Multivariate calibration of energy-dispersive X-ray diffraction data for predicting the composition of pharmaceutical tablets in packaging

A system using energy-dispersive X-ray diffraction (EDXRD) has been developed and tested using multivariate calibration for the quantitative analysis of tablet-form mixtures of common pharmaceutical ingredients. A principal advantage of EDXRD over the more traditional and common angular dispersive X-ray diffraction technique (ADXRD) is the potential of EDXRD to analyse tablets within their packaging, due to the higher energy X-rays used. In the experiment, a series of caffeine, paracetamol and microcrystalline cellulose mixtures were prepared and pressed into tablets. EDXRD profiles were recorded on each sample and a principal component analysis (PCA) was carried out in both unpackaged and packaged scenarios. In both cases the first two principal components explained >98% of the between-sample variance. The PCA projected the sample profiles into two dimensional principal component space in close accordance to their ternary mixture design, demonstrating the discriminating potential of the EDXRD system. A partial least squares regression (PLSR) model was built with the samples and was validated using leave-one-out cross-validation. Low prediction errors of between 2% and 4% for both unpackaged and packaged tablets were obtained for all three chemical compounds. The prediction capability through packaging demonstrates a truly non-destructive method for quantifying tablet composition and demonstrates good potential for EDXRD to be applied in the field of counterfeit medicine screening and pharmaceutical quality control

Perspectives on global leadership and the Covid-19 crisis

As the world struggled to come to grips with the Covid-19 pandemic, over twenty scholars, practitioners, and global leaders wrote brief essays for this curated chapter on the role of global leadership in this extreme example of a global crisis. Their thoughts span helpful theoretical breakthroughs to essential, pragmatic adaptations by companies

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