Manufacturing Of Solid Dosage Forms Research Articles

Autoencoder-based inverse design and surrogate-based optimization of an integrated wet granulation manufacturing process

In pharmaceutical manufacturing, integrating model-based design and optimization can be beneficial for accelerating process development. This study explores the utilization of Machine Learning (ML) techniques as a surrogate model for the optimization of a three-unit wet-granulation based flowsheet model for solid dosage form manufacturing. First, a reduced representation of a wet granulation flowsheet model is developed, incorporating a granulation and milling process, along with a novel dissolution model that accounts for the effect of particle size, porosity, and microstructure on dissolution rate. Two optimization approaches are compared, including an autoencoder-based inverse design and a surrogate-based forward optimization. Both methods address the bi-objective problem of maximizing dissolution time and product yield by identifying the optimal granulation and mill process parameters. For this case study, both approaches were effective and incurred a similar computational cost, averaging under 4 s. However, the autoencoder approach offers an advantage through dimensionality reduction, a feature not available in surrogate-based optimization. Dimensional reduction is particularly beneficial for complex process designs with numerous inputs and outputs. The lower dimensional representation helps improve process understanding through enhanced visualization of the process design space and facilitates feasibility studies involving multiple constraints. The autoencoder-based inverse design introduced in this work showcases an implementation of AI and ML in pharmaceutical process development, demonstrating the potential to enhance process efficiency and product quality in complex manufacturing scenarios.

Solidifying Fenofibrate Nanocrystal Suspension: A Scalable Approach via Granulation Method

The pharmaceutical industry has highlighted particle-size reduction via preparing aqueous suspensions containing nano- or submicron drug particles. Owing to the risk of agglomeration and complications during the manufacturing of solid dosage forms, the problems associated with the solidification of nanosuspensions need to be addressed. Herein, the nanocrystallized suspension of fenofibrate (Feno) was prepared using the wet-milling technique, and then two solidification methods, mixing (liquid mixing) and granulation (dry powder blending and wet massing) methods, were investigated. The solidification process involved the adsorption of Feno as a very thin layer on the high-surface-area Florite® to prevent drug accumulation. The critical quality attributes, particle size and dissolution rate, were performed. Infrared spectroscopy, X-ray diffraction, differential scanning calorimetry, and scanning electron microscopy were also used to monitor the existence and physical state of drug molecules in the carrier. The final solidified powders and tablets containing Feno nanocrystals improved the dissolution profile (>90% in 15 min), in which the physical properties of Feno were maintained during solidification and tableting. In general, the granulation method is more advantageous than the mixing method in terms of maintaining amorphous proportion and dissolution rate. These results implied a potential approach for manufacturing solid dosage forms from nanoscale products.

Flow behavior under shear cell analysis of two HMPC grades

A comparative analysis was conducted to examine the flow characteristics of two HPMC grades and their fractions. Excipients processing contains critical steps in the manufacturing of solid dosage forms and therefore it is essential to determine their flowability. Flow characterization was done using conventional and shear cell methods. After the division into different particles size, HPMC2910 showed an increase of the ffc for the fractions with the largest particle size and HPMC2208 showed an unprecedented result for the fraction with the smallest size. Thus, for this excipient, the best ffc was obtained with the fraction containing the smallest particles which surprisingly contradicted the literature (shape effect overlapped the size effect). It was also found for different fractions that the ffc increased with the increasing of the σ1, showing in some of them a decrease of the same from a certain σ1 value. Furthermore, caking was not observed in both cases.

Continuous Manufacturing of Cocrystals Using 3D-Printed Microfluidic Chips Coupled with Spray Coating.

Using cocrystals has emerged as a promising strategy to improve the physicochemical properties of active pharmaceutical ingredients (APIs) by forming a new crystalline phase from two or more components. Particle size and morphology control are key quality attributes for cocrystal medicinal products. The needle-shaped morphology is often considered high-risk and complex in the manufacture of solid dosage forms. Cocrystal particle engineering requires advanced methodologies to ensure high-purity cocrystals with improved solubility and bioavailability and with optimal crystal habit for industrial manufacturing. In this study, 3D-printed microfluidic chips were used to control the cocrystal habit and polymorphism of the sulfadimidine (SDM): 4-aminosalicylic acid (4ASA) cocrystal. The addition of PVP in the aqueous phase during mixing resulted in a high-purity cocrystal (with no traces of the individual components), while it also inhibited the growth of needle-shaped crystals. When mixtures were prepared at the macroscale, PVP was not able to control the crystal habit and impurities of individual mixture components remained, indicating that the microfluidic device allowed for a more homogenous and rapid mixing process controlled by the flow rate and the high surface-to-volume ratios of the microchannels. Continuous manufacturing of SDM:4ASA cocrystals coated on beads was successfully implemented when the microfluidic chip was connected in line to a fluidized bed, allowing cocrystal formulation generation by mixing, coating, and drying in a single step.

