Importance of evaluating the consolidation of granules manufactured by high shear mixer

Predicting tablet properties using In-Line measurements and evolutionary equation Discovery: A high shear wet granulation study

High shear wet granulation (HSWG) is widely used in tablet manufacturing mainly because of its advantages in improving flowability, powder handling, process run time, size distribution, and preventing segregation. In line process analytical technology measurements are essential in capturing detailed particle dynamics and presenting real-time data to uncover the complexity of the HSWG process and ultimately for process control. This study presents an opportunity to predict the properties of the granules and tablets through torque measurement of the granulation bowl and the force exerted on a novel force probe within the powder bed. Inline force measurements are found to be more sensitive than torque measurements to the granulation process. The characteristic force profiles present the overall fingerprint of the high shear wet granulation, in which the evolution of the granule formation can improve our understanding of the granulation process. This provides rich information relating to the properties of the granules, identification of the even distribution of the binder liquid, and potential granulation end point. Data were obtained from an experimental high shear mixer across a range of key process parameters using a face-centred surface response design of experiment (DoE). A closed-form analytical model was developed from the DOE matrix using the discovery of evolutionary equations. The model is able to provide a strong predictive indication of the expected tablet tensile strength based only on the data in-line. The use of a closed form mathematical equation carries notable advantages over other AI methodologies such as artificial neural networks, notably improved interpretability/interrogability, and minimal inference costs, thus allowing the model to be used for real-time decision making and process control. The capability of accurately predicting, in real time, the required compaction force required to achieve the desired tablet tensile strength from upstream data carries the potential to ensure compression machine settings rapidly reach and are maintained at optimal values, thus maximising efficiency and minimising waste.

Effect of process parameters in high shear granulation on characteristics of a novel co-processed mesoporous silica material

In this study, insights into the development and optimization of a co-processed excipient based on mesoporous silica are presented. The main advantage of such a material is that it is appropriate for direct tablet compression and has a sufficiently large specific surface area to be suitable for potential subsequent drug loading and formulation of (amorphous) solid dispersions. Our aim was to use a Design of Experiments approach to investigate which process parameters in high shear granulation affect the characteristics of such a co-processed material. The parameters included were the amount of binder (isomalt), the amount of water (granulation liquid), the water addition rate and the speed of the impeller. The responses evaluated and modelled were particle size and its distribution, specific surface area, bulk density, flowability, compressibility and compactibility. The models obtained showed good quality in terms of goodness of fit and predictive power. Active effects were identified for all responses, giving a thorough insight into factors affecting the material characteristics. Optimization experiments resulted in products with the desired characteristics (high specific surface area, large particle size, good flow and compression properties) and confirmed the validity of the generated models.

Application of unsupervised and supervised learning to a material attribute database of tablets produced at two different granulation scales

The purpose of this study is to demonstrate the usefulness of machine learning (ML) for analyzing a material attribute database from tablets produced at different granulation scales. High shear wet granulators (scale 30 g and 1000 g) were used and data were collected according to the design of experiments at different scales. In total, 38 different tablets were prepared, and the tensile strength (TS) and dissolution rate after 10 min (DS10) were measured. In addition, 15 material attributes (MAs) related to particle size distribution, bulk density, elasticity, plasticity, surface properties, and moisture content of granules were evaluated. By using unsupervised learning including principal component analysis and hierarchical cluster analysis, the regions of tablets produced at each scale were visualized. Subsequently, supervised learning with feature selection including partial least squares regression with variable importance in projection and elastic net were applied. The constructed models could predict the TS and DS10 from the MAs and the compression force with high accuracy (R²= 0.777 and 0.748, respectively), independent of scale. In addition, important factors were successfully identified. ML can be used for better understanding of similarity/dissimilarity between scales, for constructing predictive models of critical quality attributes, and for determining critical factors.

Use of machine learning in prediction of granule particle size distribution and tablet tensile strength in commercial pharmaceutical manufacturing

In the manufacturing of pharmaceutical Oral Solid Dosage (OSD) forms, Particle Size Distribution (PSD) and Tensile Strength (TS) are common in-process tests that are controlled in order to achieve the quality targets of the end-product. The Quality by Design (QbD) concept elaborates process understanding and sufficient controls. However, for older pharmaceutical products upscaled to commercial phase with Quality by Testing (QbT) approach, the knowhow of the product-specific critical parameters is often limited. In this study, two predictive machine learning (ML) models were used for a commercial tablet product, for which historical data of raw materials, production, in-process controls and condition monitoring were available. With the aforementioned data, the aim was to predict the PSD and the TS that indicate the product quality. The feature importance was used to evaluate the parameter importance for the PSD and the TS. Partial dependence, in turn, was used to estimate the parameter impact on the predicted TS. The study illustrates the capability of the ML models to bring additional value for commercial products through the enhanced product-related knowhow.

