A quantitative near infrared spectroscopy model for the assay of efavirenz in tablets

Abstract

Near-infrared-spectroscopy combined with multivariate data analysis represents the most recent and efficient technology in analytical chemistry. The objective of this study was to utilize near infrared spectroscopy as an adapted technology for the quantitative assay of efavirenz. The study developed and validated a quantitative model for estimating the amount of efavirenz in efavirenz uncoated tablets. The quantification was based on the partial least squares algorithm and constructed by cross-validation. A UV spectrophotometric procedure was used as the reference method. Different pre-processing methods were employed in the development of calibration models. The best calibration model was that using partial least squares as the regression algorithm in association with Multiplicative Scattering Correction as the spectrum pre-processing method. The model estimators were: coefficient of determination (R²) 0.9815, standard error of cross validation 2.0346 and a factor of 5. The chosen model correlated well with the prediction results in accordance with the Mahalabinos distance limits. The developed NIR method allows the estimation of the amount of efavirenz in tablets without sample preparation thus proving to be a simple, fast and suitable method for the quantitative assay of efavirenz in uncoated tablets. Hence, NIR coupled with chemometric methods can be used for on-line, in-line or at-line monitoring of the manufacturing process and are helpful in achieving the goals of Process Analytical Technology.

Keywords: Near Infrared Spectroscopy, chemometrics, multivariate data analysis, efavirenz, Partial Least Squares, cross validation