Matrix-enhanced calibration procedure for multivariate calibration models with near-infrared spectra

Abstract

A novel method is introduced for developing calibration models for the spectroscopic measurement of chemical concentrations in an aqueous environment. To demonstrate this matrix-enhanced calibration procedure, we developed calibration models to quantitate glucose and glutamine concentrations in an insect cell culture medium that is a complex mixture of more than 20 components, with three components that manifest significant concentration changes. Accurate calibration models were generated for glucose and glutamine by using a calibration data set composed of 60 samples containing the analytes dissolved in an aqueous buffer along with as few as two samples of the analytes dissolved in culture medium. Standard errors of prediction were 1.0 mM for glucose and 0.35 mM for glutamine. The matrix-enhanced method was also applied to culture medium samples collected during the course of a second bioreactor run. Addition of three culture medium samples to a buffer calibration reduced glucose prediction errors from 3.8 mM to 1.0 mM; addition of two culture medium samples reduced glutamine prediction errors from 1.6 mM to 0.76 mM. Results from this study suggest that spectroscopic calibration models can be developed from a relatively simple set of samples provided that some account for variations in the sample matrix.