A modified mechanistic approach for predicting ribbon solid fraction at different roller compaction speeds
Abstract
This research investigates the modeling of the pharmaceutical roller compaction process, focusing on the application of the Johanson model and the impact of varying roll speeds from 1 to 15 RPM on predictive accuracy of ribbon solid fraction. The classical Johanson’s model was integrated with a dwell time parameter leading to an expression of a floating correction factor as a function of roll speed. Through systematic analysis of the effect of different roll speeds on the solid fraction of ribbons composed of microcrystalline cellulose, lactose, and their blends, corrective adjustment to the Johanson model was found to depend on both roll speed and formulation composition. Interestingly, the correction factor demonstrated excellent correlation with the blend’s mechanical properties, namely yield stress (Py) and elastic modulus (E0), representative of the deformability of the powder. Validated by a multicomponent drug formulation with ±0.6–1.6% differences, the findings underscore the utility of this modified mechanistic approach for precise prediction of ribbon solid fraction when Py or E0 is known for a given blend. Hence, this work advances the field by offering early insights for more accurate and controllable roller compaction operations during late-stage pharmaceutical manufacturing.
Introduction
Roller compaction (RC) is a critical process used in the pharmaceutical industry, particularly in the manufacturing of solid dosage forms such as tablets and capsules (Chang et al., 2008). This dry granulation process is distinguished by its avoidance of moisture and heat, providing the stability requirements of moisture-sensitive active pharmaceutical ingredients (API) (Kleinebudde, 2004, Rogers et al., 2013). It enhances powder blend flowability, essential for consistent dosing and efficient tableting. Notably, this process minimizes dust generation and increase bulk density of the blends (Parikh, 2016). RC also offers a shorter processing time, lower capital costs and easier scale-up approach compared to various wet granulation (WG) processes. Given these advantages, roller compaction (RC) has emerged as the predominant process in the industry, with numerous researchers contributing to the development of RC models. These models are instrumental in facilitating scale-up processes and conserving materials during the early stages of drug development. First, the one-dimension Johanson’s rolling model perhaps is the most well-known and cited RC model (Johanson, 1964). It provides a mathematical approach to predict solid fraction of ribbon using roll geometries process parameter and material properties. Later, the “slab” method has also been proposed, which like Johanson’s model based on one-dimensional powder movement (Dec et al., 2003, Patel et al., 2010). What’s more, computational discrete elements method (DEM) and finite element method (FEM) are becoming more common since these can provide extensive information on powder state and involve more dimensions to give greater insight into the pressure and density distribution during roll compaction processes (Awasthi et al., 2023, Mazor et al., 2018), but at the expense of increased model complexity and computation effort.
However, several models, built either fully or partially on the Johanson’s theory, have been reported to describe the overestimated prediction of ribbon solid fraction of the original Johanson model. From Bi et al. (Bi et al., 2014) study, it was found that the inadequate assumption of continuity transport theory in deriving the mass balance equations caused the model overpredicting the maximum roll surface pressure. What’s more, Liu et al (Liu and Wassgren, 2016) also stated that the Johanson’s model led to overpredictions in ribbon solid fraction due to its one-dimensional assumption. They generated a semi-empirical model based on two-dimensional FEM and the modified Johanson’s model developed by Bi et al. They introduced a mass correction factor to compensate for the overprediction in the original model, which unlike Bi et al. (Bi et al., 2014) that corrects the mass flow at the minimum gap but adjust the mass flow varied with roll position starting from nip angle to minimum gap. But, like other researchers, the modified Johanson’s model still relied on complex material behavior to determine the nipping and slipping region which need good amount of material to perform characterization tests. Subsequently, So et al. (So et al., 2021) stated a simplified friction angle-free Johanson’s model where he demonstrated that the nip angles in his study from Johanson’s model were all below 17°. Therefore, an upper bound value of nip angles can be set to calculate the maximum pressure from the Johanson’s model without doing material’s friction tests.
By modifying or simplifying the Johanson’s roller compaction model, these derived models did not take into account the effects of roll speed on the final ribbon solid fraction. However, in Amini et al’s (Amini and Akseli, 2020) study, they observed the impact of roll speed on ribbon solid fraction, even though the impact was negligible under low roll speed (<6 RPM). Moreover, Luck et al (Lück et al., 2022) observed clear effect of roll speed on the solid fraction of the ribbon for plastic materials but less effect on the brittle materials. He proposed a concept to define the dwell time of roller compaction based on the roll speed changes. The dwell time of roller compaction is similar to the tablet compaction process, where Paul and Sun (Paul and Sun, 2017) showed tablet density and strength were increased with longer dwell time during compaction. Furthermore, the sensitivity of the tablet dwell time is dependent on materials properties, where dwell time will have larger impact on plastic materials but smaller on brittle powder (Ruegger and Çelick, 2000, Tye et al., 2005). Understanding roll speed effect on ribbon solid fraction is a crucial aspect based on the fact that early-stage development contains smaller batch size and therefore roll speed is set low to efficiently reach the steady state process with minimal amount of API (Akande et al., 1997, Katz and Buckner, 2013). However, roll speed is increased at late stages during formulation and process handover to production. Therefore, significant effect of roll speed on ribbon solid fraction variation could affect downstream quality attributes such as particle size of milled ribbons, flowability and tabletability of the resulting granules (Haeffler et al., 2019, Wilms et al., 2022).
In this study, a modified Johanson’s roller compaction model has been developed based on materials properties to predict the ribbon solid fraction under different roll speeds. Unlike previously proposed approaches in the literature that predicted maximum pressure of roller compaction with ribbon density relationship by applying one global correction factor, this study shows that the correction factor is related with roll speed and material properties. Specifically, the objectives of this study are to: 1) provide a relationship between dwell time and correction factor of Johanson’s model, 2) establish the materials properties correlation with the correction factor, 3) propose and verify a modified Johanson’s model based on different roll speed.
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Materials
Microcrystalline cellulose (MCC − Avicel PH102; FMC Biopolymer, Philadelphia, PA) and lactose (LAC − Flowlac 100; Meggle Pharma, Megglestrasse, Germany) were used as model plastic and brittle excipients, respectively. Acetaminophen (APAP; Sigma-Aldrich, Austria) was used as model API, MCC (Vivapur 102; Weißenborn GmbH & Co KG, Germany) and mannitol (Partek 200; Roquette Frères SA, Lestrem) as fillers and Kolidon (VA 64; BASF SE, Ludwigshafen, Germany) as binder respectively.
Jingzhe Li, Yin-Chao Tseng, Shubhajit Paul, A modified mechanistic approach for predicting ribbon solid fraction at different roller compaction speeds, International Journal of Pharmaceutics, 2024, 124366, ISSN 0378-5173, https://doi.org/10.1016/j.ijpharm.2024.124366.
Read also our introduction article on “Microcrystalline Cellulose“ here:
