A novel method for analyzing thick tablets by near infrared spectroscopy

A near-infrared (NIR) spectroscopic method to determine content uniformily of a large, thick tablet using an approach that could facilitate future validations has been developed. A CT ibuprofen 800-mg tablet weighs about 1150 mg and is about 18.6 mm wide and 7.6 mm thick. The FT NIR spectrometer was optimized for transmission spectra of the tablets by moving it to the sample compartment and placing it immediately behind the tablet. In spite of this dedicated setup, the transmission spectra obtained were very poor, indicating that the NIR radiation was not reaching the detector. The spectra of the tablet improved with use of a simple preparation in which a flat-face die applies pressure of 20 000 psi to the tablet, this reduced the thickness of the tablet from 7.6 mm to 3.6 mm. A calibration model was developed for tablets with drug content ranging from 70% to 130% of label. The calibration model was tested using a validation set of tablets with a drug content of 752, 800, and 848 mg. The results obtained were within 1.5% of the known drug content of the validation set, tablets. Even with the sample preparation, the content uniformity results of 10 tablets could be determined using this method in less than 1 hour. The approach described in this article could also be used to validate NIR content uniformity methods for orther formulations

Rapid Poultry Spoilage Evaluation Using Portable Fiber-Optic Raman Spectrometer

The freshness changes in poultry fillets during storage were studied using a portable fiber-optic Raman spectrometer. Poultry fillets with the same storage life (9 days) and expiry date were purchased from a local store and stored at 4 °C. Their Raman spectra were measured on a daily basis up to day 21 using a QE Pro-Raman spectrometer with a laser excitation wavelength of 785 nm. The complex spectra were analyzed using Principal Components Analysis (PCA), which resulted in a separation of the samples into three quality classes according to their freshness: fresh, semi-fresh, and spoiled. These classes were based on and similar to the information inferred from the product label on the packages of poultry fillets. The PCA loadings revealed a decrease in the protein content of the poultry meat during spoilage, an increase in the formation of free amino acids, an increase in oxidation of amino acid residues, and an increase in microbial growth on the surface of the poultry fillets, as well as revealing information about hydrophobic interaction around the aliphatic residues. Similar groupings (fresh, semi-fresh, and spoiled) were also obtained from the results of an Agglomerative Hierarchical Cluster Analysis (AHCA) of the first five principal components. The results allow the conclusion that the portable fiber-optic Raman spectrometer can be used as a reliable and fast method for real-time freshness evaluation of poultry during storage