<p>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.</p> Graphical abstract <p></p>