Twin Screw Wet Granulation Research Articles

Population balance modelling and reconstruction by quadrature method of moments for wet granulation

Population balance methods utilised in multiphase flow simulations mark a significant advancement in computational fluid dynamics. However, existing approaches exhibit shortcomings, such as being prone to inaccuracies or being computationally prohibitive. Addressing these challenges, a recent innovation in closure for the method of moments is the introduction of quadrature based moments methods (QBMM). Discretising a distribution by a number of discrete elements, QBMM facilitate efficient and accurate tracking of density distributions, particularly for particle size distributions (PSD). However, obtaining the full particle size distribution information using these methods requires reconstructing the distribution from a finite set of moments, which is not a trivial step.This study introduces a novel combination of the maximum entropy reconstruction (MER) and QBMM, establishing a robust and rapid framework for the time evolution and reconstruction of PSDs. As proof of concept for this framework, we focus on the direct quadrature method of moments (DQMOM) with spatially homogeneous and monovariate distributions. We show that coupling of MER with DQMOM has numerous advantages. To verify the framework, special cases of constant growth, aggregation, and breakage are considered for which analytical solutions can be found. Furthermore, we show the advantage of using DQMOM with volume-based over length-based distributions, and address numerical as well as theoretical issues.Application of the framework is successfully conducted on the evolution of the PSD from a twin-screw wet granulation dataset, considering all active primary physical mechanisms in a wet granulation process, namely growth, aggregation, and breakage. This showcases the consistency of the proposed framework and underscores its applicability to real-world scenarios.

In-line indirect concentration measurement of ultralow dose API during twin-screw wet granulation based on NIR and Raman spectroscopy

Twin-screw wet granulation (TWSG) is a promising continuous alternative of pharmaceutical wet granulation. One of its benefits is that the components dissolved in the granulation liquid are distributed homogeneously in the granules. This provides an elegant way to manufacture products with ultralow drug doses. Near-infrared (NIR) and Raman spectroscopy are well-established process analytical technology (PAT) tools that can be used for the in-line monitoring of TSWG. However, their detection limit does not enable the measurement of components in the ultralow (i.e., ppm) range. In this paper, an indirect approach is presented that enables the real-time determination of the concentration of a drug in concentrations between 40 and 100 ppm by using the signal of an excipient, in this case, the polyvinylpyrrolidone (PVP). This component is also dissolved in the granulation liquid; therefore, it is distributed in the same way as the active ingredient. Results of HPLC measurements have proved that the models trained to quantify the concentration of PVP in real-time gave an accurate determination for the active ingredient as well (root mean squared error was 7.07 ppm for Raman and 5.31 ppm for NIR spectroscopy, respectively). These findings imply that it is possible to indirectly predict the concentration of ultralow dose drugs with in-line analytical techniques based on the concentration of an excipient.

Towards the prediction of barrel fill level in twin-screw wet granulation

The barrel fill level is defined as the fraction of the free available volume for a given screw configuration that is occupied by the wet material and is an interplay of the material throughput, screw speed, screw setup, barrel length of the twin-screw granulator used and the properties of the starting material. The fill level has a major impact on mixing and densification of the wetted mass and thus on the granules produced. It influences the twin-screw granulation process accordingly.In the current study, a model has been developed which is predictive in terms of material hold-ups in the barrel at various process settings by considering the geometries of the different screw elements in a configuration and the conveying velocity of the wet mass through the barrel. The model was checked on two granulators of different dimensions with various screw configurations, different materials and at different process settings.The model represents a step forward in predicting the barrel fill level but further research with a broader spectrum of materials, screw configurations and process settings is still needed and additional twin-screw granulators of other dimensions must be investigated.

Evaluation of Polyvinyl Alcohol as Binder during Continuous Twin Screw Wet Granulation.

Binder selection is a crucial step in continuous twin-screw wet granulation (TSWG), as the material experiences a much shorter residence time (2-40 s) in the granulator barrel compared to batch-wise granulation processes. Polyvinyl alcohol (PVA) 4-88 was identified as an effective binder during TSWG, but the potential of other PVA grades-differing in polymerization and hydrolysis degree-has not yet been studied. Therefore, the aim of the current study was to evaluate the potential of different PVA grades as a binder during TSWG. The breakage and drying behavior during the fluidized bed drying of drug-loaded granules containing the PVA grades was also studied. Three PVA grades (4-88, 18-88, and 40-88) were characterized and their attributes were compared to previously investigated binders by Vandevivere et al. through principal component analysis. Three binder clusters could be distinguished according to their attributes, whereby each cluster contained a PVA grade and a previously investigated binder. PVA 4-88 was the most effective binder of the PVA grades for both a good water-soluble and water-insoluble formulation. This could be attributed to its high total surface energy, low viscosity, good wettability of hydrophilic and hydrophobic surfaces, and good wettability by water of the binder. Compared to the previously investigated binders, all PVA grades were more effective in the water-insoluble formulation, as they yielded strong granules (friability below 30%) at lower L/S-ratios. This was linked to the high dispersive surface energy of the high-energy sites on the surface of PVA grades and their low surface tension. During fluidized bed drying, PVA grades proved suitable binders, as the acetaminophen (APAP) granules were dried within a short time due to the low L/S-ratio, at which high-quality granules could be produced. In addition, no attrition occurred, and strong tablets were obtained. Based on this study, PVA could be the preferred binder during twin screw granulation due to its high binder effectiveness at a low L/S-ratio, allowing efficient downstream processing. However, process robustness must be controlled by the included excipients, as PVA grades are operating in a narrow L/S-ratio range.

