from the wall. However, those agglomerates were easily broken in compression cycles. Powder No. 3 did not pass through the bag-filter but did a little through the distributor.
From Powder Nos. 4–7, these showed good agglomerating fluidization. All of their product granules then did not pass through the bag-filter nor the distributor. From the above results, the limiting size of primary particles for reasonable binderless granulation of lactose is found to be roughly 4.8 mm, which corresponds to the mean size of No. 4. However, although Powder No. 5 had smaller particle size than No. 4, the granules obtained from No. 5 were poorer than those from No. 4. As mentioned in Section 3, Powder No. 4 had larger surface area. More strictly, the specific surface area could be more important factor than particle size for successful binderless granulation. More work is however necessary to further generalize this point. 4.2. Characterization of PSG granules Fig. 7 shows the SEM image of the granules with their surface-to-volume mean diameter d a,sv . Granule products Nos. 4, 5, and 6 were spherical and their surfaces were rough. On the other hand, granule product No. 7 was spherical with rather smooth surface. Fig. 8 shows the size distributions of granules. For larger S w,BET of primary particles the size distribution of
Table 3 Primary particles’ characteristics Sample No. 1 2 3 4 5 6 7
d p,50 Žmm. 27.1 12.5 9.36 7.77 4.67 4.20 2.97
d p,sv Žmm. 13.8 7.48 4.95 4.79 4.14 3.71 2.58
S w,BET Žm2rkg. 3
0.56 = 10 0.86 = 10 3 0.73 = 10 3 1.60 = 10 3 1.17 = 10 3 2.04 = 10 3 4.48 = 10 3
S w,calc Žm2 rkg. 3
0.30 = 10 0.75 = 10 3 0.79 = 10 3 0.82 = 10 3 0.95 = 10 3 1.06 = 10 3 1.52 = 10 3
r bulk Žkgrm3 .
fs,BET Ž – .
5.4 = 10 2 3.6 = 10 2 4.1 = 10 2 2.5 = 10 2 2.4 = 10 2 1.7 = 10 2 1.8 = 10 2
0.541 0.855 1.08 0.496 0.809 0.520 0.339
K. Takano et al.r Powder Technology 122 (2002) 212–221
216
granules tended to become narrower. In particular, No. 7 had a very narrow size distribution in comparison with other’s. As fluidizing velocity was increased from 0.263 to 0.351 mrs, the fraction of larger granules increased and also mean diameter of product granules increased Žcf. Fig. 9.. Fig. 10 shows the pore size distribution of granules determined by mercury porosimetry. As the mean diameter of primary particles become smaller, the pore size shifted to smaller side. In Fig. 10, the part of the distribution below the separation size of about 7 mm should correspond to the voidage inside of granules Ži.e. pores., and the part above the separation size should be to the void in between granules. From these data, the granule porosity ´a was determined as shown in Table 4. Table 4 also shows compression strength s and bulk density of granules r bulk,a . The compression strength of granules No. 7 was more than three times as large as the other samples. Except for No. 4, ´a decreased as primary particle size decreased. Fig. 11Ža. shows the effect of primary particle diameter on the cohesive force between primary particles Fpp estimated by Eq. Ž2. from experimental data for s and ´a . Although there exists a wide scatter, mean values of Fpp increased as the primary particle diameter increased except for No. 7. The higher mean cohesion force of No. 7 is consistent with its lower porosity shown in Table 4. Fig. 11Žb. shows the proportion of the three fracture types of granules defined in Fig. 2Žb.. All granules of Nos. 4–6 were classified into Type C Žplastic deformation.. Roughly 90% of granules of product No. 7 was classified into Type B Želastic brittle.. This is probably because No. 7 had a hard shell around the granules but the others did not. 5. Prediction of agglomerate sizes 5.1. Outline of Iwadate–Horio (IH) [1] model IH model is based on the knowledge of bed compaction and expansion by bubbles w10x. By careful examination of
Fig. 5. Relationship between the mean diameter and the specific surface area of primary particles.
Davidson’s w11x bubble model, they found that the bed expansion force acts on the emulsion phase above a bubble and that the compaction force acts below it. In an agglomerating fluidized bed agglomerates are attrited on the one hand, and re-agglomerated on the other by the bubble motion, reaching those with an equilibrium size. In IH model the equilibrium agglomerate size is derived by equating the cohesive force Fcoh,rup between two agglomerates with the hydrodynamic expansion force Fexp which is a function of bubble size, based on the following assumptions: 1. At an equilibrium condition the bed expansion force above a bubble equals the cohesive rupture force between agglomerates. Thus, we can write Fcoh ,rup s Fexp .
Ž 4.
2. The bed consists of spherical agglomerates of uniform size d a , voidage ´a and minimum fluidization velocity u mf,a . 3. The emulsion phase voidage is uniform and equal to ´mf . 4. The bed expansion force is estimated by Horio et al. w10x model with a representative bubble size predicted by Mori–Wen w12x correlation for z s Lc Ž Lc : static bed height.. The effective expansion stress is proportional to the stress at the bubble nose multiplied by a factor h. Thus, Fexp s
ps b ,exp d a2
s b ,exp s h Ž yPˆs ,max .
Ž yPˆs ,max . s D b y D bm Fig. 4. Size distributions of primary particles.
Ž 5.
Ž 1 y ´mf . n k
D b 0 y D bm
½
1 0.843
ž
Db 2
ra g Ž 1 y ´mf .
for 2D bubble for 3D bubble
s exp y0.3
Lc Dt
/
.
Ž 6. Ž 7. Ž 8.
K. Takano et al.r Powder Technology 122 (2002) 212–221
217
Fig. 6. Microphotographs of PSG granules of lactose.
