Prediction of critical quality attributes and optimization of continuous dry granulation process via flowsheet modeling and experimental validation

Flowsheet modelling of a powder continuous feeder-mixer system

In this study, an integrated flowsheet model of the continuous feeder-mixer system was calibrated, simulated and compared against experimental data. The feeding process was first investigated using two major components (ibuprofen and microcrystalline cellulose (MCC)), in a formulation comprised of: 30 wt% of ibuprofen, 67.5 wt% MCC, 2 wt% of sodium starch glycolate and 0.5 wt% of magnesium stearate. The impact of a refill on feeder performance was experimentally evaluated for different operating conditions. Results showed that it had no influence on feeder performance. While simulations with the feeder model fairly reproduced the material behaviour observed in the feeder, unintended disturbances were underpredicted due to the model's low complexity. Experimentally, mixer's efficiency was assessed based on ibuprofen residence time distribution. Mean residence time pointed to a higher mixer's efficiency at lower flow rates. Blend homogeneity results showed that for the entire set of experiments, ibuprofen RSD <5%, irrespective of process variables. A feeder-mixer flowsheet model was calibrated, after regressing the axial model coefficients. The regression curves exhibited a R² above 0.96, whereas the RMSE varied from 1.58x10^-4 to 1.06x10^-3 s^-1 across all fitted curves. Simulations confirmed that flowsheet model captured the powder dynamics inside the mixer and qualitatively predicted the mixer's filtering ability against feeding composition fluctuations, as well as ibuprofen RSD in blend, in line with real experiments.

Developing a Virtual Flowability Sensor for Monitoring a Pharmaceutical Dry Granulation Line

Current technologies to measure granule flowability involve at-line methods that can take hours to perform. This is problematic for a continuous dry granulation tableting line, where the quality assurance and control of the final tablet products depend on real-time monitoring and control of powder flowability. Hence, a real-time alternative is needed for measuring the flowability of the granular products coming out of the roller compactor, which is the unit operation immediately preceding the tablet press. Since particle analyzers have the potential to take inline measurements of the size and shape of granules, they can potentially serve as real-time flowability sensors, given that the size and shape measurements can be used to reliably predict flowability measurements. This paper reports on the use of Partial Least Squares (PLS) regression to utilize distributions of size and shape measurements in predicting the output of three different types of flowability measurements: rotary drum flow, orifice flow, and tapped density analysis. The prediction performance of PLS had a coefficient of determination ranging from 0.80 to 0.97, which is the best reported performance in the literature. This is attributed to the ability of PLS to handle high collinearity in the datasets and the inclusion of multiple shape characteristics-eccentricity, form factor, and elliptical form factor-into the model. The latter calls for a change in industry perspective, which normally dismisses the importance of shape in favor of size; and the former suggests the use of PLS as a better way to reduce the dimensionality of distribution datasets, instead of the widely used practice of pre-selecting distribution percentiles.

Application of Supervised and Unsupervised Learning Approaches for Mapping Storage Conditions of Biopharmaceutical Product-A Case Study of Human Serum Albumin

The stability of biopharmaceutical therapeutics over the storage period/shelf life has been a challenging concern for manufacturers. A noble strategy for mapping best and suitable storage conditions for recombinant human serum albumin (rHSA) in laboratory mixture was optimized using chromatographic data as per principal component analysis (PCA), and similarity was defined using hierarchical cluster analysis. In contrast, separability was defined using linear discriminant analysis (LDA) models. The quantitation was performed for rHSA peak (analyte of interest) and its degraded products, i.e., dimer, trimer, agglomerates and other degradation products. The chromatographic variables were calculated using validated stability-indicating assay method. The chromatographic data mapping was done for the above-mentioned peaks over three months at different temperatures, i.e., 20°C, 5-8°C and at room temperature (25°C). The PCA had figured out the ungrouped variable, whereas supervised mapping was done using LDA. As an outcome result of LDA, about 60% of data were correctly classified with the highest sensitivity for 25°C (Aq), 25°C and 5-8°C (Aq with 5% glucose as a stabilizer), whereas the highest specificity was observed for samples stored at 5-8°C (Aq with 5% glucose as a stabilizer).

System model driven selection of robust tablet manufacturing processes based on drug loading and formulation physical attributes

Mechanistic process modelling presents an opportunity to reduce experimental burden, enabling relationships between process parameters and product attributes to be mapped out using in-silico experiments. A system model of a pharmaceutical tablet manufacturing process comparing dry granulation with direct compression is developed to answer key material and process design questions. The system model links API physical properties and formulation to process parameters to map out the robust operating space. To demonstrate the application of the model, several drug product formulation design questions were considered: •Which processing route is the most robust given the API material properties and dosage requirements?;• How does drug loading and tablet size impact the robustness of the manufacturing process?; •What process settings are required for a robust manufacturing route for the API material properties and drug loading requirements?; A computational framework was developed using the system models to generate process classification and design space maps to aid robust pharmaceutical formulation and process decision making. Process classification maps were produced to assess the feasibility of roller compaction and direct compression for different material properties and formulations. Constraints on the critical quality attributes of the intermediate and final products were defined using the Manufacturing Classification System. Design space maps presented here demonstrate how system models can be used to support formulation and process design. The design space maps illustrate how the process operating space can be increased or decreased as the API mass fraction is varied.; The process design and selection system model demonstrate how an understanding of the API physical properties can be used to model the impact of formulation and process design. Furthermore, these models can be instrumental in the dialogue with colleagues developing the API in order to set the requirements of the API physical properties to ensure successful and robust formulation and process designs.

