Evaluation of the impact of mixing speed on the compressibility and compactibility of paracetamol-isomalt containing granules with factorial design

Powder Technology 213 (2011) 132–140

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Powder Technology j o u r n a l h o m e p a g e : w w w. e l s ev i e r. c o m / l o c a t e / p ow t e c

Evaluation of the impact of mixing speed on the compressibility and compactibility of paracetamol-isomalt containing granules with factorial design Zs. Sáska a, J. Dredán a, O. Luhn b, E. Balogh a, G. Shafir a, I. Antal a,⁎ a b

Semmelweis University, Department of Pharmaceutics, Budapest, Hungary BENEO-Palatinit GmbH, Mannheim, Germany

a r t i c l e

i n f o

Article history: Received 22 June 2010 Received in revised form 20 June 2011 Accepted 8 July 2011 Available online 23 July 2011 Keywords: Wet granulation Isomalt Paracetamol Compaction Factorial design

a b s t r a c t The aim of the present study is to evaluate the effect of a new formulation parameter on the characteristics of dosage form and manufacturing process. In our previous work the effects of isomalt and compression force on compaction and tablet properties were investigated. In this research paper the particles were agglomerated with purified water without using other binders. To set up the 33 type factorial design a new independent variable – mixing speed (X2) – was added to paracetamol:isomalt ratio in granules (X1) and to compression force during the tabletting process (X3). Each of these variables was examined at three levels to characterize their power and interactions. As granule's properties mass flow, densities and particle size were investigated. From the aspect of compression process lubrication coefficient and friction work were the evaluated response variables. As tablet characteristics tablet resistance to crushing and tensile strength were studied. The results indicated that the agglomeration process did not need any other binders to obtain granules with good quality. Moreover, the addition of mixing speed as a new independent variable was appropriate, since it had significant effect among others on the particle size distribution of the granules and on tablet characteristics. According to the results of the tablet quality tests the optimal mixing speed at granulation is needed which offers not only sufficient homogeneity of the granules but also appropriate tablet characteristics. Furthermore, the enhancing effect of isomalt on the compaction of granules and on the tablet characteristics is observed. © 2011 Elsevier B.V. All rights reserved.

1. Introduction Wet granulation is a widely used method in the pharmaceutical industry to enhance the flowability of powders to obtain free flowing, homogenous granules with defined particle size and density [1]. This process is required when, for example, an active ingredient owns inadequate flow or compaction properties. On the one hand, these inadequate properties can be modulated with the agglomeration of powder particles using a liquid binder. On the other hand, the segregation of the materials with different particle sizes can be avoided and for active ingredients with low dosage the homogeneity of the powder mixtures can be improved [2]. During the agglomeration process the bulk particle is forced to move and contacted with the sufficient amount of the wetting material using a high-shear mixer, a fluidized bed or some other equipment. According to the view of Iveson et al. (2001) the three important processes determining the wet granulation behavior of materials are as follows [3]: • wetting and nucleation • consolidation and growth • breakage and attrition ⁎ Corresponding author at: Semmelweis University, Department of Pharmaceutics, Budapest, Hungary, 7., Hőgyes Endre str., 1092, Budapest, Hungary. Tel./fax: +36 1 217 0914. E-mail address: [email protected] (I. Antal). 0032-5910/$ – see front matter © 2011 Elsevier B.V. All rights reserved. doi:10.1016/j.powtec.2011.07.019

These phenomena should be understood in depth to predict the effect of different process parameters. Recently, numerous publications have been issued in the field of wet granulation. Hegedűs et al. (2007) compared different production-scale high-shear granulator models to optimize and reproduce a robust technology to obtain granules (and the tablets formed from them) with similar physical properties [4]. Rajniak et al. (2007) investigated the effect of physicochemical properties of aqueous hydroxypropyl cellulose solutions and the morphological properties (size and surface roughness) of mannitol and anhydrous dibasic calcium phosphate on the agglomeration kinetics and granule characteristics. They found among others, that both these studied factors of hydroxypropyl cellulose have impact on granule growth and granule properties. Moreover, correlation between the granule porosity and the binder concentration was found for the mannitol granules [5]. Bacher et al. (2008) examined the properties of granules containing calcium carbonate of different morphological forms or the sorbitol in different particle sizes made by two different granulation methods such as wet and dry granulation. According to their results referring to the granulation methods, both techniques produced granules with acceptable flow properties. Nevertheless, the dry granulation produced irregular granules with higher density, compared to the wet granulation, which could make more compressible agglomerates [6]. Schenck and Plank (2008) studied the milling of agglomerates before and after drying. As their results show, there is a significant difference found in the sequence of breakage in wet and dry states of the granules. Furthermore,

