Detection of low numbers of bacterial cells in pharmaceutical drug product using Raman Spectroscopy and PLS-DA multivariate analysis

Abstract

AbstractSterility testing is a laborious and slow process to detect contaminants present in drug products. Raman spectroscopy is a promising label-free tool to detect microorganisms and thus gaining relevance as future alternative culture-free method for sterility testing in pharmaceutical industry. However, reaching detection limits similar to standard procedures while keeping a high accuracy remains challenging, due to weak bacterial Raman signal. In this work, we show a new non-invasive approach focusing on detect different bacteria in concentrations below 100 CFU/ml within drug product containers using Raman spectroscopy and multivariate data analysis. Even though Raman spectra form drug product with and without bacteria are similar, a partial least squared discriminant analysis (PLS-DA) model shows great performance to distinguish samples with bacteria contaminants in limits below 10 CFU/ml. We use spiked samples with bacteria spores for independent validation achieving a detection accuracy of 99%. Our results indicate a great potential of this rapid, and cost-effective approach to be use in quality control of pharmaceutical industry.