Linking material properties to 1D-PBM parameters towards a generic model for twin-screw wet granulation

Population balance models (PBM) have been widely used to model the twin-screw wet granulation (TSWG) in the continuous manufacturing of solid dosage forms. However, some knowledge gaps, such as material properties and process parameters, remain, which hampers the applicability of new drug developments. This work presents a hybrid model of a compartmental one-dimensional PBM and partial least squares (PLS) towards a generic model. The PBM that considers aggregation and breakage was calibrated with experimental data of ten different formulations with different liquid-to-solid ratios. The PLS models were built to predict the PBM parameters based on the material properties and liquid-to-solid ratio. The proposed model was validated by testing it with four formulations containing new active pharmaceutical ingredients (APIs) using maximum mean discrepancy. The model captured the peak of each granule size distribution for all formulations. This approach has the advantage that the hybrid model of the PBM and PLS can compute the resulting granule size distribution without granulation experiments. This work enhanced the applicability of PBM, which can reduce experimental efforts in new drug development.

Over-blending effect of lubricants on capsules manufacturing: a simple and fast wettability technique to predict batch dissolution performance

Mixing/blending is a crucial operation in the manufacturing of solid drug products in the pharmaceutical industry. Although usually described and controlled in specific steps, blending is also inherent to other operations such as the transference of materials and equipment feeding systems. This study aimed to investigate a simple and fast wettability testing procedure capable to foresee the potential over-blending effects of lubricants occurring during the manufacturing of solid dosage forms. An industrial batch blend was submitted to two mixing mechanisms studies (diffusion and shear) during increasing time periods, and the developed wettability testing procedure was applied to assess their impact on blend water uptake. Capsules filled with these blends were tested for dissolution and disintegration. The method was applied to capsules with known dissolution results manufactured at an industrial scale. Results demonstrated that processes inducing shear stress led to less permeable blends with consequent retardation on capsules dissolution of at least 35% in the tested timepoints and obtained study metrics above 500 s. Moreover, disintegration testing was not able to detect non-compliant dissolutions, while the proposed wettability testing procedure proved to be able to identify performance failures. Wettability results correlate the effect of mixing mechanisms to capsules dissolution performance, evidencing that this technique can be applied in the pharmaceutical industry to evaluate possible over-blending effects.

Challenges and opportunities in modelling wet granulation in pharmaceutical industry – A critical review

Wet granulation is a key step in the pharmaceutical manufacturing of solid-dosage forms. Wet granulation is used in pharmaceutical production to enhance formulation qualities such as flowability, compressibility, etc. Different methods are used for wet granulation, including fluidised bed, twin-screw extrusion, and high-shear method, leading to different mechanisms and granule properties. Modelling wet granulation is of great importance for the pharmaceutical industry, which is aspiring to shift from batch mode to a continuous one. Moreover, model-based understanding is critical for implementing the Quality-by-Design (QbD) approach in the pharmaceutical industry. The current critical review represents an overview of current approaches in modelling wet granulation. Three major models, including the population balance model (PBM), discrete element method (DEM), and data-driven models, are evaluated, and the advantages of each approach are outlined. The PBM is the primary approach for modelling granulation in which granule properties are tracked in the process. On the other hand, DEM provides a better understanding of granulation at the particle level. Recent DEM modelling studies have significantly advanced the knowledge for design and scale-up of DEM models, such as capturing the suitable wetting physics and particle scaling and thus mitigating the traditionally known challenges in the application of DEM for wet granulation processes. However, further research is required to include particle level effects, like breakage, attrition, into the DEM model through either built-in approaches or hybrid approaches. Data-driven models are fast and accurate but do not investigate the mechanisms involved in granulation. Data-driven models based on neural networks have been indicated to be adopted for application in continuous granulation with great accuracy compared to other approaches, which can also be implemented for process control. A great joint prospect for first-principles and data-driven modelling approaches is anticipated, which can play an important role in future process design, optimisation, and control of pharmaceutical wet granulation processes.

