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International Journal of Pharmaceutics

journal homepage: www.elsevier.com/locate/ijpharm

Continuous twin screw granulation: A complex interplay betweenformulation properties, process settings and screw design

Christoph Portiera, Kenny Pandelaerea, Urbain Delaetb, Tamas Vighb, Giustino Di Pretorob,Thomas De Beerc, Chris Vervaeta, Valérie Vanhoornea,⁎

a Laboratory of Pharmaceutical Technology, Department of Pharmaceutics, Ghent University, Ottergemsesteenweg 460, B-9000 Ghent, Belgiumb Pharmaceutical Research and Development, Division of Janssen Pharmaceutica, Johnson & Johnson, Turnhoutseweg 30, B-2340 Beerse, Belgiumc Laboratory of Pharmaceutical Process Analytical Technology, Department of Pharmaceutical Analysis, Ghent University, Ottergemsesteenweg 460, B-9000 Ghent, Belgium

A R T I C L E I N F O

Keywords:Continuous manufacturingTwin screw granulationWet granulationFormulationProcess variableGranule qualityDesign of experiments

A B S T R A C T

Due to the numerous advantages over batch manufacturing, continuous manufacturing techniques such as twinscrew wet granulation are rapidly gaining importance in pharmaceutical production. Since a large knowledgegap on the importance of formulation variables exists, this study systematically assessed the impact of differentscrew configurations and process settings on eight model formulations, varying in filler type, active pharma-ceutical ingredient (API) characteristics and drug load. Although liquid to solid (L/S) ratio was the most in-fluential variable for all formulations, also a large effect of the kneading element thickness was observed. Narrowkneading elements with a length to diameter ratio (L/D) of 1/6 had a significant detrimental effect on granulesize, flow and strength compared to 1/4 L/D elements. The effects of kneading element distribution and barrelfill level were less pronounced. At low drug load, both filler types could be used to obtain granules with ac-ceptable critical quality attributes (CQAs) for both APIs. Granulation at high drug load of the poorly soluble,poorly wettable API mebendazole proved challenging as it could not be processed using lactose as filler, incontrast to lactose/MCC. As formulations containing lactose/MCC as filler were less influenced by differentscrew configurations, process settings and API characteristics than formulations without MCC, lactose/MCC/HPMC was considered a promising platform formulation.

1. Introduction

After the publication of the Food and drug Administration (FDA)guidance for process analytical technology (PAT) in 2004, a significantamount of research has been conducted in the field of continuousmanufacturing (Kumar et al., 2013; Meier et al., 2017; U.S. Food andDrug Administration, 2004). Since the first FDA-approval of a con-tinuously manufactured drug product, Orkambi (Vertex) in 2015, sev-eral major pharmaceutical companies have obtained market access withthis novel manufacturing concept (Portier et al., 2020; Yu, 2016). Al-though direct compression is the preferred continuous manufacturingpathway due to the limited number of processing steps, it is often notapplicable due to inappropriate blend characteristics such as poorflowability, electrostatics and cohesiveness (Van Snick et al., 2017).

The last fifteen years, continuous twin screw wet granulation gained

a significant amount of interest within the pharmaceutical industry.Several publications focus on different screw configurations (Djuric andKleinebudde, 2008; Li et al., 2014; Thompson, 2015; Thompson andSun, 2010; Vercruysse et al., 2015), process settings (Fonteyne et al.,2015; Meier et al., 2017; Vanhoorne et al., 2016b; Vercruysse et al.,2012, 2015) and in recent years the implementation of PAT and real-time process control (Harting and Kleinebudde, 2018; Madarász et al.,2018; Verstraeten et al., 2018). Most of these studies are however re-stricted to a single formulation, basically limiting the applicability ofthe results to formulations with similar characteristics.

As only limited knowledge is available on the importance of for-mulation variables (Thompson, 2015; Yu et al., 2014), this study aimsto provide a systematic comparison between the behavior of differentmodel formulations, varying in API characteristics, filler type and drugload. By investigating the effect of different screw configurations, barrel

https://doi.org/10.1016/j.ijpharm.2019.119004Received 2 October 2019; Received in revised form 23 December 2019; Accepted 26 December 2019

Abbreviations: API, Active Pharmaceutical Ingredient; CQA, Critical Quality Attribute; DoE, Design of Experiments; FDA, Food and Drug Administration; HR,Hausner Ratio; KE, Kneading Element; KZ, Kneading Zone; L/D, Length to Diameter; LOD, Loss On Drying; L/S, Liquid to Solid; MCC, Microcrystalline Cellulose; PCA,Principle Component Analysis; PSD, Particle Size Distribution; rpm, Revolutions Per Minute; SCE, Size Control Element

⁎ Corresponding author.E-mail address: Valerie.Vanhoorne@UGent.be (V. Vanhoorne).

International Journal of Pharmaceutics 576 (2020) 119004

Available online 11 January 20200378-5173/ © 2020 Elsevier B.V. All rights reserved.