Z. Sáska et al. / Powder Technology 213 (2011) 132–140

the size of the feed material and the impeller speed during milling had some influence on the dry granule attrition [7]. Da Cunha et al. (2009) investigated the suitability of both conventional and draft tube fluidized beds, with and without injection of compressed air for the granulation process of microcrystalline cellulose with maltodextrin [8]. Giry et al. (2009) estimated the effects of a switch between single pot and multiphase wet granulation processes on granule and tablet characteristics according to the formulation parameters such as drug substance properties and concentration [9]. Vemavarapu et al. (2009) employed different active pharmaceutical ingredients and excipients to test the effect of several physical and physical–chemical properties (for example, wettability and particle size distribution) on the characteristics of granules (granule growth, compactibility and flow properties) [10]. Paracetamol (acetaminophen) has been used as the model drug in our investigations, since it represents poor compactibility and reduced plastic deformation. These properties can result in many difficulties during the process of the compaction of this material. Several solutions are to find in the literature to enhance its flow properties and compactibility. In order to achieve these, Garekani et al. (2000) and Alander et al. (2003) worked out different crystallization methods [11,12]. Fichtner et al. (2005; 2007) agglomerated paracetamol by crystallization in water [13], and investigated agglomeration and granulation in different solvents [14]. Turkoglu et al. (1999) used roller compaction with different binders (hydroxypropyl methyl cellulose, polyethylene glycol, Carbopol) and extragranular microcrystalline cellulose addition [15]. Martinello et al. optimized a tablet formulation by direct compression without previous paracetamol treatment with the application of conventional raw materials and equipment [16]. Isomalt is a sugar alcohol with a wide range of potential pharmaceutical applications as a result of its physicochemical properties. Besides its advantages compared to other types of sugars such as the resistance to chemical degradation and low hygroscopicity, it offers several more advantages when formulated in pharmaceutical dosage forms, particularly when used as a tablet excipient [17]. The compaction behavior of isomalt was investigated by Ndindayino et al. (1999) [18] and Bolhuis et al. (2009) [19,20]. In the present study granules were formulated from paracetamol (API) and milled isomalt — galenIQ 801™ (EXC) with purified water utilizing a 3 3 type face-centered full factorial design. The granules were compressed into tablets with the external phase which consisted of crospovidone as disintegrant and magnesium stearate as lubricant. In our previous work the effect of API:EXC ratio and compression force was investigated [21]. In this research paper the effect of the mixing speed of the machine as a new independent variable was added to the factorial design. 2. Materials and methods 2.1. Materials Isomalt GS — galenIQ 801™ (EXC) was supplied by Beneo-Palatinit GmbH, Mannheim, Germany. Paracetamol (API) was obtained from Merck Schuchardt OHG, Hohenbrunn, Germany. As further component purified water, crospovidone (Kollidon CL BASF, Ludwigshafen, Germany) and magnesium stearate (REANAL, Budapest, Hungary) were used.

then sized with an ERWEKA oscillating granulator through a 630 μm sieve. 2.2.2. Characterization of granules Physical characteristics of the granules were tested according to the European Pharmacopoeia methods. 2.2.2.1. Flowability. The flowability of the granules was determined with funnel with stem maintained in upright position. The test sample was introduced (50 ± 0.25 g) into the dry funnel without compacting which bottom opening was blocked before. With unblocking the bottom of the funnel the time needed for the entire sample to flow out was measured. The flowability of the granules was expressed in seconds related to 100 g sample. Three determinations were carried out with each sample. 2.2.2.2. Angle of repose. To measure the angle of repose, 50 g of granules was poured into a dry funnel which bottom opening was blocked before. The funnel was fixed approximately 4 cm above the powder pile. The angle of repose was determined by measuring the height of the cone of powder and calculating the angle of repose, α with the following equation: tanðα Þ =

height : 0:5 × base

ð1Þ

The mean of three determinants was taken as the angle of repose. 2.2.2.3. Densities. The bulk density of granules was determined by pouring a determined mass 100 g (m) of them into a graduated, 250 cm 3 dry cylinder. The apparent volume (V0) was read to the nearest graduated unit and the bulk density was calculated in grams per cubic centimeter with the following formula: ρb =

m : V0

ð2Þ

The mean of three determinants was taken as the bulk density. The tapped density was measured by Ph. Eur. Method 1. The sample (100 g of granules) was poured into a graduated, 250 cm 3 dry cylinder which was secured to an automatic tapper (Stav 2003 — Stampfvolumeter with Omron HFCX-A4 counter). 10, 500 and 1250 taps were carried out and the corresponding volumes (V10, V500 and V1250) were read to the nearest graduate. Since the difference between V500 and V1250 was less than 2 cm 3, no more taps were done. The final tapped density was calculated by reading the volume after tapping and using Eq. (3): ρf =

m : V1250

ð3Þ

Three determinations were carried out. 2.2.2.4. Compressibility index and Hausner ratio. The compressibility index and the Hausner ratio can be calculated using measured values of bulk (ρb) and final tapped density (ρf). The compressibility index can be calculated as follows: Compressibility index =