Where D b0 and D bm in Eq. Ž8. are obtained as Db0 s
3.77 g
Ž u 0 y u mf ,a . y0.2
D bm s 2.59 g
½
2
: initial bubble diameter
Ž u 0 y u mf ,a .
p Dt2 4
Ž 9.
this difficulty, let us check the possibility of utilizing the experimentally determined values of s for agglomerates Žcf. Section 2.3. to predict Fcoh,rup . Since we can write Eq. Ž7. for the cohesive force
0.4
5
: maximum allowable bubble diameter.
Fpp f FvdW s
Ž 10.
For minimum fluidization velocity of agglomerates u mf,a we can write the following expression by applying Wen– Yu correlation w13x for agglomerates of mean diameter d a and density ra :
m s da rf
ž(
33.7 2 q
0.0408 d a3
r f Ž ra y r f . g m2
/
y 33.7 .
Ž 11 . 5. The cohesive rupture force Fcoh,rup for the two spherical agglomerates in contact having the gap between surfaces d we can write: Fcoh ,rup s
Ha d a Ž 1 y ´a . 24d 2
Ž 12 .
where Ha is Hammaker constant. As investigated by Tsubaki and Jimbo w14x, cohesive force between solid surfaces depends not only bed voidage but also the surface characteristics and compaction pressure. In Eq. Ž12., the effects of both compaction as well as surface morphology are included through d . However, in many cases, both Ha and d 2 are unknown. To overcome
Ž 13 .
24dpp2
where dpp is the gap between primary particles. By equating Eq. Ž13. with Eq. Ž2. and solving it for Hard 2 , we obtain. Ha
dpp2 u mf ,a
Ha d p
24p d p s
s
Ž 1 y ´a . n pk ,a
.
Ž 14 .
By assuming dpp 6 d and by substituting Eq. Ž14. into Eq. Ž12., finally the following expression is obtained for cohesive rupture force Fcoh,rup between agglomerates: Fcoh ,rup s
d pps n pk ,a
da .
Ž 15 .
In the following calculation the experimentally determined values shown in Table 4 are substituted. Fig. 12 shows a calculated example for the relationship between Fcoh,rup and Fexp as a function of d a . In Fig. 12 Fcoh,rup and Fexp have two intersections. Point A is a stable solution but Point B is an unstable one. At Point A a positive perturbation of d a creates a situation of Fexp ) Fcoh,rup , and a negative perturbation does Fexp - Fcoh,rup . In both cases the deviation from the intersection can therefore be recovered. However, in the case of Point B, this happens in an opposite way. Therefore, Point A should be the solution we aim at. However, we still have an unknown parameter
218
K. Takano et al.r Powder Technology 122 (2002) 212–221
Fig. 7. SEM images and surface-to-volume mean diameter of product granules d a,sv .
h in Eq. Ž6.. Iwadate–Horio calculated the average value of h for the upper half of a spherical region of radius R b to 3 R b around a 3D bubble and obtained hav s 0.0611 and used this value to obtain d a . However, it is still not clear if this average value is effective. Therefore, in the present work, an extreme case where Fexp contacts with Fcoh,rup , i.e. Point C in Fig. 12, is taken as a critical solution or an index that separates stable and unstable agglomerate sizes. 5.2. Comparison of granulate size of experiment and prediction Fig. 8. Size distributions of product lactose granules.
For lactose granulates, Fcoh,rup and Fexp were predicted. Experimental values were needed for granule voidage ´a , mean diameter of primary particles d p , and the tensile strength of agglomerates s . Bed voidage ´ and the static bed height Lc are given respectively by: r bulk ,a ´s1y Ž 16 . ra Lc s
W
r bulk ,a A t
Ž 17 .
where W is charged mass of powder, r bulk,a is bulk density of granules, A t is the bed cross sectional area and
Fig. 9. Effect of fluidizing velocity on product granule diameter.
Fig. 10. Pore size distribution of PSG granules determined by mercury porosimetry.
K. Takano et al.r Powder Technology 122 (2002) 212–221
219
Table 4 Granules’ characteristics Ž u 0 s 0.351 mrs except for No. 6=Ž u 0 s 0.263 mrs.. Sample No.
d a,sv Žmm.
´a Ž – .
s ŽNrm2 .
ra Žkgrm3 .
r bulk,a Žkgrm3 .
No. 4 No. 5 No. 6 No. 7 No. 6 Ž u0 s 0.263 mrs.
677 788 607 373 533
0.493 0.601 0.596 0.579 0.603
2.00=10 4 1.22=10 4 2.36=10 4 7.38=10 4 1.38=10 4
776 610 618 644 607
4.2=10 2 3.4=10 2 3.1=10 2 3.5=10 2 2.8=10 2
ra is agglomerate density. ra is calculated by using rp and ´ a : ra s rp Ž 1 y ´a . .
Ž 18 .
In Fig. 13, the prediction procedure is demonstrated for several cases, where h was adjusted until Fexp contacts with Fcoh,rup with only one point Ži.e. critical condition.. The value of h , thus, determined is expressed, in the following, by hcr . hcr is different for different lactose
Fig. 12. A model of agglomerating fluidization and defluidization w1x.
