In-Depth Understanding of Granule Compression Behavior under Variable Raw Material and Processing Conditions

Development of a PAT platform for the prediction of granule tableting properties

In this work, the feasibility of implementing a process analytical technology (PAT) platform consisting of Near Infrared Spectroscopy (NIR) and particle size distribution (PSD) analysis was evaluated for the prediction of granule downstream processability. A Design of Experiments-based calibration set was prepared using a fluid bed melt granulation process by varying the binder content, granulation time, and granulation temperature. The granule samples were characterized using PAT tools and a compaction simulator in the 100-500 kg load range. Comparing the systematic variability in NIR and PSD data, their complementarity was demonstrated by identifying joint and unique sources of variation. These particularities of the data explained some differences in the performance of individual models. Regarding the fusion of data sources, the input data structure for partial least squares (PLS) based models did not significantly impact the predictive performance, as the root mean squared error of prediction (RMSEP) values were similar. Comparing PLS and artificial neural network (ANN) models, it was observed that the ANNs systematically provided superior model performance. For example, the best tensile strength, ejection stress, and detachment stress prediction with ANN resulted in an RMSEP of 0.119, 0.256, and 0.293 as opposed to the 0.180, 0.395, and 0.430 RMSEPs of the PLS models, respectively. Finally, the robustness of the developed models was assessed.

Simulation of roller compaction by combination of a compaction simulator and oscillating mill - A material sparing approach

This study investigates the feasibility of a compaction simulator and oscillating mill to mimic a roller compactor as a material sparing approach for process development. Microcrystalline cellulose and dicalcium phosphate dihydrate were selected to represent soft and hard materials, respectively. The relative density of ribbons and riblets was determined using a pycnometer and granules size distribution was determined by laser diffraction. Tablet tensile strength and relative density were determined using a hardness tester and pycnometer, respectively. This study showed that the relative density of riblets and ribbons were similar between 1 and 12 kN/cm, which indicates that the compaction simulator adequately mimics the compaction of the roller compactor using a Kp of 1. The size distribution of granules produced by the oscillating mill and roller compactor were similar, which indicates that the oscillating mill adequately mimics the roller compactor when using a similar gap and sieve design. Finally, the tablet tensile strength and relative density were similar independent of the applied granulation method and deformation behaviour of the material. In conclusion, the use of a compaction simulator and an oscillating mill in combination adequality mimics the roller compactor, which ultimately can save large amounts of material and time during process development.

Attribute transmission and effects of diluents and granulation liquids on granule properties and tablet quality for high shear wet granulation and tableting process

This study aims to examine (i) the effect of diluent types (lactose monohydrate, corn starch, and microcrystalline cellulose) and granulation liquids (20% polyvinylpyrrolidone-k30, 65% alcohol, and dispersion containing 40% model drug- Pithecellobium clypearia Benth extracted powder) on granule properties and tablet quality for high shear wet granulation and tableting (HSWG-T) and, more importantly, (ii) the attribute transmission in the process. In general, the impact of diluents on granule properties and tablet quality was more dominant than that of granulation liquids. Attribute transmission patterns were revealed as follows. The granules' ISO. Roundness and density correlated with raw material (i.e., model drug, diluent, and/or granulation liquid) properties such as density and viscosity. The granules' compressibility parameter a correlated with the granules' Span, and parameter y₀ correlated with the granules' flowability and friability. Compactibility parameters k_a and k_b correlated mainly with granule flowability and density, and parameter b correlated significantly and positively with tablet tensile strength. The compressibility correlated negatively with tablet solid fraction (SF) and friability, while the compactibility correlated positively with tablet disintegration time. Moreover, the rearrangement and elasticity of granules correlated positively with SF and friability, respectively. Overall, this study provides some guides for achieving high-quality tablets via HSWG-T.

Interpretable artificial neural networks for retrospective QbD of pharmaceutical tablet manufacturing based on a pilot-scale developmental dataset

As the pharmaceutical industry increasingly adopts the Pharma 4.0. concept, there is a growing need to effectively predict the product quality based on manufacturing or in-process data. Although artificial neural networks (ANNs) have emerged as powerful tools in data-rich environments, their implementation in pharmaceutical manufacturing is hindered by their black-box nature. In this work, ANNs were developed and interpreted to demonstrate their applicability to increase process understanding by retrospective analysis of developmental or manufacturing data. The in vitro dissolution and hardness of extended-release, directly compressed tablets were predicted from manufacturing and spectroscopic data of pilot-scale development. The ANNs using material attributes and operational parameters provided better results than using NIR or Raman spectra as predictors. ANNs were interpreted by sensitivity analysis, helping to identify the root cause of the batch-to-batch variability, e.g., the variability in particle size, grade, or substitution of the hydroxypropyl methylcellulose excipient. An ANN-based control strategy was also successfully utilized to mitigate the batch-to-batch variability by flexibly operating the tableting process. The presented methodology can be adapted to arbitrary data-rich manufacturing steps from active substance synthesis to formulation to predict the quality from manufacturing or development data and gain process understanding and consistent product quality.

