Data Descriptor: Multimodal Dataset of Bioreactor Cell Cultivations Including Turbidity, Permittivity, O₂ and CO₂ Measurements

We present a comprehensive, time-resolved dataset of Chinese Hamster Ovary (CHO) cultivation dynamics to support data-driven bioprocess engineering and process analytical technology development. The dataset includes 24 controlled bioreactor cultivations, representing 12 experiments performed in duplicate in a parallel bioreactor system with a working volume of 0.55 – 0.8 L and cultivation durations of 161.5 – 328.5 h. A total of 48 variables are provided, comprising 38 continuous inline variables and 10 offline variables sampled up to twice daily. In addition to standard process measurements, the dataset includes multimodal inline monitoring using turbidity, permittivity, and dissolved CO₂ sensors. The experiments systematically vary cultivation medium, agitation rate, aeration rate, and process mode (batch and fed-batch), providing diverse operating conditions for sensor evaluation, process modeling, and bioprocess analysis. Furthermore, the inoculation cell density, glutamine concentration, and impeller position were varied to further expand the range of investigated process conditions. The dataset preserves realistic measurement characteristics, including noise, and missing values, enabling robust benchmarking of data-driven methods for process monitoring, modeling, and control.