Effect of pH variation on Raman-based quantification of active pharmaceutical ingredients: implications for model accuracy and robustness.

Raman spectroscopy is a non-destructive method that enables the measurement of liquid samples without any pretreatment. Quantitative analysis of active pharmaceutical ingredients (APIs) is necessary for drug quality control and Raman spectroscopy offers significant potential as a rapid analytical method. Multivariate analysis (MVA) is helpful for the simultaneous quantification of multiple compounds with high accuracy in spectroscopic analysis. In liquid formulations, pH variation can occur and is expected to induce changes in Raman spectral features. However, the impact of such pH-induced spectral variations on quantitative modeling and prediction performance has not been systematically investigated, despite its potential importance in multivariate calibration. In our study, model liquid formulations were prepared, and the effect of pH variation on Raman spectra and quantitative models for APIs was investigated. Quantification models were constructed using MVA, and the quantification accuracy of the liquid samples containing both single and multiple APIs was high, while systematic variations in prediction performance were observed depending on pH conditions. Our study highlights the importance of considering pH variation in Raman-based quantitative analysis and provide practical insights for achieving robust and reliable MVA models.