Label-free Raman spectroscopy for rapid identification of biologics

Recorded On: 02/06/2018

Monoclonal antibody based biologics are gaining immense popularity as therapeutic agents to treat a wide array of diseases such as cancer and inflammation. As a result, increasing number of biologics are currently undergoing clinical development and approval for clinical translation. Such a rise in demand for biologics necessitate the development of rapid, label-free and automated characterization tools for meeting stringent quality control requirements during their manufacturing. To meet regulatory requirements and reduce business risk associated with fill operations, accurate identification of the drug products is a critical and necessary analysis during multiple stages of manufacturing and distribution. However, due to high similarity in the chemical structures of these drugs, establishing product identification is challenging and the traditional wet lab techniques are destructive, labor intensive and expensive to perform multiple times during production and, even more so, for fill finish testing. Therefore, there is an urgent need for quick, inexpensive and reliable methods for biologics identification. Here, we report the first application of spontaneous and label-free plasmon-enhanced Raman spectroscopy coupled with multivariate data analysis for identification of a cohort of closely related human and murine antibody drugs. Building on finite difference time domain simulations, we synthesized nanoparticles of optimal morphology to compare the feasibility of performing SERS-based bulk sample detection with that of spontaneous Raman spectroscopy. We have developed partial least squares-discriminant analysis derived decision algorithms that provide near-perfect classification accuracy in predicting the identity of these drugs based on the subtle, but consistent, differences in their spectra, which are otherwise invisible to gross visual inspection. We have shown that the performance of the decision algorithm with plasmon-enhanced Raman spectroscopy, even at much lower biologic concentrations, is comparable with that of spontaneous Raman spectroscopy. Together, these results establish the feasibility of developing an automated non-perturbative spectroscopic pipeline for rapid identification and quality control during manufacturing and fill-finish testing of biologics – thus alleviating the principal limitations of conventional wet chemistry analyses.

Santosh Paidi

Department of Mechanical Engineering, Johns Hopkins University

Santosh Paidi is a graduate student in the Department of Mechanical Engineering at Johns Hopkins University. His current research efforts in Dr. Ishan Barman’s lab are directed towards application of Raman spectroscopy and multivariate data analysis to develop novel quantitative approaches for addressing unmet needs in life sciences. A major focus of Santosh’s graduate study is the development of non-perturbative tool for rapid identification of closely related biologics in real time during their manufacturing, with the ultimate goal of translation to fill-finish sites. Prior to commencing graduate study at Johns Hopkins University, Santosh obtained a B.Tech in Mechanical Engineering and a minor in Aerospace Engineering from Indian Institute of Technology Bombay.

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