Get a Grip: Controlling Solid Product Properties

Aug. 12, 2009
Spectroscopic and other analytical techniques can enhance control of blending, granulation, drying and coating.

Operations such as drying and granulation are as old as drugmaking itself. However, until fairly recently, tools were not widely used to control these processes and eliminate variable product quality caused by mechanical or thermal stress, or solvent interaction. In operations such as blending, lack of uniformity and homogeneity can lead to rejected batches. Even worse, when such problems are not detected during quality control, there can be adverse patient reactions.

Since FDA published its Process Analytical Technologies (PAT) guidance document in 2004, a growing number of pharmaceutical manufacturers are using spectroscopic techniques to detect reaction endpoints, and thus, better monitor and control processes such as blending, granulation, drying and coating. These techniques can be used online, allowing deviations to be detected and corrected during manufacturing, without removing samples from the process.  They can also be used at-line or off-line. 

This article briefly summarizes how techniques including near infrared, FTIR, and mass spectroscopy and focused beam reflectance measurement (FBRM) are being applied to improve the control of pharmaceutical blending, granulation, drying and coating operations.

During manufacturing, solids must interact with equipment and solvents, which may result in thermal or mechanical stress, leading to process-induced transformations (PITs) that lead to variability in the material properties and quality of the final product.

For the past few decades, other industries have recognized that variability in product quality can be addressed by monitoring a process at critical points and using the information gathered during monitoring to actively control the manufacturing process [1]. Focus must be on four main areas: monitoring, supervision, control and diagnosis.

We will now look at each individual technique, staring with near-infrared (NIR) spectroscopy.

NIR spectroscopy has become a workhorse technique for both qualitative and quantitative applications [2, 3]. Used widely to characterize raw materials [4], NIR is becoming accepted for the analysis of intact tablets [5, 6], blend homogeneity [7], particle size determination [8] and moisture measurement [9]. Use of NIR can enable continuous and real-time quality assurance, but also reduce product development time, speed scale-up and time-to-market for new products [10].

NIR in Milling and Blending

In order to work for in-process measurement in nano-milling operations, dealing with particles from the nanometer to hundreds of microns in diameter, in-process tools must be able to determine endpoint in 30% wt/wt solid dispersions, and to achieve precision on the order of nanometers.

In-line NIR spectroscopy has been shown to allow for nanometer-scale particle size determinations in addition to providing the opportunity for real-time control of a critical quality attribute of the complex formulation. The technique has been proven in milling, in which spectra taken from 400-2500 nm using an in-line Foss reflectance probe offered a precise graphical look at endpoint [11].

NIR has also been used [12] to visualize chemical content in a blend. By illuminating a specific area in the process vessel with a source containing light in the NIR region and regularly acquiring images, this method used an NIR CCD camera with spectra sensitivity of 900-1700 nm to visualize chemical content. A band-pass optical filter was placed in front of the camera lens and then images were taken using a high-resolution image acquisition board. Principal component analysis (PCA), a multivariate projection tool, was then used to extract blending process information from the data matrix, to provide an overview of dominant patterns and major trends in the data.
Acoustic Analysis for Granulation

In granulation, liquid droplets typically initiate the agglomeration process by creating liquid bridges between particles. Changes to the frequency and intensity of the sound can be expected as the particles become incorporated into granules and the size and number of granules change. Acoustic methods have been used to monitor this process and determine the endpoint. In this case, a microphone was suspended in the filtered air exhaust from the granulator bowl. An additional microphone was mounted to the wall behind the granulator to record any significant background noise in the room. A 16-bit National Instruments DAQCard-6036E was used for data acquisition [13].

Focused Beam Reflectance Measurement

Focused Beam Reflectance Measurement (FBRM) uses a laser beam focused on the sapphire window of a probe to determine particle size distribution. The beam follows a circular path at speeds of up to 6 m/s. When it intersects with the edge of a particle passing by a window surface, an optical collector records a backscatter signal. The time interval of the signal multiplied by the beam speed represents a chord length between two points on the edge of a particle. The chord length distribution (CLD) can be recalculated to represent either a number or volume weighted particle size distribution [14].

In many cases, where precision is more important than accuracy, CLD measurements are adequate to monitor dynamic changes in process parameters related to particle size and shape, concentration, and rheology of fluid suspensions.

The in-line real-time particle distributions can be characterized using in situ PAT, FBRM and PVM technology. FBRM and PVM were used to ultimately control the real-time particle distribution during the fluidized bed process. In the bottom spray granulation process, liquid binder and water are continuously sprayed during three stages. Following moisture addition, the bed is dried. Using real-time PAT, one can track the number of fine particles in the range 0-100μm decrease in number over time as the number of coarse particles in the range 200-300μm and 500-600μm grow over time [15]). The square weighted (volume based) mean eventually reaches a steady state. However, when filter blow back occurs during the third spraying regime, there is an obvious upset of fines seen by the increase in particle counts/second 0-100μm. The particle growth and fines upset were verified by the in-line PVM microscope.