Fig. 11. Fracture tensile strength and cohesive force.
samples as a result of the difference in Fcoh,rup which was obtained from the experimentally determined s . The agglomerate sizes thus predicted are compared with those experimentally determined in Fig. 14. Predicted results for Nos. 4 and 5 are within "10% accuracy showing the validity of the modified IH model with the critical condition. However, for smaller primary particles, i.e. for Nos. 6 and 7, predicted results became larger. Particularly for No. 7, predicted result is about two times as large as the experimental. Here, it should be noted that the observed agglomerate sizes are all less than or almost equal to the predicted ones for the critical condition. This is a reasonable tendency because the critical condition gives the maximum size of stable agglomerates. Iwadate and Horio w1x examined the effect of gas velocity on granule size. In their work, both predicted and experimentally determined granule sizes increased as gas
220
K. Takano et al.r Powder Technology 122 (2002) 212–221
Fig. 13. Agglomerate size determination by I-H model with the critical condition ŽPSG: 2 h, pre-sieving by 16 mesh..
velocity decreased. In their prediction, Fcoh,rup was kept constant for different gas velocity. However, in the present work, the average value of d a,sv increased from 533 to 607 mm with a gas velocity increase of from 0.263 to 0.351 mrs as already shown in Fig. 8, obtained by using the value ´a and s shown in Table 4, d a,calc was predicted from IH model as 690 and 726 mm for u 0 s 0.263 and 0.351 mrs, respectively. Although the predicted values are
larger than the experimental data, the experimental tendency of size increase with gas velocity at least for the case of lactose was confirmed. From experimentally determined size of lactose granules’, the coefficient h in Eq. Ž6. can be obtained by equating Eq. Ž5. with Eq. Ž15. and solving it for h. Thus, determined h , expressed by h ) , is then given by
h)s
2 n k d p s d a ,obs
Ž yPˆmax . D b ra gn pk ,a
.
Ž 19 .
Table 5 shows the comparison between hcr and h ) . For Nos. 4 and 5, h ) is close to hcr . However, for Nos. 6 and 7 h ) was larger than hcr . The observed size smaller than predicted may be because of the effect of increased granule density but the search for the reason of the discrepancy is still a tough open issue for the future work.
Table 5 Comparison between hcr and hobs Ž u 0 s 0.351 mrs.
Fig. 14. Comparison of predicted and observed granule diameters.
Sample No.
hcr
h)
4 5 6 7
0.0577 0.0390 0.0808 0.152
0.0581 0.0391 0.0842 0.202
hav s Žy Ps,av .rŽy Ps,max . s 0.0611. Ps,av sy0.0515, Ps,max sy0.843 for a 3D bubble w1x.
K. Takano et al.r Powder Technology 122 (2002) 212–221
6. Conclusions
n pk,a
To extend the Pressure Swing Granulation ŽPSG. technology to pharmaceutical processes, milled lactose powders were granulated without binders by PSG and the properties of product granules were investigated. The big potential of the pharmaceutical application of PSG and our capability of quantitative prediction of product granule size has been confirmed. Ž1. Limiting primary particle size to obtain granulates was 4.79 mm and the minimum requirement for specific surface area was 1 = 10 3 m2rg. Ž2. The product granules had small mean diameter, narrow size distribution, spherical shape and rather smooth surface. Ž3. When fluidization velocity was increased from 0.236 to 0.351 mrs, the mean diameter of product granules increased. Ž4. For finer primary particles, stronger cohesive force was obtained for a contact point between particles inside a granule. Ž5. Experimentally determined granule sizes were compared with those predicted by Iwadate–Horio model combined with a critical condition where the curve of cohesive rupture force vs. granule size contacts with the curve of bed expansion force. By using experimentally determined tensile strength s , predicted results for Nos. 4 and 5 were within the accuracy of "10% of the experimental.
Pˆs Pˆs,max
List of At Db D b0 D bm Dt da d a,calc d a,obs d a,sv dp d p,50 d p,sv Fcoh,rup Fexp Ff Fpp FvdW g Ha Lc nk
symbols cross section area of column Žm2 . bubble diameter Žm. initial bubble diameter Žm. maximum attainable bubble diameter Žm. column diameter Žm. agglomerate diameter Žm. calculated agglomerate diameter Žm. observed agglomerate diameter Žm. surface-to-volume mean diameter of agglomerates Žm. primary particle diameter Žm. median diameter of primary particles Žm. surface-to-volume mean diameter of primary particles Žm. cohesive rupture force ŽN. expansion force ŽN. load Žkgfrm2 . cohesive force between primary particles ŽN. van der Waals force ŽN. gravity acceleration Žmrs 2 . Hamaker constant ŽJ. settled bed height Žm. coordination number Ža.
Rb S w,BET S w,calc u0 u mf u mf,a W z d ´ ´a ´mf
fs,BET h hav hcr h) m ra r bulk r bulk,a rf rp s s b,exp
221
coordination number for primary particles in agglomerates Ža. dimensionless particle pressure in bed Ž – . maximum dimensionless particle pressure around a bubble Ž – . bubble radius Žm. particle specific surface area measured by BET Žm2rkg. specific surface area calculated for spherical particle Žm2rkg. superficial gas velocity Žmrs. minimum fluidization velocity Žmrs. minimum fluidization velocity of bed of agglomerates Žmrs. powder batch mass Žkg. height Žm. micro scale gap between surface Žm. bed voidage Ž – . agglomerate voidage Ž – . bed voidage at minimum fluidization condition Ž–. Carman’s shape factor, S w,calcr S w,BET Ž – . ŽyPˆs .rŽyPˆs,max . Ž – . average value of h Ž – . critical value of h defined in Fig. 12b Ž – . value of h at d a,obs Ž – . gas viscosity ŽPa s. agglomerate density Žkgrm3 . bulk density of solids Žkgrm3 . bulk density of agglomerate Žkgrm3 . gas density Žkgrm3 . particle density Žkgrm3 . tensile strength of an individual agglomerate ŽNrm2 . tensile stress in bed ŽNrm2 .