T

fill levels and liquid to solid (L/S) ratios on these model formulations,the general applicability of the findings can be evaluated. Previousstudies mainly focused on the effect of different grades of pure ex-cipients (Keleb et al., 2004a; Lute et al., 2018a; Yu et al., 2014) orchanging a single component in a more complex formulation (ElHagrasy et al., 2013; Fonteyne et al., 2015, 2014; Meier et al., 2015;Vanhoorne et al., 2016a). Recently, a novel approach was proposed byWillecke et al. who used principal component analysis (PCA) on rawmaterial characterization and subsequently integrated these quantifiedoverarching properties in a design of experiments (DoE) approach(Willecke et al., 2018).

2. Materials and methods

2.1. Materials

Microcrystalline cellulose (MCC) and α-lactose monohydrate wereused as fillers and were purchased from DowDuPont (Avicel PH 101,Midland, MI, USA) and DFE Pharma (Pharmatose 200M, Goch,Germany), respectively. Hydroxypropylmethylcellulose (HPMC)(Methocel E15 LV, Colorcon, Dartford, UK) was used as a dry binder ina 5% concentration. Distilled water was used as granulation liquid andadded on top of the screws using two 1.6 mm nozzles. Metformin hy-drochloride and mebendazole (both obtained via JanssenPharmaceutica) were used as model APIs, having a good versus poorsolubility and wettability, respectively. Based on these raw materials, 8different formulations were composed, differing in model API, drugload (5 and 50%) and filler type (lactose or lactose:MCC 1:1) as shownin Table 1. Filler types and ratios were chosen based on an earliercomparative study on model formulations (Portier et al., 2020), as wellas existing literature on both conventional batch and continuousmanufacturing (Djuric and Kleinebudde, 2008; El Hagrasy et al., 2013;Fonteyne et al., 2014; Keleb et al., 2004b; Li et al., 2014; Osei-Yeboahet al., 2014; Thompson and Sun, 2010).

2.2. Preparation of granules

Prior to granulation, a preblend of the raw materials was madeusing a tumbling blender (Inversina Bioengineering, Wald, Switzerland)operated at 25 rpm during 15 min. If metformin.HCl was included inthe formulation, the API was first milled due to its cohesive natureusing a U5 Quadro Comil (3000 rpm, round holed screen, screen size1397 µm, Quadro, Waterloo, Canada). Granules were produced using acontinuous co-rotating intermeshing twin screw granulator with alength to diameter (L/D) ratio of 20:1 (Consigma™-25, GEA, Düsseldorf,Germany). Using a gravimetrically controlled twin screw feeder (KT20,K-Tron Soder, Niederlenz, Switzerland), the preblend was fed into thetemperature-controlled barrel (T = 30 °C). Distilled water was added asgranulation liquid before the first kneading zone using two out-of-phaseperistaltic pumps (pump speed between 60 and 100 rpm) and silicontubings (Watson Marlow, Cornwall, UK). The general screw setupconsisted of 2 kneading zones (KZ1, KZ2) with kneading elements in aforward stagger angle of 60°, followed by a zone of size control

elements, as a previous study showed these were beneficial for ob-taining a more narrow particle size distribution (PSD) (Portier et al.,2020). Wet granules were collected at the outlet of the granulator barreland dried in an oven at 40 °C until a moisture content between 1 and3% was obtained prior to characterization. The moisture content wasdetermined by heating 1 g of granules to 105 °C until a stable mass wasrecorded during 30 s (Mettler Toledo LP 16 moisture analyzer, MettlerToledo, Zaventem, Belgium).

2.3. Design of experiments

In the current study, the effect of five factors was evaluated in a D-optimal design: (i) fraction of kneading elements (KE) in the firstkneading zone, (ii) KE thickness, (iii) screw speed, (iv) throughput and(v) liquid to solid (L/S) ratio. The first two factors were included toassess the effect of screw configuration differences. The total length ofKZ1 + KZ2 was kept fixed at a length to diameter (L/D) ratio of 3(Fig. 1), and therefore screw configurations with either 12 pieces of 1/4D-long or 18 pieces of 1/6D-long kneading elements were used. Theeffect of the barrel fill level was estimated by the specific feed load(SFL), which is defined as the ratio between throughput and screwspeed (Harting and Kleinebudde, 2019; Lute et al., 2018b). Throughputwas varied between 15 and 20 kg/h to operate at the high end of thegranulator capacity. The screw speed range (500–800 rpm) was basedon preliminary tests to ensure sufficient processing capacity at thechosen throughput range. L/S ratio was included in the study as this iscommonly described as the most influential factor for twin screw wetgranulation (El Hagrasy et al., 2013; Keleb et al., 2004b; Portier et al.,2020; Thompson, 2015). Center point L/S ratios (Table 1) were basedon preliminary trials and chosen to obtain roughly 15% of oversizedgranules at center point conditions. Ranges were set to 87.5% and112.5%, relative to the center point’s L/S values. A D-optimal optimi-zation design was chosen as this is ideally suited for evaluation ofqualitative factors (e.g. different kneading element thicknesses) andalso provides an estimation of interactions and quadratic terms to buildresponse surface models (Eriksson et al., 2001; Vercruysse et al., 2012).The factor settings of the individual runs in the experimental design aregiven in Table 2. The experimental design was set up and analyzedusing MODDE Pro 12.0 (Umetrics, Sartorius Stedim Biotech, Malmö,Sweden). Response surface models were built using multiple linearregression (MLR). The models terms with the smallest effect werestepwise excluded for each response as long as there was no globalreduction of the predictive power larger than 0.1 compared to thehighest achievable Q2. Main effects were however retained if their in-teractions or quadratic terms contributed to the predictive power of themodel (Eriksson et al., 2001).

