Multivariate statistical process control of a continuous pharmaceutical twin-screw granulation and fluid bed drying process

Experimental investigation of dynamic drying in single pharmaceutical granules containing acetaminophen or carbamazepine using synchrotron X-ray micro computed tomography

Drying time, velocity, and temperature are important aspects of the drying process for pharmaceutical granules observed during tablet manufacturing. However, the drying mechanism of single granules is often limited to modelling and simulation, with the internal and physical changes difficult to quantify at an experimental level. In this study, in-situ synchrotron-based X-ray imaging techniques were used for the first time to investigate the dynamic drying of single pharmaceutical granules, quantifying internal changes occurring over the drying time. Two commonly used excipients (lactose monohydrate (LMH) and microcrystalline cellulose (MCC)) were used as pure components and binary mixtures with one of either two active pharmaceutical ingredients of differing hydrophilicity/hydrophobicity (acetaminophen (APAP) and carbamazepine (CBZ)). Water was used as a liquid binder to generate single granules of 25 % to 30 % moisture content. Results showed that for most samples, the drying time and composition significantly influences the pore volume evolution and the moisture ratio, with the velocity and temperature of the drying air possessing mixed significance on increasing the rate of pore connectivity and moisture removal depending on the sample composition. Effects of active ingredient loading resulted in minimal influence on the drying of CBZ and generated binary mixtures, with APAP and its respective mixtures' drying behaviour dominated by the material's hydrophilic nature.

Demonstrating scalability between two blender types using DEM

Powder blending is a critical step in pharmaceutical manufacturing that can impact product quality such as tablet tensile strength. This study utilized the Discrete Element Method (DEM) to investigate blending in a 5-liter mini-batch and a 2-liter Turbula blender. DEM parameters were calibrated using small-scale powder characterization tests, so that the particle behavior in the DEM simulations matches the measured behavior. The research explored the effects of blender designs and process conditions on blending and lubricant dispersion. A predictive model for tablet tensile strength was developed. The model takes the lubricant's dispersion via the lubrication energy into account. The model is then used to predict the tablet tensile strength depending on the chosen process parameters, blending speed, duration, and fill level. DEM simulations enabled scaling between the two blenders, providing valuable insights for a semi-continuous manufacturing process based on mini-batch blending. The findings contribute to a deeper understanding of blending mechanics, offering potential enhancements in pharmaceutical manufacturing efficiency and product consistency.

Real-time detection of mean and variance changes in experience sampling data: A comparison of existing and novel statistical process control approaches

Retrospective analyses of experience sampling (ESM) data have shown that changes in mean and variance levels may serve as early warning signs of an imminent depression. Detecting such early warning signs prospectively would pave the way for timely intervention and prevention. The exponentially weighted moving average (EWMA) procedure seems a promising method to scan ESM data for the presence of mean changes in real-time. Based on simulation and empirical studies, computing and monitoring day averages using EWMA works particularly well. We therefore expand this idea to the detection of variance changes and propose to use EWMA to prospectively scan for mean changes in day variability statistics (i.e.,s 2 , s , ln( s )). When both mean and variance changes are of interest, the multivariate extension of EWMA (MEWMA) can be applied to both the day averages and a day statistic of variability. We evaluate these novel approaches to detecting variance changes by comparing them to EWMA-type procedures that have been specifically developed to detect a combination of mean and variance changes in the raw data: EWMA-S 2 , EWMA-ln(S 2 ), and EWMA- X ¯ -S 2 . We ran a simulation study to examine the performance of the two approaches in detecting mean, variance, or both types of changes. The results indicate that monitoring day statistics using (M)EWMA works well and outperforms EWMA-S 2 and EWMA-ln(S 2 ); the performance difference with EWMA- X ¯ -S 2 is smaller but notable. Based on the results, we provide recommendations on which statistic of variability to monitor based on the type of change (i.e., variance increase or decrease) one expects.