References w1x Y. Iwadate, M. Horio, Powder Technol. 100 Ž1998. 223. w2x K. Nishii, Y. Itoh, N. Kawakami, M. Horio, Powder Technol. 74 Ž1993. 1. w3x D. Geldart, Powder Technol. 7 Ž1973. 285. w4x M. Sugihara, J. Res. Assoc. Powder Technol., Jpn. 3 Ž1966. 21. w5x G. Jimbo, J. Res. Assoc. Powder Technol., Jpn. 3 Ž1966. 27. w6x K. Nishii et al., J. Jpn. Soc. Powder Powder Metall. 41 Ž1994. 1288. w7x Y. Hiramatsu, Y. Oka, Int. J. Rock Mech. Min. Sci. 3 Ž1966. 89. w8x H. Rumpf, Chem. Ing. Tech. 42 Ž1970. 538. w9x M. Nakagaki, H. Sunada, Yakugaku Zasshi 83 Ž1968. 651. w10x M. Horio, Y. Iwadate, T. Sugaya, Powder Technol. 96 Ž1998. 148. w11x J.F. Davidson, Trans. Inst. Chem. Eng. 39 Ž1961. 230. w12x S. Mori, C.Y. Wen, AIChE J. 32 Ž1975. 109. w13x C.Y. Wen, Y.H. Yu, AIChE J. 12 Ž1966. 610. w14x J. Tsubaki, G. Jimbo, Powder Technol. 37 Ž1984. 219.
Binderless granulation of pharmaceutical lactose powders Katsura Takano a , Kazuo Nishii a , Akiko Mukoyama b, Yuki Iwadate b, Hidehiro Kamiya b, Masayuki Horio b,) a
b
Fuji Paudal Co. Ltd., Osaka 536-0005, Japan Department of Chemical Engineering, Tokyo UniÕersity of Agriculture and Technology, 2-24-16 Nakamachi, Koganei, Tokyo 184-8588, Japan Received 26 September 2000; received in revised form 30 December 2000; accepted 11 January 2001
Abstract With a binderless fluidized bed granulation method ŽPressure Swing Granulation, PSG., jet-milled lactose particles were successfully agglomerated into narrow and spherical granules. This should be the first achievement of binderless granulation from an organic powder indicating the high potential of PSG application to pharmaceutical processes. With a decrease in the mean diameter of primary particles, the granules’ mean diameter decreased, and the compression strength of a single granule increased. The size of product lactose granules predicted by the Iwadate–Horio wPowder Technol. 100 Ž1998. 223x model was in good agreement with the experimental results obtained by sieve analysis. q 2002 Elsevier Science B.V. All rights reserved. Keywords: Fluidized bed; Pressure Swing Granulation; Binderless; Lactose; Dry powder inhalation
1. Introduction In many powder process industries, including pharmaceutical, ceramics and powder metallurgy, granulation is an important method for the improvement of powder handling. Especially for fine powders, which are difficult to handle due to their fliability and cohesiveness, granulation is effective to reduce the difficulties. To obtain granules from fine powders, most granulation systems use binders in wet conditions. However, binders often cause troubles such as contamination in products, unwanted solubility reduction or too much strength to disintegrate. Concerning the strength, those granules applicable to dry powder inhalation have to be sufficiently weak to be easily decomposed and dispersed to form aerosols. Accordingly, Pressure Swing Granulation ŽPSG. granules have a potential for dry powder inhalation, for which wet granulation would never provide any possibilities. To solve the above problems, the PSG, a binderless fluidized bed granulation method, has been proposed by Nishii et al. w2x. It utilizes the spontaneously agglomerating nature of group C powders of the Geldart classification w3x, which was quantitatively investigated by Sugihara w4x and
Jimbo w5x early in 1966. In PSG, their agglomerating nature is accelerated and controlled by the cyclic fluidization and compaction by the alternative upward and downward gas flow. The down blow also returns the fines captured by the filter. Thus, agglomerates are subject to the controlled growth by adjusting their sizes, strength and shapes effectively. PSG granules have rather spherical shape, uniform diameter and strength sufficient to keep them as granules during storage, weighing and feeding but sufficiently weak to shape or dissolve into a solvent in downstream processes. The PSG technology has already been successfully applied to hardmetal cutting tool manufacturing process w6x and will be further applied to other industries. This work aims at examining the possibility of PSG in pharmaceutical granulation processes. Since lactose is generally used for excipients, it was chosen for the test material. In this paper, the maximum allowable lactose diameter to obtain good PSG granules, the product granule properties and the theoretical prediction of granule sizes are investigated. 2. Experimental procedures
)
Corresponding author. Tel.: q81-42-388-7067; fax: q81-42-3863303. E-mail addresses: [email protected] ŽK. Takano., [email protected] ŽM. Horio..
2.1. Primary particle preparation Seven samples were prepared from DMV Pharmatose 200 M by hammer-mill ŽFuji Paudal, K II G-1S. or jet-mill
0032-5910r02r$ - see front matter q 2002 Elsevier Science B.V. All rights reserved. PII: S 0 0 3 2 - 5 9 1 0 Ž 0 1 . 0 0 4 1 8 - 1
K. Takano et al.r Powder Technology 122 (2002) 212–221 Table 1 Milling condition
213
Table 2 Granulation conditions
Jet mill
No. 4
Sample no.
Milling cycles Ža.
Jet pressure ŽMPa.
Feed pressure ŽMPa.
