Benefits of the Continuous Wet Granulation Line

The Continuous Wet Granulation Process may have a number of benefits. This article describes the continuous process, a predictive model for the process, twin screw extrusion, and a Raman spectroscopy method for continuous API quantification during high-shear wet granulation.

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Predictive Model for a Continuous Wet Granulation Line

Real-time monitoring of continuous wet granulation processes is critical to ensuring high-quality end products. The primary attributes that require monitoring are moisture content and particle size. Several optical methods have been used to measure these properties. Raman spectroscopy and near infrared spectroscopy are widely used. These optical methods have several advantages, such as non-invasive monitoring. However, these methods may be difficult to collect representative data, and they require the attachment of the wet powder to a probe window. Another method of in-line monitoring is acoustic emission.

We also explored a number of granule properties and their correlations with granulation progress. Our results showed that the PLS model could effectively predict the key granule properties. We found that the predicted properties of the granules had high coefficients of determination. We also found that the RMSECV and RMSEP values of the investigated granule properties were low. In addition, the bulk density of granules was a critical factor that affected our calibration accuracy.

Another useful method for analyzing granule properties in high shear wet granulation processes is in-line near-infrared spectroscopy. This method was used for 11 batches as calibration and an additional batch as validation datasets. The NIR spectra correlated to the chemical and physical changes in the granules. We also evaluated the particle size using a chemometrics approach.

Solid Dose granulation line
Granulation line 250 Kg Pharmaceutical Nutraceutical

Extrusion with Twin Screw Extruders

Twin screw extruders are used to manufacture pharmaceutical compounds. The twin screw extruder is a self-wiping, intermeshing design that produces enormous output while retaining the best mixing and conveying characteristics. Twin screw extruders were first used in 1986 to manufacture paracetamol. Its use in the pharmaceutical industry sped up the development of new drug formulations. Since then, the technology has been utilized for various pharmaceutical applications.

The configuration of twin screw extruders varies according to their screw diameter. Some have a diameter of five mm, while others are around ten, twelve, or sixteen mm. The smallest ones are suitable for laboratory development, while the largest models are designed for pilot and commercial production. Bohle is one of the major manufacturers of continuous twin screw granulators.

Twin screw extruders are suitable for continuous manufacturing processes for OSD pharmaceuticals. These extruders have the versatility to process dry and wet granulate pharmaceuticals. Twin screw extruders are also suitable for small scale production. In addition, they offer minimal downtime and feature online monitoring.

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Raman Spectroscopy Method for Continuous API Quantification During High-Shear Wet Granulation

The Raman spectroscopy method is an important tool in continuous API quantification in pharmaceutical products. This technique can be applied to identify critical variables in formulations, evaluate the quality attributes of formulations, and improve analytical models. In pharmaceutical development, it has become a critical component of current good manufacturing practices.

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Continuous API quantification during high-shear granulation can be achieved by implementing an in-line Raman spectroscopy system. This method involves the implementation of a Raman probe in front of the granulator barrel and continuously collecting Raman spectra. For the study, eight binary mixtures of API and lactose monohydrate were pre-blended and granulated to develop an in-line PLS calibration model. To determine whether the Raman technique is reliable, the model must be calibrated and compared with actual data. For example, the RMSECV value is used to test the calibration model’s fit. However, the results from the analysis of tablets coated with a particular color.