Implementation of near-infrared spectroscopy and convolutional neural networks for predicting particle size distribution in fluidized bed granulation.

Monitoring the particle size distribution (PSD) is crucial for controlling product quality during fluidized bed granulation. This paper proposed a rapid analytical method that quantifies the D10, D50, and D90 values using a Convolutional Block Attention Module-Convolutional Neural Network (CBAM-CNN) framework tailored for deep learning with near-infrared (NIR) spectroscopy. This innovative framework, which fuses CBAM with CNN, excels at extracting intricate features while prioritizing crucial ones, thereby facilitating the creation of a robust multi-output regression model. To expand the training dataset, we incorporated the C-Mixup algorithm, ensuring that the deep learning model was trained comprehensively. Additionally, the Bayesian optimization algorithm was introduced to optimize the hyperparameters, improving the prediction performance of the deep learning model. Compared with the commonly used Partial Least Squares (PLS), Support Vector Machine (SVM), and Artificial Neural Network (ANN) models, the CBAM-CNN model yielded higher prediction accuracy. Furthermore, the CBAM-CNN model avoided spectral preprocessing, preserved the spectral information to the maximum extent, and returned multiple predicted values at one time without degrading the prediction accuracy. Therefore, the CBAM-CNN model showed better prediction performance and modeling convenience for analyzing PSD values in fluidized bed granulation.

Mining association rules between the granulation feasibility and physicochemical properties of aqueous extracts from Chinese herbal medicine in fluidized bed granulation.

Fluidized bed granulation (FBG) is a widely used granulation technology in the pharmaceutical industry. However, defluidization caused by the formation of large aggregates poses a challenge to FBG, particularly in traditional Chinese medicine (TCM) due to its complex physicochemical properties of aqueous extracts. Therefore, this study aims to identify the complex relationships between physicochemical characteristics and defluidization using data mining methods. Initially, 50 types of TCM were decocted and assessed for their potential influence on defluidization using a set of 11 physical properties and 10 chemical components, utilizing the loss rate as an evaluation index. Subsequently, the random forest (RF) and Apriori algorithms were utilized to uncover intricate association rules among physicochemical characteristics and defluidization. The RF algorithm analysis revealed the top 8 critical factors associated with defluidization. These factors include physical properties like glass transition temperature (Tg) and dynamic surface tension (DST) of DST100ms, DST1000ms, DST10ms and conductivity, in addition to chemical components such as fructose, glucose and protein contents. The results from Apriori algorithm demonstrated that lower Tg and conductivity were associated with an increased risk of defluidization, resulting in a higher loss rate. Moreover, DST100ms, DST1000ms and DST10ms exhibited a contrasting trend in the physical properties Specifically, defluidization probability increases when Tg and conductivity dip below 29.04℃ and 6.21 ms/m respectively, coupled with DST10ms, DST100ms and DST1000ms values exceeding 70.40 mN/m, 66.66 mN/m and 61.58 mN/m, respectively. Moreover, an elevated content of low molecular weight saccharides was associated with a higher occurrence of defluidization, accompanied by an increased loss rate. In contrast, protein content displayed an opposite trend regarding chemical properties. Precisely, the defluidization likelihood amplifies when fructose and glucose contents surpass 20.35 mg/g and 34.05 mg/g respectively, and protein concentration is less than 1.63 mg/g. Finally, evaluation criteria for defluidization were proposed based on these results, which could be used to avoid this situation during the granulation process. This study demonstrated that the RF and Apriori algorithms are effective data mining methods capable of uncovering key factors affecting defluidization.

One Step In Situ Co-Crystallization of Dapsone and Polyethylene Glycols during Fluidized Bed Granulation.

Several studies have demonstrated the feasibility of in situ co-crystallization in different pharmaceutical processes such as spray drying, hot melt extrusion, and fluidized bed granulation (FBG) to produce co-crystal-in-excipient formulations. However, no previous studies have examined such a one step in situ co-crystallization process for co-crystal formulations where the coformer is a polymer. In the current study, we explored the use of FBG to produce co-crystal granules of dapsone (DAP) and different molecular weight polyethylene glycols (PEGs). Solvent evaporation (SE) was proven to generate DAP-PEGs co-crystals at a particular weight ratio of 55:45 w/w between DAP and PEG, which was subsequently used in FBG, using microcrystalline cellulose and hydroxypropyl methyl cellulose as filler excipient and binder, respectively. FBG could generate co-crystals with higher purity than SE. Granules containing DAP-PEG 400 co-crystal could be prepared without any additional binder. DAP-PEG co-crystal granules produced by FBG demonstrated superior pharmaceutical properties, including flow properties and tableting properties, compared to DAP and DAP-PEG co-crystals prepared by SE. Overall, in situ co-crystallization via FBG can effectively produce API-polymer co-crystals and enhance the pharmaceutical properties.

