Fogale nanotech has added the dielectric spectroscopy feature to its capacitance measurements. By applying multiple frequencies scanning from 0.1 to 15 Mhz, the system determines online the permittivity spectra that are described in the literature as the beta-dispersion phenomenon.
Figure 3 shows the beta-dispersion spectra obtained from the Biomass spectrometer. Each spectra is analyzed online to extract biomass physiological information. Each spectra is a function of six parameters: cell suspension biovolume, cell radius, membrane capacitance, internal conductivity of cells, homogeneity of cells, and medium conductivity. These parameters are believed to provide valuable physiological information about the cells in culture.
The Advanced cell analyzer assesses the beta-dispersion spectra to measure biovolume, viable cell number, and cell size and also determine cell size distribution.
By measuring the true cell number, the Fogale system eliminates concern about the deviation between online biovolume and off-line cell count in cell-size changing conditions (Figure 4).
In addition to cell number, cell size, and cell-size distribution, scanning dielectric spectroscopy provides information on the cytoplasmic membrane capacitance and the internal conductivity of cells.
For example, it has been reported that a sudden drop of membrane capacitance two days before the end of a bioreactor run could optimize yield. We have found that in three different CHO cultures, the cells stop producing just after a membrane capacitance drop. This phenomenon may then be used to define the optimal harvesting time and potentially gain 5–10% in additional productivity annually.
With Fogale’s biomass system (Figure 5), users obtain, with a single probe, six different process parameters in real time, which enables detailed characterization of the process dynamics controlling and driving the process in the optimal operating range.
Use of the Advanced cell analyzer in process development has proven to be a valuable addition, enabling greater process understanding and leading to invaluable applications in large-scale manufacturing, including identification of process deviations and optimal harvesting time.