Multi-modal thermal and impedance sensing for the decoupling of biomass and ionic strength in a microplate format

Abstract

Real-time monitoring of cell culture environments is essential in bioprocessing, yet isolating biomass growth from changes in medium conductivity remains a challenge. This work presents a multi-modal signal-decoupling methodology applied to a microplate-based sensing platform to simultaneously and independently monitor cell count and ionic strength (NaCl content). The system utilizes a dual-parameter approach: transient thermal sens ing to assess biomass and electrical impedance spectroscopy (EIS) to characterize the medium. Calibration was performed using varying cell counts (up to 2.6 & times; 107 cells) across five NaCl concentrations (0.1 to 1.5 wt%). Results indicate that the thermal slope is a robust indicator of cell count, remaining largely independent of ionic conductivity. In contrast, the impedimetric signal correlates with both variables. To decouple these signals, an Inverse Distance Weighting (IDW) algorithm was implemented, utilizing the combined thermal and electrical datasets to estimate NaCl concentration. Validation with independent datasets and dynamic spiking experiments demonstrated that the IDW model accurately predicts NaCl content without interference from cell sedimentation. This integrated sensing strategy presents a pathway for the autonomous, real-time control of culture conditions for a wide range of applications.