Yeung, Ken SY; (1998) Near infrared spectroscopy technique for bioprocess monitoring and control. Doctoral thesis (Ph.D), UCL (University College London).

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Abstract

The thesis described an application of near infrared (NIR) spectroscopy to a specific characterisation of a complex biological process stream. Its use is for the monitoring and control of a downstream process in which alcohol dehydrogenase (ADH) is to be recovered from a broth of homogenised yeast. Other than the product ADH, the yeast homogenate consists of contaminants such cell debris, protein, nucleic acids, lipids and others. While the first two represented a large fraction of the total contaminant and could be removed sufficiently by centrifugation and fractional precipitation, respectively. The remains residuals of contaminants often poses a fouling problem to the final stage of hydrophobic interaction chromatography (HIC) purification. The fouling has been minimised by the inserting a flocculation process at the early stage of recovery so that the problem contaminants are removed and the overall recovery is enhanced. A low budget instrument has been developed for sensitivity in the region of the NIR spectrum (from 1900 to 2500 nm) where preliminary work found distinctive NIR signatures from cell debris, protein and RNA in the yeast homogenate. The instrument is configured as a scanning spectrophotometer. Multivariate calibration technique with partial least squares (PLS) has been used for the three mentioned contaminants calibration. Two types of samples are used for calibrating the NIR instrument. In one case samples are prepared by adding materials representative of the contaminates to clarified yeast homogenate. In the other samples are taken from the process stream after flocculation and floe removal. In the former case the contaminant levels are well known but are outside the range of interest; in the latter there is uncertainty of analysis of contaminant level but the calibration is in the range of interest. The NIR instrument together with the calibration models has demonstrated potential in rapid monitoring of contaminants.

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