Granulator barrel temperature was not evaluated as the Consigma™-25 unit is equipped with an active cooling system. All analyzed granuleswere collected at a barrel temperature of 30° C as the cooling systemwas always able to compensate for the heat generated inside the barrel.Torque was not described in detail as this was not a limiting factor forany granulation run and it is an equipment-specific measure and limit.Time to reach steady state heavily relies on the previously performedexperiments (run order). As the individual runs were performed se-quentially (in a randomized order), time to steady state was notquantitatively assessed in current study.

2.4. Granule characterization

2.4.1. Particle size analysisParticle size distribution (PSD) was measured in triplicate by sieve

analysis (Retsch VE 1000, Haan, Germany). The sieving tower includedsieves of 2000, 1000, 850, 500, 250, 150 and 75 µm. After loading100 g on the top sieve, the tower was shaken for 5 min at an amplitudeof 2 mm. Process yield was defined as the granule fraction between 150and 1000 µm. The oversized and fine fraction were defined as

Table 1Overview of the different formulations with indication of the L/S ratio of theDOE center points.

Model API Metforminhydrochloride

Mebendazole

Drug load Low (5%) High(50%)

Low (5%) High(50%)

Filler type Lactose 0.078 0.066 0.090 N/ALactose:MCC(1:1)

0.248 0.132 0.270 0.276

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particles> 1000 µm and<150 µm, respectively.

2.4.2. Bulk and tapped densityBulk and tapped density were measured in triplicate with a tapping

device (J. Engelsmann, Ludwigshafen, Germany). A graduated cylinderof 250 ml was filled with ± 100 g (m) granules to determine the initialvolume (V0). Bulk density (ρB) was calculated by dividing the mass (m)by the initial volume (V0). If the difference between the volume after500 (V500) and 1250 taps (V1250) exceeded 2 ml, 500 additional tapswere performed (V1750). In this case, the tapped density (ρT) was de-fined as the ratio between m and V1750 instead of the ratio between mand V1250 (European Directorate for the Quality of Medicine, 2017).

2.4.3. FlowabilityTo estimate granule flowability, the Hausner ratio (HR) was calcu-

lated from the ratio between bulk and tapped density, as shown in Eq.(1) (European Directorate for the Quality of Medicine, 2017).

=HRρρ

T

B (1)

2.4.4. FriabilityFriability of granules was determined in triplicate by loading±10 g

(m1) of a granular fraction larger than 250 µm in a plexiglass drumequipped with baffles. Subsequently 200 glass beads (Carl Roth GmbH,Karlsruhe, Germany) with a mean diameter of 4 mm were added andgranules were rotated for 10 min at 25 rpm on the friabilator(Pharmatest PTF E, Hainburg, Germany). Glass beads and granuleswere separated and subsequently the granular mass larger than 250 µmwas determined (m2). Friability (Fr) was calculated using Eq. (2). Afriability limit of 30% is maintained as cut-off value above whichgranules are prone to extensive breakage and/or attrition duringdownstream processing.

=−

×Fr m mm

(%) 1001 2

1 (2)

2.5. Correlation between model formulations

The Pearson correlation coefficient r was calculated using Eq. (3)and was used to determine the linear correlation between the responsedatasets of two individual formulations. x and y were defined as theaverage of the first and second response dataset, respectively. Thenumber of experiments (n) was 27 for all responses.

