NIR Chemical Imaging of Pharmaceutical GranulesSatisfying PAT and QbD aims, NIRCI offers various benefits in granulation testing and characterizing species uniformity within granules.by Lisa Makein, Malvern Instruments, and Mansoor Ansari, Imperial College London
Granulation, though a key processing technique within the pharmaceutical industry, can result in product inhomogeneity. With growing regulatory demand for intermediate and end-product quality testing, technologies that support a more detailed understanding of critical granulation parameters, and their influence on blend content uniformity, are needed.
While traditional technologies can provide limited structural information, near infrared chemical imaging (NIRCI) gives detailed spatial and chemical data quickly and easily.
Granulation and granules
Granulation is a generic term for particle agglomeration processes combining fine, powdered solids with liquid or melt binder to form larger aggregates1 (see Table).
Different Product Types Prepared Using Granulation
| Product |
Materials |
| Pharmaceuticals |
Feedstock for tabletting, pellets, capsules
Feedstock for dispersion by the pharmacist |
| Fine chemicals |
Dyestuffs, additives for polymers |
| Human food |
Starch-based products: sauces, soups, baby foods
Beverages: coffee, instant tea
Milk-based products: drinking chocolate, milk, ice cream |
| Animal food |
Fish and mammal feeds, yeasts |
| Household |
Detergents for fabric, dish and hard surface cleaning |
| Microbiological |
Enzyme, yeast, bacterial granules |
| Compacted metallurgical objects |
Used in cars, (i.e. brake-pads), domestic and industrial machinery and electronic goods |
| Compacted ceramics |
Kaolin, feldspar, silica, silicon carbide |
| Waste treatment |
Pelletising of waste sludges and slurries | Granules help reduce dustiness and improve product safety during processing and handling. In some cases, granulation can improve the final product from a sensory perspective, i.e. make it more visually attractive. Granulation can also enhance dispersion and dissolution characteristics, reduce or increase the bulk density, and reduce the tendency to compact during storage. In pharmaceuticals, it is useful for mixing active pharmaceutical ingredients (APIs) with an excipient.
One disadvantage is that granulation can introduce inhomogeneity. In industries that process materials in large quantities, variation in granule composition may not pose problems because the bulk is homogeneous. In the pharmaceutical industry, however, relatively small quantities of granules make up single tablets or capsules. Blend uniformity and the fraction of API within each dose are critical parameters.
Blend content uniformity
With the advent of process analytical technology (PAT) and quality by design (QbD) initiatives, regulatory authorities such as the Food and Drug Administration (FDA) and European Medicines Agency (EMEA) now recommend sampling and testing of in-process materials and drug products2,3. According to Good Manufacturing Practice (GMP) guidelines4,5, such as CFR 21 Part 211, control procedures to assure batch uniformity and integrity of drug products must be established. These must include performance validation of all manufacturing processes that might cause variability in the characteristics of in-process material, such as granulation, as well as the final drug product.
Efficient and cost-effective in-process PAT testing requires robust technology suitable for the manufacturing environment and capable of high-throughput, real-time testing. Implementing QbD, on the other hand, requires a detailed understanding of critical parameters to control and manage quality-defining variables such as homogeneity.
Characterizing homogeneity
Optical microscopy, scanning electron microscopy (SEM) and X-ray microtomography (XMT) provide homogeneity characterization data. However, these processes are limited, and near infrared chemical imaging is rapidly gaining importance in this field6. NIRCI combines NIR spectroscopy and digital imaging, delivering a spatially resolved chemical map of the sample.
NIRCI acquires multiple spectral images across a large and usually contiguous series of narrow spectral bands to produce a data cube. Analysis software then integrates the data to give the complete spatial and chemical information of the sample.
NIRCI benefits
NIRCI offers data acquisition rates of approximately 2 min/sample for detailed scans and little or no sample preparation. It can also distinguish the majority of compounds used in the pharmaceutical industry7. Current research in anti-counterfeiting methodology shows that near real-time analysis is possible with little or no operator intervention by selectively pre-programming precise test ranges for comparing against validating characteristics of a pure component sample.
Robustness and flexibility, coupled with the simple optical design and compact size of the instrumentation, make NIRCI easy to use and suitable for validating both intermediary and end products in the lab or processing plant.
Figure 1. NIRCI of end product: (Left) wide field view of six intact tablets and (Right) tablet cross section. Click here to enlarge. | NIRCI is capable of non-destructive analysis of the microstructure at the surface of the exterior or a cross-section of the tablet or granule. Figure 1 shows both types of image from a study designed to evaluate coatings on pharmaceutical dosage forms. Comparison at a NIR wavelength related to the coating component shows clear distribution differences with some tablets showing regions of higher intensity and, thus, thicker coating. The interior microstructure is also visible through the more thinly coated tablets.
