A Review On Chemometrics In Pharmaceutical Analysis

Chemometrics is the use of mathematical and statistical methods to improve the understanding of chemical information and to correlate quality parameters or physical properties to analytical instrument data. It is a data-driven multidisciplinary science that allows maximum collection and extraction of useful information from the analytical data of numerous application areas such as chemistry, biochemistry, medicine, biology and chemical engineering. This review focuses mainly on numerous chemometric models used such as like parallel factor analysis (PARAFAC), Tucker-3, N-partial least square (NPLS), and bilinear models like principal component regression (PCR) and partial least squares (PLS) and their relevant applications in the field of pharmaceutical sciences. Chemometric approaches can be used to analyze the data obtained from various instruments including near infrared (NIR), attenuated total reflectance Fourier transform infrared (ATR-FTIR), high-performance liquid chromatography (HPLC), and terahertz pulse spectroscopy. The technique has been used in the quality assurance and quality control of pharmaceutical solid dosage forms. Also, this review gives idea about list of software used for multivariate analysis.