=∑ − −

∑ − ∑ −

=

= =

rx x y y

x x y y

( ¯)( ¯)

( ¯) ( ¯)in

i i

in

i in

i

1

12

12

(3)

3. Results and discussion

3.1. Model quality

For all formulations, MLR models with a reproducibility> 0.5 andpredictive power (Q2)> 0.5 could be obtained with a model fit(R2)> 0.5 and validity> 0.25 for most responses, as illustrated inFig. 2a for the low-dosed lactose/MCC/metformin.HCl formulation.Data on the model quality of the other formulations is provided in thesupplementary data. R2 is the model fit, which indicates the fraction ofvariation explained by the model. Q2 estimates the ability of the modelto predict new data points, based on internal cross-validation. Modelvalidity compares the model error to the pure error (based on re-producibility of the center points). Reproducibility indicates the var-iation of the response when experiments are performed under the sameconditions (center point level) (Eriksson et al., 2001). The reportedmodels are based on an optimized Q2, where the smallest factors (in-teractions or squared terms) were sequentially removed as long as therewas no global reduction of the predictive power larger than 0.1 com-pared to the highest achievable Q2. Main factors were only removed ifthe main factor itself, as well as its interactions and quadratic terms did

Fraction of kneading elements in first kneading zone (KZ1): 1/3

1/2

2/3

Fig. 1. Modular screw configuration of twin screw granulator. Total kneading zone length (KZ1 + KZ2) fixed at 3 L/D. T: transport zone; KZ: kneading zone; SCE:size control element.

Table 2Experimental D-optimal design.

Experimentnumber

Fraction ofkneadingelements(KE) in firstkneadingzone

KE thickness Screwspeed(rpm)

Throughput(kg/h)

L/S ratio(% ofcenterpoint)(i)

1 1/3 1/4 LD 500 20.0 87.52 1/3 1/4 LD 500 16.7 112.53 1/3 1/4 LD 800 15.0 95.84 1/3 1/4 LD 800 20.0 104.25 1/3 1/4 LD 800 18.3 112.56 1/3 1/4 LD 700 15.0 87.57 1/3 1/4 LD 600 15.0 112.58 1/2 1/4 LD 500 15.0 104.29 1/2 1/4 LD 800 16.7 87.510 1/2 1/4 LD 700 20.0 112.511 2/3 1/4 LD 500 15.0 87.512 2/3 1/4 LD 800 20.0 87.513 2/3 1/4 LD 800 15.0 112.514 2/3 1/4 LD 500 20.0 112.515 2/3 1/4 LD 650 17.5 100.016 1/3 1/6 LD 500 15.0 87.517 1/3 1/6 LD 800 20.0 87.518 1/3 1/6 LD 800 15.0 112.519 1/3 1/6 LD 500 20.0 112.520 1/2 1/6 LD 650 17.5 100.021 2/3 1/6 LD 800 15.0 87.522 2/3 1/6 LD 500 20.0 87.523 2/3 1/6 LD 500 15.0 112.524 2/3 1/6 LD 800 20.0 112.525 1/2 1/6 LD 650 17.5 100.026 1/2 1/6 LD 650 17.5 100.027 1/2 1/6 LD 650 17.5 100.0

(i) The L/S ratios of the center point for the individual formulations are givenin Table 1.

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not significantly contribute to the predictive power of the model.The predictive power for the yield fraction was limited (0.2–0.3) for

the high-dosed metformin formulations and the formulation containing5% metformin and lactose as filler. For these formulations, the quad-ratic term L/S*L/S had the most dominant effect, whereas for all otherformulations L/S ratio had the largest effect. These differences werepartially attributed to the choice of the L/S ranges, which was based onpreliminary trials and the varying sensitivity of formulations to changesin L/S ratio. Depending on the location of the evaluated L/S range withrespect to the optimum yield, either a quadratic or more linear behavioris to be expected. If the optimum is situated near one of the limits of theevaluated L/S ratio, a linear relationship is most suited, whereas aquadratic term is required to describe the relationship between L/Sratio and yield if the optimum is situated more within the evaluated L/Srange. Quadratic terms have a higher uncertainty, resulting in worsemodels than models with a predominating linear effect. Secondly,previous studies have shown the high susceptibility of lactose tochanges in L/S ratio, thus leading to a small granulation window,whereas lactose/MCC-based formulations have a very wide granulationwindow, originating from the high water binding capacity of MCC(Schmidt et al., 2016). Metformin, as high soluble drug, is expected tobehave similar to lactose. Hence the quadratic effect was dominant informulations with a high soluble content.

Models with a reproducibility approaching unity, often had poormodel validity because this estimate compares the uncertainty/error onthe model to the experimental error, which approaches zero in thesecases. As this is a relative measure, the consequent poor model validitydid not indicate a poor model (Eriksson et al., 2001).