2.2. Methods 2.2.1. Formulation The granules were made with a Stephan UMC-5 Electronic Laboratory Mixer. The aqueous binder liquid was sprayed onto the mixture of the API and EXC through a 0.8 mm spray nozzle with 200 kPa pressure. The granules were dried for 24 h in a drying chamber (40 °C),

133

  ρf −ρb × 100 ρf

ð4Þ

The Hausner ratio is the quotient of bulk (ρb) and final tapped density (ρf) and can be given with Eq. (5):

Hausner ratio =

ρf : ρb

ð5Þ

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In case of both parameters the average of three determinations is presented. 2.2.2.5. Particle size analysis. The particle size distribution of the prepared granules was determined using conventional sieve analysis on a Retsch AS 200 apparatus containing a set of sieves of 800, 315, 160, and 63 μm. 50 g sample from each batch was vibrated for 5 min with the amplitude of 2.5 mm and interval of 5 s. The mean particle size was calculated with the following equation (Eq.(6)): −

d =

m1 d1 + m2 d2 + …mn dn n

ð6Þ

∑ mi

i=1

where d1, d2, dn represent the sieve size in μm and m1, m2, mn the mass on the related sieve. Three determinations were carried out. 2.2.3. Tablet processing technique The granules were compressed into tablets with a single punch tablet machine (Type TM 20, Diaf, Copenhagen, Denmark) with flat, sharp-edged punches of 10 mm diameter. The external phase of the tablets contained 5% crospovidone as disintegrant and 1% magnesium stearate as lubricant. The instrumentation of the punches involves strain gauges (KMT-LIAS-06-3/350-5E type, Kaliber Ltd., Budapest, Hungary) on both the upper and lower punches. The displacement was measured by a magnetic sensor (Limes L2 type, Kübler GmbH, Villingen-Schwenningen, Germany) with a resolution of 5 μm and signaling at 1 μs pulse interval. All signals were transferred through cables to the data recorder (USB-6210, National Instruments Corp., Austin, USA) involving signal conditioning. The data acquisition was performed using NI-DAQmx 8.3. software (National Instruments Corp., Austin, USA). Data were analyzed by MS Excel macroprogram developed in-house. The calibration of sensors was made by Kaliber Ltd. Budapest, Hungary. The compression was carried out at ambient conditions (20–22 °C; 45–50% relative humidity). The average mass of the tablets was 0.300 ± 0.05 g. 50 tablets were compressed at each compression force (10 kN; 12.5 kN and 15 kN) for each sample. During the compression both the upper and the lower forces were detected in each batch twice for 10 consecutively compressed tablets. 4000 data points were measured during a single compression cycle. 2.2.4. Data analysis The compaction and ejection cycles provide us suitable signals about the tabletting process. By measuring the compression force both of the upper and the lower punch and the displacement of the upper punch force as a function of displacement can be given. From these data the lubrication of the tablets and the occurred friction during the compaction can be calculated [22–25]. To investigate the friction appearing during the compaction and the lubrication effect the comparison of the maximum force measured on the upper (Fup) and the lower punch (Flp) is a proper method. The quotient of Flp and Fup, the R-value (lubrication coefficient) can be calculated (Eq. (7)). Flp; max R= Fup; max

ð7Þ

Fig. 1. Compression force as a function of displacement (Fup: upper punch force, Flp: lower punch force, Fup,max: maximum upper punch force, Flp,max: maximum lower punch force).

curves. The work parameters can be expressed as absolute values in Joules (J). 2.2.5. Tablet characteristics Physical characteristics of the tablets were tested according to the European Pharmacopoeia methods. 2.2.5.1. Tablet weight. Tablet weight was measured using an analytical balance (Sartorius basic BA 1005, Germany). The data was obtained from 10 tablets, prepared at the same compression force. 2.2.5.2. Resistance to crushing of tablets. The tablet hardness was measured with a crushing strength tester (TBH 200, Erweka instrument GmbH Heusenstamm, Germany). The data was obtained from 10 tablets, prepared at the same compression force. 2.2.5.3. Calculation of tablet tensile strength. Tensile strength of tablets was calculated by the following equation:

σ =

2H π dt

ð9Þ

where H represents the tablet hardness, d is the diameter and t is the thickness of the investigated tablets [26]. The mean of 10 determinants was taken as tensile strength prepared at the same compression force. The tablet thickness and diameter were measured with a tablet testing apparatus (TBH 200, Erweka instrument GmbH Heusenstamm, Germany) equipped with a digital micrometer (Digimatic Indicator ID-C1012CB, Mitutoyo Corp., Tokyo, Japan) using a spherical probe. 2.2.5.4. Investigation of tablets with near infrared spectroscopy. Near infrared spectroscopic analysis of the produced tablets was carried out using a MPA Multi Purpose FT-NIR Analyzer spectrometer (Bruker Optik

The friction work (FW) can be calculated with Eq. (8). as follows: Dm

FW = ∫

Ds



 Fup −Flp dD

ð8Þ

where D refers to the displacement of the upper punch. The compression values are integrated taking the starting position,DS and maximum displacement of the punch,DM into consideration (Fig. 1.). The work can be given with numerical integration based on the trapezoidal method to estimate areas under the force-displacement

Table 1 Factorial design parameters and experimental conditions. Coded levels

X1 API:EXC ratio

X2 mixing speed (rpm)

X3 compression force (kN)

−1 0 1

5:1 5:3 1:1

1000 1500 2000

10 12.5 15

−1: factor at low level; 0: factor at medium level; 1:factor at high level.

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Table 2 Physical properties of the prepared granules with the coded levels of the operational parameters and their standard errors. Batch code

1 2 3 4 5 6 7 8 9

X1 API:EXC ratio

−1 0 1 −1 0 1 −1 0 1

X2 mixing speed

−1 −1 −1 0 0 0 1 1 1

Ygranule1 flowability

Ygranule2 angle of repose

Ygranule3 bulk density

Ygranule4 tapped density

Ygranule5 compressibility index

(s/100 g)

(°)

(g/cm3)

(g/cm3)

(%)

6.3 ± 0.23 6.9 ± 0.46 4.0 ± 0.00 5.9 ± 0.23 6.3 ± 0.23 6.1 ± 0.23 6.4 ± 0.40 5.7 ± 0.23 4.4 ± 0.00

28.9 ± 0.41 28.1 ± 0.33 24.7 ± 0.66 29.1 ± 1.22 29.0 ± 0.63 26.6 ± 0.62 29.7 ± 1.70 28.4 ± 0.90 25.8 ± 0.69

0.463 ± 0.0022 0.554 ± 0.0035 0.589 ± 0.0020 0.447 ± 0.0012 0.542 ± 0.0034 0.579 ± 0.0039 0.430 ± 0.0021 0.533 ± 0.0016 0.577 ± 0.0076

0.533 ± 0.0016 0.651 ± 0.0025 0.752 ± 0.0057 0.524 ± 0.0027 0.628 ± 0.0023 0.683 ± 0.0071 0.513 ± 0.0026 0.634 ± 0.0062 0.690 ± 0.0048

18.2 ± 0.58 14.9 ± 0.86 21.6 ± 0.38 14.6 ± 0.65 13.7 ± 0.23 15.3 ± 0.40 16.2 ± 0.22 16.0 ± 0.58 16.3 ± 0.68

Ygranule6 Hausner ratio

Ygranule7 mean particle size (μm)

1.22 ± 0.009 1.18 ± 0.012 1.28 ± 0.006 1.17 ± 0.009 1.16 ± 0.003 1.18 ± 0.006 1.19 ± 0.003 1.19 ± 0.008 1.20 ± 0.010

194.4 ± 9.81 247.6 ± 7.73 209.5 ± 8.24 150.7 ± 7.33 223.6 ± 9.13 236.9 ± 6.55 148.5 ± 5.32 189.4 ± 6.75 190.1 ± 5.48

The presented values are means of three parallels.

Table 3a Dependent variables of granules with their polynomial coefficients and standard errors.

A B A2 B2 AB R

Flowability

± S.E.

Angle of repose

±S.E.

Bulk density

± S.E.

Tapped density

± S.E.

− 0.7 − 0.1 − 0.7 − 0.4 − 0.1 0.8017

± 0.26 ± 0.26 ± 0.39 ± 0.39 ± 0.32

− 1.8 0.4 − 1.1 − 0.7 0.1 0.9730

±0.15 ±0.15 ±0.22 ±0.22 ±0.19

0.067 − 0.011 − 0.029 0.002 0.005 0.9999

± 0.0004 ± 0.0004 ± 0.0006 ± 0.0006 ± 0.0005

0.092 − 0.017 − 0.023 0.016 − 0.010 0.9936

± 0.0041 ± 0.0041 ± 0.0061 ± 0.0061 ± 0.0050

The significant coefficients are bolded.