Evaluation of the Formulation Parameter-Dependent Redispersibility of API Nanoparticles from Fluid Bed Granules.

The production of nanosuspensions of poorly soluble active pharmaceutical ingredients (API) is a popular technique to counteract challenges regarding bioavailability of such active substances. A subsequent drying of the nanosuspensions is advantageous to improve the long-term stability and the further processing into solid oral dosage forms. However, associated drying operations are critical, especially with regard to nanoparticle growth, loss in redispersibility and associated compromised bioavailability. This work extends a previous study regarding the applicability of an API (itraconazole) nanosuspension as a granulation liquid in a fluidized bed process with focus on the influence of applied formulation parameters on the structure of obtained nanoparticle-loaded granules and their nanoparticle redispersibility. Generally, a higher dissolution rate of the carrier material (glass beads, lactose, mannitol or sucrose) and a higher content of a matrix former/hydrophilic polymer (PVP/VA or HPMC) in the granulation liquid resulted in the formation of coarser and more porous granules with improved nanoparticle redispersibility. HPMC was found to have advantages as a polymer compared with PVP/VA. In general, a better redispersibility of the nanoparticles from the granules could be associated with better dispersion of the API nanoparticles at the surface of the granules as deduced from the thickness of nanoparticle-loaded layers around the granules. The layer thickness on granules was assessed by means of confocal Raman microscopy. Finally, the dispersion of the nanoparticles in the granule layers was exemplarily described by calculation of theoretical mean nanoparticle distances in the granule layers and was correlated with data obtained from redispersibility studies.

Design Space Approach for the Optimization of Green Fluidized Bed Granulation Process in the Granulation of a Poorly Water-Soluble Fenofibrate Using Design of Experiment.

In the pharmaceutical industry, the systematic optimization of process variables using a quality-by-design (QbD) approach is highly precise, economic and ensures product quality. The current research presents the implementation of a design-of-experiment (DoE) driven QbD approach for the optimization of key process variables of the green fluidized bed granulation (GFBG) process. A 32 full-factorial design was performed to explore the effect of water amount (X1; 1-6% w/w) and spray rate (X2; 2-8 g/min) as key process variables on critical quality attributes (CQAs) of granules and tablets. Regression analysis have demonstrated that changing the levels of X1 and X2 significantly affect (p ≤ 0.05) the CQAs of granules and tablets. Particularly, X1 was found to have the pronounced effect on the CQAs. The GFBG process was optimized, and a design space (DS) was built using numerical optimization. It was found that X1 and X2 at high (5.69% w/w) and low (2 g/min) levels, respectively, demonstrated the optimum operating conditions. By optimizing X1 and X2, GFBG could enhance the disintegration and dissolution of tablets containing a poorly water-soluble drug. The prediction error values of dependent responses were less than 5% that confirm validity, robustness and accuracy of the generated DS in optimization of GFBG.

[Granulation of Yangxue Qingnao Granules in fluidized bed based on near-infrared spectroscopy].

To realize the real-time monitoring of the production process of Yangxue Qingnao Granules and improve the inter-batch consistency of granule quality in the granulation process, this study established a near-infrared quantitative prediction model of moisture, particle size, bulk density, and angle of repose in the fluidized bed granulation process of Yangxue Qingnao Granules based on near-infrared spectroscopy(NIRS). The near-infrared spectra were collected from 355 samples in 12 batches in the granulation process by integrating the sphere detection module of the near-infrared spectrometer. In combination with the pretreatment methods such as the first derivative, multiplicative scatter correction(MSC), and standard normal variate(SNV), the model was established by partial least squares(PLS) regression. The root mean square error of prediction(RMSEP) of moisture was 0.347 and R_P~2 was 0.935. The RMSEP of the D_(50) particle size model was 38.4 and R_P~2 was 0.980. The RMSEPs of bulk density and angle of repose were 0.018 8 and 0.879, with R_P~2 of 0.085 9 and 0.958. The results showed that the prediction of the PLS quantitative model combined with NIRS was accurate, and this model can be applied to the monitoring of key quality attributes in the fluidized bed granulation of Chinese medicinal granules in the production scale.