3 4 5 6 7
1 2 1 1 2
0.05 0.10 0.60 0.45 0.30
0.10 0.10 0.35 0.45 0.40
ŽFuji Paudal, JM-1.. Table 1 shows the milling condition. The primary particle diameter was determined by a laser diffraction particle size analyzer ŽShimadzu, SALD-1100 Ver.2.10., and the specific surface area was by BET ŽYuasa Ionics, QUANTASORB Jr... Bulk density was determined by weighing a 50 = 10y6 m3 cup full powder. 2.2. Granulation Fig. 1 shows a schematic of the PSG granulator. The fluidized bed column was made of PMMA resin. Its internal surface was covered with a cellophane tape ŽNichiban, CT-18. so that the electrostatic adhesion of particles can be reduced. The internal diameter of the column was 0.108 m in lower part and 0.151 m in its upper part, where a bag-filter of 0.07 m in diameter and 0.157 m long was hung from the top flange. Table 2 shows the experimental conditions. In each granulation run, lactose powder was charged into the col-
Powder batch mass Gas velocity and fluidization time Compaction pressure and time Distributor vibration frequency Granulation time
120 g 0.263 mrs: 15 s 0.351 mrs: 15 s 0.03 MPa: 1 s 40 Hz 120 min
umn through a 16 mesh Ž1.0 mm. sieve to adjust initial agglomerate sizes by disintegrating large agglomerates. The distributor plate was vibrated at 40 Hz to assist fluidization. 2.3. Characterization of product granules The size distribution of product granules was determined by standard sieves, and the surface-to-volume mean diameter d a,sv was determined. Bulk density r bulk was determined by weighing a 50 = 10y6 m3 cup full granules of the size y12 mesh Ž1.41 mm.. The external surface of granules of the size y32 q 42 mesh Ž0.5–0.35 mm. was observed by an optical microscope as well as by a SEM. The porosity was measured by mercury porosimetry ŽShimadzu, Pore Sizer 9310. for granules of size y24 q 32 mesh Ž0.71–0.5 mm.. The compression strength of granules was measured by a micro compression testing machine ŽShimadzu, MCTE-200, the indenter rod diameters 0.5 mm. for granules of size y32 q 42 mesh Ž0.5–0.35 mm..
Fig. 1. Experimental apparatus and condition.
K. Takano et al.r Powder Technology 122 (2002) 212–221
214
plastic deformation, Type B is elastic brittle fracture and Type C is plastic deformation. For each case, Ff was determined as illustrated. The cohesive force of a primary particle Fpp was calculated with the following Rumpf w8x equation from the tensile strength s and the porosity of a granule ´a : Fpp s
ps d p2
Ž 2.
Ž 1 y ´a . n pk ,a
where n pk,a is the coordination number of primary particles in agglomerates. According to Nakagaki and Sunada w9x, n pk,a is correlated by .48 n pk ,a s 1.61 ´y1 a
Ž ´a O 0.82 . .
Ž 3.
3. Preparation and characterization of primary powders
Fig. 2. Classification of fracture tensile strength measurements by a micro compression testing machine.
Fig. 2Ža. shows a conceptual compression force vs. displacement relationship. When breakage of a granule takes place, there appears a nearly horizontal part in the force-displacement curve. From the fracture force Ff , the tensile strength s can be calculated by the following Hiramatsu and Oka w7x equation:
ss
2.8 Ff
p d a2
Fig. 3 shows the SEM images of lactose powders before and after milling. For Nos. 2 and 3 powders, we can observe many large particles of 10–100 mm, having crystal facets. As particle sizes became smaller, their edges were rounded off and more spherical particles were obtained. Table 3 shows properties of milled lactose powders. Fig. 4 shows size distributions of lactose powders before and after milling, from which surface-to-volume mean diameter d p,sv was calculated. Specific surface area S w,calc was calculated by d p,sv on the assumption that particles were spherical. Then, Carman’s shape factor fs,BET is equal to S w,calcrS w,BET . If fs,BET is close to 1, particles are of smooth surface and spherical. Fig. 5 shows the relationship between the mean diameter and the specific surface area S w,BET of primary particles. Except for Powder No. 4, specific surface area S w,BET was larger for smaller mean diameter. Powder No. 4 had a surface area larger than No. 5. However, the mean diameter of Powder No. 5 was smaller than No. 4. The reason of this contradictory phenomenon is thought to be because Powder No. 5 was milled only once. Instead, Powder No. 4 was obtained by milling two times and had more damage on particle surface, as can be seen from the cracks on the surface in the SEM image.
4. Granulation results 4.1. Limiting factors to produce PSG granules
.
Ž 1.
In reality, there were several types in force–displacement curves as shown in Fig. 2Žb.. Type A is the elastic
Fig. 6 shows microphotographs of PSG granules obtained from Nos. 2–7 powders. From Nos. 1–3 powders no good agglomerates were obtained.
K. Takano et al.r Powder Technology 122 (2002) 212–221
215
Fig. 3. SEM images of primary particles of lactose before and after milling.
When Powder No. 1 was fluidized, the bed was in slugging condition in the beginning then uniformly fluidized. This was in contrast with other powders, all of which showed channeling in the beginning. Powder No. 1 is classified into group C but very close to group A in Geldart classification. The poor agglomeration tendency of Powder No. 1 was also confirmed by the fact that Powder No. 1 particles passed through both the bag-filter and the distributor. The bed of Powder No. 2 was partly channeled and partly fluidized. Agglomerates were visually observed both on its bed surface and on the wall side, but they were easily broken during compression cycles. However, Powder No. 2 did not pass through the bag-filter nor the distributor. Powder No. 3 was fluidized in a manner similar to No. 2. When gas flow rate was 0.263 mrs, agglomerates were observed only on the bed surface. When gas flow rate was increased to 0.351 mrs, fluidization and formation of small agglomerates in the bed were confirmed by visual observation from the wall. However, those agglomerates were easily broken in compression cycles. Powder No. 3 did not pass through the bag-filter but did a little through the distributor.