3.2. Low drug load formulations

3.2.1. Particle size distributionParticle size-related measures (fines, yield and oversized) of low-

dosed formulations were dominated by the L/S ratio (Fig. 2b). HigherL/S ratios significantly increased the fraction of oversized granules forall formulations which is consistent with current literature and inherentto wet granulation (El Hagrasy et al., 2013; Fonteyne et al., 2015; Kelebet al., 2004b; Portier et al., 2020; Thompson, 2015). Despite the simi-larity at center point level, the lactose/metformin.HCl/HPMC for-mulation had, on average, a lower amount of fines compared to theother formulations (Fig. 3). Similar to the results obtained by Hwanget al., larger L/S ratio factor effects were observed for the formulationscontaining only lactose as a filler, which is reflected by the broaderfines fraction (Hwang et al., 2019). This was attributed to the solublenature of lactose, which was more susceptible to the amount of avail-able granulation liquid, compared to the insoluble MCC (Schmidt et al.,2016). In contrast to lactose-based formulations, the effect sizes oflactose/MCC-based formulations varied less in function of the experi-ments and were less influenced by the API properties. As a more con-sistent and smaller effect was found for this filler type, it can potentiallybe used as a robust platform formulation in formulation development.Since throughput had no significant effect on PSD measures, the effectof the specific feed load and thus barrel fill level was mainly dictated byscrew speed. These results were consistent with a previous study, whichassessed the effect of throughput on model formulations when variedbetween 15 and 20 kg/h (Portier et al., 2020). A larger factor effectcould be expected when expanding this factor range in both studies.Higher screw speeds consistently resulted in smaller granules due to thelower specific feed load and hence barrel fill level, similar to the find-ings of Dhenge et al. who evaluated the effect of screw speed on aplacebo formulation consisting of lactose (73.5%), MCC (20%),

Fig. 2. Summary of fit plot (A) and optimized effect plots of included factors, interactions and quadratic terms on oversized fraction (B), Hausner ratio (C) andfriability (D) for lactose/MCC/metformin.HCl/HPMC (45/45/5/5). L/S = liquid to solid ratio, Thick = kneading element thickness, KE1 = fraction of kneadingelements in the first kneading zone, Scr = screw speed, Thr = throughput.

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croscarmellose sodium (1.5%) and hydroxypropyl cellulose (1%)(Dhenge et al., 2010). Due to the opposite effect of screw speed on theoversized and fines fraction, no significant impact was observed on theyield fraction except for lactose/metformin.HCl/HPMC. Other studies,using several extruder types, mainly reported a very limited effect ofscrew speed (Djuric et al., 2009; Thompson and Sun, 2010; Vanhoorneet al., 2016b; Vercruysse et al., 2012). In contrast, an increase in theoversized fraction at higher screw speeds has been described byThompson and O’Donnell, who studied the effect on a controlled releaseformulation (Thompson and O’Donnell, 2015). Although the effect ofscrew speed is also determined by the studied range, its impact isclearly formulation-dependent. A lower screw speed is either favorabledue to a higher specific feed load and therefore barrel fill level, or it isdetrimental due to the lower kinetic energy transferred into the system.

Narrow kneading elements (1/6 L/D) significantly and consistentlyreduced the particle size and fraction of oversized granules for all for-mulations and had an even more pronounced effect on the fines frac-tion. This can be attributed to the larger chopping effect when the totalshear plane is split up into more individual elements. Furthermore, lessdensification and granule growth was expected due to the smaller in-dividual shear areas between both screws. The effect of using 1/6 L/Dkneading elements ranged from− 6 to− 9% for the oversized fraction,although the combined length of both kneading zones was constant. Onthe other hand, these narrow elements increased the amount of fines by8–15%, resulting in a net yield decrease. When shifting more kneadingelements towards the first kneading zone, the oversized fraction in-creased by 3–6%. As no effect was observed on the amount of fines, thisresulted in a limited yield decrease, except for lactose/metformin.HCl/HPMC, where a statistically non-significant effect was obtained.Overall, both lactose- and lactose/MCC-based formulations showedhigh correlations for PSD-related measures except yield. The lactoseand lactose/MCC formulations had a correlation coefficient (r) of 0.81

and 0.84 for the oversized fraction, respectively.

3.2.2. Bulk and tapped densityLactose-based formulations showed limited susceptibility of bulk

density towards changes in process settings and screw configurations(factor effects< 0.04 g/ml), resulting in ranges of 0.47–0.56 g/ml and0.48–0.57 g/ml for the formulations containing metformin.HCl andmebendazole, respectively. Although the average bulk density of lac-tose/MCC formulations was lower due to the lower density of the mi-crocrystalline cellulose (Portier et al., 2020) and the effect sizes werenotably larger, similar maximum bulk densities could be achieved:0.36–0.55 g/ml for the mebendazole formulation and 0.37–0.56 g/mlfor the metformin.HCl formulation.

Similar to the effect on particle size, a high L/S ratio and 1/4 KEthickness was beneficial for obtaining granules with good quality at-tributes as these conditions yielded denser granules for lactose/MCC-based formulations. The effect of the screw speed and throughput onbulk density was generally more limited and the fraction of kneadingelements in the first kneading zone had a negligible impact. Similarfactor influences were obtained for tapped density.

3.2.3. FlowabilityThe lowest Hausner ratios, indicating good flow properties, were

obtained for the lactose/metformin.HCl/HPMC formulation (Fig. 4) asthis was the formulation with, on average, the largest granules andconsisting of the raw materials with the highest bulk density. The otherlow-dosed formulations varied within a similar range, varying from fairto passable flow (European Directorate for the Quality of Medicine,2017).

