Application of Near-infrared Spectroscopy and Multivariate Methods for the Estimation of Isopropyl Alcohol Content in Hand Sanitizer Formulation

Abstract

To address the need of alcohol-based hand sanitizers during COVID-19, U.S. FDA has issued a guidance for the preparation of hand sanitizers that recommends 80% v/v ethanol or 75%v/v isopropyl alcohol (IPA) along with other ingredients. The aim of this study was to develop a new method to estimate IPA content in hand sanitizers by using Near-infrared (NIR) spectroscopy with a multivariate chemo-metric approach. Calibration samples containing 10-90% of IPA were used for model development. NIR data was mathematically pretreated with multiple scattering correction before development of partial least squares (PLSR) and principal component regressions (PCR) model. Both models showed good linearity over the selected range of IPA content with high R2 (>0.993), low root mean squared error (<2.163), minimum difference between standard errors between calibration and validation models (0.0009). The proposed NIR with multivariate methods provide rapid analysis of IPA content in the hand sanitizer.