From Powder Nos. 4–7, these showed good agglomerating fluidization. All of their product granules then did not pass through the bag-filter nor the distributor. From the above results, the limiting size of primary particles for reasonable binderless granulation of lactose is found to be roughly 4.8 mm, which corresponds to the mean size of No. 4. However, although Powder No. 5 had smaller particle size than No. 4, the granules obtained from No. 5 were poorer than those from No. 4. As mentioned in Section 3, Powder No. 4 had larger surface area. More strictly, the specific surface area could be more important factor than particle size for successful binderless granulation. More work is however necessary to further generalize this point. 4.2. Characterization of PSG granules Fig. 7 shows the SEM image of the granules with their surface-to-volume mean diameter d a,sv . Granule products Nos. 4, 5, and 6 were spherical and their surfaces were rough. On the other hand, granule product No. 7 was spherical with rather smooth surface. Fig. 8 shows the size distributions of granules. For larger S w,BET of primary particles the size distribution of
Table 3 Primary particles’ characteristics Sample No. 1 2 3 4 5 6 7
d p,50 Žmm. 27.1 12.5 9.36 7.77 4.67 4.20 2.97
d p,sv Žmm. 13.8 7.48 4.95 4.79 4.14 3.71 2.58
S w,BET Žm2rkg. 3
0.56 = 10 0.86 = 10 3 0.73 = 10 3 1.60 = 10 3 1.17 = 10 3 2.04 = 10 3 4.48 = 10 3
S w,calc Žm2 rkg. 3
0.30 = 10 0.75 = 10 3 0.79 = 10 3 0.82 = 10 3 0.95 = 10 3 1.06 = 10 3 1.52 = 10 3
r bulk Žkgrm3 .
fs,BET Ž – .
5.4 = 10 2 3.6 = 10 2 4.1 = 10 2 2.5 = 10 2 2.4 = 10 2 1.7 = 10 2 1.8 = 10 2
0.541 0.855 1.08 0.496 0.809 0.520 0.339
K. Takano et al.r Powder Technology 122 (2002) 212–221
216
granules tended to become narrower. In particular, No. 7 had a very narrow size distribution in comparison with other’s. As fluidizing velocity was increased from 0.263 to 0.351 mrs, the fraction of larger granules increased and also mean diameter of product granules increased Žcf. Fig. 9.. Fig. 10 shows the pore size distribution of granules determined by mercury porosimetry. As the mean diameter of primary particles become smaller, the pore size shifted to smaller side. In Fig. 10, the part of the distribution below the separation size of about 7 mm should correspond to the voidage inside of granules Ži.e. pores., and the part above the separation size should be to the void in between granules. From these data, the granule porosity ´a was determined as shown in Table 4. Table 4 also shows compression strength s and bulk density of granules r bulk,a . The compression strength of granules No. 7 was more than three times as large as the other samples. Except for No. 4, ´a decreased as primary particle size decreased. Fig. 11Ža. shows the effect of primary particle diameter on the cohesive force between primary particles Fpp estimated by Eq. Ž2. from experimental data for s and ´a . Although there exists a wide scatter, mean values of Fpp increased as the primary particle diameter increased except for No. 7. The higher mean cohesion force of No. 7 is consistent with its lower porosity shown in Table 4. Fig. 11Žb. shows the proportion of the three fracture types of granules defined in Fig. 2Žb.. All granules of Nos. 4–6 were classified into Type C Žplastic deformation.. Roughly 90% of granules of product No. 7 was classified into Type B Želastic brittle.. This is probably because No. 7 had a hard shell around the granules but the others did not. 5. Prediction of agglomerate sizes 5.1. Outline of Iwadate–Horio (IH) [1] model IH model is based on the knowledge of bed compaction and expansion by bubbles w10x. By careful examination of
Fig. 5. Relationship between the mean diameter and the specific surface area of primary particles.
Davidson’s w11x bubble model, they found that the bed expansion force acts on the emulsion phase above a bubble and that the compaction force acts below it. In an agglomerating fluidized bed agglomerates are attrited on the one hand, and re-agglomerated on the other by the bubble motion, reaching those with an equilibrium size. In IH model the equilibrium agglomerate size is derived by equating the cohesive force Fcoh,rup between two agglomerates with the hydrodynamic expansion force Fexp which is a function of bubble size, based on the following assumptions: 1. At an equilibrium condition the bed expansion force above a bubble equals the cohesive rupture force between agglomerates. Thus, we can write Fcoh ,rup s Fexp .
Ž 4.
2. The bed consists of spherical agglomerates of uniform size d a , voidage ´a and minimum fluidization velocity u mf,a . 3. The emulsion phase voidage is uniform and equal to ´mf . 4. The bed expansion force is estimated by Horio et al. w10x model with a representative bubble size predicted by Mori–Wen w12x correlation for z s Lc Ž Lc : static bed height.. The effective expansion stress is proportional to the stress at the bubble nose multiplied by a factor h. Thus, Fexp s
ps b ,exp d a2
s b ,exp s h Ž yPˆs ,max .
Ž yPˆs ,max . s D b y D bm Fig. 4. Size distributions of primary particles.
Ž 5.
Ž 1 y ´mf . n k
D b 0 y D bm
½
1 0.843
ž
Db 2
ra g Ž 1 y ´mf .
for 2D bubble for 3D bubble
s exp y0.3
Lc Dt
/
.
Ž 6. Ž 7. Ž 8.
K. Takano et al.r Powder Technology 122 (2002) 212–221
217
Fig. 6. Microphotographs of PSG granules of lactose.