Due to the limited flowability differences within each formulation,only a limited correlation was obtained between the lactose (r = 0.48)and lactose/MCC formulations (r = 0.71). Using high L/S ratios and 1/

Fig. 3. Fraction of fines for low drug load formulations. Lac = lactose, MCC = microcrystalline cellulose, Meb = Mebendazole, Met = Metformin.HCl.

Fig. 4. Hausner ratio of low drug load formulations. Lac = lactose, MCC = microcrystalline cellulose, Meb = Mebendazole, Met = Metformin.HCl.

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4 L/D kneading elements proved beneficial to obtain granules withgood flow properties (Fig. 2c). This observation is aligned with theobtained results on bulk and tapped density.

3.2.4. FriabilityFormulations containing lactose/MCC as filler performed sig-

nificantly better during friability testing (Fig. 5), as almost all runsresulted in granules with a friability lower than 30%, indicating gran-ules which are strong enough for further downstream processing (VanMelkebeke et al., 2008; Vanhoorne et al., 2016a). L/S ratio was themost influential factor on granule friability, followed by a detrimentaleffect of narrow kneading elements (Fig. 2d). These findings are similarto previous studies evaluating the effect of kneading element thickness(Li et al., 2014; Thompson, 2015; Van Melkebeke et al., 2008). As these

factors were also the driving factors for particle size, a clear correlationbetween these responses was observed, which can be attributed to thefriability measurement principle. Due to the initial selection of theentire granule fraction larger than 250 µm, granules with a largerparticle size were expected to be less susceptible to attrition andbreakage. Attrition of granules of similar intrinsic bonding strength islower because of the lower total surface area. Breakage is also detectedto a lower extent since larger particles can break up into several par-ticles larger than 250 µm, which are still retained on the sieve.Therefore, the friability measurement does not only represent theamount of bonds within the granule and subsequently the granulestrength, but it is confounded with the granule size.

Although the produced lactose/MCC granules were only slightlylarger than the lactose granules at center point, the magnitude of the

Fig. 5. Friability of low drug load formulations. Lac = lactose, MCC = microcrystalline cellulose, Meb = Mebendazole, Met = Metformin.HCl.

Fig. 6. Optimized effect plots of included factors, interactions and quadratic terms on oversized fraction (A), bulk density (B), Hausner ratio (C) and friability (D) forlactose/MCC/mebendazole/HPMC (22.5/22.5/50/5). L/S = liquid to solid ratio, Thick = kneading element thickness, KE1 = fraction of kneading elements in thefirst kneading zone, Scr = screw speed, Thr = throughput.

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factor effects on friability was significantly smaller for the former for-mulations. Furthermore, a clear correlation between both lactose/MCCformulations was observed (r = 0.85 versus 0.51 for lactose-basedformulations). Combined with the similar effect sizes, this again in-dicated the limited susceptibility of this filler type towards alteredprocess settings and API properties.

3.3. High drug load formulations

Preliminary trials indicated that no acceptable granules could beobtained when combining 50% mebendazole with only lactose as afiller as initial trials resulted in highly friable granules with too muchfines and poor flow properties. This is accounted for by the high drugload of the poorly soluble and poorly wettable API mebendazole. Whencombining this API with the soluble and highly wettable filler lactosewithout a compound with sufficient amphiphilic properties, granuleswith poor quality attributes were obtained. Consequently, no DoE wasset up for this formulation, and it was retained from further analysis.

3.3.1. Particle size distributionThe effects on the particle size-related measures were similar to

those of low-dosed formulations. The most significant influences ori-ginated from the L/S ratio and KE thickness (Fig. 6a). Screw speed,throughput and the fraction of kneading elements in the first kneadingzone were less influential. The size of the effects was generally com-parable to that of the corresponding low-dosed formulations. Re-markably, a low barrel fill level (indicated by low specific feed loadwith low throughput and high screw speed) contributed to moreoversized granules for the high-dosed mebendazole formulation, in-dicating that this formulation benefits more from an increased energyinput rather than densification inside the barrel.

In contrast to low-dosed lactose/MCC formulations, no strong cor-relations were found at a high drug load (r = 0.51), as can be seen inFig. 7 for the fraction of fines. Although the oversized fraction was thesame for all three formulations at center point level, the lactose/met-formin formulation yielded less fines, resulting in a larger yield. Thiswas attributed to the very high aqueous solubility of the API. A similareffect was, to a lesser extent, also observed at a low drug load.