Pharmaceutical Application of Process Understanding and Optimization Techniques: A Review on the Continuous Twin-Screw Wet Granulation

Twin-screw wet granulation (TSWG) is a method of continuous pharmaceutical manufacturing and a potential alternative method to batch granulation processes. It has attracted more and more interest nowadays due to its high efficiency, robustness, and applications. To improve both the product quality and process efficiency, the process understanding is critical. This article reviews the recent work in process understanding and optimization for TSWG. Various aspects of the progress in TSWG like process model construction, process monitoring method development, and the strategy of process control for TSWG have been thoroughly analyzed and discussed. The process modeling technique including the empirical model, the mechanistic model, and the hybrid model in the TSWG process are presented to increase the knowledge of the granulation process, and the influence of process parameters involved in granulation process on granule properties by experimental study are highlighted. The study analyzed several process monitoring tools and the associated technologies used to monitor granule attributes. In addition, control strategies based on process analytical technology (PAT) are presented as a reference to enhance product quality and ensure the applicability and capability of continuous manufacturing (CM) processes. Furthermore, this article aims to review the current research progress in an effort to make recommendations for further research in process understanding and development of TSWG.

Challenges and Opportunities of Implementing Data Fusion in Process Analytical Technology-A Review

The release of the FDA's guidance on Process Analytical Technology has motivated and supported the pharmaceutical industry to deliver consistent quality medicine by acquiring a deeper understanding of the product performance and process interplay. The technical opportunities to reach this high-level control have considerably evolved since 2004 due to the development of advanced analytical sensors and chemometric tools. However, their transfer to the highly regulated pharmaceutical sector has been limited. To this respect, data fusion strategies have been extensively applied in different sectors, such as food or chemical, to provide a more robust performance of the analytical platforms. This survey evaluates the challenges and opportunities of implementing data fusion within the PAT concept by identifying transfer opportunities from other sectors. Special attention is given to the data types available from pharmaceutical manufacturing and their compatibility with data fusion strategies. Furthermore, the integration into Pharma 4.0 is discussed.

Control strategy definition for a drug product continuous wet granulation process: Industrial case study

This paper describes the specific control strategy of the commercial manufacturing process of an immediate release tablet formulation based on continuous twin-screw wet granulation. This control strategy has been defined by a multidisciplinary team using an enhanced approach, in alignment with the quality by design principles. During process development, experiments have been performed according to multivariate designs first to identify critical material attributes and critical process parameters and then, to define process conditions generating a product having the required quality. Hence, controls have been applied on critical quality attributes and on related critical process parameters and critical material attributes. Due to the specificity of the process that combines batch and continuous unit operations, a specific control strategy has been designed to ensure intermediate and end product quality. Therefore, controls including soft sensor model and in process controls have been developed to continuously monitor granules residual moisture content, assay and dissolution as granules and tablets critical attributes. In addition, process analytical technology implementation enabled increased process understanding and provided support for the development of the control strategy. This study is therefore considered as a real industrial case study of control strategy definition and implementation for an intended commercial continuous manufacturing process.

Pharmaceutical application of multivariate modelling techniques: a review on the manufacturing of tablets

The tablet manufacturing process is a complex system, especially in continuous manufacturing (CM). It includes multiple unit operations, such as mixing, granulation, and tableting. In tablet manufacturing, critical quality attributes are influenced by multiple factorial relationships between material properties, process variables, and interactions. Moreover, the variation in raw material attributes and manufacturing processes is an inherent characteristic and seriously affects the quality of pharmaceutical products. To deepen our understanding of the tablet manufacturing process, multivariable modeling techniques can replace univariate analysis to investigate tablet manufacturing. In this review, the roles of the most prominent multivariate modeling techniques in the tablet manufacturing process are discussed. The review mainly focuses on applying multivariate modeling techniques to process understanding, optimization, process monitoring, and process control within multiple unit operations. To minimize the errors in the process of modeling, good modeling practice (GMoP) was introduced into the pharmaceutical process. Furthermore, current progress in the continuous manufacturing of tablets and the role of multivariate modeling techniques in continuous manufacturing are introduced. In this review, information is provided to both researchers and manufacturers to improve tablet quality.