Where D b0 and D bm in Eq. Ž8. are obtained as Db0 s
3.77 g
Ž u 0 y u mf ,a . y0.2
D bm s 2.59 g
½
2
: initial bubble diameter
Ž u 0 y u mf ,a .
p Dt2 4
Ž 9.
this difficulty, let us check the possibility of utilizing the experimentally determined values of s for agglomerates Žcf. Section 2.3. to predict Fcoh,rup . Since we can write Eq. Ž7. for the cohesive force
0.4
5
: maximum allowable bubble diameter.
Fpp f FvdW s
Ž 10.
For minimum fluidization velocity of agglomerates u mf,a we can write the following expression by applying Wen– Yu correlation w13x for agglomerates of mean diameter d a and density ra :
m s da rf
ž(
33.7 2 q
0.0408 d a3
r f Ž ra y r f . g m2
/
y 33.7 .
Ž 11 . 5. The cohesive rupture force Fcoh,rup for the two spherical agglomerates in contact having the gap between surfaces d we can write: Fcoh ,rup s
Ha d a Ž 1 y ´a . 24d 2
Ž 12 .
where Ha is Hammaker constant. As investigated by Tsubaki and Jimbo w14x, cohesive force between solid surfaces depends not only bed voidage but also the surface characteristics and compaction pressure. In Eq. Ž12., the effects of both compaction as well as surface morphology are included through d . However, in many cases, both Ha and d 2 are unknown. To overcome
Ž 13 .
24dpp2
where dpp is the gap between primary particles. By equating Eq. Ž13. with Eq. Ž2. and solving it for Hard 2 , we obtain. Ha
dpp2 u mf ,a
Ha d p
24p d p s
s
Ž 1 y ´a . n pk ,a
.
Ž 14 .
By assuming dpp 6 d and by substituting Eq. Ž14. into Eq. Ž12., finally the following expression is obtained for cohesive rupture force Fcoh,rup between agglomerates: Fcoh ,rup s
d pps n pk ,a
da .
Ž 15 .
In the following calculation the experimentally determined values shown in Table 4 are substituted. Fig. 12 shows a calculated example for the relationship between Fcoh,rup and Fexp as a function of d a . In Fig. 12 Fcoh,rup and Fexp have two intersections. Point A is a stable solution but Point B is an unstable one. At Point A a positive perturbation of d a creates a situation of Fexp ) Fcoh,rup , and a negative perturbation does Fexp - Fcoh,rup . In both cases the deviation from the intersection can therefore be recovered. However, in the case of Point B, this happens in an opposite way. Therefore, Point A should be the solution we aim at. However, we still have an unknown parameter
218
K. Takano et al.r Powder Technology 122 (2002) 212–221
Fig. 7. SEM images and surface-to-volume mean diameter of product granules d a,sv .
h in Eq. Ž6.. Iwadate–Horio calculated the average value of h for the upper half of a spherical region of radius R b to 3 R b around a 3D bubble and obtained hav s 0.0611 and used this value to obtain d a . However, it is still not clear if this average value is effective. Therefore, in the present work, an extreme case where Fexp contacts with Fcoh,rup , i.e. Point C in Fig. 12, is taken as a critical solution or an index that separates stable and unstable agglomerate sizes. 5.2. Comparison of granulate size of experiment and prediction Fig. 8. Size distributions of product lactose granules.
For lactose granulates, Fcoh,rup and Fexp were predicted. Experimental values were needed for granule voidage ´a , mean diameter of primary particles d p , and the tensile strength of agglomerates s . Bed voidage ´ and the static bed height Lc are given respectively by: r bulk ,a ´s1y Ž 16 . ra Lc s
W
r bulk ,a A t
Ž 17 .
where W is charged mass of powder, r bulk,a is bulk density of granules, A t is the bed cross sectional area and
Fig. 9. Effect of fluidizing velocity on product granule diameter.
Fig. 10. Pore size distribution of PSG granules determined by mercury porosimetry.
K. Takano et al.r Powder Technology 122 (2002) 212–221
219
Table 4 Granules’ characteristics Ž u 0 s 0.351 mrs except for No. 6=Ž u 0 s 0.263 mrs.. Sample No.
d a,sv Žmm.
´a Ž – .
s ŽNrm2 .
ra Žkgrm3 .
r bulk,a Žkgrm3 .
No. 4 No. 5 No. 6 No. 7 No. 6 Ž u0 s 0.263 mrs.
677 788 607 373 533
0.493 0.601 0.596 0.579 0.603
2.00=10 4 1.22=10 4 2.36=10 4 7.38=10 4 1.38=10 4
776 610 618 644 607
4.2=10 2 3.4=10 2 3.1=10 2 3.5=10 2 2.8=10 2
ra is agglomerate density. ra is calculated by using rp and ´ a : ra s rp Ž 1 y ´a . .
Ž 18 .
In Fig. 13, the prediction procedure is demonstrated for several cases, where h was adjusted until Fexp contacts with Fcoh,rup with only one point Ži.e. critical condition.. The value of h , thus, determined is expressed, in the following, by hcr . hcr is different for different lactose
Fig. 12. A model of agglomerating fluidization and defluidization w1x.
