Development and application of control concepts for twin-screw wet granulation in the ConsiGmaTM-25: Part 2 granule size.

Traditional operation modes, such as running the production processes at constant process settings or within a narrow design space, do not fully exploit the advantages of continuous pharmaceutical manufacturing. Integrating Quality by Control (QbC) algorithms as a standard component of production processes can mitigate the effect of diverse process disturbances and enhance process efficiency, particularly in terms of production costs and environmental footprint. This paper explores the potential of QbC algorithms for optimizing twin-screw wet granulation in the ConsiGmaTM-25 manufacturing line, specifically addressing granule size. It represents the second part of a study (Celikovic et al., 2024) focused on granule composition. The concepts proposed in this work rely on process analytical technology (PAT) equipment for real-time monitoring of the granulation CQAs and a dynamic process model linking the granulation process parameters and the monitored CQAs. The granule size model identified via the local-linear-model-tree (LoLiMoT) algorithm is used to develop both a model predictive controller (MPC) and a granule size soft sensor. The MPC employs this model as a core component for selecting optimal granulation parameters to ensure the production of granules with target size. A digital operator assistant is developed to address disturbances that cannot be mitigated via MPC but can be eliminated by the plant operators. This study systematically outlines a workflow, starting from conceptualization, moving through simulation development, and finally ending with real-world application on a production line. In this final step, all proposed concepts are transferred to the ConsiGmaTM-25 manufacturing line, where their performance is validated through selected disturbance scenarios.

Development and application of control concepts for twin-screw wet granulation in the ConsiGmaTM-25, Part 1: Granule composition.

Continuous manufacturing of pharmaceuticals offers several benefits, such as increased production efficiency, enhanced product quality control, and lower environmental footprint. To fully exploit these benefits, standard operation mode (production processes with no or minimal disturbance mitigation measures) should be supported by adopting novel quality-by-control (QbC) methodologies. The paper at hand is the first part of a study focused on developing QbC algorithms for optimizing twin-screw wet granulation in the industrial manufacturing line ConsiGmaTM-25, specifically addressing granule composition. This work relieson previously established process-analytical-technology (PAT) equipment for real-time monitoring of the granule composition, i.e., the active pharmaceutical ingredient (API) and liquid content in wet granules. The developed control platform integrates model-based process control algorithms that aim to keep the API- and liquid content at target values through real-time adjustments of the process parameters. Furthermore, the platform integrates a digital operator assistant, which aims to detect and classify granulation disturbances and provides messages and instructions for the plant operator. The present manuscript systematically outlines all design steps from the development phase in the simulation environment to the final real system application and validation. The control platform's performance is demonstrated through selected test scenarios on the ConsiGmaTM-25 manufacturing line. The obtained results indicate improved disturbance robustness and an increase in intermediate/final product quality (compared to conventional operating modes): The process control algorithms successfully maintained the API- and liquid content at target values despite process disturbances. Furthermore, realistic disturbances (feeder, pump, and material) were accurately detected and classified by the digital assistant algorithm. The information was provided through a user interface, offering real-time support for plant personnel.

Cracking the code: Spatial heterogeneity as the missing piece for modeling granular fluidized bed drying.

Pharmaceutical twin-screw wet granulation is a multifaceted and intricate process pivotal to drug product development. Accurate modeling of this process is indispensable for optimizing manufacturing parameters and ensuring product quality. The fluid bed dryer, an integral component of this granulation process, significantly influences the granular critical quality attributes. This study builds upon prior research by integrating experimental findings on granule segregation during fluid bed drying into an existing compartmental model, enhancing its predictive capabilities. An additional model layer on granule segregation behavior is composed and integrated into the existing model structure in this study. The added model compartment describes probability distributions on the vertical position of granules within each granule size class considered. To beware of overfitting, predictions of both the moisture content after drying and the granule bed temperature throughout drying are discussed in this study relative to experimental data from earlier published studies. These independent analyses demonstrated a marked improvement in prediction accuracy compared to earlier published model structures. The refined model accurately predicts the residual moisture content after drying for an untrained formulation. Moreover, it simultaneously makes accurate predictions of the granular bed temperature, which emboldens its structural correctness. This advancement makes it a powerful tool for predicting the behavior of the pharmaceutical fluid bed drying, which holds significant promise to facilitate pharmaceutical product development.

Studying the API Distribution of Controlled Release Formulations Produced via Continuous Twin-Screw Wet Granulation: Influence of Matrix Former, Filler and Process Parameters.