Investigating the flow behaviour of pharmaceutical blends using shear cell methodology

Powder flow properties are critical bulk level features for the manufacturing of solid dosage forms. Small-scale powder flow measurements are also widely accepted as a tool for predicting large-scale production failure. The aim of this study is to explore the flow properties of a two-component powder mixture and investigate the effect of mixing two powders with different properties on the flow properties parameters. To achieve this aim, 12 blends were prepared using an acoustic mixer (Labram). The flow properties were studied using rotational shear cell methodology. The results showed that the addition of Micr APAP into the excipients with good flow properties significantly increased the flow resistance of the prepared blends and consequently reduced their flow properties. The main driving factor in determining the flow properties is the particle size of the blend’s components. The results of this study suggest that it is very important to measure the flow properties of any pharmaceutical blends and not depend only on the flow properties of the original components before mixing.

Direct Granule Feeding of Thermal Droplet Deposition 3D Printing of Porous Pharmaceutical Solid Dosage Forms Free of Plasticisers

PurposeTo develop a new direct granule fed 3D printing method for manufacturing pharmaceutical solid dosage forms with porous structures using a thermal droplet deposition technology.MethodsEudragit® E PO was used as the model polymer, which is well-known to be not FDM printable without additives. Wet granulation was used to produce drug loaded granules as the feedstock. The flow and feedability of the granules were evaluated. The physicochemical properties and in vitro drug release performance of the granules and the printed tablets were fully characterised.ResultsUsing the method developed by this study, Eudragit E PO was printed with a model drug into tablets with infills ranging from 30–100%, without additives. The drug was confirmed to be molecularly dispersed in the printed tablets. The printing quality and performances of the porous tablets were confirmed to be highly compliant with the pharmacopeia requirement. The level of infill density of the porous tablets had a significant effect on their in vitro drug release performance.ConclusionThis is the first report of thermal droplet deposition printing via direct granule feeding. The results of this study demonstrated that this new printing method can be used as a potentially valuable alternative for decentralised pharmaceutical solid dosage form manufacturing.

Control of Drug-Excipient Particle Attributes with Droplet Microfluidic-based Extractive Solidification Enables Improved Powder Rheology

Industrial implementation of continuous oral solid dosage form manufacturing has been impeded by the poor powder flow properties of many active pharmaceutical ingredients (APIs). Microfluidic droplet-based particle synthesis is an emerging particle engineering technique that enables the production of neat or composite microparticles with precise control over key attributes that affect powder flowability, such as particle size distribution, particle morphology, composition, and the API's polymorphic form. However, the powder properties of these microparticles have not been well-studied due to the limited mass throughputs of available platforms. In this work, we produce spherical API and API-composite microparticles at high mass throughputs, enabling characterization and comparison of the bulk powder flow properties of these materials and greater understanding of how particle-scale attributes correlate with powder rheology. A multi-channel emulsification device and an extractive droplet-based method are harnessed to synthesize spherical API and API-excipient particles of artemether. As-received API and API crystallized in the absence of droplet confinement are used as control cases. Particle attributes are characterized for each material and correlated with a comprehensive series of powder rheology tests. The droplet-based processed artemether particles are observed to be more flowable, less cohesive, and less compressible than conventionally synthesized artemether powder. Co-processing the API with polycaprolactone to produce composite microparticles reduces the friction of the powder on stainless steel, a common equipment material. Droplet-based extractive solidification is an attractive particle engineering technique for improving powder processing and may aid in the implementation of continuous solid dosage form manufacturing.

Evaluation of a Combined MHE-NMPC Approach to Handle Plant-Model Mismatch in a Rotary Tablet Press.

The transition from batch to continuous processes in the pharmaceutical industry has been driven by the potential improvement in process controllability, product quality homogeneity, and reduction of material inventory. A quality-by-control (QbC) approach has been implemented in a variety of pharmaceutical product manufacturing modalities to increase product quality through a three-level hierarchical control structure. In the implementation of the QbC approach it is common practice to simplify control algorithms by utilizing linearized models with constant model parameters. Nonlinear model predictive control (NMPC) can effectively deliver control functionality for highly sensitive variations and nonlinear multiple-input-multiple-output (MIMO) systems, which is essential for the highly regulated pharmaceutical manufacturing industry. This work focuses on developing and implementing NMPC in continuous manufacturing of solid dosage forms. To mitigate control degradation caused by plant-model mismatch, careful monitoring and continuous improvement strategies are studied. When moving horizon estimation (MHE) is integrated with NMPC, historical data in the past time window together with real-time data from the sensor network enable state estimation and accurate tracking of the highly sensitive model parameters. The adaptive model used in the NMPC strategy can compensate for process uncertainties, further reducing plant-model mismatch effects. The nonlinear mechanistic model used in both MHE and NMPC can predict the essential but complex powder properties and provide physical interpretation of abnormal events. The adaptive NMPC implementation and its real-time control performance analysis and practical applicability are demonstrated through a series of illustrative examples that highlight the effectiveness of the proposed approach for different scenarios of plant-model mismatch, while also incorporating glidant effects.

