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NIR Spectroscopy in Bioprocessing

Real–Time Data on Manufacturing Bio–Processes with NIR spectroscopy

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Simultaneous Multiparameter Analysis

NIR spectroscopy provides reliable quantitative data from multiple parameters at the same time. This method also allows a number of different parameters to be measured simultaneously during fermentation. Its biggest advantage lies in the prediction of cell parameters, since this information is extracted from stray light levels.

Figure 2: a) Profile as predicted by the NIR device, number of cells of a batch (solid line)compared to the reference values, (Points), b) The quality of the calibration illustrates theplot of the calculated values of the model against the reference laboratory; c) Course ofviability for a batch, d) Development of the glucose concentration.
Figure 2: a) Profile as predicted by the NIR device, number of cells of a batch (solid line)compared to the reference values, (Points), b) The quality of the calibration illustrates theplot of the calculated values of the model against the reference laboratory; c) Course ofviability for a batch, d) Development of the glucose concentration.
(Picture: Sartorius Stedim Biotech)

This makes it possible to determine the overall cell number when cultivating mammallian cells (Figure 2). A prediction made using statistic models is more accurate than one calculated using generic laboratory analysis. This is due to the method laboratories use to count cells as well as the variations caused by sample removal and preparation. The viability (i.e. the amount of living cells as a proportion of the overall cell count) can also be measured to within a few percent using NIR spectroscopy (Figure 2c). This is important when determining the timeout of a cultivation because it becomes more difficult to purify the product as the viability decreases.

Determining Individual Nutrients with NIR

Like cell parameters, NIR spectroscopy also determines individual nutrients such as glucose, as long as they are available in a sufficient concentration (a few grams per liter) (Figure 2d). Prediction accuracy here cannot compete with laboratory methods, which produce outstanding results. However, NIR does deliver a real-time profile which can offer enormous advantages, particularly in terms of feed strategies.

Figure 2: a) Profile as predicted by the NIR device, number of cells of a batch (solid line)compared to the reference values, (Points), b) The quality of the calibration illustrates theplot of the calculated values of the model against the reference laboratory; c) Course ofviability for a batch, d) Development of the glucose concentration.
Figure 2: a) Profile as predicted by the NIR device, number of cells of a batch (solid line)compared to the reference values, (Points), b) The quality of the calibration illustrates theplot of the calculated values of the model against the reference laboratory; c) Course ofviability for a batch, d) Development of the glucose concentration.
(Picture: Sartorius Stedim Biotech)

Although a feed control system based solely on NIR spectroscopy yet to be put in place, the option remains open. This could be of potential interest, particularly in terms of bacterial fermentation; laboratory analysis only provides the results with a considerable delay, meaning they are often too slow for such a highly-dynamic process. Online predictions using NIR spectro-scopy enable information to be delivered in a way that optimizes process control.

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