Fig. 11. Fracture tensile strength and cohesive force.
samples as a result of the difference in Fcoh,rup which was obtained from the experimentally determined s . The agglomerate sizes thus predicted are compared with those experimentally determined in Fig. 14. Predicted results for Nos. 4 and 5 are within "10% accuracy showing the validity of the modified IH model with the critical condition. However, for smaller primary particles, i.e. for Nos. 6 and 7, predicted results became larger. Particularly for No. 7, predicted result is about two times as large as the experimental. Here, it should be noted that the observed agglomerate sizes are all less than or almost equal to the predicted ones for the critical condition. This is a reasonable tendency because the critical condition gives the maximum size of stable agglomerates. Iwadate and Horio w1x examined the effect of gas velocity on granule size. In their work, both predicted and experimentally determined granule sizes increased as gas
220
K. Takano et al.r Powder Technology 122 (2002) 212–221
Fig. 13. Agglomerate size determination by I-H model with the critical condition ŽPSG: 2 h, pre-sieving by 16 mesh..
velocity decreased. In their prediction, Fcoh,rup was kept constant for different gas velocity. However, in the present work, the average value of d a,sv increased from 533 to 607 mm with a gas velocity increase of from 0.263 to 0.351 mrs as already shown in Fig. 8, obtained by using the value ´a and s shown in Table 4, d a,calc was predicted from IH model as 690 and 726 mm for u 0 s 0.263 and 0.351 mrs, respectively. Although the predicted values are
larger than the experimental data, the experimental tendency of size increase with gas velocity at least for the case of lactose was confirmed. From experimentally determined size of lactose granules’, the coefficient h in Eq. Ž6. can be obtained by equating Eq. Ž5. with Eq. Ž15. and solving it for h. Thus, determined h , expressed by h ) , is then given by
h)s
2 n k d p s d a ,obs
Ž yPˆmax . D b ra gn pk ,a
.
Ž 19 .
Table 5 shows the comparison between hcr and h ) . For Nos. 4 and 5, h ) is close to hcr . However, for Nos. 6 and 7 h ) was larger than hcr . The observed size smaller than predicted may be because of the effect of increased granule density but the search for the reason of the discrepancy is still a tough open issue for the future work.
Table 5 Comparison between hcr and hobs Ž u 0 s 0.351 mrs.
Fig. 14. Comparison of predicted and observed granule diameters.
Sample No.
hcr
h)
4 5 6 7
0.0577 0.0390 0.0808 0.152
0.0581 0.0391 0.0842 0.202
hav s Žy Ps,av .rŽy Ps,max . s 0.0611. Ps,av sy0.0515, Ps,max sy0.843 for a 3D bubble w1x.
K. Takano et al.r Powder Technology 122 (2002) 212–221
6. Conclusions
n pk,a
To extend the Pressure Swing Granulation ŽPSG. technology to pharmaceutical processes, milled lactose powders were granulated without binders by PSG and the properties of product granules were investigated. The big potential of the pharmaceutical application of PSG and our capability of quantitative prediction of product granule size has been confirmed. Ž1. Limiting primary particle size to obtain granulates was 4.79 mm and the minimum requirement for specific surface area was 1 = 10 3 m2rg. Ž2. The product granules had small mean diameter, narrow size distribution, spherical shape and rather smooth surface. Ž3. When fluidization velocity was increased from 0.236 to 0.351 mrs, the mean diameter of product granules increased. Ž4. For finer primary particles, stronger cohesive force was obtained for a contact point between particles inside a granule. Ž5. Experimentally determined granule sizes were compared with those predicted by Iwadate–Horio model combined with a critical condition where the curve of cohesive rupture force vs. granule size contacts with the curve of bed expansion force. By using experimentally determined tensile strength s , predicted results for Nos. 4 and 5 were within the accuracy of "10% of the experimental.
Pˆs Pˆs,max
List of At Db D b0 D bm Dt da d a,calc d a,obs d a,sv dp d p,50 d p,sv Fcoh,rup Fexp Ff Fpp FvdW g Ha Lc nk
symbols cross section area of column Žm2 . bubble diameter Žm. initial bubble diameter Žm. maximum attainable bubble diameter Žm. column diameter Žm. agglomerate diameter Žm. calculated agglomerate diameter Žm. observed agglomerate diameter Žm. surface-to-volume mean diameter of agglomerates Žm. primary particle diameter Žm. median diameter of primary particles Žm. surface-to-volume mean diameter of primary particles Žm. cohesive rupture force ŽN. expansion force ŽN. load Žkgfrm2 . cohesive force between primary particles ŽN. van der Waals force ŽN. gravity acceleration Žmrs 2 . Hamaker constant ŽJ. settled bed height Žm. coordination number Ža.
Rb S w,BET S w,calc u0 u mf u mf,a W z d ´ ´a ´mf
fs,BET h hav hcr h) m ra r bulk r bulk,a rf rp s s b,exp
221
coordination number for primary particles in agglomerates Ža. dimensionless particle pressure in bed Ž – . maximum dimensionless particle pressure around a bubble Ž – . bubble radius Žm. particle specific surface area measured by BET Žm2rkg. specific surface area calculated for spherical particle Žm2rkg. superficial gas velocity Žmrs. minimum fluidization velocity Žmrs. minimum fluidization velocity of bed of agglomerates Žmrs. powder batch mass Žkg. height Žm. micro scale gap between surface Žm. bed voidage Ž – . agglomerate voidage Ž – . bed voidage at minimum fluidization condition Ž–. Carman’s shape factor, S w,calcr S w,BET Ž – . ŽyPˆs .rŽyPˆs,max . Ž – . average value of h Ž – . critical value of h defined in Fig. 12b Ž – . value of h at d a,obs Ž – . gas viscosity ŽPa s. agglomerate density Žkgrm3 . bulk density of solids Žkgrm3 . bulk density of agglomerate Žkgrm3 . gas density Žkgrm3 . particle density Žkgrm3 . tensile strength of an individual agglomerate ŽNrm2 . tensile stress in bed ŽNrm2 .
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