Implementation of Dynamic and Static Moisture Control in Fluidized Bed Granulation.

The application of process analysis and control is essential to enhance process understanding and ensure output material quality. The present study focuses on the stability of the feedback control system for a fluidized bed granulation process. Two strategies of dynamic moisture control (DMC) and static moisture control (SMC) were established based on the in-line moisture value obtained from the near-infrared sensor and control algorithm. The performance of these strategies on quality consistency control was examined using process moisture similarity analysis and principal component analysis. The stable moisture control performance and low batch-to-batch variability indicated that the DMC method was significantly better than other granulation methods. In addition, the investigation of robustness further showed that the implemented DMC method was able to produce predetermined target moisture values by varying process parameters. This study provides an advanced and simple control method for fluidized bed granulation quality assurance.

Method development and validation of a near-infrared spectroscopic method for in-line API quantification during fluidized bed granulation.

Near-infrared spectroscopy (NIRS) is an excellent process analytical technology (PAT) tool for active pharmaceutical ingredient (API) quantification during fluidized granulation. Therefore, a portable near-infrared spectrometer combined with a new innovative method of extended iterative optimization technique (EIOT) was used to in-line monitor the API content uniformity during fluidized bed granulation. The principal component analysis (PCA) and partial least squares regression (PLSR) were also used to characterize and predict API concentration with changes from 75% to 125% of the label claim to prove the superiority of EIOT. The API content prediction accuracy of the EIOT method was verified through offline High Performance Liquid Chromatography (HPLC) measurement. Also, the spatial distribution of API in granules was visualized by Raman imaging technology. The results showed that the established NIRS method was suitable for the prediction of API content in fluidized bed granulation, which provides a new idea for the determination of API content during granulation.

Gray-box Soft Sensor for Water Content Monitoring in Fluidized Bed Granulation.

Soft sensors are powerful tools for the implementation of process analytical technology (PAT). They are categorized into white-box (first-principle), black-box (statistical), and gray-box models. Gray-box models integrate white-box and black-box models to address each drawback, i.e., prediction accuracy and intuitiveness. Although they have been applied to various industrial processes, their applicability to water content monitoring in fluidized bed granulation has not been reported. In this study, we evaluated three types of gray-box models, i.e., parallel, serial, and combined gray-box models, in terms of prediction accuracy using real operating data on a commercial scale with two formulations. The gray-box models were constructed by integrating the heat and mass balance model (white-box model) and locally weighted partial least squares regression (LW-PLSR) model (black-box model). LW-PLSR was utilized to cope with collinearity and nonlinearity. In the serial gray-box models, LW-PLSR models adjusted the fitting parameters of the white-box model depending on the process parameters for each query. In the parallel gray-box or combined gray-box models, LW-PLSR models compensated for the output error of the white-box or serial gray-box models, respectively. The results demonstrated that all three types of gray-box models improved the prediction accuracy of the white-box models regardless of the formulation. Besides, we proposed the assessment method based on Hotelling's T2 and Q residual for gray-box models using LW-PLSR, which contributes decision support to select gray-box or white-box model. The accurate and descriptive gray-box models are expected to enhance process understanding and precise quality control in fluidized bed granulation.

Fluidized-Bed Granulation of Probiotics-Encapsulated Spray-Dried Skim Milk Powder: Effects of a Fluidizing Aid, Moisture-Activation and Dehydration.

A probiotic powder of poor flowability with high dust content, prepared by spray drying reconstituted skim milk fermented with Lactobacillus rhamnosus GG (LGG), was granulated by fluidized-bed granulation (FBG). The effects of the addition of skim milk powder (SMP) as a fluidizing aid, and of simple moisture-activation with or without dehydration, were investigated with respect to the performance of the FBG process. A fine, poorly fluidizable LGG powder (Geldart Group C) could be fluidized and granulated, with a 4- to 5-fold increase in particle size (d4,3 = 96-141 µm), by mixing with SMP (30-50%), which has larger, fluidizable particles belonging to Geldart Group A. Moisture-activation after the mixing, followed by fluidized-bed dehydration with hot air to remove excess moisture, further improved the FBG; the yield of the granules increased from 42% to 61% and the particle size distribution became much narrower, although the average particle size remained almost the same (d4,3 = 142 µm). These granules showed a popcorn-type structure in scanning electron microscopy images and encapsulated a sufficient level of viable LGG cells (1.6 × 108 CFU g-1). These granules also exhibited much better flowability and dispersibility than the spray-dried LGG powder.

