Extrusion-based Technologies for 3D Printing: a Comparative Study of the Processability of Thermoplastic Polyurethane-based Formulations

Depósito de Investigación de la Universidad de Sevilla https://idus.us.es/ This is an Accepted Manuscript of an article published by Taylor & Francis in PHARMACEUTICAL DEVELOPMENT AND TECHNOLOGY, Vol. 28 , Issue 10, on 31 Oct 2023 available at: https://doi.org/10.1080/10837450.2023.2274945 1 Extrusion-based technologies for 3D printing: a comparative study of the processability of thermoplastic polyurethane-based formulations. Ángela Aguilar-de-Leyva, Vicente Linares*, Juan Domínguez-Robles, Marta Casas, Isidoro Caraballo Department of Pharmacy and Pharmaceutical Technology, Faculty of Pharmacy, Universidad de Sevilla, C/Profesor García González 2, 41012 Seville, Spain. *Corresponding author: vlin[email protected] 2 Extrusion-based technologies for 3D printing: a comparative study of the processability of thermoplastic polyurethane-based formulations. Thermoplastic polyurethanes (TPU) offer excellent properties for a wide range of dosage forms. These polymers have been successfully utilized in personalized medicine production using Fused Deposition Modeling 3D printing (3DP). However, Direct Powder Extrusion (DPE) has been introduced recently as a challenging technique since it eliminates filament production before 3DP, reducing thermal stress, production time, and costs. This study compares DPE and single-screw extrusion for binary (drug-TPU) and ternary (drug-TPUmagnesium stearate) mixtures containing from 20 to 60 % w/w of theophylline. Powder flow, mechanical properties, fractal analysis and percolation theory were utilized to analyze critical properties of the extrudates. All the mixtures could be processed at a temperature range between 130 and 160ºC. Extrudates containing up to 50% w/w of drug (up to 30% w/w of drug in the case of single-screw extrusion binary filaments) showed toughness values above the critical threshold of 80 kg/mm2. Magnesium stearate improved flow in mixtures where the drug is the only percolating component, reduced until 25 °C the DPE temperature and decreased the extrudate roughness in high drug content systems. The potential of DPE as an efficient one-step additive manufacturing technique in healthcare environments to produce TPU-based tailored on-demand medicines has been demonstrated. Keywords: 3D printing; Thermoplastic Polyurethanes; Single Screw Extrusion; Direct Powder Extrusion; fractal analysis. 3 1. Introduction 3D printing technology is being widely applied in different industries such as automotive, construction, or aerospace. In the healthcare sector, it is applied to the production of dental apparatuses, implants, or even bone scaffolds. In the field of pharmacy, investigation related to 3D printing technologies is gaining an increasing interest due to the possibility that offers relationed with the production of personalised medicines (Aguilar-De-Leyva et al. 2020; Krueger et al. 2022) 3D printing is an additive manufacturing technology in which an object is constructed using computer-aided design software, sliced, and transferred to a printer where the product is constructed layer by layer using the principle of layered manufacturing (Wang et al. 2023). This way of producing medicines has the advantage of developing dosage forms with complex structures and geometries that are difficult to produce with conventional manufacturing methods. These products can be adjusted to the specific dose requirements, drug combinations or release profiles of different patiens based on their age, genetics or physiological conditions. This possibility is of special importance in the case of paediatric or geriatric patients (Parulski et al. 2021; Muhindo et al. 2023) . Direct Powder Extrusion (DPE) is an additive manufacturing technique that relies on the feeding of a powder mixture into the printer, heating, extrusion and printing by deposition onto a building platform, layer by layer to create three-dimensional objects (SánchezGuirales et al. 2021) . One of the main advantages of this technique, compared to fused deposition modelling (FDM), is that it is not necessary to produce thermoplastic filaments (usually obteined by Hot Melt Extrusion (HME)) with suitable properties (nor too brittle neither too flexible) before the final step of 3D printing. This fact avoids complications when high drug doses are required, since HME needs a large amount of excipient to obtain adequate filaments. Furthermore, the impact of high temperatures, which can lead to drug degradation, is decreased, since the materials are subjected to a unique thermal process, allowing the use of drugs with lower degradation temperatures (Pistone et al. 2022). Therefore, this single-step manufacturing process helps to reduce time and cost in the production of drug delivery systems, making possible its implementation in hospital settings (Annaji et al. 2020; Malebari et al. 2022) . 