Enhancing analytical sensitivity in upstream bioprocess using time-gated Raman spectroscopy

Upstream bioprocessing is a very complex system and requires rapid responses to process deviations. Mammalian cell culture processes are conventionally monitored for process-related and cell growth-related parameters, including pH, dissolved oxygen, viable cell density, cell viability, and key analyte concentrations that serve as primary indicators of the metabolic state of the cell culture. Raman spectroscopy (RS) has been increasingly applied as a viable inline process analytical technology (PAT) tool for cell culture monitoring and prediction of key analytes and attributes. The primary limitation to RS in these measurements is fluorescence (also referred to as sample-induced fluorescence), which interferes with the Raman signal and creates noise that makes detection of the signal from the analytes difficult. As a result, fluorescence interference decreases the signal to noise ratio (SNR) of the acquired spectra and increases the limit of detection (LOD) of analytical methods. Time-gated Raman spectroscopy (TGRS) takes advantage of the temporal delay between inelastic light scatter (Raman signal) and fluorescence emission to reduce interference from fluorescence. In this study, a pure component modeling approach and Net Analyte Signal (NAS) were applied to calculate the SNR and LOD of independent CHO cell culture samples. By reducing fluorescence interference, improving the SNR and LOD, TGRS enhanced the detectability of five key analytes in the cell culture samples, facilitating accurate monitoring and detection of analytes in a complex bioprocess system, thereby demonstrating its viability as a PAT tool for upstream bioprocess environment.

Authors

Institutions

Publication Details

Journal
Bioprocess and Biosystems Engineering
Published
2025-12-20
DOI
https://doi.org/10.1007/s00449-025-03261-y
Primary Topic
Viral Infectious Diseases and Gene Expression in Insects
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Enhancing analytical sensitivity in upstream bioprocess using time-gated Raman spectroscopy

James K. Drennen, Venkata Gayatri Dhara, Carl A. Anderson, Guogang Dong et al.
Bioprocess and Biosystems Engineering
Viral Infectious Diseases and Gene Expression in Insects
article

Enhancing analytical sensitivity in upstream bioprocess using time-gated Raman spectroscopy

James K. Drennen, Venkata Gayatri Dhara, Carl A. Anderson, Guogang Dong, Mahdi Mubin Shaikat
article en

Abstract

Upstream bioprocessing is a very complex system and requires rapid responses to process deviations. Mammalian cell culture processes are conventionally monitored for process-related and cell growth-related parameters, including pH, dissolved oxygen, viable cell density, cell viability, and key analyte concentrations that serve as primary indicators of the metabolic state of the cell culture. Raman spectroscopy (RS) has been increasingly applied as a viable inline process analytical technology (PAT) tool for cell culture monitoring and prediction of key analytes and attributes. The primary limitation to RS in these measurements is fluorescence (also referred to as sample-induced fluorescence), which interferes with the Raman signal and creates noise that makes detection of the signal from the analytes difficult. As a result, fluorescence interference decreases the signal to noise ratio (SNR) of the acquired spectra and increases the limit of detection (LOD) of analytical methods. Time-gated Raman spectroscopy (TGRS) takes advantage of the temporal delay between inelastic light scatter (Raman signal) and fluorescence emission to reduce interference from fluorescence. In this study, a pure component modeling approach and Net Analyte Signal (NAS) were applied to calculate the SNR and LOD of independent CHO cell culture samples. By reducing fluorescence interference, improving the SNR and LOD, TGRS enhanced the detectability of five key analytes in the cell culture samples, facilitating accurate monitoring and detection of analytes in a complex bioprocess system, thereby demonstrating its viability as a PAT tool for upstream bioprocess environment.

Bioprocess and Biosystems EngineeringVol. 49(2)
Duquesne University (US), Pfizer (United States) (US)
U.S. Department of Commerce, Pfizer, National Institute of Standards and Technology, National Institute for Innovation in Manufacturing Biopharmaceuticals
Openalex Percentile: Top 62%
Viral Infectious Diseases and Gene Expression in Insects
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.