Table 3b Dependent variables of granules with their polynomial coefficients and standard errors.

A B A2 B2 AB R

Compressibility index

± S.E.

Hausner ratio

±S.E.

Mean particle size

± S.E.

0.7 − 1.0 − 1.9 2.4 − 0.8 0.9246

± 0.47 ± 0.47 ± 0.69 ± 0.69 ± 0.57

0.01 − 0.02 0.03 0.04 − 0.01 0.9267

±0.007 ±0.007 ±0.010 ±0.010 ±0.008

23.8 − 20.6 − 31.3 − 6.6 6.6 0.9387

± 5.65 ± 5.65 ± 8.32 ± 8.32 ± 6.92

The significant coefficients are bolded.

GmbH, Ettlingen, Germany). Spectral manipulation was carried out using OPUS 6.5 software (Bruker Optik GmbH, Ettlingen, Germany). 2.2.6. Experimental design Paracetamol — isomalt granules were prepared based on the 3 2 factorial design. As independent variable paracetamol — isomalt ratio (API:EXC ratio; X1), mixing speed (X2) as a new independent variable at the granulation process were chosen each at three levels. At tabletting process and tablet characteristics evaluation a third independent variable, the compression force during tabletting (X3) was taken into the statistical analysis. The three factors with their levels are represented in Table 1. The levels for each parameter are expressed by (−1) for the low level, (0) for the medium and (1) for the high level. Experimental trials of granules were performed at all 9, of compaction and tablet properties at all 27 possible combinations. The matrix of the factorial plan and the referred results of both granulation and tabletting are shown in Tables 2 and 3a and 3b. The 27 points of 3 factors on 3 levels in the three-dimensional design space are illustrated in Fig. 2. Besides the granule properties – flowability, angle of repose, bulk and tapped density, compressibility index, Hausner ratio and mean particle size – dependent variables for the investigation of the compaction process, lubrication coefficient and friction work were selected. To evaluate the tablet characteristics tablet hardness and tensile strength were chosen.

The statistical analysis was carried out with the assistance of Design Expert 7.1. software (Minneapolis, USA). The quadratic model was used to analyze the responses. A, B and C represent the main effects of the three independent variables. A refers to the API:EXC ratio (X1), B to mixing speed (X2) and C to compression force (X3). AB, AC and BC are the polynomial coefficients of the interactions between two factors. A 2, B 2 and C 2 are the quadratic coefficients of the concerning factors representing the nonlinearity. ABC is the coefficient of the interaction between the three factors. The response

Fig. 2. The three-dimensional design space of 33 type face-centered full factorial design.

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Z. Sáska et al. / Powder Technology 213 (2011) 132–140

variables Ygranule and Ytablet can be given with the following form of corresponding polynomial equations: 2

2

2

2

ð10Þ

Ygranule = a + AX1 + BX2 + A X1 + B X2 + ABX1 X2 2

2

2

2

2

2

Ytablet = a + AX1 + BX2 + CX3 + A X1 + B X2 + C X3

ð11Þ

+ ABX1 X2 + ACX1 X3 + BCX2 X3 + ABCX1 X2 X3 where Y is the dependent variable and a is the arithmetic mean response of the 27 combinations. The significance of the three factors and their interactions were evaluated with analysis of variance (ANOVA) where F statistics and t-values were calculated as well [27]. The effect of each factor and their possible interactions can be studied over the responses taken into consideration if they reach the significant level. 3. Results 3.1. Study of granule properties

Fig. 3. Particle size distribution of granules at the three different mixing speeds. a) API: EXC ratio 5:1; b) API:EXC ratio 5:3; c) API:EXC ratio 1:1.

Table 2 represents the results of granule characterization measurements. All formulated granules meet the requirements of the European Pharmacopoeia. Moreover, the repose angle values of all the nine batches (values from 24.7 to 29.7) are in the excellent category based on the scaling of Carr [28]. The Hausner ratios and compressibility indexes confirm the good flow of granules obtained in eight batches. As Fig. 3 demonstrates, with the increasing of mixing speed the homogeneity of the granules raises on all levels of API:EXC ratio. However, the particle size shifts to lower values. At 5:1 API:EXC ratio there is no significant difference between the particle size distribution of 1500 rpm and 2000 rpm except at 1000 rpm where the homogeneity is decreased.

Table 4 Experimental matrix of the 33 full factorial design and the results of the measured responses with their standard errors.