Evaluation of binders in twin-screw wet granulation – Optimization of tabletability

The influence of hydroxypropyl cellulose type (HPC-SSL SFP, HPC-SSL), concentration (2 %, 3.5 %, 5 %) and filler (lactose, calcium hydrogen phosphate (DCP)/microcrystalline cellulose (MCC)) on twin-screw wet granulation and subsequent tableting was studied. The aim was to identify the formulation of the highest tabletability which still fulfills the requirements of the disintegration. Lactose combined with 5 % binder enabled a higher tabletability and a faster disintegration than DCP/MCC. It was found that tabletability of lactose formulations can be increased by higher binder concentration and higher compression pressure while tabletability of DCP/MCC formulations can be only increased by higher compression pressure. It was observed that batches containing DCP/MCC failed the disintegration test, if the highest binder concentration and the highest compression pressure were used. To ensure a fast disintegration, the compression pressure or at least the binder concentration had to be low. Changing the disintegrant and its localization improved the DCP/MCC formulation, resulting in faster disintegration than lactose tablets. However, it also resulted in a lower tabletability. In this study best tablets were achieved with 3.5 % or 5 % binder and lactose as filler. These tablets presented the highest tabletability but still disintegrated in less than 500 s.

Mechanistic modeling of twin screw wet granulation for pharmaceutical formulations: Calibration, sensitivity analysis, and model-driven workflow

Wet granulation, a particle size enlargement process, can significantly enhance the critical quality attributes of powders and improve the ability to form tablets in pharmaceutical manufacturing. In this study, a mechanistic-based population balance model is applied to twin screw wet granulation. This model incorporated a recently developed breakage kernel specifically designed for twin screw granulation, along with nucleation, layering, and consolidation. Calibration and validation were performed on Hydrochlorothiazide and Acetaminophen formulations, which exhibit different particle size and wettability characteristics. Utilizing a compartmental experimental dataset, a comprehensive global sensitivity analysis identified critical inputs impacting quality attributes. The study revealed that the nucleation rate process model, effectively represented particle size distributions for both formulations. Adjustments to nucleation and breakage rate parameters, influenced by material properties and screw configuration, improved the model’s accuracy. A model-driven workflow was proposed, offering step-by-step guidelines and facilitating PBM model usage, providing essential details for future active pharmaceutical ingredient (API) formulations.

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.

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 relies on 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.

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.

A novel combination of machine learning models and metaheuristic algorithm to predict important parameters of twin screw wet granulation process

Twin screw granulation (TSG) has recently been emerged as a novel approach for the continuous wet granulation of fine particles (i.e., powders) in the pharmaceutical industry. The presence of brilliant advantages like the ability of operation at very low liquid concentrations and excellent product consistency has made this technique promising. Except positive points, the existence of major challenges like scalability and flexibility in the processing regimes has enhanced the importance of deeper investigations towards true recognition of this process. The central aim of this theoretical article is to develop the modeling process of TSG employing four machine learning models and one metaheuristic algorithms in a hybrid approach. Screw speeds, material throughputs, liquid binder (water)-to-solid ratios, and screw configurations are known as important parameters of TSG process, which were validated via their comparison with the obtained experimental data. GBR, SGD, and SVR were finally selected for 3 targets with their best combinations of hyper-parameters employing FA. The output is based on d-values (d10, d50, d90) for the granulate particle size distribution (PSD). Final models have R2 scores of 0.919, 0.960, and 0.877 for d10, d50, d90 outputs, respectively.

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.

Assessing Abuse-Deterrent formulations utilizing Ion-Exchange resin complexation processed via Twin-Screw granulation for improved safety and effectiveness