3.3.2. Bulk and tapped densityWhereas L/S ratio and KE thickness were the dominant factors for

low-dosed formulations, the bulk and tapped density of the lactose/metformin formulation were almost solely dictated by the screw speedand throughput. For lactose/MCC-based formulations, the effect of L/Sratio and KE thickness was also much less pronounced (Fig. 6b). Screwspeed and throughput had a more limited effect on the lactose/MCCformulations. A high barrel fill level, determined by a high throughputand low screw speed, was favorable for the metformin formulation,whereas lower barrel fill levels (indicated by lower specific feed loads)

were preferable for the mebendazole formulation, again indicating thatthe latter formulation required a high energy input, rather than den-sification within the barrel. Bulk and tapped densities were, on average,slightly lower than those of low-dosed formulations due to the lowerAPI densities compared to the fillers. No correlations between bothlactose/MCC-based formulations were obtained: r = 0.03 and 0.07 forbulk and tapped density, respectively, indicating that at 50% drug load,the lactose/MCC filler combination is much more susceptible to APIproperties.

3.3.3. FlowabilityAs shown in Fig. 8, flowability of the high-dosed mebendazole

granules was significantly worse than those of high-dosed metfor-min.HCl granules, which were less affected by process settings or screwconfigurations. This effect was related to the different API properties,with metformin.HCl able to dissolve in the binder liquid and re-crystallize upon drying, in contrast to the hydrophobic API mebenda-zole. For the latter, further formulation or process optimization (e.g.higher binder concentration, different binder, screw configuration withmore shear …) would be required.

The influence of the model factors on flowability was strongly for-mulation-dependent as no general tendencies or correlations could beobserved. For the 50% mebendazole formulation (Fig. 6c), L/S ratioshowed the strongest contribution, comparable to its low-dosed coun-terpart. The effect of screw speed was more pronounced compared tothe low-dosed formulation and, unique for this formulation, a higherscrew speed resulted in better flowing granules, in alignment with thelarger granules due to a dominant effect of the higher kinetic energyover a reduced barrel fill level.

3.3.4. FriabilityCompared to the low-dosed formulations, the obtained high-dosed

granules were, on average, weaker (Fig. 9). As mebendazole is in-soluble, it cannot contribute to the formation of additional bonds withinthe granules. For metformin.HCl formulations, it was hypothesized thatthe strength of bonds involving the API was substantially lower thanbonds formed through dissolution and recrystallization of lactose.However, for all formulations, a friability lower than 30% could bereached at specific combinations of process settings and screw config-urations. When comparing the friability of both metformin.HCl for-mulations, it was clear that lactose/MCC was superior as substantiallystronger granules were created. Despite having larger granules than theother high-dosed formulations, the friability of lactose/metformin oftenexceeded 50%.

Considering the individual factor effects, L/S ratio was still the mostinfluential for the metformin formulations, but a stronger relativecontribution of the screw speed was observed compared to low-dosedformulations, especially for lactose/MCC/mebendazole (Fig. 6d). Thiscould be attributed to the lower bulk density of the APIs compared to

Fig. 7. Fraction of fines for high drug load formulations. Lac = lactose, MCC = microcrystalline cellulose, Meb = Mebendazole, Met = Metformin.HCl.

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the excipients, resulting in a higher barrel fill level and higher sus-ceptibility towards process changes impacting the barrel fill level. Thefraction of kneading elements positioned in the first kneading zone hada very limited and formulation-dependent impact. Taking into accountthat lactose is not a suitable filler in combination with a highly dosed,poorly soluble API (based on the higher friability and the larger factoreffects), for this formulation lactose/MCC is preferred as filler.

3.4. Use of lactose/MCC as robust platform formulation

The data in the current study indicated that lactose/MCC/HPMC is avery versatile and robust platform formulation for low-dosed formula-tions, towards both susceptibility of API properties as process settingsand screw configurations. This was illustrated by the higher correla-tions (Table 3) for this filler type compared to lactose as well as nar-rower response ranges, especially for particle size and friability. Fur-thermore, these formulations yielded significantly stronger granules,which is beneficial for downstream processing. This indicates that theexcipient combination lactose/MCC/HPMC could be useful during thedevelopment of new drug products, independent of the API properties,thus limiting API-consumption in early R&D. In the current study, a lowdrug load of 5% was used. However, to further explore the full potentialof this robust filler combination, additional tests with higher drug loadsand additional APIs with different properties should be performed.

At high drug load, lactose/MCC performed better than lactose,especially for the poorly soluble API mebendazole, as only with thisfiller combination granules with acceptable CQAs were obtained.Additional studies for these poorly soluble APIs should focus on opti-mization of this formulation using different binders, surfactants andscrew configurations. For the highly soluble API, the advantages overpure lactose were less pronounced, although granule strength was, onaverage, higher.

Despite the clear advantages of lactose/MCC, several aspects ofusing MCC require further attention. Due to the high water bindingcapacity, substantially high amounts of water are required to obtaingranules with good quality attributes (Table 1). Due to the continuousnature of the subsequent drying unit operation, and therefore limiteddrying capacity, these higher L/S ratios could potentially limit thethroughput at which the manufacturing line can be operated. Furtherresearch is required to evaluate if these formulations can be dried atmaximum throughput. Secondly, MCC is an excipient originating fromnatural resources (wood pulp) and therefore prone to seasonal andyearly variability (Fonteyne et al., 2015). To assess the impact of thenatural variability, additional research on granulation, fluid bed drying,milling and tableting is required.