Process Analytical Technology Tools for Monitoring Pharmaceutical Unit Operations: A Control Strategy for Continuous Process Verification

Various frameworks and methods, such as quality by design (QbD), real time release test (RTRT), and continuous process verification (CPV), have been introduced to improve drug product quality in the pharmaceutical industry. The methods recognize that an appropriate combination of process controls and predefined material attributes and intermediate quality attributes (IQAs) during processing may provide greater assurance of product quality than end-product testing. The efficient analysis method to monitor the relationship between process and quality should be used. Process analytical technology (PAT) was introduced to analyze IQAs during the process of establishing regulatory specifications and facilitating continuous manufacturing improvement. Although PAT was introduced in the pharmaceutical industry in the early 21st century, new PAT tools have been introduced during the last 20 years. In this review, we present the recent pharmaceutical PAT tools and their application in pharmaceutical unit operations. Based on unit operations, the significant IQAs monitored by PAT are presented to establish a control strategy for CPV and real time release testing (RTRT). In addition, the equipment type used in unit operation, PAT tools, multivariate statistical tools, and mathematical preprocessing are introduced, along with relevant literature. This review suggests that various PAT tools are rapidly advancing, and various IQAs are efficiently and precisely monitored in the pharmaceutical industry. Therefore, PAT could be a fundamental tool for the present QbD and CPV to improve drug product quality.

Comprehensive Study of Intermediate and Critical Quality Attributes for Process Control of High-Shear Wet Granulation Using Multivariate Analysis and The Quality by Design Approach

A robust manufacturing process and the relationship between intermediate quality attributes (IQAs), critical quality attributes (CQAs), and critical process parameters (CPPs) for high-shear wet granulation was determined in this study. Based on quality by the design (QbD) approach, IQAs, CQAs, and CPPs of a telmisartan tablet prepared by high-shear wet granulation were determined and then analyzed with multivariate analysis (MVA) to evaluate mutual interactions between IQAs, CQAs, and CPPs. The effects of the CPPs on the IQAs and CQAs were quantitatively predicted with empirical models of best fit. The models were used to define operating space, and an evaluation of the risk of uncertainty in model prediction was performed using Monte Carlo simulation. MVA showed that granule size and granule hardness were significantly related to % dissolution. In addition, granule FE (Flow Energy) and Carr's index had effects on tablet tensile strength. Using the manufacture of a clinical batch and robustness testing, a scale-up from lab to pilot scale was performed using geometric similarity, agitator torque profile, and agitator tip speed. The absolute biases and relative bias percentages of the IQAs and CQAs generated by the lab and pilot scale process exhibited small differences. Therefore, the results suggest that a risk reduction in the manufacturing process can be obtained with integrated process parameters as a result of the QbD approach, and the relationship between IQAs, CQAs, and CPPs can be used to predict CQAs for a control strategy and SUPAC (Scale-Up and Post-Approval Guidance).

Effects of granulation process variables on the physical properties of dosage forms by combination of experimental design and principal component analysis

The current study was to understand how process variables of high shear wet granulations affect physical properties of granules and tablets. The knowledge gained was intended to be used for Quality-by-Design based process design and optimization. The variables were selected based on the risk assessment as impeller speed, liquid addition rate, and wet massing time. Formulation compositions were kept constant to minimize their influence on granules properties. Multiple linear regression models were built providing understanding of the impact of each variable on granule hardness, Carr's index, tablet tensile strength, surface mean diameter of granules, and compression behavior. The experimental results showed that the impact of impeller speed was more dominant compared to wet massing time and water addition rate. The results also revealed that quality of granules and tablets could be optimized by adjusting specific process variables (impeller speed 1193 rpm, water spray rate 3.7 ml/min, and wet massing time 2.84 min). Overall desirability was 0.84 suggesting that the response values were closer to the target one. The SEM image of granules showed that spherical and smooth granules produced at higher impeller speed, whereas rough and irregular shape granules at lower speed. Moreover, multivariate data analysis demonstrated that impeller speed and massing time had strong correlation with the granule and tablet properties. In overall, the combined experimental design and principal component analysis approach allowed to better understand the correlation between process variables and granules and tablet attributes.