Opioid misuse is a public health crisis in the United States. In response, the FDA has approved drug products with abuse-deterrent features to reduce the risk of prescription opioid abuse. Abuse-deterrent formulations (ADFs) typically employ physical or chemical barriers or incorporate agonist–antagonist combinations as mechanisms to deter misuse. This study aims to assess the impact of abuse-deterrent properties, specifically ion-exchange resin complexation as a chemical barrier, on a model drug, promethazine hydrochloride (PMZ) tablets. Various formulations were developed through twin-screw wet granulation (TSWG) followed by twin-screw melt granulation (TSMG). In the TSWG process, the drug interacts with the resin through an exchange reaction, forming a drug-resin complex. Additionally, the study explored factors influencing the complex formation between the drug and resin, using the drug loading status as an indicator. DSC and ATR studies were carried out to confirm the formation of the drug-resin complex. Subsequently, hot melt granulation was employed to create a matrix tablet incorporating Kollidon® SR and Kollicoat® MAE 100P, thereby enabling sustained release properties. The drug-resin complex embedded in the matrix effectively deters abuse through methods like smoking, snorting, or parenteral injection, unless the drug can be extracted. In order to assess this, solvent extraction studies were conducted using an FDA-recommended solvents, determining the potential for abuse. Further investigations involved dissolution tests in change-over media, confirming the extended-release properties of the formulation. Results from dissolution studies comparing the ground and intact tablets provided positive evidence of the formulation's effectiveness in deterring abuse. Finally, alcohol-induced dose-dumping studies were conducted in compliance with FDA guidelines, concluding that the formulation successfully mitigates dose dumping in the presence of alcohol.

A Colourful Way to Unravel the Important Fluidization-Related Granule Size Effect on Semi-Continuous Drying.

Continuous twin screw wet granulation (TSWG) systems are possible pathways for oral solid dosage manufacturing in the pharmaceutical industry. TSWG requires a drying step after granulation before the tableting process. Typically, semi-continuous fluidized bed dryers (FBDs) are used for this purpose. At the same time, the pharmaceutical sector is interested in mathematical prediction models to save resources during the early drug product development (DPD) stage or to control manufacturing. Several authors have already developed prediction models for semi-continuous drying processes. However, these model structures reported systematic prediction offsets, which could be related to the incomplete implementation of fluidization and granule segregation phenomena. This study evaluates the complex fluidization behavior of wet granules in industrially relevant semi-continuous FBDs. A transparent perspex version of the dryer was used for the analysis of bed height, pressure drop, porosity, segregation, and spatial heating patterns at varying process settings. The investigated behaviors of the fluidizing bed will be helpful to derive phenomenological (sub)models for the detailed description of segregation in the semi-continuous fluidized bed system. In this study, it was found that semi-continuous FBDs are characterized by a change in fluidization regime from plug flow to a bubbling bed at the moment that the granule bed slumps. Secondly, the presence of size-based vertical segregation phenomena as well as spatial temperature differences were proven. The experimental results suggest that larger granules are dried under more intense drying conditions than smaller granules.

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.

Analysis of the effect of formulation properties and process parameters on granule formation in twin-screw wet granulation

In the last few years, twin-screw wet granulation (TSWG) has become one of the key continuous pharmaceutical unit operations. Despite the many studies that have been performed, only little is known about the effect of the starting material properties on the stepwise granule formation along the length of the twin-screw granulator (TSG) barrel. Hence, this study obtained a detailed understanding of the effect of formulation properties (i.e., Active Pharmaceutical Ingredient (API) properties, formulation blend particle size distribution and formulation drug load) and process settings on granule formation in TSWG. An experimental set-up was used allowing the collection of granules at the different TSG compartments. Granules were characterized in terms of granule size, shape, binder liquid and API distributions. Liquid-to-solid (L/S) ratio was the only TSG process parameter impacting the granule size and shape evolution. Particle size and flow properties (e.g., flow rate index) had an important effect on the granule size and shape changes whereas water-related properties (e.g., water binding capacity and solubility) became influential at the last TSG compartments. The API solubility and L/S ratio were found to have a major impact on the distribution of binder liquid over the different granule size fractions. In the first TSG compartment (i.e., wetting compartment), the distribution of the API in the granules was influenced by its solubility in the granulation liquid.

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.

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.

Exploring the effect of raw material properties on continuous twin-screw wet granulation manufacturability

Twin-screw wet granulation (TSWG) stands out as a promising continuous alternative to conventional batch fluid bed- and high shear wet granulation techniques. Despite its potential, the impact of raw material properties on TSWG processability remains inadequately explored. Furthermore, the absence of supportive models for TSWG process development with new active pharmaceutical ingredients (APIs) adds to the challenge. This study tackles these gaps by introducing four partial least squares (PLS) models that approximate both the applicable liquid-to-solid (L/S) ratio range and resulting granule attributes (i.e., granule size and friability) based on initial material properties. The first two PLS models link the lowest and highest applicable L/S ratio for TSWG, respectively, with the formulation blend properties. The third and fourth PLS models predict the granule size and friability, respectively, from the starting API properties and applied L/S ratio for twin-screw wet granulation. By analysing the developed PLS models, water-related material properties (e.g., solubility, wettability, dissolution rate), as well as density and flow-related properties (e.g., flow function coefficient), were found to be impacting the TSWG processability. In addition, the applicability of the developed PLS models was evaluated by using them to propose suitable L/S ratio ranges (i.e., resulting in granules with the desired properties) for three new APIs and related formulations followed by an experimental validation thereof. Overall, this study helped to better understand the effect of raw material properties upon TSWG processability. Moreover, the developed PLS models can be used to propose suitable TSWG process settings for new APIs and hence reduce the experimental effort during process development.

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.