Powder composition monitoring in continuous pharmaceutical solid-dosage form manufacturing using state estimation – Proof of concept

In continuous solid-dosage form manufacturing, the powder feeding system is responsible for supplying downstream the correct formulation of the drug product ingredients. The composition of the powder delivered by the feeding system is inferred from the measurements of powder mass flow from the system feeders. The mass flows are, in turn, inferred from the loss in weight measured in the feeder hoppers. Most loss-in-weight feeders post-process the mass flow signal to deliver a smoothed value to the user. However, such estimated mass flows can exhibit a low signal-to-noise ratio. As the feeders are critical elements of the control strategy of the manufacturing line, better instantaneous estimates of mass flow are desirable for improving the quality assurance. In this study, we propose a model-based approach for monitoring the composition of the powder fed to a continuous solid-dosage line. The monitoring system is based on a moving-horizon state estimator, which carries out model-based reconciliation of the feeder mass measurements, thus enabling accurate composition estimation of the powder mixture. Experimental datasets from a direct compression line are used to validate the methodology. Results demonstrate improvement with respect to current industrial solutions.

Solvent-free temperature-facilitated direct extrusion 3D printing for pharmaceuticals

In an era moving towards digital health, 3D printing has successfully proven its applicability in providing personalised medicine through a technology-based approach. Among the different 3D printing techniques, direct extrusion 3D printing has been demonstrated as a promising approach for on demand manufacturing of solid dosage forms. However, it usually requires the use of elevated temperatures and/or the incorporation of an evaporable solvent (usually water). This can implicate the addition of a drying step, which may compromise the integrity of moisture- or temperature-sensitive drugs, and open the door for additional quality control challenges.Here, we demonstrate a new approach that simplifies direct extrusion 3D printing process with the elimination of the post-printing drying step, by merely adding a fatty glyceride, glyceryl monostearate (GMS), to a model drug (theophylline) and permeable water insoluble methacrylate polymers (Eudragit RL and RS). Indeed, rheological studies indicated that the addition of a combination of a plasticiser, (triethyl citrate), and GMS to theophylline: methacrylate polymer blends significantly reduced the extensional viscosity (to <2.5 kPa·Sec) at 90 °C. Interestingly, GMS demonstrated a dual temperature-dependant behaviour by acting both as a plasticiser and a lubricant at printing temperature (90–110 °C), while aiding solidification at room temperature. X-ray powder diffraction indicated incomplete miscibility of GMS within the polymeric matrix at room temperature with the presence of a subtle diffraction peak, at 2(Θ) = 20°. The 3D printed tablets showed acceptable compendial weight and content uniformity as well as sufficient mechanical resistance. In vitro theophylline release from 3D printed tablets was dependant on Eudragit RL:RS ratio.All in all, this work contributes to the efforts of developing a simplified, facile and low-cost 3D printing for small batch manufacturing of bespoke tablets that circumvents the use of high temperature and post-manufacturing drying step.

Predicting Pharmaceutical Particle Size Distributions Using Kernel Mean Embedding.