Determining the Influence of Granule Size on Simulation Parameters and Residual Shear Stress Distribution in Tablets by Combining the Finite Element Method into the Design of Experiments

The influence of granule size on simulation parameters and residual shear stress in tablets was determined by combining the finite element method (FEM) into the design of experiments (DoE). Lactose granules were prepared using a wet granulation method with a high-shear mixer and sorted into small and large granules using sieves. To simulate the tableting process using the FEM, parameters simulating each granule were optimized using a DoE and a response surface method (RSM). The compaction behavior of each granule simulated by FEM was in reasonable agreement with the experimental findings. Higher coefficients of friction between powder and die/punch (μ) and lower by internal friction angle (α^y) were generated in the case of small granules, respectively. RSM revealed that die wall force was affected by α^y. On the other hand, the pressure transmissibility rate of punches value was affected not only by the α^y value, but also by μ. The FEM revealed that the residual shear stress was greater for small granules than for large granules. These results suggest that the inner structure of a tablet comprising small granules was less homogeneous than that comprising large granules. To evaluate the contribution of the simulation parameters to residual stress, these parameters were assigned to the fractional factorial design and an ANOVA was applied. The result indicated that μ was the critical factor influencing residual shear stress. This study demonstrates the importance of combining simulation and statistical analysis to gain a deeper understanding of the tableting process.

Characterisation of pore structures of pharmaceutical tablets: A review

Traditionally, the development of a new solid dosage form is formulation-driven and less focus is put on the design of a specific microstructure for the drug delivery system. However, the compaction process particularly impacts the microstructure, or more precisely, the pore architecture in a pharmaceutical tablet. Besides the formulation, the pore structure is a major contributor to the overall performance of oral solid dosage forms as it directly affects the liquid uptake rate, which is the very first step of the dissolution process. In future, additive manufacturing is a potential game changer to design the inner structures and realise a tailor-made pore structure. In pharmaceutical development the pore structure is most commonly only described by the total porosity of the tablet matrix. Yet it is of great importance to consider other parameters to fully resolve the interplay between microstructure and dosage form performance. Specifically, tortuosity, connectivity, as well as pore shape, size and orientation all impact the flow paths and play an important role in describing the fluid flow in a pharmaceutical tablet. This review presents the key properties of the pore structures in solid dosage forms and it discusses how to measure these properties. In particular, the principles, advantages and limitations of helium pycnometry, mercury porosimetry, terahertz time-domain spectroscopy, nuclear magnetic resonance and X-ray computed microtomography are discussed.

Relationships between response surfaces for tablet characteristics of placebo and API-containing tablets manufactured by direct compression method

In this study, we evaluated the correlation between the response surfaces for the tablet characteristics of placebo and active pharmaceutical ingredient (API)-containing tablets. The quantities of lactose, cornstarch, and microcrystalline cellulose were chosen as the formulation factors. Ten tablet formulations were prepared. The tensile strength (TS) and disintegration time (DT) of tablets were measured as tablet characteristics. The response surfaces for TS and DT were estimated using a nonlinear response surface method incorporating multivariate spline interpolation, and were then compared with those of placebo tablets. A correlation was clearly observed for TS and DT of all APIs, although the value of the response surfaces for TS and DT was highly dependent on the type of API used. Based on this knowledge, the response surfaces for TS and DT of API-containing tablets were predicted from only two and four formulations using regression expression and placebo tablet data, respectively. The results from the evaluation of prediction accuracy showed that this method accurately predicted TS and DT, suggesting that it could construct a reliable response surface for TS and DT with a small number of samples. This technique assists in the effective estimation of the relationships between design variables and pharmaceutical responses during pharmaceutical development.

Preparation and Evaluation of Solid Dispersion Tablets by a Simple and Manufacturable Wet Granulation Method Using Porous Calcium Silicate

The aim of this study was to prepare and evaluate solid dispersion tablets containing a poorly water-soluble drug using porous calcium silicate (PCS) by a wet granulation method. Nifedipine (NIF) was used as the model poorly water-soluble drug. Solid dispersion tablets were prepared with the wet granulation method using ethanol and water by a high-speed mixer granulator. The binder and disintegrant were selected from 7 and 4 candidates, respectively. The dissolution test was conducted using the JP 16 paddle method. The oral absorption of NIF was studied in fasted rats. Xylitol and crospovidone were selected as the binder and disintegrant, respectively. The dissolution rates of NIF from solid dispersion formulations were markedly enhanced compared with NIF powder and physical mixtures. Powder X-ray diffraction (PXRD) confirmed the reduced crystallinity of NIF in the solid dispersion formulations. Fourier transform infrared (FT-IR) showed the physical interaction between NIF and PCS in the solid dispersion formulations. NIF is present in an amorphous state in granules prepared by the wet granulation method using water. The area under the plasma concentration-time curve (AUC) and peak concentration (C(max)) values of NIF after dosing rats with the solid dispersion granules were significantly greater than those after dosing with NIF powder. The solid dispersion formulations of NIF prepared with PCS using the wet granulation method exhibited accelerated dissolution rates and superior oral bioavailability. This method is very simple, and may be applicable to the development of other poorly water-soluble drugs.