Manufacturability and Properties of Granules and Tablets Using the Eco-Friendly Granulation Method Green Fluidized Bed Granulation Compared to Direct Compression.

This study aimed to compare the manufacturability and granule and tablet properties of green fluidized bed granulation (GFBG) and of direct compression (DC). Acetaminophen was used as a low compactability model drug. The process time of GFBG to produce final mixtures was comparable to that of DC, and thus GFBG could be considered a simple process. DC could not produce 30% drug load tablets owing to poor granule flowability, whereas no problems were observed in the GFBG tableting process up to 80% of drug load. Tablets prepared with GFBG showed higher tensile strength than those prepared using DC. Compactability evaluation results show that the yield pressure of the granules prepared with GFBG was significantly lower than that of DC, suggesting that the granules prepared with GFBG were easily plastically deformed. Moreover, tablets prepared with GFBG showed fast disintegration, which was faster than that of DC. We conclude that GFBG produces granules with higher drug content and desired physicochemical properties at low cost.

Development and characterization of ibuprofen co-crystals granules prepared via fluidized bed granulation in a one-step process - a design of experiment approach.

OBJECTIVE: The focus of this study was to investigate the possibility of producing ibuprofen-nicotinamide (IBU-NIC) and ibuprofen-isonicotinamide (IBU-INA) cocrystal-containing granules, using a one-step fluidized bed dryer granulation manufacturing process, and evaluate their mechanical properties. SIGNIFICANCE: Pharmaceutical cocrystals represent a suitable strategy to improve properties of active pharmaceutical ingredients (APIs), such as solubility and processability. Ibuprofen (IBU) is a small molecule API which can form cocrystals with different coformers, including NIC and INA. An improvement in mechanical properties for IBU-NIC cocrystals relative to IBU was previously reported but, to date, the formulation of IBU cocrystals in a solid dosage form has not been investigated. METHODS: In situ cocrystallization and granulation were achieved concurrently by processing in a lab-scale fluidized bed granulator following a design of experiment (DoE) approach using a two-level factorial design with both process and formulation variables. Solid-state, micrometric, dissolution, and mechanical (tabletability) characteristics of granules were assessed post-processing. RESULTS: Granules containing cocrystals were successfully prepared for 11 of 16 DoE runs. Parameters with a significant effect on granule drug loading, flow function, porosity, and size could be identified from the DoE model. Process yield was increased by using a high inlet temperature at high solution feed rate. To avoid the formation of sticky particles, caking and over-wetting of the powder during the process, the utilization of high inlet temperature, low API + coformer:filler ratio, low API concentration in solution and low solution feed rate were suggested by the model. CONCLUSION: The multivariable model developed enables accurate optimization of the granulation process for IBU cocrystals.

Influence of Formulation Parameters on Redispersibility of Naproxen Nanoparticles from Granules Produced in a Fluidized Bed Process.

The particle size reduction of active pharmaceutical ingredients is an efficient method to overcome challenges associated with a poor aqueous solubility. With respect to stability and patient's convenience, the corresponding nanosuspensions are often further processed to solid dosage forms. In this regard, the influence of several formulation parameters (i.e., type of carrier material, type and amount of additional polymeric drying excipient in the nanosuspension) on the redispersibility of naproxen nanoparticle-loaded granules produced in a fluidized bed process was investigated. The dissolution rate of the carrier material (i.e., sucrose, mannitol, or lactose) was identified as a relevant material property, with higher dissolution rates (sucrose > mannitol > lactose) resulting in better redispersibility of the products. Additionally, the redispersibility of the product granules was observed to improve with increasing amounts of polymeric drying excipient in the nanosuspension. The redispersibility was observed to qualitatively correlate with the degree of nanoparticle embedding on the surface of the corresponding granules. This embedding was assumed to be either caused by a partial dissolution and subsequent resolidification of the carrier surface dependent on the dissolution rate of the carrier material or by resolidification of the dissolved polymeric drying excipient upon drying. As the correlation between the redispersibility and the morphology of the corresponding granules was observed for all investigated formulation parameters, it may be assumed that the redispersibility of the nanoparticles is determined by their distance in the dried state.