A choice of different magnifications accommodates a wide range of sample sizes and types, as well as the capacity to image multiple samples within a single field of view. This enables direct sample-to-sample comparison and high-throughput measurements.
These measurements were made in diffuse reflectance, meaning that the sample is illuminated and radiation travels a short distance in the tablet before being reflected back to the NIR imaging camera.
The depth of penetration in the sample depends on the wavelength. Consequently, images of granule surfaces or coated tablets include contributions from both the coating and core, and the relative contributions depend on the coating thickness. The NIR spectral range also enables imaging through capsules or tablet packaging.
Granule characterization
Studying both the external surfaces and cross-sections of granule interiors gives detailed qualitative and quantitative information on granulation mechanisms, species distribution and homogeneity.
In a recent study, Mansoor Ansari and Frantisek Stepanek (Imperial College London) used NIRCI to characterize the microstructure of two sets of granules combining solids commonly used as pharmaceutical excipients and typical examples of melt and aqueous binders8. They used an NIRCI system, Malvern Instrument’s SyNIRgi, to image different components in the granular structures of sugar spheres bound with polyethylene glycol (PEG) and D-mannitol bound with an aqueous solution of hydroxypropyl cellulose (HPC). They also used ISys chemical imaging data analysis software to create a partial least squares (PLS) model, which was then applied to each data cube to determine spectral contributions from each component at every pixel.
Figure 2. PLS score images from the two different granule types. (Left) Suglet-PEG granule: (a) Suglet score image and (b) PEG score image. (Right) Mannitol-HPC(aq) granule: (a) Mannitol score image and (b) HPC(aq) score image.
Click here to enlarge. | Figure 2 shows PLS score images from the two different granule types used to select the spectra: Suglet-PEG (left) and Mannitol-HPCaq (right). Visual inspection of these findings helps to predict the product’s end-use performance.
This result suggested that the HPC was uniformly distributed and present in the form of a thin layer on mannitol particles. The fact that the processing and formulation conditions used in preparing these granules encouraged even binder spreading supports the results.
External surface analysis of the Suglet-PEG granule gave respective compositional proportions of 94% and 6%. Researchers, however, knew that the actual proportion of PEG in the formulation was 10%, suggesting interior localization of the binder. To confirm this, two granules were cross-sectioned and their interiors analyzed.
Images and PLS score results of the interior of the granules clearly indicated that areas of high PEG abundance within the granule matrix were indeed predominantly restricted to the core region.
Conclusion
Assessing blend content uniformity following granulation is increasingly significant within the pharmaceutical industry. Able to characterize component uniformity quantitatively within a product, an NIRCI system can be configured for both macroscopic applications, such as end-product testing, or microscopic applications, such as granule testing. The speed, flexibility, robustness and amenability of NIRCI techniques and instrumentation make them suitable for QbD purposes.
References
1. Ramachandran, R., et al. December 2008. “Experimental studies on distributions of granule size, binder content and porosity in batch drum granulation: Inferences on process modelling requirements and process sensitivities.” Powder Technology. Vol. 188, Issue 2, 20, 89-101.
2. Food and Drug Administration (FDA). “Guidance for industry PAT – A framework for innovative pharmaceutical development, manufacturing and quality assurance.” http://www.fda.gov/Cder/OPS/PAT.htm Accessed: 07/28/08.
3. European Medicines Agency (EMEA). 2007. “ICH draft consensus guideline; pharmaceutical development. Annex to Q8.”
4. Code of Federal Regulation. “CFR 21 Part 211: Current good manufacturing practice for finished pharmaceuticals. http://law.justia.com/us/cfr/title21/21cfr211_main_02.html Accessed: 07/28/08.
5. European Commission. 2005. “Good Manufacturing Practice Guidelines.” 4; 5-6 revision. http://ec.europa.eu/enterprise/pharmaceuticals/eudralex/vol4_en.htm Accessed: 0728/08.
6. Lewis, E. N., E. Lee and L. H. Kidder. 2004. Combining imaging and spectroscopy: Solving problems with near-infrared chemical imaging. Microscopy Today. Vol. 12, No. 6, 11.
7. Lewis, E. N., et al. 2007. “Near-infrared chemical imaging a valuable tool for the pharmaceutical industry.” GIT Laboratory Journal. Vol. 1, No. 2, 26-28.
8. Ansari, M. and F. Stepanek. 2009. Application Note: “Near infrared imaging of pharmaceutical granules”. www.malvern.com
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