4 Thermoplastic polyurethanes (TPU) have been widely employed in the production of different types of dosage forms such as vaginal rings or implants as well as in drug loaded cardiovascular prothesis, stents or medical tubing. Their inert, non-ionic and waterinsoluble properties together with their high tensile strengh, highly elastomeric features and biocompatibility make these products very suitable for healthcare applications (Claeys et al. 2015). Recently, these polymers have been employed in the production of 3D printed drug loaded systems prepared by FDM (Verstraete et al. 2018; Domínguez-Robles et al. 2020; Arany et al. 2021; Domínguez-Robles et al. 2022). The study of the filaments for FDM has been carried out employing different tools such as percolation theory and fractal analysis (Linares et al. 2021; Linares et al. 2022). Percolation theory, derived from the statistic physics, studies disordered or caotic systems in which the components are distributed in a network in a random way. The main concept of this theory is the percolation threshold, which is defined as the minimum concentration of a component at which there is a maximum probability of appearance of an infinite or percolating cluster of this material. A cluster is defined as a group of neighbour particles of the same component that share one side of the cell representing them on the grid. When a component starts to spread over the hole sample, it forms a percolating cluster. At this concentration point a geometrical phase transition takes place and this componet starts to exert a much stronger influence on the properties of the system. Abrupt changes in the properties of the systems are expected near this concentration point (Fuertes et al. 2006; Caraballo 2009; Caraballo 2010). Euclidean geometry has been commonly used to describe mostly ordered systems and therefore does not fit well with more chaotic systems such as those found in nature (Pippa et al. 2013). It was the mathematician Benoit Mandelbrot who introduced the first mathematical model to describe geometrically the apparent irregularities of systems present in nature. Studying some natural objects at different magnifications, he realized that there is a symmetry, an invariant pattern independent of the scale used. Fractality is therefore defined by the presence of self-similarity, which is a property of an object or system to resemble itself at different scales (Young and Crawford 1991). This self-similarity gives the system different degrees of complexity and can be quantified thanks to the fractal dimension. Fractality analysis results in a value that determines the fractal dimension, 5 which relates the surface area or volume of an object and the scale at which it is being measured (Dillon et al. 2001). Among the possible methods for studying the fractal dimension, one of the most popular is the box-counting method which has been previously employed by (Linares et al. 2021) according to the methodology proposed by (Dillon et al. 2001). This method assumes that the system to be analysed is covered by a square mesh of different sizes (λ), so that by counting the number of boxes (N) that contain part of the system, the value of the fractal dimension (D) can be obtained based on equation (1): N(λ) = Cλ-D (1) Where C is a proportionality constant. The fractal dimension has been applied in pharmaceutical technology in several areas, such as the study of formulations with solid particles. Of particular relevance is the characterisation of the roughness of powders, and the impact this in turn has on the powder flow properties or bioavailability of pharmaceutical systems such as tablets (Thibert et al. 1988; Fernández-Hervás et al. 1994; Burnett et al. 2011; Abreu-Villela et al. 2019). More recently, it can be highlighted the application of the study of fractality in drug-loaded thermoplastic filaments which were used in FDM for the 3D printing of drug delivery systems. The roughness resulting from the analysis was related to the printability of the system (Linares et al. 2021; Mora-Castaño et al. 2022; Linares et al. 2022). The aim of this work is to compare the processability of different types of binary and ternary TPU powder mixtures employing two different extrusion-based 3DP technologies: DPE and single-screw extrusion. Powder flow studies of the powder blends have been carried out and relationed with the extrusion process. Critical properties of the resulting extrudates have been studied using different approaches such as fractal analysis and percolation theory in order to compare both 3D printing technologies. 