Process analytical technology aims to improve biomanufacturing by providing real-time information about the product, enabling real-time release. This team will use of spectroscopy techniques for continuous in-process monitoring of virus particles and establish the basis for a standardized detection method. Doing so will establish a standard method that follows FDA guidance for future manufacturing of vaccines and address the need for uniform and controlled platform approaches.
Successful completion of the project will lead to a spectro-acoustic process analytical technology that enables real-time quantification of virus particles necessary for continuous manufacturing of future vaccines towards coronaviruses.
By integrating Raman spectroscopy with acoustofluidics, this process analytical technology (PAT) platform enables Real-Time Release (RTR), potentially reducing the time from production to distribution by 50–70% by eliminating traditional 5-to-14-day offline potency assay delays. The transition to a continuous manufacturing model supported by deep learning can increase facility volumetric productivity by up to 400%, while significantly reducing the overhead associated with manual sampling and batch-based QC. Ultimately, this standardized approach provides a "pandemic-ready" infrastructure that lowers the cost of goods (COGS) and ensures 100% in-process visibility for virus-like particles and attenuated live viruses.
Design and produce prototype acoustofluidic device
Couple Raman spectrometer to acoustofluidic device and optimize conditions and characterize viral media for high-quality Raman spectra
Validate the deep learning algorithm for analyzing virus particles and build a graphical user interface
Athalye, S., Maruthamuthu, M., Esmaili, E., Boodaghidizaji, M., Raffaele, J., Selvamani, V., Smith, J., Matos, T., Rustandi, R., Ardekani, A., & Verma, M. (2024). Real-time monitoring of attenuated cytomegalovirus using Raman spectroscopy allows non-destructive characterization during flow. BioRxIV https://doi.org/10.1101/2024.05.08.593031
Barrio-Zhang, A., & Ardekani, A. M. (2023). Sub-micron weak phase particle characterization using the reconstructed volume intensities from in-line digital holography microscopy. Optics and Lasers in Engineering, 170. https://doi.org/10.1016/j.optlaseng.2023.107779
Boodaghidizaji, M., Milind Athalye, S., Thakur, S., Esmaili, E., Verma, M. S., & Ardekani, A. M. (2022). Characterizing viral samples using machine learning for Raman and absorption spectroscopy. MicrobiologyOpen, 11(6). https://doi.org/10.1002/mbo3.1336
Mayorga, C., Athalye, S., Boodaghidizaji, M., Sarathy, N., Hosseini, M., Ardekani, A., & Verma, M. (2025). Limit of Detection of Raman Spectroscopy Using Polystyrene Particles from 25 to 1000 nm in Aqueous Suspensions. American Chemical Society. https://doi.org/10.1021/acs.analchem.5c00182
Ardekani, A., Presenter, ARP- 18 Spectro-acoustic process analytical technology for continuous manufacturing of coronavirus vaccine, NIIMBL National Meeting, Washington, D.C., July 28, 2022.
Ardekani, A. M., Verma, M., Hosseini, M., Esmaili, E., Athalye, S., Kannan, M., Lei, Y., Boodaghidizaji, M., Sukirt, Kim., Kim, T., Matos, T., Smith, J., Rustandi, R., Presenter, Spectro-acoustic Process Analytical Technology for Continuous Manufacturing of Coronavirus Vaccines, NIIMBL National Meeting, Washington DC, July 16, 2022.
Barrio Zhang, A., More, R., Dabiri, S., & Ardekani, A.M., Presenter, Monitoring heterogeneity and diffusive processes in therapeutic samples using Schlieren, 75th Annual Meeting of the APS Division of Fluid Dynamics, Indianapolis, IN, November 20–22, 2022.
Login to the NIIMBL member portal to access additional project information, including presentations, progress updates, reports, and more.
Not yet a member? Learn more about which level of NIIMBL membership is right for you and your organization.
Purdue University