Effect of process variables on the Drucker-Prager cap model and residual stress distribution of tablets estimated by the finite element method

A multivariate statistical technique was applied to clarify the causal correlation between variables in the manufacturing process and the residual stress distribution of tablets. Theophylline tablets were prepared according to a Box-Behnken design using the wet granulation method. Water amounts (X1), kneading time (X2), lubricant-mixing time (X3), and compression force (X4) were selected as design variables. The Drucker-Prager cap (DPC) model was selected as the method for modeling the mechanical behavior of pharmaceutical powders. Simulation parameters, such as Young's modulus, Poisson rate, internal friction angle, plastic deformation parameters, and initial density of the powder, were measured. Multiple regression analysis demonstrated that the simulation parameters were significantly affected by process variables. The constructed DPC models were fed into the analysis using the finite element method (FEM), and the mechanical behavior of pharmaceutical powders during the tableting process was analyzed using the FEM. The results of this analysis revealed that the residual stress distribution of tablets increased with increasing X4. Moreover, an interaction between X2 and X3 also had an effect on shear and the x-axial residual stress of tablets. Bayesian network analysis revealed causal relationships between the process variables, simulation parameters, residual stress distribution, and pharmaceutical responses of tablets. These results demonstrated the potential of the FEM as a tool to help improve our understanding of the residual stress of tablets and to optimize process variables, which not only affect tablet characteristics, but also are risks of causing tableting problems.

Development strategies for herbal products reducing the influence of natural variance in dry mass on tableting properties and tablet characteristics

One “Quality by Design” approach is the focus on the variability of the properties of the active substance. This is crucially important for active substances that are obtained from natural resources such as herbal plant material and extracts. In this paper, we present various strategies for the development of herbal products especially taking into account the natural batch-to-batch variability (mainly of the dry mass) of tablets that contain a fixed amount of tincture. The following steps in the development have been evaluated for the outcome of the physico-chemical properties of the resulting tablets and intermediates: concentration of the tincture extracted from Echinacea fresh plant, loading of the concentrate onto an inert carrier, the respective wet granulation and drying step, including milling, and the adjuvant excipients for the tablet compression step. The responses that were investigated are the mean particle size of the dried and milled granulates, compaction properties and disintegration time of the tablets. Increased particle size showed a significant increase of the disintegration time and a decrease of the compaction properties. In addition, our results showed that the particle size has a great dependency on the ratio of liquid to carrier during the wet granulation process. Thus, the variability of the respective parameters tested was influenced by the performed strategies, which is how the tincture correlated to its dry mass and the relation of the amount of carrier used. In order to optimize these parameters, a strategy considering the above-mentioned points has to be chosen.

An investigation on the correlation between drug dissolution properties and the growth behaviour of granules in high shear mixer

OBJECTIVES

The aim of this study was to investigate the correlation between the growth behaviour and in-vitro dissolution rate of water-insoluble drugs prepared with high-shear wet granulation.

METHODS

Granules containing nimodipine, microcrystalline cellulose, low-substituted hydroxypropylcellulose and aqueous solution of hydroxypropylcellulose were prepared and the effects of independent process variables, including impeller speed and liquid-to-solid ratio were taken into consideration. The mean granule size, granule-size distribution (GSD), porosity and surface properties were monitored at different kneading times to identify the granule-growth mechanisms simultaneously. A computer-based method was applied to simulate the dissolution behaviour of polydisperse granules based on the GSD data.

KEY FINDINGS

The in-vitro dissolution rate of drug was high for the early stages of granulation and sharply decreased when coalescence and consolidation of granules started, approaching a flat and low level when granules were sufficiently consolidated. The simulated dissolution results were in agreement with experimental observations and were significantly affected by the GSD, porosity and surface properties of granules during the granulation process. Moreover the GSD was directly related to the granule-growth behaviour and mechanisms.

CONCLUSIONS

In general, it was concluded that the dissolution properties of nimodipine basically correlated with the growth behaviour of granules in a high-shear mixer. The simulation method based on GSD can be used as a convenient and rapid way to predict the dissolution properties for formulation development and granulation optimization.