2. Materials and Methods 2.1. Materials Anhydrous theophylline (AT), employed as model drug, was bought from Acofarma (batch 151209-P-1, Barcelona, Spain). Medical grade TecoflexTM EG-72D thermoplastic 6 polyurethane (TPU), used as a matrix forming polymer, was supplied by Lubrizol Advanced Materials (Barcelona, Spain). Magnesium stearate (MS) (mean diameter 20 μm), used as a lubricant, was purchased from Acofarma (batch 201081, Barcelona, Spain). 2.2. Methods 2.2.1. Preparation of the binary and ternary mixtures TPU powder was obtained from previously frozen TPU pellets pulverized in a mill (Retsch ZM 200, Haan, Germany) using liquid nitrogen and a 1.0 mm output sieve. A 227.9 ± 166.0 μm mean diameter was obtained. AT with a mean diameter of 121.5 ± 45.0 μm was employed. The binary mixtures of AT and TPU powder and the ternary mixtures obtained after adding MS were blended for 15 min in a Turbula mixer (Willy A. Bachofen, Basel, Switzerland). The optimum mixing time was chosen according to a previously published work (Galdón et al. 2019). The composition of the different batches manufactured can be observed in Table 1. 2.2.2. Powder flow studies of binary and ternary powder blends Different tests have been performed in order to characterize the powder flow of the mixtures prepared. Bulk density (qbulk), tapped density (qtapped), rest angle (α) and powder flow were measured in accordance with the methods described in the European Pharmacopoeia 11th Edition (section 2.9.34-36) (Council of Europe. European Directorate for the Quality of Medicines & Healthcare 2023) . Inter particle porosity (IP); Carr’s Index (CI) and Hausner Ratio (HR) are derived from the following equations: HR = qtapped / qbulk (2) IP = qtapped - qbulk / qtapped x qbulk (3) CI = (qtapped - qbulk / qtapped) x 100 (4) 2.2.3. Extrusion Process All the physical mixtures were subjected to an extrusion process using both, a single screw Noztek Pro extruder (Noztek, Sussex, UK) and a DPE 3D printer M3dimaker (FabRx, 7 London, UK) at the temperatures recorded in Table 1. The conditions employed with the Noztek Pro extruder for all batches were a screw speed of 33 rpm, a diameter of the nozzle of 1.75 mm and a preheat of 30 min in order to establish thermal equilibrium before extrusion. With the aim of checking that the required diameter value of 1.75 mm for FDM 3D printing was obtained, the diameter of the filaments produced was measured using a digital micrometer (Comecta, SA, Barcelona, Spain). In the case of the M3dimaker 3D printer, the parameters utilized were the maximum screw speed allowed, a nozzle diameter of 0.8 mm and a preheat of 15 min, as recommended by the fabricant. The diameter of the strands was also measured with a digital micrometer (Comecta, SA, Barcelona, Spain) in order to check the concordance with the nozzle diameter and the variability between different batches. The extrudates produced for both methods were stored in an appropriate packaging at 25 ºC. 2.2.4. Thermal Analysis of the extrudates Thermal properties of the pure materials and extrudates prepared by both techniques were evaluated using Differential Scanning Calorimetry (DSC) and Thermogravimetric Analysis (TGA) in order to study the stability and compatibility of the components utilized as well as their thermal decomposition. DSC analyses were carried out in a DSC Q20 V24.11 Build 124 (TA Instruments, New Castle, DE, USA) in the Functional Characterization Service of the Center for Research, Technology, and Innovation of the University of Seville (CITIUS). Crimped hermetical aluminum pans were used to place about 2-12 mg of each sample that were heated from 30 ◦C to 300 ◦C at a heating rate of 5 ◦C/min under a dry nitrogen flow (100 mL/min). TGA were performed in a thermal analyzer (SDT Q600 V20.9 Build 20, TA Instruments, New Castle, DE, USA) in the Functional Characterization Service of the University of Seville (CITIUS). About 4-11 mg of each sample were placed in an aluminum crucible and heated from room temperature to 600 ◦C employing a heating rate of 10 ◦C/min under a nitrogen gas purge of 100 mL/min. DSC and TGA data were analyzed using Universal Analysis 2000 V4.5A software (TA Instruments, UK). 8 2.2.5. Scanning electron microscopy (SEM) Scanning Electron Microscopy (SEM) was carried out in the Microscopy Service of the Center for Research, Technology, and Innovation of the University of Seville (CITIUS) to evaluate the surface of the extrudates obtained. A FESEM (Field Emission Scanning electron microscope) Schottky type (Thermofisher, Eindhoven, Holland) operating at 5 kV was used. A Leica ACE 600 high vacuum sputter coater was employed to coat the samples with a 10 nm-thin Pt layer before the analysis of the images. 