Multivariate feed forward process control and optimization of an industrial, granulation based tablet manufacturing line using historical data

The purpose of this work was to understand the variability in disintegration time and tableting yield of high drug load (>60%) tablets prepared by batch-wise high shear wet granulation. The novelty of the study is the use of multivariate methods (Batch Evolution Models - BEMs and Batch Level Models - BLMs) to enhance process control, with a feed forward component, using prediction models built from a historical dataset acquired for 95 industrial scale batches. Time dependent process variables and significant influences on investigated parameters were identified. Prediction of output from input was tested with Partial Least Squares (PLS) and Artificial Neural Network (ANN) modeling. A reliable prediction ability was achieved for granulation water amount (±2 kg in a 16-31 kg range), tableting speed (±5000 tablets/h in a 23,000-72,500 tabl./h range) and disintegration time of cores (±100 s; in a 250-900 s range). Offsets from the optimal process evolution and certain raw material properties were correlated with differences observed in the output variables. Improvement options were identified for 80% of the batches with high disintegration time. Hence, the trained models can be applied for systematic process improvement, enabling feed forward control.

Process optimization of twin-screw melt granulation of fenofibrate using design of experiment (DoE)

The purpose of this study was to optimize the melt granulation process of fenofibrate using twin-screw granulator. Initial screening was performed to select the excipients required for melt granulation process. A 3 × 3 factorial design was used to optimize the processing conditions using the % drug loading (X₁) and screw speed (X₂) as the independent parameters and granule friability (Y₁) % yield (Y₂) as the dependent parameters. The effect of the independent parameters on the dependent parameters was determined using response surface plots and contour plots. A linear relationship was observed between % drug loading (X₁) and % friability (Y₁) and a quadratic relationship was observed between the independent parameters (X₁ and X₂) and % yield (Y₂). The processing conditions for optimum granules were determined using numerical and graphical optimization and it was found that 15% drug loading at 50 rpm results in maximum % yield of 82.38% and minimum friability of 7.88%. The solid-state characterization of the optimized granules showed that the drug turned from crystalline state to amorphous state during melt granulation process. The optimized granules were compressed into tablets using Purolite® as the super disintegrating agent. The optimized formulation showed >85% drug release in 0.75% SLS solution within 60 min.

Determination of Residence Time Distribution in a Continuous Powder Mixing Process With Supervised and Unsupervised Modeling of In-line Near Infrared (NIR) Spectroscopic Data

Successful implementation of continuous manufacturing processes requires robust methods to assess and control product quality in a real-time mode. In this study, the residence time distribution of a continuous powder mixing process was investigated via pulse tracer experiments using near infrared spectroscopy for tracer detection in an in-line mode. The residence time distribution was modeled by applying the continuous stirred tank reactor in series model for achieving the tracer (paracetamol) concentration profiles. Partial least squares discriminant analysis and principal component analysis of the near infrared spectroscopy data were applied to investigate both supervised and unsupervised chemometric modeling approaches. Additionally, the mean residence time for three powder systems was measured with different process settings. It was found that a significant change in the mean residence time occurred when comparing powder systems with different flowability and mixing process settings. This study also confirmed that the partial least squares discriminant analysis applied as a supervised chemometric model enabled an efficient and fast estimate of the mean residence time based on pulse tracer experiments.

Continuous Twin Screw Wet Granulation and Drying-Control Strategy for Drug Product Manufacturing

The use of continuous manufacturing has been increasing within the pharmaceutical industry over the last few years. Continuous direct compression has been the focus of publications on the topic to date. The use of wet granulation can improve segregation resistance, uniformity, enhance density, and flow properties for improved tabletability, or improve stability of products that cannot be manufactured by using a direction compression process. This article focuses on development of appropriate control strategies for continuous wet granulation (especially twin screw wet granulation) through equipment design, material properties and manufacturing process along with areas where additional understanding is required. The article also discusses the use of process analytical technologies as part of the control and automation approach to ensure a higher assurance of product quality. Increased understanding of continuous wet granulation should result in increased utilization of the technique, thereby allowing for an increase in diversity of products manufactured by continuous manufacturing and the benefits that comes with a more complex process such as wet granulation compared with direct compression process.