Using a Material Library to Understand the Change of Tabletability by High Shear Wet Granulation

Understanding the tabletability change of materials after granulation is critical for the formulation and process design in tablet development. In this paper, a material library consisting of 30 pharmaceutical materials was used to summarize the pattern of change of tabletability during high shear wet granulation and tableting (HSWGT). Each powdered material and the corresponding granules were characterized by 19 physical properties and nine compression behavior classification system (CBCS) parameters. Principal component analysis (PCA) was used to compare the physical properties and compression behaviors of ungranulated powders and granules. A new index, namely the relative change of tabletability (CoT_r), was proposed to quantify the tabletability change, and its advantages over the reworking potential were demonstrated. On the basis of CoT_r values, the tabletability change classification system (TCCS) was established. It was found that approximately 40% of materials in the material library presented a loss of tabletability (i.e., Type I), 50% of materials had nearly unchanged tabletability (i.e., Type II), and 10% of materials suffered from increased tabletability (i.e., Type III). With the help of tensile strength (TS) vs. compression pressure curves implemented on both powders and granules, a data fusion method and the PLS2 algorithm were further applied to identify the differences in material properties requirements for direct compression (DC) and HSWGT. Results indicated that increasing the plasticity or porosity of the starting materials was beneficial to acquiring high TS of tablets made by HSWGT. In conclusion, the presented TCCS provided a means for the initial risk assessment of materials in tablet formulation design and the data modeling method helped to predict the impact of formulation ingredients on the strength of compacts.

Impact of Amylose-Amylopectin Ratio of Starches on the Mechanical Strength and Stability of Acetylsalicylic Acid Tablets

The two main components of starch - amylose and amylopectin, are responsible for its interaction with moisture. This study investigated how moisture sorption properties of the starches with different amylose-amylopectin ratio impacted tablet properties including drug stability. The starch samples were equilibrated to 33, 53, and 75% relative humidity (RH) and then assessed for tabletability, compactibility, and yield pressure. Effect of humidity on viscoelastic recovery was also evaluated. Tabletability and compactibility of high-amylose starch were better than that of high-amylopectin starch at 33 and 53% RH. However, at 75% RH, the reverse was observed. In terms of yield pressure, high-amylose starch had lower yield pressure than high-amylopectin starch. High-amylose starch tablets also exhibited lower extent of viscoelastic recovery than high-amylopectin starch tablets. The variations in the tableting properties were found to be related to relative locality of the sorbed moisture. Degradation of acetylsalicylic acid in high-amylose starch tablets at 75% RH, 40°C was less than the tablets with high-amylopectin starch. This observation could be attributed to the greater amount of water molecules binding sites in high-amylose starch. Furthermore, most of the sorbed moisture of high-amylose starch was internally absorbed moisture, therefore limiting the availability of diffusible sorbed moisture for degradation reaction. Findings from this study could provide better insights on the influence of amylose-amylopectin ratio on tableting properties and stability of moisture-sensitive drugs. This is of particular importance as starch is a common excipient in solid dosage forms.

Understanding the implication of Kawakita model parameters using in-die force-displacement curve analysis for compacted and non-compacted API powders

The aim of this study was to investigate powder mechanics upon compression using data obtained from force-displacement (F-D) curves. The Kawakita model of powder compression analysis was adopted in order to compare the pressure-volume reduction relationship of the drug powders in relation to the F-D curves. Experiments were carried out on six model drugs (metronidazole, metformin, secnidazole, ciprofloxacin, norfloxacin, and mebeverine). The drugs were compressed at different pressures in the non-processed or processed (using a roller compactor) forms. Results indicate the similarity between the F-D curves and a rearranged form of the Kawakita model. The foregoing enables the calculation of two important powder parameters, “a” (maximum powder volume reduction) and “Pk” (pressure required to achieve half of the maximum volume reduction) from the F-D curves without the need, as in the case of the conventional Kawakita model, to compress powders into tablets at different compression forces.

Graphical abstract