Multicomponent granular mixing in a Bohle bin Blender-Experiments and simulation

Detailed accounts of segregation mechanisms and the evolution of pharmaceutical blend segregation analysis: A review

Segregation refers to the separation of components in a powder mixture, resulting in potential issues related to concentration inhomogeneity. Any well-mixed blend that undergoes secondary processing is inherently susceptible to segregation which, if unmitigated, will lead to active compound concentration variance and poorer product quality. The consequences range from adverse financial impact to manufacturers with product failures to the detrimental health effects to product users. Hence, the topic of segregation is of paramount importance to the industry, requiring it to be dissected and scrutinized intensively by scientists worldwide. This review provides a well-crafted theoretical framework designed to understand the common segregation mechanisms that manufacturing facilities face, followed by the efforts to gauge the degree of segregation. To minimize segregation in blends, various approaches - mathematical modeling, empirical experiments, and empirical methods with modeling consideration - have been utilized in segregation research and are covered in this review. The past segregation studies from many fields are discussed, with particular emphasis on pharmaceuticals. The review also discusses the evolution and advances in mixing technology and storage systems implemented by the pharmaceutical industry to prevent segregation. In the conclusion, the authors articulated their perspectives on potential mitigation measures, including suggestions for improvements and future studies.

Development of a Near-Infrared Spectroscopy (NIRS)-Based Characterization Approach for Inherent Powder Blend Heterogeneity in Direct Compression Formulations

With the advent of continuous direct compression (CDC) process, it becomes increasingly desirable to characterize inherent powder blend heterogeneity at a small batch scale for a robust and CDC-amenable formulation. To accomplish this goal, a near infrared spectroscopy (NIRS)-based characterization approach was developed and implemented on multiple direct compression (DC) blends in this study, with the intended purpose of complementing existing formulation development tools and enabling to build an early CMC data package for late-phased process analytical technology (PAT) method development. Three fumaric acid DC blends, designed to harbor varied degrees of inherent blend heterogeneity, were employed. Near infrared spectral data were collected on a kg-scale batch blender via both time- and angle-based triggering modes. The time-triggered data were used to investigate the blending heterogeneity with respect to rotation angles, while the angle-triggered data were used to provide blending variability characterization and compare against off-line HPLC-based results. The time-triggered data revealed that the greatest blend variability was observed between revolutions, while the blending variability within a single revolution stayed relatively low with respect to rotation angles. This confirmed earlier literature findings that the bottom layer of powder blends tends to move with the blender within each revolution, and the most intense powder mixing takes place across revolutions. This also indicates the use of blending speed and the number of co-adds are not able to increase sampling volume to improve signal-to-noise ratio under a tumble-bin blender as what were typically done in a feedframe application. The angle-triggered data showed that there is a consistent trend between NIRS and HPLC-based methods on characterizing blend heterogeneity across the blends at a given sample size. This study contributes to establishing NIRS as a potential characterization approach for inherent powder blend heterogeneity for early R&D. It also highlights the promise of continuous characterization of inherent powder blend heterogeneity from gram scale to mini-batch CDC scale.

Computational Modeling of Fluidized Beds with a Focus on Pharmaceutical Applications: A Review

The fluidized bed is an essential and standard equipment in the field of process development. It has a wide application in various areas and has been extensively studied. This review paper aims to discuss computational modeling of a fluidized bed with a focus on pharmaceutical applications. Eulerian, Lagrangian, and combined Eulerian-Lagrangian models have been studied for fluid bed applications with the rise of modeling capabilities. Such models assist in optimizing the process parameters and expedite the process development cycle. This paper discusses the background of modeling and then summarizes research papers relevant to pharmaceutical unit operations.

Streamlining of the Powder Mixing Process based on a Segregation Test

In direct compression of tablets, it is crucial to maintain content uniformity within acceptable margins, especially in formulations with low drug loading. To assure it, complex and multistep mixing processes are utilized in the industry. In this study, we suggest the use of a simple segregation test to evaluate mixing process performance and mixture segregation to produce tablets having satisfying content uniformity while keeping the process as simple and low cost as possible. Eventually, the formulation propensity to segregation can be evaluated using process analytical technology (PAT) to adjust the mixing process parameters to changing source drug properties. In this study, that approach was examined on a model drug with a broad batch-to-batch variability in particle size and shape. Excipients were chosen so that the resulting blend composition mimicked some marketed formulations. For each drug batch, two formulation blends were prepared through different preparation processes (one simple and one complex) and subsequently subjected to segregation tests. From those, segregation coefficients were obtained to compare segregation tendencies and homogeneity robustness between the drug batches and the blend preparation methods. The inter-particulate interactions were substantially influenced by the drug particle morphology and size and resulted in different segregation behavior. Based on these findings, a simple segregation test proved to be a useful tool for determining the suitability of different batches of the model drug to be used in a certain formulation. Moreover, for a particular batch A, the test revealed a potential for mixing process simplification and therefore process intensification and cost reduction.

Impact of powder-binder interactions on 3D printability of pharmaceutical tablets using drop test methodology

In this study, a pre-screening test has been developed for the binder-jet 3D printing process (BJ3DP) which has been validated using statistical analysis. The pre-screening test or drop test has been adapted from the wet granulation field and modified later on to be used for tablet manufacturing in BJ3DP. Initially, a total of eight powders and ten water-based binder solutions have been introduced in the preliminary test to understand the powder-binder interactions. Afterward, based on the preliminary test results, three blends were developed which had undergone the same drop test. All these powder and binder combinations were then used for 3D printing. The key parameters such as mechanical strength and shape factors of the drop test agglomerates and 3D printed tablets were then compared using multiple linear regressions. Few dimensionless parameters were introduced in this study such as binding capacity and binding index to capture the printability properties of the powders used in this study. Significant relations (p<0.05) were found between the drop test and the BJ3DP process. Application of drop test was carried out to establish a prescreening test, ii) to develop new blend formulations as well as iii) to develop a fundamental understanding of powder-binder interaction during BJ3DP process.

DEM based investigation of powder packing in 3D printing of pharmaceutical tablets

3D printing is emerging as one of the most promising methods to manufacture Pharmaceutical dosage forms as it offers multiple advantages such as personalization of dosage forms, polypill, fabrication of complex dosage forms etc. 3D printing came into existence in 1980s but its use was extended recently to pharmaceutical industry along with the approval of first 3D printed tablet Spritam by FDA in 2015. Spritam was manufactured by Aprecia pharmaceuticals using binder jetting technology. Binder jet 3D printing involves a hopper for powder discharge and printheads for ink jetting. The properties of tablets are highly dependent upon the discharge quality of powder mixture from the hopper and jetting of the ink/binder solution from the printhead nozzle. In this study, numerical models were developed using Discrete element method (DEM) to gain better understanding of the binder jet 3D printing process. The DEM modeling of hopper discharge was performed using in-house DEM code to study the effect of raw material attributes such as powder bed packing density (i.e. particle size, particle density etc) on the printing process, especially during powder bed preparation. This DEM model was further validated experimentally, and the model demonstrated good agreement with experimental results.