Fast Fourier Transform

Fast Fourier Transform (FFT) can also be used to determine the granulation end point, concurrently with the progress of the granulation process. The probe was pre-determined in terms of the shape of the bottom end, width and length of the shaft, and the position in the vessel.

From the beginning to the end of the granulation, a specific wave pattern was seen, which persisted until the end point was reached. The width of the probe vibration increasesd with the progress of granulation, and the displacement of the probe increased as well, as indicated by the vertical axes.

In addition, frequency analysis by FFT showed that the probe vibration consisted of elements of specific constant frequencies throughout the granulation. By counting the main peaks in each specific wave pattern, it was found that the frequency of the wave fitted with that of the impeller blade of the high speed mixer passing below the probe. It was confirmed that the waves were composed of the main elemental strength at the impeller blade frequency with their harmonic frequencies [16].

These phenomena were interpreted as showing the impact of the granules upon the probe being made by the blade throughout the granulation process; at the beginning of the granulation process, the finer granules would cause a smaller impact on the probe. With the progress of granulation, as granules developed in size, stronger impacts would thus be made on the probe. The harmonic frequencies were considered to be due to the vibration of the shaft of the probe.

Measuring Power Consumption and Temperature

The degree of process control is often linked to torque of the mixer shaft in the granulating equipment [17] or by power consumption of the mixer motor [18, 19]. Other research had found that one could control granulation by measuring the power consumption of the mixer motor as a function of the granulating liquid added per unit time. They found that power consumption measurement is an alternative, simple and inexpensive method to determine the cohesion of powder particles. In order to analyze the power consumption profile in process a computer program was developed in a previous work [20, 21] to calculate the characteristic points and to save the obtained data digitally.

For low saturation levels, friction forces increase as the interparticle contact area increases.  At high saturation levels, capillary forces lubricate particles that come into contact with each other. Friction between particles during granulation causes the temperature within the wet powder bed to rise, due to a combination of conduction through the solid, radiation at the particle surfaces and a combination of conduction and convection through the gaseous and liquid space. This temperature rise can be monitored to measure granulation endpoint [22].

Controlling Drying: Mass Spec Analysis of Online Gas

Solvent removal, whether partial or complete, is a key process step for manufacturing pharmaceutical intermediates and products. However, taking sample measurements to determine endpoint is labor and time intensive, especially with vacuum drying, where sampling interferes with the drying process itself. Online measuring methods offer a better alternative.

During the complete drying process, the gas atmosphere inside the drying apparatus may be monitored and documented continuously with a process gas mass spectrometer. GAM 200, GAM 300 and GAM 400 mass spectrometers from In Process Instruments are suitable for this task. The continuous sampling of gas samples can be taken at the drying apparatus outlet, in the outlet air or in the vacuum suction line. When the drying is to be monitored both in the vacuum area and when working with carrier gas, the mass spectrometer will be equipped with a two-stage, pressure controlled gas inlet to adjust constant pressure conditions for the mass spectrometer [23].

Acoustic-Resonance Spectrometry for Tablet Compression

Acoustic-resonance spectrometry (ARS) is an underutilized PAT tool that could become an analytical method of choice for the physical characterization of some analytes in pharmaceutical manufacturing. Although it has not yet been found to identify specific functional groups, ARS can easily be applied to the quantification of active pharmaceutical ingredient (API) or moisture in tablets because of the high correlation between AR spectral features and chemical composition. For dense materials with very little compressibility, a sound wave propagates very rapidly, while for less dense samples, sound travels more slowly  [24].

Research has shown that the technique could, theoretically, be capable of testing 100% of the tablets passing down the manufacturing line, eliminating the need for scale-up, and offering a high-throughput assay suitable for testing 100% of product.

Laser-Induced Breakdown Spectroscopy

LIBS, a laser based technique, uses a high power laser that ablates the surface of the sample medium to form a plasma plume of finely dispersed material. Some research [25] has looked at the Pharma LIBS 200 instrument, which employs a pulsed laser with high power to form plasma. In one case, plasma emissions were transmitted to an imaging spectrograph of Czerny-Turner configuration by a fiber optic bundle with three gratings: 600 g/mm, 1200 g/mm and 1200 g/mm.  These were then detected by an interline readout charge coupled device (CCD). The grating used allowed for a 20-nm detection window in order to simultaneously monitor the elements of interest, and the tablets were placed in an XY rotational stage [26]. The sampling plan of the model formulation was optimized for the resolution of the laser shot, and the change in signal intensity with number of shots was profiled. Pharsight Corp.’s WinNonlin professional software (version 4.1) was then used to calculate the AUC of the elemental signal intensity as a function of the number of laser [27]. Coating uniformity was evaluated by plotting the cumulative emission signal as a function of the different locations (sites) across the tablet surface.


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P. Patel | R. Kamani