TY - JOUR T1 - Detection of low numbers of bacterial cells in pharmaceutical drug product using Raman Spectroscopy and PLS-DA multivariate analysis JF - bioRxiv DO - 10.1101/2022.04.26.489535 SP - 2022.04.26.489535 AU - R.A. Grosso AU - A.R. Walther AU - E. Brunbech AU - A. Sørensen AU - B. Schebye AU - K.E. Olsen AU - H. Qu AU - M.A.B. Hedegaard AU - E. C. Arnspang Y1 - 2022/01/01 UR - http://biorxiv.org/content/early/2022/04/26/2022.04.26.489535.abstract N2 - Sterility 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.Competing Interest StatementThe authors have declared no competing interest. ER -