2.2.6. Powder X-Ray diffraction (PXRD) Powder X-ray diffractometry analysis (PXRD) were carried out to the pure components as well as to the binary and ternary strands containing 20 and 60% w/w of AT prepared by DPE. The X-ray diffraction patterns were collected with a Bruker D8 Advance A25 diffractometer (Karlsruhe, Germany) equipped with a lineal Lynexe detector with an opening of 3.3º. X-rays were generated with a copper anode operating at 40 kV and a current of 30 mA. The data were acquired over the 2θ range of 3º to 70º at a scanning step of 0.015º and measurement time of 0.1 s per step. 2.2.7. Mechanical properties of the extrudates The stiffness of the filaments and strands was assessed using a Texture Analyser TA.XTPlus (Stable Micro Systems, Godalming, UK) at room temperature. Stiffness test following the previous methodology outlined by Xu et al., (Xu et al. 2020) was employed to measure the toughness of the performed extrudates. Briefly, five samples of each lot were cut into pieces of 6 cm in length and placed on the Texture Analyzer platform. Equipped with a set with knife blade, the Texture Analyzer was set to 50 g, and the blade was programmed to cut the extrudate piece until 1 mm in distance (57% strain) at a speed 2 mm/s. The maximum force and fracture distance were recorded by Texture Analyzer software, Texture Expert v.1.22 (Stable Micro Systems, Godalming, UK). Moreover, the Macro program in Texture Analyzer software was used to determine the area under curve (AUC) and maximum stress. Additionally, three anchors were inserted into the plot through the Macro program in the Texture Analyzer software. Anchor 1 marked the starting point of strain, anchor 2 represented the maximum strain, and anchor 3 indicated the end of the test when the stress 15 associated with the higher amount of AT present in the extrudates. This ultimately has implications for the 3D printing process. 4. Conclusions Both binary and ternary mixtures based in TPU have proved to be suitable to be processed by DPE and single screw extrusion, including those having a high drug concentration. The presence of MS masks the negative effect of AT in the blends where the drug is the only percolating component, improving the flow properties and reducing the extrusion temperature until 25ºC in the case of DPE. Regarding the roughness of the extrudates obtained, we can confirm that the presence of lubricant softens the surface of the systems with a higher content of AT, showing all the ternary batches obtained by both techniques similar fractal dimension values. Binary strands obtained by DPE showed better toughness values, in spite of the lower torque that applies this technology in comparison with the single screw extruder. DPE has demonstrated to be an adequate technology to process TPU formulations, which have been lately employed in the production of different dosage forms due to their favourable features. This technology showed important advantages such as the reduced impact of high temperatures as well as its simplification to a one-step process. Therefore, DPE is a valuable option to be implemented in healthcare settings for the production of customized on-demand drug delivery systems. Acknowledgements We thank Ministerio de Ciencia, Innovación y Universidades of Spain (Grant RTI2018 095041-B-C31) for financial support. This work has been supported by a PIF VI PPIT-US grant of the Universidad de Sevilla. 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Journal of Soil Science. 42(2):187–192. https://doi.org/10.1111/j.13652389.1991.tb00400.x 19 Table 1. Composition and extrusion temperature of the studied batches. Bin20 Bin30 Bin40 Bin50 Bin60 Ter20 Ter30 Ter40 Ter50 Ter60 AT (% w/w) 20 30 40 50 60 20 30 40 50 60 TPU (% w/w) 80 70 60 50 40 75 65 55 45 35 MS (% w/w) 0 0 0 0 0 5 5 5 5 5 Noztek extrusion temperature (° C) 130 130 130 130 130 150 145 135 135 135 DPE extrusion temperature (° C) 150 145 135 150 160 150 145 135 135 135 AT: Theophylline anhydrous TPU: Thermoplastic Polyurethane MS: Magnesium stearate Bin20-Bin60: binary extrudates containing from 20 to 60 % w/w of AT Ter20-Ter60: ternary extrudates containing from 20 to 60 % w/w of AT 20 Table 2. Powder flow results from binary and ternary mixtures. Batch qbulk (g/ml) qtapped (g/ml) IP CI (%) HR α (°) Bin20 0.300±0.002 0.360±0.003 0.558±0.020 16.72±0.55 1.201±0.008 45.2±0.5 Bin30 0.304±0.002 0.379±0.003 0.646±0.020 19.66±0.12 1.245±0.002 54.9±1.6 Bin40 0.307±0.002 0.398±0.003 0.745±0.000 22.83±0.92 1.296±0.015 53.8±1.1 Bin50 0.310±0.002 0.407±0.003 0.767±0.034 23.77±1.06 1.312±0.018 53.1±1.0 Bin60 0.317±0.002 0.455±0.004 0.956±0.039 30.33±0.19 1.435±0.004 55.3±1.2 Ter20 0.335±0.002 0.429±0.006 0.656±0.038 21.93±1.22 1.281±0.020 51.0±2.3 Ter30 0.345±0.004 0.445±0.004 0.652±0.051 22.47±1.52 1.290±0.025 53.8±1.1 Ter40 0.358±0.002 0.463±0.004 0.635±0.000 22.71±0.16 1.294±0.003 49.5±0.9 Ter50 0.390±0.003 0.497±0.005 0.554±0.020 21.58±0.69 1.275±0.011 49.6±0.7 Ter60 0.401±0.003 0.528±0.000 0.597±0.020 23.96±0.60 1.315±0.010 46.0±0.8 21 Table 3. Fractal dimension values defined by the equation of the graph from different drug contents. 22 Figures Figure 1. Figure 2. Figure 3. 23 Figure 4. Figure 5. 24 Figure 6. Figure 7.