Background/Aims
Previous work developed a quantitative model using capacitance spectroscopy in an atâline setup to predict the dying cell percentage measured from a flow cytometer. This work aimed to transfer the atâline model to monitor labâscale bioreactors in realâtime, waiving the need for frequent sampling and enabling precise controls.
Methods and Results
Due to the difference between the atâline and inâline capacitance probes, direct application of the atâline model resulted in poor accuracy and high prediction bias. A new model with a variable range and offering similar spectral shape across all probes was first constructed, improving prediction accuracy. Moreover, the global calibration method included the variance of different probes and scales in the model, reducing prediction bias. External parameter orthogonalization, a preprocessing method, also mitigated the interference from feeding, which further improved model performance. The rootâmeanâsquare error of prediction of the final model was 6.56% (8.42% of the prediction range) with an R2 of 92.4%.
Conclusion
The culture evolution trajectory predicted by the inâline model captured the cell death and alarmed cell death onset earlier than the trypan blue exclusion test. Additionally, the incorporation of atâline spectra following orthogonal design into the calibration set was shown to generate calibration models that are more robust than the calibration models constructed using the inâline spectra only. This is advantageous, as atâline spectral collection is easier, faster, and more materialâsparing than inâline spectra collection.