Hydroxypropyl methylcellulose (HPMC) is a preferred hydrophilic matrix former for controlled release formulations produced through continuous twin-screw wet granulation. However, a non-homogeneous API distribution over sieve fractions with underdosing in the fines fraction (<150 µm) was previously reported. This could result in content uniformity issues during downstream processing. Therefore, the current study investigated the root cause of the non-homogeneous theophylline distribution. The effect of process parameters (L/S-ratio and screw configuration) and formulation parameters (matrix former and filler type) on content uniformity was studied. Next, the influence of the formulation parameters on tableting and dissolution behavior was investigated. Altering the L/S-ratio or using a more aggressive screw configuration did not result in a homogeneous API distribution over the granule sieve fractions. Using microcrystalline cellulose (MCC) as filler improved the API distribution due to its similar behavior as HPMC. As excluding HPMC or including a hydrophobic matrix former (Kollidon SR) yielded granules with a homogeneous API distribution, HPMC was identified as the root cause of the non-homogeneous API distribution. This was linked to its fast hydration and swelling (irrespective of the HPMC grade) upon addition of the granulation liquid.

An Evaluation of Wet Granulation Process Selection for API Prone to Polymorphic Form Conversion in the Presence of Moisture and Heat.

PURPOSE: Wet granulation (WG) is one of the most versatile processes to improve blend properties for processing. However, due to its need for moisture and heat, it is often considered not amenable to active pharmaceutical ingredients (APIs) prone to forming hydrates. Despite this claim, little literature exists evaluating the extent to which polymorphic form conversions occur for such API when processed with WG. This work sets out to explore two common WG methods, high-shear (HSG) and fluid-bed (FBG), and two drying processes, tray-drying (TD) and fluid-bed drying (FBD), and evaluate the risk they pose to hydrate form conversion. METHODS: The progression of anhydrous to hydrate form conversion of two model compounds with vastly different solubilities, fexofenadine hydrochloride and carbamazepine, was monitored throughout the various processes using powder X-ray diffraction. The resultant granules were characterized using thermogravimetric analysis, differential scanning calorimetry, BET adsorption, and sieve analysis. RESULTS: FBG and FBD processing resulted in the preservation of the original form of both APIs, while HSG+TD resulted in the complete conversion of the API. The FBD of fexofenadine and carbamazepine granules prepared with HSG resulted in partial and complete re-conversion back to the original anhydrous forms, respectively. CONCLUSION: The drying process is a critical factor in anhydrous form conservation. FBG and FBD yielded better preservation of the initial anhydrous forms. HSG could be an acceptable granulation method for API susceptible to hydrate formation if the API solubility is low. Selecting an FBG+FBD process minimizes API hydrate formation and preserves the original anhydrous form.

Comparison of Properties of Acetaminophen Tablets Prepared by Wet Granulation Using Freeze-Dried Versus Phase-Inversion Bacterial Cellulose as Diluent.

Bacterial cellulose (BC) is an interesting material for drug delivery applications due to its high purity. This study aimed to compare the properties of tablets prepared by the wet granulation method using bacterial cellulose prepared by different methods as a diluent, using acetaminophen as a model drug. BC used as diluents were prepared using two different methods: freeze-drying (BC-FD) and phase-inversion (BC-PI), and their characteristics were analyzed and compared with that of commercial microcrystalline cellulose PH 101 (Comprecel® M101). Acetaminophen tablets were prepared by wet granulation using BC-FD, BC-PI, or Comprecel® M101 as diluents, and their tablet properties were examined. The result showed that the morphology, polymorph, and crystallinity of BC-PI and Comprecel® M101 were similar but they were different compared with that of BC-FD. Tablets could be successfully formed using BC-PI and Comprecel® M101 as diluents without any physical defects but the tablet prepared using BC-FD as diluent appeared chipped edge. The characteristics (thickness, weight variation, hardness, friability, disintegration, drug content, and dissolution) of the tablets prepared using BC-PI diluent were also similar to those prepared using Comprecel® M101 diluent, but those of BC-FD diluent were inferior. This indicates that BC prepared in BC-PI can potentially be used as a diluent for tablets prepared by wet granulation.

Characterizing a design space for a twin-screw wet granulation process: A case study of extended-release tablets.

