Multivariate modelling to study the effect of the manufacturing process on the complete tablet dissolution profile

Flexible modelling of the dissolution performance of directly compressed tablets

In this study, a compartmental disintegration and dissolution model is proposed for the prediction and evaluation of the dissolution performance of directly compressed tablets. This dissolution model uses three compartments (Bound, Disintegrated, and Dissolved) to describe the state of each particle of active pharmaceutical ingredient. The disintegration of the tablet is captured by three fitting parameters. Two disintegration parameters, β0 and βt,0, describe the initial disintegration rate and the change in disintegration rate, respectively. A third parameter, α, describes the effect of the volume of dissolved drug on the disintegration process. As the tablet disintegrates, particles become available for dissolution. The dissolution rate is determined by the Nernst-Brunner equation, whilst taking into account the hydrodynamic effects within the vessel of a USP II (paddle) apparatus. This model uses the raw material properties of the active pharmaceutical ingredient (solubility, particle size distribution, true density), lending it towards early development activities during which time the amount of drug substance available may be limited. Additionally, the strong correlations between the fitting parameters and the tablet porosity indicate the potential to isolate the manufacturing effects and thus implement the model as part of a real-time release testing strategy for a continuous direct compression line.

Development and Validation of a Discriminatory Dissolution Model for an Immediately Release Dosage Form by DOE and Statistical Approaches

A discriminatory dissolution model was built through DOE with multivariate analysis of variance (MANOVA) and multiple linear regression (MLR) modeling to assess dissolution operational space for a highly water soluble immediate-release solid dosage drug product. The dissolution was utilized in the following five aspects: (1) understand the impact of individual variables and their interactions on dissolution performance through effect analysis; (2) explain the lack of discriminatory power of the initial dissolution condition used in early phase development by prediction profiler; (3) predict discriminatory dissolution operational space to differentiate photo degraded drug products from control with contour profiler analysis; (4) validate by the external experimental data acquired with the initial nondiscriminatory dissolution condition and the predicted discriminatory dissolution condition, followed by model independent statistical analysis (e.g., f2); and (5) establish correlation of the discriminatory dissolution with disintegration. The selected discriminatory dissolution method was validated by demonstrating accuracy, precision and linearity, specificity, repeatability, intermediate precision, stability, filter verification, and robustness.

A Fast and Non-destructive Terahertz Dissolution Assay for Immediate Release Tablets

There is a clear need for a robust process analytical technology tool that can be used for on-line/in-line prediction of dissolution and disintegration characteristics of pharmaceutical tablets during manufacture. Tablet porosity is a reliable and fundamental critical quality attribute which controls key mass transport mechanisms that govern disintegration and dissolution behavior. A measurement protocol was developed to measure the total porosity of a large number of tablets in transmission without the need for any sample preparation. By using this fast and non-destructive terahertz spectroscopy method it is possible to predict the disintegration and dissolution of drug from a tablet in less than a second per sample without the need of a chemometric model. The validity of the terahertz porosity method was established across a range of immediate release (IR) formulations of ibuprofen and indomethacin tablets of varying geometries as well as with and without debossing. Excellent correlation was observed between the measured terahertz porosity, dissolution characteristics (time to release 50% drug content) and disintegration time for all samples. These promising results and considering the robustness of the terahertz method pave the way for a fully automated at-line/on-line porosity sensor for real time release testing of IR tablets dissolution.

Multivariate analysis in the development of bioequivalent tablets containing bicalutamide

The pharmaceutical industry has to tackle the explosion of high amounts of poorly soluble APIs. This phenomenon leads to numerous sophisticated solutions. These include the use of multifactorial data analysis identifying correlations between the components and dosage form properties, laboratory and production process parameters with respect to the API liberation Example of such API is bicalutamide. Improved liberation is achieved by particle size reduction. Laboratory batches, with different PSD of API, were filled into gelatinous capsules and consequently granulated for tablet compression. Comparative dissolution profiles with Casodex 150 mg (Astra Zeneca) were performed. The component analysis was used for the statistical evaluation of f₁ and f₂ factors and D(v,0.9) and D[4,3] parameters of PSD to identify optimal PSD values. Suitable PSD limits for API were statistically confirmed in laboratory and in commercial scale with respect to optimized tablet properties. The tablets were bioequivalent with originator (n = 20; 90% CI for ln AUC_0-120: 99.8-111.9%; 90% CI for ln c_max: 101.1-112.9%). In conclusion, the micronisation of the API is still an efficient and inexpensive method improving the bioavailability, although there are more complicated and expensive methods available. Statistical multifactorial methods improved the safety and reproducibility of production.

