Evaluation of Infrared-Reflection Absorption Spectroscopy Measurement and Locally Weighted Partial Least-Squares for Rapid Analysis of Residual Drug Substances in Cleaning Processes

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Abstract

The usefulness of infrared-reflection absorption spectroscopy (IR-RAS) for the rapid measurement of residual drug substances without sampling was evaluated. In order to realize the highly accurate rapid measurement, locally weighted partial least-squares (LW-PLS) with a new weighting technique was developed. LW-PLS is an adaptive method that builds a calibration model on demand by using a database whenever prediction is required. By adding more weight to samples closer to a query, LW-PLS can achieve higher prediction accuracy than PLS. In this study, a new weighting technique is proposed to further improve the prediction accuracy of LW-PLS. The root-mean-square error of prediction (RMSEP) of the IR-RAS spectra analyzed by LW-PLS with the new weighting technique was compared with that analyzed by PLS and locally weighted regression (LWR). The RMSEP of LW-PLS with the proposed weighting technique was about 36% and 14% smaller than that of PLS and LWR, respectively, when ibuprofen was a residual drug substance. Similarly, LW-PLS with the weighting technique was about 39% and 24% better than PLS and LWR in RMSEP, respectively, when magnesium stearate was a residual excipient. The combination of IR-RAS and LW-PLS with the proposed weighting technique is a very useful rapid measurement technique of the residual drug substances.

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