−

Batch Code

X1

X2

X3

Ytablet1

Ytablet2

Ytablet3

Ytablet4

API:EXC ratio

Mixing speed

Compression force

R-valuea

Friction worka (J)

Hardnessb (N)

Tensile strengthb (kg/cm2)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27

−1 0 1 −1 0 1 −1 0 1 −1 0 1 −1 0 1 −1 0 1 −1 0 1 −1 0 1 −1 0 1

−1 −1 −1 0 0 0 1 1 1 −1 −1 −1 0 0 0 1 1 1 −1 −1 −1 0 0 0 1 1 1

−1 −1 −1 −1 −1 −1 −1 −1 −1 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1

0.7498 ± 0.00248 0.7956 ± 0.00049 0.8279 ± 0.02774 0.7311 ± 0.01103 0.8059 ± 0.00176 0.8189 ± 0.00043 0.7585 ± 0.00583 0.7949 ± 0.00253 0.8026 ± 0.00015 0.7837 ± 0.00210 0.8291 ± 0.00193 0.8581 ± 0.00122 0.7782 ± 0.00047 0.8314 ± 0.00067 0.8502 ± 0.00001 0.8003 ± 0.00398 0.8194 ± 0.00488 0.8434 ± 0.00006 0.8224 ± 0.00098 0.8708 ± 0.00193 0.8813 ± 0.00361 0.8222 ± 0.00177 0.8749 ± 0.00145 0.8914 ± 0.00142 0.8352 ± 0.00221 0.8757 ± 0.00004 0.8759 ± 0.00318

2.4646 ± 0.05515 1.5992 ± 0.17926 1.1500 ± 0.02408 2.5213 ± 0.13016 1.4285 ± 0.06138 1.1475 ± 0.01752 2.3582 ± 0.05997 1.6448 ± 0.07408 1.2851 ± 0.08169 2.7169 ± 0.06784 1.6818 ± 0.10595 1.2048 ± 0.00903 2.8219 ± 0.10444 1.7334 ± 0.08659 1.3523 ± 0.05038 2.7158 ± 0.32188 1.7940 ± 0.04042 1.5238 ± 0.00867 3.2619 ± 0.02622 1.8291 ± 0.09953 1.8498 ± 0.12586 3.2191 ± 0.08792 1.9862 ± 0.07963 1.5973 ± 0.08576 3.0500 ± 0.06227 1.9629 ± 0.14779 1.6454 ± 0.11600

30.6 ± 3.77 21.7 ± 2.91 35.8 ± 4.52 26.3 ± 3.86 21.8 ± 3.39 20.3 ± 2.83 25.1 ± 3.48 22.0 ± 1.94 23.8 ± 3.77 38.4 ± 3.13 33.8 ± 5.22 44.6 ± 6.11 35.7 ± 5.25 33.2 ± 5.41 37.1 ± 3.45 38.8 ± 5.92 29.1 ± 2.81 39.7 ± 5.56 34.8 ± 7.00 50.8 ± 5.01 69.9 ± 5.86 42.2 ± 5.07 47.9 ± 5.76 54.8 ± 5.61 41.7 ± 4.88 42.8 ± 4.34 53.2 ± 6.55

0.5580 ± 0.06768 0.4028 ± 0.10191 0.7107 ± 0.09135 0.4767 ± 0.06914 0.4266 ± 0.06697 0.3927 ± 0.05562 0.4655 ± 0.06508 0.4336 ± 0.03795 0.4574 ± 0.07307 0.7129 ± 0.05959 0.6456 ± 0.10190 0.9191 ± 0.12608 0.6618 ± 0.09952 0.6617 ± 0.10831 0.7387 ± 0.07508 0.7421 ± 0.11149 0.5770 ± 0.05550 0.7938 ± 0.11275 0.6579 ± 0.12444 1.0024 ± 0.10191 1.4503 ± 0.13770 0.8159 ± 0.10236 0.9699 ± 0.12142 1.1129 ± 0.12710 0.8049 ± 0.10531 0.8866 ± 0.09324 1.0994 ± 0.14105

1: factor at low level; 0: factor at medium level; 1:factor at high level. a Mean of twice ten compaction cycles. b Mean of ten parallels.

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Table 5 Dependent variables of tablets with their polynomial coefficients and standard errors.

A B C A2 B2 C2 AB AC BC ABC R

R-value

± S.E.

Friction work

±S.E.

Hardness

±S.E.

Tensile strength

±S.E.

