Development of a fluid bed granulation process control strategy based on real-time process and product measurements

Evaluation of the effect of granule size of raw tableting materials on critical quality attributes of tablets during the continuous tablet manufacturing process using near-infrared spectroscopy

OBJECTIVE

The effects of granule size of raw materials on tablet hardness (TH) and weight (TW) in the continuous tablet manufacturing process (CTMP) were investigated using near-infrared spectroscopy (NIRS).

METHODS

Granule materials of different sizes were prepared by extrusion granulation from a standard granule formula powder containing lactose/starch and 4.5% acetaminophen. Large-, small-, and medium-sized granules were sequentially filled in a hopper, and tablets were produced continuously using a single-shot tableting machine. After arranging approximately 500 tablets in order, the tablets were subjected to NIRS. A total of 450 NIRS datasets were divided into three groups of 150 each (calibration, validation 1, and validation 2 datasets).

RESULTS

The best fitted calibration models for predicting TH and TW were obtained, with sufficient accuracy, based on NIRS using the partial least squares regression, and comprised both physical and chemical information. The regression and loading vectors of the calibration models suggested that the models used to predict TH and TW involve physical information based on geometrical factors of the tablet and chemical information related to binder-related intermolecular interactions.

CONCLUSIONS

The changes in the predicted value profiles of TH and TW using NIRS reflected the changes in the measured values depending on the raw granule size during CTMP.

Real-Time Monitoring of Critical Quality Attributes during High-Shear Wet Granulation Process by Near-Infrared Spectroscopy Effect of Water Addition and Stirring Speed on Pharmaceutical Properties of the Granules

To produce high-quality pharmaceuticals, a real-time monitoring method for the high-shear wet granulation process (HSWG) was developed based on near-infrared spectroscopy (NIRS). Samples consisting of lactose, potato starch, and hydroxypropyl cellulose were prepared using HSWG with varying amounts of purified water (80, 90, and 100 mL) and impeller speed (200, 400, and 600 rpm), which produces granules of different characteristics. Twelve batches of samples were used for the calibration and nine batches were used for validation. After drying, the median particle size (D50), tapped density (TD), and Hauser ratio (HR) were measured. The best calibration models to predict moisture content (MC), D50, TD, and HR were determined based on pretreated NIR spectra using partial least squares regression analysis (PLSR). The temporal changes in the pharmaceutical properties under different amounts of water added and stirring speed were monitored in real time using NIRS/PLSR. Because the most important critical quality attribute (CQA) in the process was MC, granule characteristics such as D50, TD, and HR were analyzed with respect to MC. They might be used as robust and simple monitoring methods based on MC to evaluate the pharmaceutical properties of HSWG granules.

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

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

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.

Process Analytical Technology Tools for Monitoring Pharmaceutical Unit Operations: A Control Strategy for Continuous Process Verification

Various frameworks and methods, such as quality by design (QbD), real time release test (RTRT), and continuous process verification (CPV), have been introduced to improve drug product quality in the pharmaceutical industry. The methods recognize that an appropriate combination of process controls and predefined material attributes and intermediate quality attributes (IQAs) during processing may provide greater assurance of product quality than end-product testing. The efficient analysis method to monitor the relationship between process and quality should be used. Process analytical technology (PAT) was introduced to analyze IQAs during the process of establishing regulatory specifications and facilitating continuous manufacturing improvement. Although PAT was introduced in the pharmaceutical industry in the early 21st century, new PAT tools have been introduced during the last 20 years. In this review, we present the recent pharmaceutical PAT tools and their application in pharmaceutical unit operations. Based on unit operations, the significant IQAs monitored by PAT are presented to establish a control strategy for CPV and real time release testing (RTRT). In addition, the equipment type used in unit operation, PAT tools, multivariate statistical tools, and mathematical preprocessing are introduced, along with relevant literature. This review suggests that various PAT tools are rapidly advancing, and various IQAs are efficiently and precisely monitored in the pharmaceutical industry. Therefore, PAT could be a fundamental tool for the present QbD and CPV to improve drug product quality.

Continuous manufacturing process monitoring of pharmaceutical solid dosage form: A case study

Continuous Manufacturing (CM) of pharmaceutical drug products is a rather new approach within the pharmaceutical industry. In the presented paper, a GMP continuous wet granulation line used for clinical production of solid dosage forms was investigated with a thorough monitoring strategy regarding process performance and robustness. The line was composed of the subsequent continuous unit operations feeding - twin-screw wet-granulation - fluid-bed drying - sieving and tableting; the formulation of a new pharmaceutical entity in development was selected for this study. In detail, a Design of Experiments (DoE) was used to evaluate the impact of the three main factors (amount of water, filling rate, and shear force in twin-screw granulator) on the tablet quality. The process was monitored via in-process control (IPC) tests (e.g. weight, hardness, disintegration, and loss-on-drying), Process Analytical Technologies (PAT), and through the analysis of the process parameters (multivariate process control). The tested formulation was very robust to the large process variation of the DoE: all IPC results were in specification, the PAT probes provided stable results for the content uniformity and no critical variations can be detected in the process parameters. An adequate monitoring strategy was presented and the robustness of the process with one formulation has been demonstrated. In summary, this continuous process in combination with smart formulation development allows the robust production of constant quality tablets. The synergy between PAT, process data science and IPC creates an adequate monitoring framework of the continuous manufacturing line.

Accuracy Improvement of In-line Near-Infrared Spectroscopic Moisture Monitoring in a Fluidized Bed Drying Process

An exploratory analysis of a large representative dataset obtained in a fluidized bed drying process of a pharmaceutical powder has revealed a significant correlation of spectral intensity with granulate humidity in the whole studied range of 1091.8–2106.5 nm. This effect was explained by the dependence of powder refractive properties, and hence light penetration depth, on the water content. The phenomenon exhibited a close spectral similarity to the well-known stochastic variation of spectral intensities caused by the process turbulence (the so-called “scatter effect”). Therefore, any traditional scatter-corrective preprocessing incidentally eliminates moisture-correlated variance from the data. To preserve this additional information for a more precise moisture calibration, a time-domain averaging of spectral variables has been suggested. Its application resulted in a distinct improvement of prediction accuracy, as compared to the scatter-corrected data. Further improvement of the model performance was achieved by the application of a dynamic focusing strategy when adjusting the model to a drying process stage. Probe fouling was shown to have a minor effect on prediction accuracy. The study resulted in a considerable reduction of the root-mean-square error of in-line moisture monitoring to 0.1%, which is close to the reference method's reproducibility and significantly better than previously reported results.

Rapid HPLC Analytical Method Development for Herbal Medicine Formulae Based on Retention Rules Acquired from the Constituting Herbs

Herbal medicine (HM) formulae are the combinations of two or more types of constituting herbs. This study has proposed a novel approach to efficiently develop HPLC methods for HM formulae, which take advantage of the mutual retention rules between HM formulae and their constituting herbs. An HM formula composed of two herbs, Radix Salviae Miltiorrhizae and Rhizoma Chuanxiong, was taken as a case study. Based on design of experiments and stepwise multiple linear regression, models relating the analytical parameters to the chromatographic parameters were built (correlation coefficients >0.9870) for chemical compounds in the two herbs. These models representing the retention rules were utilized to predict the elution profile of the formula. The analytical parameters were numerically optimized to ensure adequate separation of the analytes. In validation experiments, satisfactory separations were achieved without any pre-experiments on the formula. The approach can significantly increase the HPLC method development efficiency for HM formulae.

Real-time monitoring of granule properties during high shear wet granulation by near-infrared spectroscopy with a chemometrics approach

An in-line near-infrared spectroscopy monitoring method was developed for analyzing granule properties during a high shear wet granulation process.

On-line monitoring of fluid bed granulation by photometric imaging

This paper introduces and discusses a photometric surface imaging approach for on-line monitoring of fluid bed granulation. Five granule batches consisting of paracetamol and varying amounts of lactose and microcrystalline cellulose were manufactured with an instrumented fluid bed granulator. Photometric images and NIR spectra were continuously captured on-line and particle size information was extracted from them. Also key process parameters were recorded. The images provided direct real-time information on the growth, attrition and packing behaviour of the batches. Moreover, decreasing image brightness in the drying phase was found to indicate granule drying. The changes observed in the image data were also linked to the moisture and temperature profiles of the processes. Combined with complementary process analytical tools, photometric imaging opens up possibilities for improved real-time evaluation fluid bed granulation. Furthermore, images can give valuable insight into the behaviour of excipients or formulations during product development.

Quality by design for herbal drugs: a feedforward control strategy and an approach to define the acceptable ranges of critical quality attributes

INTRODUCTION

The concept of quality by design (QbD) has been widely accepted and applied in the pharmaceutical manufacturing industry. There are still two key issues to be addressed in the implementation of QbD for herbal drugs. The first issue is the quality variation of herbal raw materials and the second issue is the difficulty in defining the acceptable ranges of critical quality attributes (CQAs).

OBJECTIVE

To propose a feedforward control strategy and a method for defining the acceptable ranges of CQAs for the two issues.

METHODS

In the case study of the ethanol precipitation process of Danshen (Radix Salvia miltiorrhiza) injection, regression models linking input material attributes and process parameters to CQAs were built first and an optimisation model for calculating the best process parameters according to the input materials was established. Then, the feasible material space was defined and the acceptable ranges of CQAs for the previous process were determined.

RESULTS

In the case study, satisfactory regression models were built with cross-validated regression coefficients (Q(2) ) all above 91 %. The feedforward control strategy was applied successfully to compensate the quality variation of the input materials, which was able to control the CQAs in the 90-110 % ranges of the desired values. In addition, the feasible material space for the ethanol precipitation process was built successfully, which showed the acceptable ranges of the CQAs for the concentration process.

CONCLUSION

The proposed methodology can help to promote the implementation of QbD for herbal drugs.