Integrated continuous manufacturing in pharmaceutical industry: current evolutionary steps toward revolutionary future

Continuous manufacturing (CM) has the potential to provide pharmaceutical products with better quality, improved yield and with reduced cost and time. Moreover, ease of scale-up, small manufacturing footprint and on-line/in-line monitoring and control of the process are other merits for CM. Regulating authorities are supporting the adoption of CM by pharmaceutical manufacturers through issuing proper guidelines. However, implementation of this technology in pharmaceutical industry is encountered by a number of challenges regarding the process development and quality assurance. This article provides a background on the implementation of CM in pharmaceutical industry, literature survey of the most recent state-of-the-art technologies and critically discussing the encountered challenges and its future prospective in pharmaceutical industry.

Data fusion strategies for performance improvement of a Process Analytical Technology platform consisting of four instruments: An electrospinning case study

The aim of this work was to develop a PAT platform consisting of four complementary instruments for the characterization of electrospun amorphous solid dispersions with meloxicam. The investigated methods, namely NIR spectroscopy, Raman spectroscopy, Colorimetry and Image analysis were tested and compared considering the ability to quantify the active pharmaceutical ingredient and to detect production errors reflected in inhomogeneous deposition of fibers. Based on individual performance the calculated RMSEP values ranged between 0.654% and 2.292%. Mid-level data fusion consisting of data compression through latent variables and application of ANN for regression purposes proved efficient, yielding an RMSEP value of 0.153%. Under these conditions the model could be validated accordingly on the full calibration range. The complementarity of the PAT tools, demonstrated from the perspective of captured variability and outlier detection ability, contributed to model performance enhancement through data fusion. To the best of the author's knowledge, this is the first application of data fusion in the field of PAT for efficient handling of big-analytical-data provided by high-throughput instruments.

Influence of granulation temperature on particle size distribution of granules in twin-screw granulation (TSG)

This study investigated an influence of granulation temperature during twin-screw granulation (TSG) on particle size distributions (PSDs). The influence of the granulation temperature on granule size distributions varied, depending on the liquid to solid (L/S) ratio, the kind of binders, the method of binder addition, and the filler material. The PSD of granules was broad and bimodal at a barrel temperature of 30 °C. Granules size distributions became narrow and second height decreased at high barrel temperature. While the L/S ratio had an effect on the sharpness of granule size distributions, this effect was minor compared to the granulation temperature. Granule size distributions were influenced by binder addition methods. When the binder was added as solution, PSD became broad. In formulations using lactose as filler, PSD became broad and bimodal at 90 °C. Much lactose was dissolved in granulation solution at high temperature, because the solubility of lactose rises significantly with the solution temperature leading to higher effective L/S ratio in the granulator. Hence, granulation was proceeded and large granules were formed. From these results, the granulation temperature is one of important parameters to obtain mono-modal PSD in TSG.

Twin Screw Granulation: Effects of Properties of Primary Powders

Lactose and mannitol are some of the most commonly used powders in the pharmaceutical industry. The limited research published so far highlights the effects of process and formulation parameters on the properties of the granules and the tablets produced using these two types of powders separately. However, the comparison of the performance of these two types of powders during twin screw wet granulation has received no attention. The present research is focused on understanding the granulation mechanism of different grades of two pharmaceutical powders with varying properties (i.e., primary particle size, structure, and compressibility). Three grades each of lactose and mannitol were granulated at varying liquid to solid ratios (L/S) and screw speed. It was noticed that primary powder morphology plays an important role in determining the granule size and structure, and tablet tensile strength. It was indicated that the processed powders such as spray-dried and granulated lactose and mannitol can be used in formulation for wet granulation where flowability of active pharmaceutical ingredient (API) is poor.