0.0316 − 0.0007 0.0369 − 0.0148 0.0008 0.0025 − 0.0070 − 0.0034 0.0025 0.0020 0.9896

± 0.00159 ± 0.00159 ± 0.00159 ± 0.00252 ± 0.00252 ± 0.00252 ± 0.00194 ± 0.00194 ± 0.00194 ± 0.00238

− 0.6874 0.0123 0.2668 0.3571 − 0.0008 0.0430 0.0474 − 0.0564 − 0.0297 − 0.0292 0.9903

±0.02385 ±0.02385 ±0.02385 ±0.03783 ±0.03783 ±0.03783 ±0.02921 ±0.02921 ±0.02921 ±0.03577

3.6 − 2.5 11.7 4.5 1.8 0.0 − 3.0 5.1 − 0.1 − 2.1 0.9689

±0.78 ±0.78 ±0.78 ±1.23 ±1.23 ±1.23 ±0.95 ±0.95 ±0.95 ±1.16

0.0989 − 0.0444 0.2487 0.0787 0.0370 0.0044 − 0.0678 0.1103 − 0.0004 − 0.0421 0.9705

±0.01623 ±0.01623 ±0.01623 ±0.02575 ±0.02575 ±0.02575 ±0.01988 ±0.01988 ±0.01988 ±0.02435

The significant coefficients are bolded.

3.2. Evaluation of tabletting process The compressibility of the 9 batches at three compression forces was investigated by measuring the force of the upper and the lower punch and the displacement of the upper punch. The obtained forcedisplacement curves could be used to estimate differences as a function of mixing speed or API:EXC ratio. The relation between the upper and lower punch force characterized with R-value and the friction work were calculated using Eq. (7) and (8), respectively. Table 4 details the results evaluating force-displacement curve of each experimental trial. 3.3. Factorial design In our previous work the effect of API:EXC ratio and compression force on the compaction and tablet properties of paracetamol — isomalt granules was investigated. In this study a new independent variable — the mixing speed was added to the factorial design (3 2). Tables 2 and 4 summarize the matrix of the factorial plan and the referring results. The polynomial coefficients of each factor and their interactions concerning the response parameters to the transformed factor and the correlation coefficients of the equations are shown in Tables 3a, 3b and 5. 3.3.1. Main effects of the factors In the case of granule properties, except flowability, compressibility index and Hausner ratio, API:EXC ratio and mixing speed had their own effects on the response variables. Moreover, these independent variables affected in an antagonistic way and the coefficients describing

Fig. 4. Response surface plot for mean particle size of granules.

their linearity were significant. Furthermore, the effect of API:EXC ratio was on a higher extent than mixing speed in the studied interval (1000– 2000 rpm). The angle of repose was reduced with the API:EXC ratio. However, the mixing speed has increased it. Although bulk and tapped density like mean particle size increased with the higher isomalt content in the granules, mixing speed decreased these response parameters. The response surface plot for mean particle size of the granules (Fig. 4) represents the opposite effect of the studied independent variables, and the non-linearity of API:EXC ratio was observed as well. Although by the tabletting process API:EXC ratio and compression force had significant effect on all response variables, the mixing speed did not play important role in the influence of these parameters. Both API:EXC ratio and compression force enhance the lubrication of the produced tablets approximately on the same extent. Besides this friction decreases with the growing isomalt content, and this impact is larger than the increasing effect of compression force in this interval (Figs. 5 and 6). Nonetheless, in the case of tablet characteristics, mixing speed has its own influence on hardness and tensile strength as well. With the increase of the mixing speed the hardness and tensile strength have decreased. Both API:EXC ratio and compression force have positive effect on the studied tablet properties. The near infrared analysis demonstrates the hardness increasing effect of the applied compression force. As Fig. 7 demonstrates, there is a difference in the near infrared spectra to observe. As tablet hardness increases with the compression force, the near infrared light absorbance of the formulations increases. The following

Fig. 5. Response surface plot for friction work at medium level of compression force.

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Fig. 6. Response surface plot for friction work at medium level of mixing speed. Fig. 8. Response surface plot for R-value (lubrication coefficient) at medium level of compression force.

spectral ranges were found to be relevant by the software to evaluate the tablet resistance to crushing from the near infrared spectra: • from 11,918.9 to 10,106 cm −1 • from 9654.7 to 9199.6 cm −1 • from 8293.1 to 7386.7 cm −1 3.3.2. Interaction between the factors When an interaction occurs between two independent variables it means that a factor cannot produce the same effect on the response at different levels of the other factor [29]. As the analysis of variance demonstrated, in the case of granules, interaction between API:EXC ratio and mixing speed occurred only at bulk density. At tabletting process parameter interaction performed at lubrication, where API:EXC ratio had significant interaction with mixing speed. With the increase of mixing speed the lubrication enhancing effect of isomalt decreases (Fig. 8) at all levels of compression force. This effect is not linear and as the compression force increases, the surface gradient of the plot rises as well. On friction work the interactions do not have any significant effects. As the results of tablet characteristic studies represent, mixing speed interacts with API:EXC ratio. Furthermore, there is API:EXC ratio — compression force interaction to observe as well. The resistance to crushing of tablets is influenced by API:EXC ratio – mixing speed and API: EXC – compression force interaction. The mixing speed with API:EXC ratio has antagonistic effect (Fig. 9.) and by increasing the compression