Twin-screw wet granulation is an emerging continuous manufacturing technology for solid oral dosage forms. This technology has been successfully employed for the commercial manufacture of immediate-released tablets. However, the higher polymer content in extended-release (ER) formulations may present challenges in developing and operating within a desired design space. The work described here used a systematic approach for defining the optimum design space by understanding the effects of the screw design, operating parameters, and their interactions on the critical characteristics of granules and ER tablets. The impacts of screw speed, powder feeding rate, and the number of kneading (KEs) and sizing elements on granules and tablets characteristics were investigated by employing a definitive screening design. A semi-mechanistic model was used to calculate the residence time distribution parameters and validated using the tracers. The results showed that an increase in screw speed decreased the mean residence time of the material within the barrel, while an increase in the powder feeding rate or number of KEs did the opposite and increased the barrel residence time. Screw design and operating parameters affected the flow and bulk characteristics of granules. The screw speed was the most significant factor impacting the tablet's breaking strength. The dissolution profiles revealed that granule characteristics mainly influenced the early phase of drug release. This study demonstrated that a simultaneous optimization of both operating and screw design parameters was beneficial in producing ER granules and tablets of desired performance characteristics while mitigating any failure risks, such as swelling during processing.

Evaluation of the Mechanical and Tribological Behavior of Polyether Ether Ketone Fiber-Reinforced Resin-Based Friction Materials Fabricated by Wet Granulation.

Resin-based friction materials (RBFMs) strengthened by polyether ether ketone (PEEK) fiber were designed and prepared in this study. Specimens incorporating PEEK fiber of 2-8 wt.% were fabricated based on wet granulation, and then the effects of the PEEK fiber content on the mechanical and tribological properties of RBFMs were systematically investigated. The results showed that PEEK fiber can sense the braking temperature and then effectively regulate the comprehensive properties of RBFMs. The specimen incorporating 6 wt.% PEEK fiber obtained the optimal comprehensive performance with a stable friction coefficient (COF), excellent fade resistance and recovery properties, and better wear resistance. The worn surface was inspected using a scanning electron microscope. After the friction-wear test, the specimen with 6 wt.% PEEK fiber presented a number of primary and secondary plateaus and a reduced number of pits with wear debris on the worn surface. The study indicated that PEEK fiber could not only enhance the mechanical and tribological properties of RBFMs at low temperatures because of their high strength and self-lubrication but also adhere to wear debris to reduce abrasive wear at high temperatures; furthermore, the adhered wear debris could form a secondary plateau under normal pressure, which could alleviate abrasion.

Methods for Developing a Process Design Space Using Retrospective Data.

Prospectively planned designs of experiments (DoEs) offer a valuable approach to preventing collinearity issues that can result in statistical confusion, leading to misinterpretation and reducing the predictability of statistical models. However, it is also possible to develop models using historical data, provided that certain guidelines are followed to enhance and ensure proper statistical modeling. This article presents a methodology for constructing a design space using process data, while avoiding the common pitfalls associated with retrospective data analysis. For this study, data from a real wet granulation process were collected to pragmatically illustrate all the concepts and methods developed in this article.

T-shaped partial least squares for high-dosed new active pharmaceutical ingredients in continuous twin-screw wet granulation: Granule size prediction with limited material information.

This work presents a granule size prediction approach applicable to diverse formulations containing new active pharmaceutical ingredients (APIs) in continuous twin-screw wet granulation. The approach consists of a surrogate selection method to identify similar materials with new APIs and a T-shaped partial least squares (T-PLS) model for granule size prediction across varying formulations and process conditions. We devised a surrogate material selection method, employing a combination of linear pre-processing and nonlinear classification algorithms, which effectively identified suitable surrogates for new materials. Using only material properties obtained through four characterization methods, our approach demonstrated its predictive prowess. The selected surrogate methods were seamlessly integrated with our developed T-PLS model, which was meticulously validated for high-dose formulations involving three new APIs. When surrogating new APIs based on Gaussian process classification, we achieved the lowest prediction errors, signifying the method's robustness. The predicted d-values were within the range of uncertainty bounds for all cases, except for d90 of API C. Notably, the approach offers a direct and efficient solution for early-phase formulation and process development, considerably reducing the need for extensive experimental work. By relying on just four material characterization methods, it streamlines the research process while maintaining a high degree of accuracy.

Scale-up in twin-screw wet granulation: impact of formulation properties.