A semi-theoretical model for simulating the temporal evolution of moisture-temperature during industrial fluidized bed granulation.

Moisture plays a major role in determining the attributes of granules prepared by fluidized bed granulation (FBG). Here, a semi-theoretical droplet-based evaporation rate model was developed and incorporated into moisture mass-enthalpy balances to simulate the temporal evolution of bed moisture-temperature. Experimental data from a GPCG30 unit were used to fit the model parameters. With only two fitting parameters, the model demonstrated excellent capability to describe the moisture-temperature evolution for a wide range of operating conditions. Then, in a global process model (GPM) approach, the evaporation parameters were fitted to multi-linear functions of inlet air temperature, binder concentration, and spray rate. The GPM was validated successfully by simulating a different data set which was not used in its calibration. As the GPM demonstrated a good predictive capability, it was further used to investigate the impacts of process parameters. Numerical simulations suggest that the proposed GPM predicts the experimentally well-established trends of moisture-temperature profiles in previously published data, proving the applicability of the GPM approach. This study has demonstrated the capabilities of simple process models as a practical approach to predict time-wise evolution of bed moisture-temperature profiles in industrial FBG modeling, while also pointing out their limitations.

Empirical prediction model based process optimization for droplet size and spraying angle during pharmaceutical fluidized bed granulation.

The objective of this study was to predict the droplet size and the spraying angle during the process of binder atomization in pharmaceutical fluidized bed granulation using an empirical model. The effects of the binder viscosity, the atomization pressure, and the spray rate on the droplet size and the spraying angle were investigated using a response surface central composite design and analysis of variance. Prediction models for droplet size and spraying angle were then established using stepwise regression analysis and were validated by comparing the measured and predicted values. The results showed that the droplet size model and the spraying angle model were well established, with an R2 of 0.93 (p < 0.0001) and a root mean square error (RMSE) of 10.10, and an R2 of 0.82 (p < 0.0001) and an RMSE of 3.69, respectively. The error between the measured and predicted values of the droplet size and the spraying angle were less than 10%, indicating that the established models were accurate. The results of the present study were significant in predicting the droplet size and spraying angle in the process of pharmaceutical fluidized bed granulation.

Importance of free water in controlling granule and tablet properties in a novel granulation method, green fluidized bed granulation (GFBG).

In the pharmaceutical field, green fluidized bed granulation (GFBG) is a novel and eco-friendly manufacturing technology used to produce desired granules via simple blending and spraying steps at ambient temperature using a standard fluidized bed granulator. However, the relations between water content and granule and tablet qualities have not yet been elucidated for GFBG. The purpose of this study was to elucidate the influence of different water quantities used in the GFBG process on granule and tablet qualities. In addition, results from the GFBG process were compared with those from the moisture-activated dry granulation (MADG) process. In terms of tablet tensile strength and disintegration time, GFBG had a wider acceptable range for added water quantity (2.0-5.0%) than did MADG. For all added water quantities, the GFBG granules were within the upper limit of water activity (a surrogate of free water amount), which was 0.61 for tensile strength and 0.55 for disintegration time. The air flow in the GFBG process may have reduced the excess free water on the granules during the absorption process. It was concluded that as compared with MADG, GFBG may be a more robust process for manufacturing granules and tablets with superior properties.

A large-scale experimental comparison of batch and continuous technologies in pharmaceutical tablet manufacturing using ethenzamide.

This paper compares batch and continuous technologies in terms of product quality and process performance in pharmaceutical tablet manufacturing using ethenzamide as the active pharmaceutical ingredient. Batch and continuous processes using wet granulation were investigated by performing experiments on the scale of 5 and up to 100 kg/lot, using the same raw materials. Three technologies were tested and compared: (i) batch technology using fluidized bed granulation, (ii) batch technology using high shear granulation, (iii) continuous technology using high shear granulation. In the full-scale experiment, in all three technologies including continuous technology, the quality of the tablets fulfilled the target values regarding hardness, active pharmaceutical ingredient content, and dissolution. The granules produced by different technologies, however, presented varying attributes regarding granule size distribution, loose bulk density, or scanning electron microscope images. The process performance, more specifically the yield, was slightly better for batch technologies than for the continuous technology, mainly due to losses in the start-up operation. Notably, this study has shown that continuous technology, which is generally believed to not entail scale-up procedures, could in fact, require parameter adjustment for prolonged operation. The results provided suggestions for improvements to implement large-scale continuous technologies in the pharmaceutical industry.

