| Summary: | Industrial biotransformation processes are becoming increasingly important for the production of single enantiomers of both low value commodity and high value fine chemicals. Despite this demand and the regulatory authorities encouragement of a quality by design approach, the application of process analytical technology to these systems has, to date, been relatively limited. A more traditional off-line approach involving chromatographic methods is still commonly employed for the quantification of key analytes during the process. In-situ measurements tend to be limited to physical parameters of the system such as pH and dO₂, which give little information about the actual process progression. This study investigates the potential of applying infrared spectroscopic techniques to monitor and quantify the key components of de-racemisation and transaminase biotransformation processes. Multivariate models based on the near and mid infrared spectroscopic regions have been constructed for a variety of these processes. Each constructed model was subjected to an external validation procedure to ensure rigorous testing. Stoichiometric linkages were known to exist within these systems. Whilst steps were taken to ensure these linkages were broken, the contributors to each model were also carefully examined to ensure that co-linearity within the constructed models had been adequately addressed. Having constructed robust process models, mechanisms of ensuring the long-term suitability of the models were also investigated. This aimed to ensure the continued predictive ability of the constructed models following instrument maintenance, repair or replacement. Quantitative models resulted that were able to predict the key analyte concentrations of the external validation datasets over the course of the biotransformation processes. Predicted values from the constructed models were in good agreement with both the errors of calibration and cross validation associated with the models, and the actual concentrations predicted by the off-line chromatographic reference methods.
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