The focus of this study was to investigate the sensitivity of different drug formulations to differences in process parameters based on previously developed scale-up strategies. Three different formulations were used for scale-up experiments from a QbCon® 1 with a screw diameter of 16 mm and a throughput of 2 kg/h to a QbCon® 25 line with a screw diameter of 25 mm and a throughput of 25 kg/h. Two of those formulations were similar in their composition of excipients but had a different API added to the blend to investigate the effect of solubility of the API during twin-screw wet granulation, while the third formulation was based on a controlled release formulation with different excipients and a high fraction of HPMC. The L/S-ratio had to be set specifically for each formulation as depending on the binder and the overall composition the blends varied significantly in their response to water addition and their overall granulation behavior. Before milling there were large differences in granule size distributions based on scale (Earth Mover's Distance 140-1100 µm, higher values indicating low similarity) for all formulations. However, no major differences in granule properties (e.g. Earth Mover's Distance for GSDs: 23-88 µm) or tablet tensile strength (> 1.8 MPa at a compaction pressure of 200 MPa for all formulations with a coefficient of variation < 0.1, indicating high robustness for all formulations) were observed after milling, which allowed for a successful scale-up independent of the selected formulations.

Validation of model-based design of experiments for continuous wet granulation and drying.

This paper presents an application case of model-based design of experiments for the continuous twin-screw wet granulation and fluid-bed drying sequence. The proposed framework consists of three previously developed models. Here, we are testing the applicability of previously published unit operation models in this specific part of the production line to a new active pharmaceutical ingredient. Firstly, a T-shaped partial least squares regression model predicts d-values of granules after wet granulation with different process settings. Then, a high-resolution full granule size distribution is computed by a hybrid population balance and partial least squares regression model. Lastly, a mechanistic model of fluid-bed drying simulates drying time and energy efficiency, using the outputs of the first two models as a part of the inputs. In the application case, good operating conditions were calculated based on material and formulation properties as well as the developed process models. The framework was validated by comparing the simulation results with three experimental results. Overall, the proposed framework enables a process designer to find appropriate process settings with a less experimental workload. The framework combined with process knowledge reduced 73.2% of material consumption and 72.3% of time, especially in the early process development phase.

Drying capacity of a continuous vibrated fluid bed dryer - Statistical and mechanistic model development.

The drying capacity of a continuous vibrated fluid bed dryer was studied using a DoE by varying microcrystalline cellulose content in the formulation, water amount in the twin-screw granulation, inlet air temperature, air flow rate and the acceleration of the horizontal fluid-bed. Temperature and humidity profiles were measured along the dryer using wireless sensors. For the parameter space explored in this study, acceleration was the most influential process parameter of the dryer regarding the resulting granule moisture content. An empirical model was developed that allowed for fast and accurate moisture content prediction that could be incorporated into an enhanced control strategy. In addition, a mechanistic model was formulated that allow for prediction of temperature and moisture profiles, and most importantly the moisture content of the granules inside the dryer. The mechanistic model can be integrated to other unit operation models to provide overall understanding of an integrated continuous process line. The mechanistic model also makes it possible to define the equipment design requirements (e.g., length of the dryer) to meet the specific needs in terms of drying capacity, temperature and moisture profile.

Effects of wet granulation process variables on the quantitative assay model of transmission Raman spectroscopy for pharmaceutical tablets.

Transmission Raman spectroscopy (TRS) is a process analytical technology tool for nondestructive analysis of drug content in tablets. Although wet granulation is the most used tablet manufacturing method, most TRS studies have focused on tablets manufactured via direct compression. The effects of upstream process parameter variations, such as granulation, on the prediction performance of TRS quantitative models are unknown. We evaluated the effects of process parameter variations during granulation on the prediction performance of the TRS quantitative model. Tablets with a drug concentration of 1%w/w were used. We developed PLS calibration models for the drug concentration range of 70-130% label claims. Subsequently, we predicted the drug content of the tablets with different granulation parameters. The results of our study demonstrate that the variation in the predicted recovery due to the variation in granulation parameters was practically acceptable. The calibration model showed a good prediction performance for tablets manufactured at different granulation scales and thicknesses. Therefore, we conclude that TRS quantitative models are robust to variations in upstream processes, such as granulation and downstream variations in tableting parameters. These results suggest that TRS is a versatile non-destructive quantitative analysis method that can be applied in tablet manufacturing.

Mechanistic modeling of semicontinuous fluidized bed drying of pharmaceutical granules by incorporating single particle and bulk drying kinetics.