In the pharmaceutical industry, the transition to continuous manufacturing of solid dosage forms is adopted by more and more companies. For these continuous processes, high-quality process models are needed. In pharmaceutical wet granulation, a unit operation in the ConsiGma-25 continuous powder-to-tablet system (GEA Pharma systems, Collette, Wommelgem, Belgium), the product under study presents itself as a collection of particles that differ in shape and size. The measurement of this collection results in a particle size distribution. However, the theoretical basis to describe the physical phenomena leading to changes in this particle size distribution is lacking. It is essential to understand how the particle size distribution changes as a function of the unit operation’s process settings, as it has a profound effect on the behavior of the fluid bed dryer. Therefore, we suggest a data-driven modeling framework that links the machine settings of the wet granulation unit operation and the output distribution of granules. We do this without making any assumptions on the nature of the distributions under study. A simulation of the granule size distribution could act as a soft sensor when in-line measurements are challenging to perform. The method of this work is a two-step procedure: first, the measured distributions are transformed into a high-dimensional feature space, where the relation between the machine settings and the distributions can be learnt. Second, the inverse transformation is performed, allowing an interpretation of the results in the original measurement space. Further, a comparison is made with previous work, which employs a more mechanistic framework for describing the granules. A reliable prediction of the granule size is vital in the assurance of quality in the production line, and is needed in the assessment of upstream (feeding) and downstream (drying, milling, and tableting) issues. Now that a validated data-driven framework for predicting pharmaceutical particle size distributions is available, it can be applied in settings such as model-based experimental design and, due to its fast computation, there is potential in real-time model predictive control.

Lactose monohydrate flow characterization using shear cell method

The flow properties of pharmaceutical powders have a great importance in the manufacturing of solid dosage forms. In order to ensure the performance in the production line this parameter must be determined. There are several methods described in European Pharmacopeia that are used to measure these properties. Some of them were used in this study and the results obtained from conventional methods (Conv) and shear cell using the powder flow tester (PFT) showed differences that were more evident in fractions with smaller particle size (F < 63) and for bulk powder (FTotal). The various powder behaviors showed to be related with the size of the particles. An increase of the ffc (Flow Index) was observed with the increase of the particle size. It was also found for the different fractions that the ffc always increases with increasing major principal consolidation stress (σ1). This study shown to be predictive because it also allowed the behavior profiles of other LactMN fractions to be known by interpolation of the median size (Dv50) or σ1 values ranged between the studied intervals. Furthermore, it was also observed that ffc of the FTotal was similar to the F < 63, showing the same behavior under σ1. The occurrence of caking was not observed.

Development and applications of a material library for pharmaceutical continuous manufacturing of solid dosage forms.

The purpose of this study is to establish a material library and discuss its potential application to the development and lifecycle management of a continuous manufacturing process for solid dosage forms. Particularly, this study addresses the importance of selecting process-relevant testing conditions for material characterization, proposes a methodology to capture relevant information with a reduced set of measurements, and correlates material properties with process performance. This study included 20 pharmaceutical materials, and each material was characterized by 44 properties, capturing 880 data points. The stress conditions of a commonly used feeder hopper were calculated using the Janssen model for six selected materials. Multivariate analysis, such as principal component analysis and clustering analysis, was used to explore the knowledge space of the material library. Statistically similar and dissimilar material properties were evaluated for material feeding performance from a loss-in-weight feeder to test utility of the material library. 20 materials included in this study show a wide range of material properties. Consolidation stress during testing significantly impacts obtained material properties. Based on a material similarity metric, a reduced set of characterization tests that captures >95% of the relevant information was identified. Materials were then grouped into six clusters. The material loss-in-weight feeding results show that the materials within the same cluster show similar feeding performance, while selected materials from different cluster have different feeding performance. Additional material understanding regarding flow properties may be needed to implement a continuous manufacturing process. Characterization using multiple tests under process-relevant conditions can be helpful to establish the correlation between material properties and process and product performance using multivariate analysis tools.

Managing active pharmaceutical ingredient raw material variability during twin-screw blend feeding

Continuous powder feeding is a critical step in continuous manufacturing of solid dosage forms, as this unit operation should ensure the mass flow consistency at the desired powder feed rate to guarantee the process throughput and final product consistency. In this study, twin-screw feeding of a pharmaceutical formulation (i.e., blend) existing of a highly dosed very poorly flowing active pharmaceutical ingredient (API) leading to insufficient feeding capacity was investigated. Furthermore, the API showed very high batch-to-batch variability in raw material properties dominating the formulation blend properties. Formulation changes were evaluated to improve the flowability of the blends and to mitigate the impact of API batch-to-batch variability on the twin-screw feeding. Herewith, feeding evaluation tests and an extensive material characterization of the reformulated blends were performed to assess the impact of the formulation changes upon continuous twin-screw feeding. The transfer of the glidant from extra-granular to intra-granular phase allowed to improve the flowability of the blends. A sufficient feeding capacity for the downstream process and a mitigation of the impact of batch-to-batch variability of the API upon twin-screw feeding of the blends could be achieved. No effect of the formulation or of the API properties on the feeding stability was observed. The material characterization of the blends allowed identifying the material attributes which were critical for continuous twin-screw feeding (i.e., bulk density, mass charge and powder cohesiveness).

