Validation of an HPLC Method for the Determination of Diclofenac Diethylamine and Three of Its Impurities in a Gel Pharmaceutical Form.

BACKGROUND: Monitoring impurities in drug products is a principal requirement of pharmaceutical regulatory authorities all over the world to ensure drug safety. For this reason, there is a great need for analytical QC of dugs products. OBJECTIVE: In this study, a simple, efficient, and direct HPLC method was developed for the determination of three impurities of diclofenac. METHODS: The HPLC method was developed using a mobile phase which consisted of an HPLC grade mixture, acetonitrile-0.01M phosphoric acid adjusted to pH 2.3 (1 + 3, by volume). RESULTS: The separation was performed in 15 min. The calibration curves of the three impurities were linear; the correlation coefficients were 0.999 at concentrations of 0.00015-0.003 µg/mL. CONCLUSION: The validation of this method shows that it meets all validation criteria. This shows the reliability of this method for the routine control of diclofenac impurities. HIGHLIGHTS: The validation of a robust HPLC method for the determination of diclofenac impurities is of great importance for the pharmaceutical industry to control its products.

A Preliminary Study on the Potential of FT-IR Spectroscopy and Chemometrics for Tracing the Geographical Origin of Moroccan Virgin Olive Oils.

BACKGROUND: The authentication of the geographical origin of virgin olive oils (VOO) generally requires the use of sophisticated and time-consuming analytical techniques. There is a need for quick and simple analytical techniques to predict the origin of olive oils. OBJECTIVE: This study aims to examine the physico-chemical data of olive oils collected in six regions of Morocco during two consecutive years 2020 and 2021, and also to evaluate the ability of FT-IR in combination with discrimination tools to study the geographical origin of Moroccan olive oils. METHOD: Fourier transform infrared spectroscopy (FTIR) was used in this study as an emerging analytical technique to express a unique "fingerprint." A preliminary processing of the ATR-FTIR spectral data was performed by preprocessing algorithm to reduce the noise and the effect of signal variation as well as to minimize the effects of light scattering to extract the maximum analytical information from the spectra. A multivariate statistical procedure based on principal component analysis (PCA) coupled with linear discriminant analysis (LDA) as well as partial least-squares discriminant analysis (PLS-DA) was developed to provide a powerful classification approach. RESULTS: Based on the PCA, six clusters were identified. The application of PCA-LDA and PLS-DA procedures demonstrate a powerful capacity in predicting the geographic origin of olive oils; this capacity is shown by the high value of correct classification rate (CCR), varying between 84.09 and 100%. CONCLUSIONS: The suggested procedure has given reliable results for the classification of olive oils according to their geographical origin, with advantages such as being fast, inexpensive, and not requiring any prior separation process. HIGHLIGHTS: The performance of this approach is significantly faster and possesses a higher degree of selectivity and sensitivity. The implementation of this technique for routine analysis of olive oil would save significant time, resources, and solvents.