(274d) Leveraging Raw Material and Blend Properties with the Die Filling Step of the Tableting Process

Authors: 
Vanhoorne, V., Ghent University
Van Snick, B., Ghent University
Dhondt, J., Ghent University
Segers, C., Ghent University
Van Vooren, K., Ghent University
Eerdekens, T., Ghent University
Di Pretoro, G., Janssen pharmaceutica
De Beer, T., Ghent University
Vervaet, C., Ghent University
Leveraging raw material and blend properties with the die filling step of the tableting process

 

V. Vanhoornea*, B. Van Snicka*, W. Grymonpréa, J. Dhondtc, C. Segersa, K. Van Voorena, T. Eerdekensa, G. Di Pretorob, T. De Beerc, C. Vervaeta

aLaboratory of Pharmaceutical Technology, Ghent University,
Ottergemsesteenweg 460, B-9000 Ghent, Belgium

bPharmaceutical Research and Development, Division of Janssen Pharmaceutica, Johnson & Johnson, Turnhoutseweg 30, B-2340 Beerse, Belgium

cLaboratory of Pharmaceutical Process Analytical Technology, Ghent University, Ottergemsesteenweg 460, B-9000 Ghent, Belgium

*Both authors contributed equally

Tablets are the most widely used dosage forms for oral drug delivery, mainly due to their ease of manufacturing, accurate dosing and high patient compliance. Today, tablets still account for more than 80 % of all pharmaceutical preparations. Despite the high quantities of tablets produced daily, a lot of the established processes and formulations are the results of trial-and-error experiments. Knowledge and understanding of the influence of process parameters and formulation properties on the final product quality is of great importance for the industry, offering economic efficiency and high product quality.

Therefore, the aim of this study is to investigate the influence of a broad range of formulation properties and process parameters related to the feed frame on the tablet properties and tablet weight variation. Based on characterization of a wide range of fillers for direct compression (13 materials) and active pharmaceutical ingredients (API) (14), thirty divergent blends were composed and evaluated on the tablet press. Characterization of the individual materials included size and shape analysis (laser diffraction, static image analysis, scanning electron microscopy), specific surface analysis, tapped, bulk and true density, flowability (drained angle of repose, dynamic angle of repose, flowability index, basic flowability energy, specific energy, aeration index, permeability), compressibility, charge density, moisture content (loss-on-drying) and dynamic vapor sorption. Based on PCA analysis of the fillers and API’s, 5 fillers (Pearlitol 100SD, Emcompress, Avicel PH101, Tablettose 80, Avicel PH200) and 6 API’s (Caffeine, Metoprolol tartrate, Intelence, micronized, powdered and dense powder grades of Paracetamol) were selected to be combined into 30 blends (API/filler/magnesium stearate 9.93/89.33/0.75) in order to cover a broad range of formulations. Additionally, these blends were characterized. An experimental design with 6 runs (including 2 centerpoints) varying paddle speed (paddle 1: 15 – 100 rpm, paddle 2: 18 – 120 rpm) and turret speed (10 – 100 rpm) was performed on an instrumented rotary tablet press (Modul P, GEA Pharma systems). Experiments were performed at a fixed main compression force (15 kN), with a fixed pre-compression displacement (0.5 mm) and overfill (2 mm). Steady state of the tablet press was determined by evaluation of the tablet mass flow signal on a catch scale. After reaching steady state, the press was run for 3, 6 or 30 min at turret speeds of 10, 55 and 100 rpm, respectively. Samples were taken during 8, 2 and 2 s at intervals of 100, 20 and 10 s at turret speeds of 10, 55 and 100 rpm, respectively. Tablets of the individual samples were weighed and the pooled mean and pooled relative standard deviation was calculated. Additionally, the residence mass in the feed frame (RMF) was determined after each run and the bottom punch position to obtain a main compression force of 15 kN (BPMC) and ejection force were recorded. Multivariate data analysis was applied to investigate the relation between the process parameters, blend characteristics, product and process responses.

Blends with metoprolol tartrate as API and Pearlitol 100 SD or Emcompress as filler tended to stick on the punches. This behavior could be linked to the high wall friction value of metoprolol. Cellulose-based fillers did not exhibited this behavior because of their self-lubricating behavior. Additionally, high ejection forces were observed using Pearlitol SD100 as filler, resulting in picking and capping in combination with paracetamol.

Overall, the density of the blend impacted the mean tablet weight and residence mass in the feed frame. In contrast, the tablet weight variability could be related to the flowability of the blend expressed by the flow function coefficient obtained with the ring shear test. For the formulations with a well flowing, high density filler (e.g. Emcompress) no effect or a minor effect of the paddle speed and turret speed was detected on the tablet weight, tablet weight variability, RMF and BPMC. In contrast when a poorly flowing, low density filler (e.g. Avicel PH101) was used in the formulation, the tablet weight, RMF and BPMC were negatively and positively affected using a higher turret speed and paddle speed, respectively. These effects were most pronounced when the poorly flowing, low density filler was combined with an API with similar properties (e.g. Metoprolol tartrate, micronized Paracetamol). This signifies that die filling is incomplete and that the mass in the feed frame is low when poorly flowing, low density formulations are tableted. However, interestingly, the variability of the tablet weight of these formulations was affected by the turret speed or paddle speed. Higher paddle and turret speeds resulted in a reduction and increase of the tablet weight variability, respectively. The tablet weight variability of a very cohesive formulation, e.g. micronized paracetamol combined with Avicel PH101 (ffc=2.55), varied from 0.7 – 7.9% depending on the turret and paddle speed. Operating the tablet press at the highest paddle speed and lowest turret speed resulted in the lowest tablet weight variability, whereas operating the tablet press at the lowest paddle speed and highest turret speed resulted in the highest tablet weight variability. Intermediate settings of turret and paddle speed (center point conditions) resulted in a tablet weight variability of 3.6%. Therefore, it could be concluded that even poorly flowing formulations with a low density (e.g. consisting of a filler intended for wet granulation and a micronized API) could be tableted at high speed on a rotary tablet press, yielding acceptable tablet weight variability when the paddle speed is optimized.

The developed characterization database will be further expanded with more materials and additional material characteristics (e.g. compression properties as elastic recovery, plasticity constant, fragmentation) and a PLS model will be developed to link the material characteristics to process settings and responses of the tableting process. This way the model will be a valuable tool to compose formulations with new APIs during drug product development.