Optimization of Critical Quality Attributes in Tablet Film Coating and Design Space Determination Using Pilot-Scale Experimental Data

In this study, the novel high-speed tablet film coating process in the continuous manufacturing was investigated. The influence of key process variables (inlet air flow rate, inlet air temperature, and suspension spray rate) were investigated using a Box-Behnken experimental design method. Statistical regression models were developed to predict the outlet air temperature and relative humidity, the coating efficiency, the tablet moisture content, and coating uniformity. The effects of the three key process variables were comprehensively investigated based on mathematical analysis, contour plots, and interaction plots. The results indicate that all the process responses are affected by changing the inlet air flow rate, temperature, and suspension spray rate. A design space (DS) in terms of failure probability was determined based on specifications for tablet moisture content (< 3.5%) and coating uniformity (tablet weight standard deviation < 4 mg for tablet weight of 200 mg) using Monte Carlo simulations. Independent experiments were carried out and successfully validated the robustness and accuracy of the determined DS for the investigated tablet film coating process. All the data were generated using an industrial pilot-scale novel high-speed tablet coating unit from a continuous manufacturing line. The work facilitates the quality by design implementation of continuous pharmaceutical manufacturing.

Effects of process parameters on tablet critical quality attributes in continuous direct compression: a case study of integrating data-driven statistical models and mechanistic compaction models

Continuous manufacturing of oral-dosage drug products is increasing the need for rigorous process understanding both from a process design and control perspective. The purpose of this study is to develop a methodology that analyzes the effects of upstream process parameters on continuous tablet compaction and then correlates associated upstream variables to the final tablet attributes (e.g. relative density and hardness). The impact of three process parameters (system throughput, blender speed, and compaction force) on tablet attributes is investigated using a full factorial experimental design. As expected, the compaction force was found to be the most significant process parameter. However, importantly, throughput was discovered to have a non-negligible impact which was previously unaccounted for. This impact is proposed to be related to differing levels of powder pre-compression. An empirical model for this relationship is regressed and incorporated into a flowsheet model. The flowsheet model is then used to develop an in silico design space which is compared favorably to that built from experiments. Moreover, in the future, the in silico design space based on the validated flowsheet model can provide better manufacturing flexibility and make control strategy development simpler.

Model-based approach to the design of pharmaceutical roller-compaction processes

This work presents a new model based approach to process design and scale-up within the same equipment of a roller compaction process. The prediction of the operating space is not performed fully in-silico, but uses low-throughput experiments as input. This low-throughput data is utilized in an iterative calibration routine to describe the behavior of the powder in the roller compactor and improves the predictive quality of the mechanistic models at low and high-throughput. The model has been validated with an experimental design of experiments of two ibuprofen formulations. The predicted sweet spots in the operating space are in good agreement with the experimental results.

Dynamic Flowsheet Model Development and Sensitivity Analysis of a Continuous Pharmaceutical Tablet Manufacturing Process Using the Wet Granulation Route

In view of growing interest and investment in continuous manufacturing, the development and utilization of mathematical model(s) of the manufacturing line is of prime importance. These models are essential for understanding the complex interplay between process-wide critical process parameters (CPPs) and critical quality attributes (CQAs) beyond the individual process operations. In this work, a flowsheet model that is an approximate representation of the ConsiGma TM -25 line for continuous tablet manufacturing, including wet granulation, is developed. The manufacturing line involves various unit operations, i.e., feeders, blenders, a twin-screw wet granulator, a fluidized bed dryer, a mill, and a tablet press. The unit operations are simulated using various modeling approaches such as data-driven models, semi-empirical models, population balance models, and mechanistic models. Intermediate feeders, blenders, and transfer lines between the units are also simulated. The continuous process is simulated using the flowsheet model thus developed and case studies are provided to demonstrate its application for dynamic simulation. Finally, the flowsheet model is used to systematically identify critical process parameters (CPPs) that affect process responses of interest using global sensitivity analysis methods. Liquid feed rate to the granulator, and air temperature and drying time in the dryer are identified as CPPs affecting the tablet properties.

Use of roller compaction and fines recycling process in the preparation of erlotinib hydrochloride tablets

This study focuses on improving the manufacturing process for a generic immediate-release tablet containing erlotinib hydrochloride by adding a fines recycling process during roller compaction. Due to the large fraction of small-sized API particles, the starting powder mixture was inconsistently fed into the roller compactor. Consequently, poorly flowing granules with a high ratio of fines were produced. A fines recycling step was, therefore, added to the existing roller compaction process to minimize the risks caused by the poor granule flow. A laboratory scale roller compactor and a tablet simulator were used to prepare granules at various process conditions. The effect of dry granulation parameters on size distribution, API distribution, powder flow, compaction properties, and dissolution profile was evaluated. The granule batch after fines recycling had markedly improved size distribution and flowability while maintaining acceptable tablet tensile strength and rapid dissolution profile. The application of the fines recycling process at commercial scale resulted in reliable dissolution performance and batch-to-batch consistency, which were further confirmed by bioequivalence to the reference product. Understanding how granule properties are impacted by the fines recycling process may enable fine-tuning of the dry granulation process for optimal product quality.