For novel formulations, processed through continuous twin screwwet granulation, the ratio of lactose/MCC could be optimized, takinginto account the considerations raised above. Although a high MCCcontent is clearly beneficial in terms of process robustness and handlingAPIs with different properties, the fraction of MCC could be reduced inmost cases. For low-dosed formulations, 45% MCC was used, which ishigh given the limited impact of API properties. Rather than using afixed ratio for lactose/MCC, formulators should prefer using a fixedMCC concentration of 20–25% and adding lactose as secondary filler.This MCC content is sufficient for processing challenging APIs with a

Fig. 8. Flowability of high drug load formulations. Lac = lactose, MCC = microcrystalline cellulose, Meb = Mebendazole, Met = Metformin.HCl.

Fig. 9. Friability of high drug load formulations. Lac = lactose, MCC = microcrystalline cellulose, Meb = Mebendazole, Met = Metformin.HCl.

Table 3Overview of correlation coefficients (r) for low-dosed formulations.

Correlationcoefficient (R2)

Oversized Yield Fines Bulkdensity

Hausner ratio Friability

Lactose 0.81 −0.20 0.93 0.73 0.48 0.51Lactose:MCC

(1:1)0.84 0.79 0.90 0.84 0.71 0.85

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high drug load, while limiting the possible detrimental effects of MCCsuch as increased drying time/temperature, higher torque and batch-to-batch variability. For novel drug product development, additional ex-cipients such as disintegrants and flow-agents could also be required,potentially impacting the granulation behavior and robustness of thesuggested platform formulation. Further research is however requiredto quantify the effect of these excipient types. Additionally, other highlysoluble excipients such as mannitol could be evaluated instead of lac-tose, as lactose is prone to Maillard type condensation reactions withprimary (and some secondary) amines, resulting in the formation ofbrown-colored products (Rowe et al., 2009).

4. Conclusion

This study assessed the effect of screw configuration and processsettings on eight different model formulations varying in filler type, APIproperties and drug load. L/S ratio was the most dominant processsetting for all formulations. The use of narrow kneading elements (1/6L/D ratio) in the screw configuration showed a detrimental effect ongranule attributes, generating smaller granules with poorer flow prop-erties and higher friability compared to 1/4 L/D kneading elements.The effect of the barrel fill level (determined by screw speed andthroughput) was generally less pronounced. Higher barrel fill levelsgenerated larger granules with higher bulk density and lower friabilityfor all formulations, except the high-dosed mebendazole. The effect ofkneading element distribution was limited and formulation-dependentfor most responses.

At low drug load the filler type proved more dominant than the APIproperties as the granule characteristics of the low-dosed formulationswith the same filler were similar. In general, formulations with lactose/MCC as filler were more robust and less susceptible to different processsettings and screw configurations. Addition of MCC to the formulationdid not only affect process robustness, but also limited the effects of theAPI properties and can therefore be beneficial in formulation devel-opment of novel APIs. To assess the full robustness potential of thisfiller type, further research using higher drug loads and APIs with in-termediate properties is required.

Although 50% metformin.HCl could be properly granulated withboth filler types, granulation of the poorly soluble mebendazole at highdrug load proved impossible using lactose as filler. Granules were ob-tained with lactose/MCC, however the flowability of these granules wasoften sub-standard and required high L/S ratios, potentially challengingthe limits of the six-segmented fluid-bed dryer. Therefore, additionalresearch on formulating high-dosed poorly soluble APIs should beperformed.

CRediT authorship contribution statement

Christoph Portier: Conceptualization, Methodology, Formal ana-lysis, Investigation, Writing - original draft, Writing - review & editing,Visualization, Project administration. Kenny Pandelaere:Investigation. Urbain Delaet: Conceptualization. Tamas Vigh:Conceptualization, Methodology, Writing - review & editing. GiustinoDi Pretoro: Supervision, Project administration, Funding acquisition.Thomas De Beer: Methodology. Chris Vervaet: Conceptualization,Writing - review & editing, Supervision, Project administration,Funding acquisition. Valérie Vanhoorne: Conceptualization, Writing -review & editing, Supervision, Project administration.

Declaration of Competing Interest

The authors declare that they have no known competing financialinterests or personal relationships that could have appeared to influ-ence the work reported in this paper.

Acknowledgments

This work was supported by the agency Flanders Innovation andEntrepreneurship (IWT project n° 145059). GEA and Colorcon are ac-knowledged for kindly providing the 1/6 L/D kneading elements andHPMC, respectively.

Appendix A. Supplementary material

Supplementary data to this article can be found online at https://doi.org/10.1016/j.ijpharm.2019.119004.

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