In this work, a mechanistic fluidized bed drying model computing the granule moisture content in function of granule size, drying time, process settings and formulation properties is developed. Modeling the moisture content distribution concerning the granule size is essential for tabletability and drug product quality. This work combines a mechanistic bulk model and a single-particle drying kinetics model in a semicontinuous mode. The added model complexity allows physical approximations of drying phenomena at both the drying system level and the granular level. This includes quantifying the variations in moisture content by taking into account the specific dryer design and the variations in granule size. The model performance was quantified through industrially relevant case studies. It was revealed that the proposed model structure accurately predicts the drying behavior of the yield fraction. However, systematic model biases were observed for the fine and coarse fractions of the granule size distribution. In addition, discrepancies in the predicted outgoing air properties (relative air humidity and air temperature) were obtained. Further enhancement of the model complexity, e.g. complete incorporation of fluidization and segregation phenomena, is likely to improve the model performance. Notwithstanding, the developed model forms a step towards a formulation-generic fluidized bed drying model as interacting mechanisms on different levels of the drying system are considered.

Integrated Continuous Wet Granulation and Drying: Process Evaluation and Comparison with Batch Processing.

The pharmaceutical industry is in the midst of a transition from traditional batch processes to continuous manufacturing. However, the challenges in making this transition vary depending on the selected manufacturing process. Compared with other oral solid dosage processes, wet granulation has been challenging to move towards continuous processing since traditional equipment has been predominantly strictly batch, instead of readily adapted to material flow such as dry granulation or tablet compression, and there have been few equipment options for continuous granule drying. Recently, pilot and commercial scale equipment combining a twin-screw wet granulator and a novel horizontal vibratory fluid-bed dryer have been developed. This study describes the process space of that equipment and compares the granules produced with batch high-shear and fluid-bed wet granulation processes. The results of this evaluation demonstrate that the equipment works across a range of formulations, effectively granulates and dries, and produces granules of similar or improved quality to batch wet granulation and drying.

A Machine Learning Approach to Qualitatively Evaluate Different Granulation Phases by Acoustic Emissions.

Wet granulation is a frequent process in the pharmaceutical industry. As a starting point for numerous dosage forms, the quality of the granulation not only affects subsequent production steps but also impacts the quality of the final product. It is thus crucial and economical to monitor this operation thoroughly. Here, we report on identifying different phases of a granulation process using a machine learning approach. The phases reflect the water content which, in turn, influences the processability and quality of the granule mass. We used two kinds of microphones and an acceleration sensor to capture acoustic emissions and vibrations. We trained convolutional neural networks (CNNs) to classify the different phases using transformed sound recordings as the input. We achieved a classification accuracy of up to 90% using vibrational data and an accuracy of up to 97% using the audible microphone data. Our results indicate the suitability of using audible sound and machine learning to monitor pharmaceutical processes. Moreover, since recording acoustic emissions is contactless, it readily complies with legal regulations and presents Good Manufacturing Practices.

Wet granulation of co-amorphous indomethacin systems.

The feasibility of co-amorphous systems to be wet granulated together with microcrystalline cellulose (MCC) was investigated. Solid state and molecular interactions were analysed for various co-amorphous drug-amino acid formulations of indomethacin with tryptophan and arginine, respectively, via XRPD, DSC and FTIR. The co-amorphous binary systems were produced by ball-milling for 90 min at different molar ratios followed by wet granulation with MCC and water in a miniaturised scale. Tryptophan containing systems showed crystalline reflections in their XRPD diffractograms and endothermal events in their DSC analyses, and were therefore excluded from upscaling attempts. The systems containing arginine were found to be remain amorphous for at least ten months and were upscaled for production in a high-shear blender under application of two different parameter settings. Under the harsher instrument settings, a composition with a low MCC ratio experienced recrystallisation during wet granulation, while all other compositions could be successfully processed via wet granulation and stayed stable for a storage period of at least twelve weeks, indicating that wet granulation of co-amorphous systems can be feasible.

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.

Application of I-Optimal Design for Modeling and Optimizing the Operational Parameters of Ibuprofen Granules in Continuous Twin-Screw Wet Granulation.

The continuous twin-screw wet granulation (TSWG) process was investigated and optimized with prediction-oriented I-optimal designs. The I-optimal designs can not only obtain a precise estimation of the parameters that describe the effect of five input process parameters, including the screw speed, liquid-to-solid (L/S) ratio, TSWG feed rate, and numbers of the 30° and 60° mixing elements, on the granule quality in a TSWG process, but it can also provide a prediction of the response to determine the optimum operating conditions. Based on the constraints of the desired granule properties, a design space for the TSWG was determined, and the ranges of the operating parameters were defined. An acceptable degree of prediction was confirmed through validation experiments, demonstrating the reliability and effectiveness of using the I-optimal design method to study the TSWG process. The I-optimal design method can accelerate the screening and optimization of the TSWG process.