In Situ Cocrystallization of Dapsone and Caffeine during Fluidized Bed Granulation Processing.

Different pharmaceutical manufacturing processes have been demonstrated to represent feasible platforms for the production of pharmaceutical cocrystals. However, new methods are needed for the manufacture of cocrystals on a large scale. In this work, the suitability of the use of a fluidized bed system for granulation and concomitant cocrystallization was investigated. Dapsone (DAP) and caffeine (CAF) have been shown to form a stable cocrystal by simple solvent evaporation. DAP is the active pharmaceutical ingredient (API) and CAF is the coformer. In the present study, DAP-CAF cocrystals were produced through liquid-assisted milling and the product obtained was used as a cocrystal reference. The granulation of DAP and CAF was carried out using four different experimental conditions. The solid-state properties of the constituents of the granules were characterised by differential scanning calorimetry (DSC) and x-ray powder diffraction (PXRD) analysis while the granule size distribution and morphology were investigated using laser diffraction and scanning electron microscopy (SEM), respectively. DAP-CAF cocrystal granules were successfully produced during fluidized bed granulation. The formation of cocrystals was possible only when the DAP and CAF were dissolved in the liquid phase and sprayed over the fluidized solid particles. Furthermore, the presence of polymers in solution interferes with the cocrystallization, resulting in the amorphization of the DAP and CAF. Cocrystallization via fluidized bed granulation represents a useful tool and a feasible alternative technique for the large scale manufacture of pharmaceutical cocrystals for solid dosage forms.

Novel, lean and environment-friendly granulation method: Green fluidized bed granulation (GFBG).

The Green fluidized bed granulation (GFBG) technology is based on the moisture activated dry granulation (MADG) technique and consists only of a mixing and a spraying process using a fluidized bed granulator, requiring no heating process. This provides a less energy-consuming and environment-friendly granulation method compared to current fluidized bed granulation (FBG) and high-shear granulation (HSG) methods. The aim of this study is to compare and evaluate the manufacturability, and granule and tablet properties among GFBG, MADG, FBG and HSG. The GFBG process time took less than 20 min for producing final blends at a 700 g scale, which was comparable to MADG. This process time was significantly shorter than that of FBG and HSG. GFBG not only had the shortest process time but also reduced the number of manufacturing machines compared to FBG and HSG. The Hausner ratio (HR) of granules from GFBG (1.30) indicated a good flowability, and no problems were observed in the tablet mass variability during compression. Tablets produced using GFBG achieved sufficient tensile strength (>1.5 MPa) even at a low compression force and demonstrated the fastest disintegration time compared to the other manufacturing methods. Tablet disintegration is related to wettability and porosity, therefore the tablet wettability (initial and capillary wetting) and tablet porosity were investigated. As a result, the capillary wetting of the tablets produced using GFBG was 3.6 times higher than the tablets produced using FBG, which might have affected the fast disintegration of the tablets produced using GFBG.

Research Progress of Granulation Technology for Taste Masking of Pharmaceutical Preparation / 中国实验方剂学杂志

In commonly used oral solid preparations, poor mouthfeel results in poor patient compliance with the drug, which in turn reduces the market competitiveness of the drug. The problem of taste masking of pharmaceutical preparations has always been one of the important problems faced by pharmaceutics. With the increasing demand for the taste of drugs, the methods of masking bad taste of drugs have gradually increased in recent years. By summarizing the relevant literature covering the bad taste of drugs, the commonly used taste masking techniques include the addition of taste masking agents, inclusion techniques, microsphere/microcapsule technology, solid dispersion technology, ion exchange technology and the like. However, in addition to the above taste masking techniques, in the manufacturing process of the solid preparation, the granulation technique also can achieve the shielding of the bad taste of the medicine, and the granulation technique is simple, and can well achieve the effect of masking the bad taste of the medicine. This paper systematically introduces the research progress of granulation technology in drug taste masking, in order to provide reference for the selection of drug taste masking technology. With the increasing demand for drug taste, drug masking technology has been paid more and more attention by the majority of preparation workers, however, there are still some problems, such as imperfect taste evaluation system and low specificity of methods. This series of problems need to be further studied and solved by relevant pharmaceutical researchers.