Fig. 7. Near infrared spectra of tablets with API:EXC ratio 1:1 at 2000 rpm at three different levels of compression force.

force, the antagonism between API:EXC ratio — mixing speed is more expressed. However, the API:EXC ratio — compression force interaction is synergistic, as it led to an enhancement of tablet hardness and tensile strength on all levels of mixing speed. Tensile strength is influenced by the antagonistic interaction between mixing speed and API:EXC ratio, which is more expressed with increasing the compression force (Fig. 10). In contrast, API:EXC ratio and compression force have synergistic effect on tablet hardness on all levels of mixing speed. 4. Conclusions Overall the results indicate that paracetamol could be granulated with isomalt using only purified water without other binders. All formulated granules meet the requirements of the European Pharmacopoeia. The addition of mixing speed as a new independent variable to the statistical analysis has certified its appropriateness. Through its effect on the particle size distribution of the granules (the increase of granule homogeneity, the shift of mean particle size to lower values), it had an impact on the tablet characteristics as well — since the low

Fig. 9. Response surface plot for tablet hardness at high level of compression force.

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Fig. 10. Response surface plot for tablet tensile strength at high level of compression force.

particle size has reduced the tablet strength. Although, neither on lubrication nor on the friction appearing during compaction it does not have a remarkable effect, its interaction with API:EXC ratio on lubrication of tablets is significant. Since mixing speed takes part in the interaction with API:EXC ratio, the optimal mixing speed at granulation is crucial, which ensures not only sufficient homogeneity but also appropriate granule size to enhance tablet quality. The presence of isomalt in paracetamol containing granules has improved the lubrication and has decreased the friction during the tabletting process. Furthermore, it enhanced the tablet characteristics as well. The API:EXC ratio as an independent variable that acts on all the four investigated response variables. Moreover, it interacts with both mixing speed and compression force. Despite the fact that it has antagonistic effect with mixing speed, with compression force it proves to be synergistic. Regardless of the fact that the compression force as independent variable has significant impact on all response variables, in interaction it is significant only to the tablet characteristics.

Acknowledgments The authors wish to thank to Flextra Lab Ltd. for enabling the use of FT-NIR Analyzer and to István Fejes for the assistance at tablet investigations and data analysis.

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Zsófia Sáska Pharm.D. graduated as a pharmacist in 2007 at Semmelweis University Faculty of Pharmacy. She has been attending the Semmelweis University Ph.D. School (III. Pharmaceutical Sciences) since 2007 in the program Modern Trends in Pharmaceutical Scientific Research.

Judit Dredán Ph.D. studied pharmaceutics at the Semmelweis University where she graduated in 1977. She worked for the analytical department of a pharmaceutical industrial company. She has been teaching pharmaceutical technology at the Semmelweis University, Department of Pharmaceutics since 1990 where she obtained her Ph.D in 1998. In 2007 she obtained diploma as Legal Consulting Pharmacist. From 2008 she is an associate professor of the Semmelweis University, Department of Pharmaceutics. Her research fields are as follows: investigation of surface properties of solids, study of polymer coating systems.

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Z. Sáska et al. / Powder Technology 213 (2011) 132–140 Oliver Luhn. graduated as a Process Engineer from the University of Applied Sciences, Mannheim, in 1995. After his diploma thesis in the field of agglomeration and tabletting he joined the industry. Since 2005 he has been heading the group of pharmaceutical technology within the Central Department of Research and Development at his company and is focusing on the research and development of pharmaceutical excipients.

Gal Shafir, Pharm.D. obtained his pharmacist degree at the Semmelweis University in 2002. While working as pharmacovigilance specialist, he started his Ph.D. studies in the field of pharmaceutical technology.

Emese Balogh, Ph.D. graduated as pharmacist in 1992 at the Semmelweis University, where she is working as university lecturer after obtaining her Ph.D. in 2001. Her research interest is focused on solid dosage forms and biopharmacy.

István Antal, Ph.D. studied pharmaceutics at the Semmelweis University, where he obtained Ph.D. in 1995, associate professorship in 1998. He still works at the Department of Pharmaceutics of Semmelweis University as Deputy Head and Vice Dean. He received Janos Bolyai Certificate of Merit in 2002, and he has been the Head of Section of Pharmaceutical Technology of Hungarian Society for Pharmaceutical Sciences since 2009. His main research interest is related to development of pharmaceutical formulations, physical pharmacy, controlled drug release, mathematical–statistical modeling, scale-up, and nearinfrared reflectance spectroscopy.