Development of the methodological approach of obtaining preparations based on solid dispersions

Nowadays, the innovative direction of pharmaceutical development is the application of methods to increase the biopharmaceutical efficiency and safety of the use of already existing APIs, including method of incorporating them into solid dispersions in which the substance molecules are included in the supramolecular formations by forming non-covalent bonds by excipients. Today, the preparation of solid dispersions is considered as the most effective way of increasing oral bioavailability, in which dissolution of the carrier facilitates the release of API with its rapid solubilization. According to the literature, it is established that today there is only an empirical approach to obtaining solid dispersions. The aim of the work was the formulation of the main approaches to the development of preparations on the basis of solid dispersions, taking into account the current trends in the development of the composition and technology of preparations with sparingly soluble active pharmaceutical ingredients. Materials and methods. To develop a methodological approach, external situational content analysis of applied methods for increasing the bioavailability of active pharmaceutical ingredients used in the manufacture of solid dosage forms was used. Results. In the course of accomplishing this goal, a classification of the types of solid dispersions was proposed depending on the structure and method of production, an algorithm was developed for choosing a method for obtaining a solid dispersion, taking into account the physico-chemical properties of the active pharmaceutical ingredients, which can be used in the technological process to increase their bioavailability. Critical components were also found in the development of solid dispersions. Conclusions. Taking into account the physicochemical properties of the active pharmaceutical ingredients, was chosen an algorithm for selecting a method for preparing solid dispersions that can be used in the process to improve their bioavailability. Based on the results of the analysis of the literature data and our own research of the physico-chemical characteristics of the active pharmaceutical ingredients and excipients, type of the solid dispersion structure, the type of solvent and carrier, a methodological approach to the preparation of solid dispersions is proposed, the use of which will optimize the development of solid dosage forms

At‐Line Raman Spectroscopy Determination of Tablet Mass Gains during the Tablet Coating Process

The coating process in the manufacturing of solid dosage forms is important for optimizing therapeutic efficacy because the coating is vital for controlling the drug release rate. The coating is most commonly applied by spraying a solution containing the coating material to form a film. In this study, core tablet samples were collected at regular intervals from four batches made using a scale‐up manufacturing coating process, and the Raman spectra were obtained to determine the mass increase of the coated tablets. To acquire the spectra, a wide area illumination scheme was used to sample a large area (28.3 mm2) with a 785‐nm laser. Additionally, we established a calibration model using the Raman spectra of three tablet batches and verified the accuracy of the model by predicting the tablet weights of a fourth batch. All spectra were preprocessed with baseline correction and normalization. The spectral range was 1700 to 300 cm−1, and partial least squares analysis was performed to establish a model with full cross‐validation. The accuracy was assessed by comparing the difference between the predicted weights using the model and that measured on an analytical balance, which was the reference test method. Standard error of cross‐validation (SECV) values and standard error of prediction (SEP) values for the fourth batch were 0.0023 and 0.0020 g, respectively, showing high accuracy. We established four optimal models that encompassed all combinations of different batches in a workplace environment and verified them by predicting each of the remaining batches.

On the modelling of granule size distributions in twin-screw wet granulation: Calibration of a novel compartmental population balance model

In recent years, novel developments in the continuous manufacturing of solid dosage forms using twin-screw wet granulation have grasped the attention of the pharmaceutical industry. In spite of this progress, there still exists a lack of fundamental knowledge on the physical processes occurring in the barrel of the twin-screw granulator. A major contributor to this knowledge gap has been the unavailability of measurements of granule properties (particle size, liquid content, porosity, etcetera) along the length of the barrel. Recently conducted tedious measurements at different barrel locations have been essential to build a hypothesis in terms of locally occurring mechanisms in twin-screw wet granulation. This paper proposes a novel kernel for modelling either the uni- or bimodal behaviour observed at different L/S ratios in the wetting zone, assuming pure aggregation only. Furthermore, a two stage (wetting and kneading zone) compartmental population balance model is constructed to successfully simulate granule sizes from preblend to the end of the granulator. This population balance model can simulate granule size distributions at a reasonable accuracy both in the case of single compartments as well as in the full two stage compartmental set-up. The proposed model in this paper is a first important step in knowledge build-up of twin-screw granulation and towards a general population balance model for twin-screw wet granulation.