A Precise Prediction Method for the Properties of API-Containing Tablets Based on Data from Placebo Tablets

We previously reported a novel method for the precise prediction of tablet properties (e.g., tensile strength (TS)) using a small number of experimental data. The key technique of this method is to compensate for the lack of experimental data by using data of placebo tablets collected in a database. This study provides further technical knowledge to discuss the usefulness of this prediction method. Placebo tablets consisting of microcrystalline cellulose, lactose, and cornstarch were prepared using the design of an experimental method, and their TS and disintegration time (DT) were measured. The response surfaces representing the relationship between the formulation and the tablet properties were then created. This study investigated tablets containing four different active pharmaceutical ingredients (APIs) with a drug load ranging from 20–60%. Overall, the TS of API-containing tablets could be precisely predicted by this method, while the prediction accuracy of the DT was much lower than that of the TS. These results suggested that the mode of action of APIs on the DT was more complicated than that on the TS. Our prediction method could be valuable for the development of tablet formulations.

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).

A two-step approach for fluidized bed granulation in pharmaceutical processing: Assessing different models for design and control

Various modeling techniques were used to understand fluidized bed granulation using a two-step approach. First, Plackett-Burman design (PBD) was used to identify the high-risk factors. Then, Box-Behnken design (BBD) was used to analyze and optimize those high-risk factors. The relationship between the high-risk input variables (inlet air temperature X1, binder solution rate X3, and binder-to-powder ratio X5) and quality attributes (flowability Y1, temperature Y2, moisture content Y3, aggregation index Y4, and compactability Y5) of the process was investigated using response surface model (RSM), partial least squares method (PLS) and artificial neural network of multilayer perceptron (MLP). The morphological study of the granules was also investigated using a scanning electron microscope. The results showed that X1, X3, and X5 significantly affected the properties of granule. The RSM, PLS and MLP models were found to be useful statistical analysis tools for a better mechanistic understanding of granulation. The statistical analysis results showed that the RSM model had a better ability to fit the quality attributes of granules compared to the PLS and MLP models. Understanding the effect of process parameters on granule properties provides the basis for modulating the granulation parameters and optimizing the product performance at the early development stage of pharmaceutical products.

New gentle-wing high-shear granulator: impact of processing variables on granules and tablets characteristics of high-drug loading formulation using design of experiment approach

The aim of this work was to study the application of design of experiment (DoE) approach in defining design space for granulation and tableting processes using a novel gentle-wing high-shear granulator. According to quality-by-design (QbD) prospective, critical attributes of granules, and tablets should be ensured by manufacturing process design. A face-centered central composite design has been employed in order to investigate the effect of water amount (X₁), impeller speed (X₂), wet massing time (X₃), and water addition rate (X₄) as independent process variables on granules and tablets characteristics. Acetaminophen was used as a model drug and granulation experiments were carried out using dry addition of povidone k30. The dried granules have been analyzed for their size distribution, density, and flow pattern. Additionally, the produced tablets have been investigated for; weight uniformity, breaking force, friability and percent capping, disintegration time, and drug dissolution. Results of regression analysis showed that water amount, impeller speed and wet massing time have significant (p < .05) effect on granules and tablets characteristics. However, the water amount had the most pronounced effect as indicated by its higher parameter estimate. On the other hand, water addition rate showed a minimal impact on granules and tablets properties. In conclusion, water amount, impeller speed, and wet massing time could be considered as critical process variables. Thus, understanding the relationship between these variables and quality attributes of granules and corresponding tablets provides the basis for adjusting granulation variables in order to optimize product performance.

Statistical modeling methods to analyze the impacts of multiunit process variability on critical quality attributes of Chinese herbal medicine tablets

The quality of Chinese herbal medicine tablets suffers from batch-to-batch variability due to a lack of manufacturing process understanding. In this paper, the Panax notoginseng saponins (PNS) immediate release tablet was taken as the research subject. By defining the dissolution of five active pharmaceutical ingredients and the tablet tensile strength as critical quality attributes (CQAs), influences of both the manipulated process parameters introduced by an orthogonal experiment design and the intermediate granules’ properties on the CQAs were fully investigated by different chemometric methods, such as the partial least squares, the orthogonal projection to latent structures, and the multiblock partial least squares (MBPLS). By analyzing the loadings plots and variable importance in the projection indexes, the granule particle sizes and the minimal punch tip separation distance in tableting were identified as critical process parameters. Additionally, the MBPLS model suggested that the lubrication time in the final blending was also important in predicting tablet quality attributes. From the calculated block importance in the projection indexes, the tableting unit was confirmed to be the critical process unit of the manufacturing line. The results demonstrated that the combinatorial use of different multivariate modeling methods could help in understanding the complex process relationships as a whole. The output of this study can then be used to define a control strategy to improve the quality of the PNS immediate release tablet.